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How to Make Your Help Center LLM-Friendly
Your Help Center doesn’t need a rebuild. It just needs a smarter structure so AI can find what customers ask about most.
TL;DR:
- You don’t need to rebuild your Help Center to make it work with AI—you just need to structure it smarter.
- AI Agent reads your content in three layers: Help Center, Guidance, and Actions, following an “if / when / then” logic to find and share accurate answers.
- Most AI escalations happen because Help Docs are vague or incomplete. Start by improving your top 10 ticket topics—like order status, returns, and refunds.
- Make your articles scannable, define clear conditions, link next steps, and keep your tone consistent. These small tweaks help AI Agent resolve more tickets on its own—and free up your team to focus on what matters most.
As holiday season support volumes spike and teams lean on AI to keep up, one frustration keeps surfacing, our Help Center has the answers—so why can’t AI find them?
The truth is, AI can’t help customers if it can’t understand your Help Center. Most large language models (LLMs), including Gorgias AI Agent, don’t ignore your existing docs, they just struggle to find clear, structured answers inside them.
The good news is you don’t need to rebuild your Help Center or overhaul your content. You simply need to format it in a way that’s easy for both people and AI to read.
We’ll break down how AI Agent reads your Help Center, finds answers, and why small formatting changes can help it respond faster and more accurately, so your team spends less time on escalations.
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How AI Agent uses your Help Center content
Before you start rewriting your Help Center, it helps to understand how AI Agent actually reads and uses it.
Think of it like a three-step process that mirrors how a trained support rep thinks through a ticket.
1. Read Help Center docs
Your Help Center is AI Agent’s brain. AI Agent uses your Help Center to pull facts, policies, and instructions it needs to respond to customers accurately. If your articles are clearly structured and easy to scan, AI Agent can find what it needs fast. If not, it hesitates or escalates.
2. Follow Guidance instructions
Think of Guidance as AI Agent’s decision layer. What should AI Agent do when someone asks for a refund? What about when they ask for a discount? Guidance helps AI Agent provide accurate answers or hand over to a human by following an “if/when/then” framework.
3. Respond and perform
Finally, AI Agent uses a combination of your help docs and Guidance to respond to customers, and if enabled, perform an Action on their behalf—whether that’s changing a shipping address or canceling an order altogether.
Here’s what that looks like in practice:
This structure removes guesswork for both your AI and your customers. The clearer your docs are about when something applies and what happens next, the more accurate and human your automated responses will feel.
A Help Center written for both people and AI Agent:
- Saves your team time
- Reduces escalations
- Helps every customer get the right answer the first time
What causes AI Agent to escalate tickets, and how to fix it
Our data shows that most AI escalations happen for a simple reason––your Help Center doesn’t clearly answer the question your customer is asking.
That’s not a failure of AI. It’s a content issue. When articles are vague, outdated, or missing key details, AI Agent can’t confidently respond, so it passes the ticket to a human.
Here are the top 10 topics that trigger escalations most often:
Each of these topics needs a dedicated, clearly structured Help Doc that uses keywords customers are likely to search and spells out specific conditions.
Here’s how to strengthen each one:
- Order status: Include expected delivery timelines, tracking link FAQs, and a clear section for “what to do if tracking isn’t updating.”
- Return request: Spell out eligibility requirements, time limits, and how to print or request a return label.
- Order cancellation: Define cut-off times for canceling and link to your “returns” doc for shipped orders.
- Product quality issues: Explain what qualifies as a defect, how to submit photos, and whether replacements or refunds apply.
- Missing item: Clarify how to report missing items and what verification steps your team takes before reshipping.
- Subscription cancellation: Add “if/then” logic for different cases: if paused vs. canceled, if prepaid vs. monthly.
- Order refund: Outline refund timelines, where customers can see status updates, and any exceptions (e.g., partial refunds).
- Product details: Cover sizing, materials, compatibility, or FAQs that drive most product-related questions.
- Return status: State how long returns take to process and where to check progress once a label is scanned.
- Order delivered but not received: Provide step-by-step guidance for checking with neighbors, filing claims, or requesting replacements.
Start by improving these 10 articles first. Together, they account for nearly half of all AI Agent escalations. The clearer your Help Center is on these topics, the fewer tickets your team will ever see, and the faster your AI will resolve the rest.
How to format your Help Center docs for LLMs
Once you know how AI Agent reads your content, the next step is formatting your help docs so it can easily understand and use them.
The goal isn’t to rewrite everything, it’s to make your articles more structured, scannable, and logic-friendly.
Here’s how.
1. Use structured, scannable sections
Both humans and large language models read hierarchically. If your article runs together in one long block of text, key answers get buried.
Break articles into clear sections and subheadings (H2s, H3s) for each scenario or condition. Use short paragraphs, bullets, and numbered lists to keep things readable.
Example:
How to Track Your Order
- Step 1: Find your tracking number in your confirmation email.
- Step 2: Click the tracking link to see your delivery status.
- Step 3: If tracking hasn’t updated in 3 days, contact support.
A structured layout helps both AI and shoppers find the right step faster, without confusion or escalation.
2. Write for “if/when/then” logic
AI Agent learns best when your Help Docs clearly define what happens under specific conditions. Think of it like writing directions for a flowchart.
Example:
- “If your order hasn’t arrived within 10 days, contact support for a replacement.”
- “If your order has shipped, you can find the tracking link in your order confirmation email.”
This logic helps AI know what to do and how to explain the answer clearly to the customer.
3. Clarify similar terms and synonyms
Customers don’t always use the same words you do, and neither do LLMs. If your docs treat “cancel,” “stop,” and “pause” as interchangeable, AI Agent might return the wrong answer.
Define each term clearly in your Help Center and add small keyword variations (“cancel subscription,” “end plan,” “pause delivery”) so the AI can recognize related requests.
4. Link to next steps
AI Agent follows links just like a human agent. If your doc ends abruptly, it can’t guide the customer any further.
Always finish articles with an explicit next step, like linking to:
- A form
- Another article
- A support action page
Example: “If your return meets our policy, request your return label here.”
That extra step keeps the conversation moving and prevents unnecessary escalations.
5. Keep tone consistent
AI tools prioritize structure and wording when learning from your Help Center—not emotional tone.
Phrases like “Don’t worry!” or “We’ve got you!” add noise without clarity.
Instead, use simple, action-driven sentences that tell the customer exactly what to do:
- “Click here to request a refund.”
- “Fill out the warranty form to get a replacement.”
A consistent tone keeps your Help Center professional, helps AI deliver reliable responses, and creates a smoother experience for customers.
LLM-friendly Help Centers in action
You don’t need hundreds of articles or complex workflows to make your Help Center AI-ready. But you do need clarity, structure, and consistency. These Gorgias customers show how it’s done.
Little Words Project: Simple formatting that boosts instant answers
Little Words Project keeps things refreshingly straightforward. Their Help Center uses short paragraphs, descriptive headers, and tightly scoped articles that focus on a single intent, like returns, shipping, or product care.
That makes it easy for AI Agent to scan the page, pull out the right facts, and return accurate answers on the first try.
Their tone stays friendly and on-brand, but the structure is what shines. Every article flows from question → answer → next step. It’s a minimalist approach, and it works. Both for customers and the AI reading alongside them.
Dr. Bronner’s: Making tools work for the team
Customer education is at the heart of Dr. Bronner’s mission. Their customers often ask detailed questions about product ingredients, packaging, and certifications. With Gorgias, Emily and her team were able to build a robust Help Center that helped to proactively give this information.
The Help Center doesn't just provide information. The integration of interactive Flows, Order Management, and a Contact Form automation allowed Dr. Bronner’s to handle routine inquiries—such as order statuses—quickly and efficiently. These kinds of interactive elements are all possible out-of-the-box, no IT support needed.
Ekster: Building efficiency through automation and clarity
When Ekster switched to Gorgias, the team wanted to make their Help Center work smarter. By writing clear, structured articles for common questions like order tracking, returns, and product details, they gave both customers and AI Agent the information needed to resolve issues instantly.
"Our previous Help Center solution was the worst. I hated it. Then I saw Gorgias’s Help Center features, and how the Article Recommendations could answer shoppers’ questions instantly, and I loved it. I thought: this is just what we need." —Shauna Cleary, Head of Ecommerce at Ekster
The results followed fast. With well-organized Help Center content and automation built around it, Ekster was able to scale support without expanding the team.
“With all the automations we’ve set up in Gorgias, and because our team in Buenos Aires has ramped up, we didn’t have to rehire any extra agents.” —Shauna Cleary, Head of Ecommerce at Ekster
Learn more: How Ekster used automation to cover the workload of 4 agents
Rowan: Clean structure that keeps customers (and AI) on track
Rowan’s Help Center is a great example of how clear structure can do the heavy lifting. Their FAQs are grouped into simple categories like piercing, shipping, returns, and aftercare, so readers and AI Agent can jump straight to the right topic without digging.
For LLMs, that kind of consistency reduces guesswork. For customers, it creates a smooth, reassuring self-service experience.
TUSHY: Balancing brand voice with automation
TUSHY proves you can maintain personality and structure. Their Help Center articles use clear headings, direct language, and brand-consistent tone. It makes it easy for AI Agent to give accurate, on-brand responses.
“Too often, a great interaction is diminished when a customer feels reduced to just another transaction. With AI, we let the tech handle the selling, unabashedly, if needed, so our future customers can ask anything, even the questions they might be too shy to bring up with a human. In the end, everybody wins!" —Ren Fuller-Wasserman, Senior Director of Customer Experience at TUSHY
Quick checklist to audit your Help Center for AI
Ready to put your Help Center to the test? Use this five-point checklist to make sure your content is easy for both customers and AI to navigate.
1. Are your articles scannable with clear headings?
Break up long text blocks and use descriptive headers (H2s, H3s) so readers and AI Agent can instantly find the right section.
2. Do you define conditions with “if/when/then” phrasing?
Spell out what happens in each scenario. This logic helps AI Agent decide the right next step without second-guessing.
3. Do you cover your top escalation topics?
Make sure your Help Center includes complete, structured articles for high-volume issues like order status, returns, and refunds.
4. Does each article end with a clear next step or link?
Close every piece with a call to action, like a form, related article, or support link, so neither AI nor customers hit a dead end.
5. Is your language simple, action-based, and consistent?
Use direct, predictable phrasing. Avoid filler like “Don’t worry!” and focus on steps customers can actually take.
By tweaking structure instead of your content, it’s easier to turn your Help Center into a self-service powerhouse for both customers and your AI Agent.
Make your Help Center work smarter
Your Help Center already holds the answers your customers need. Now it’s time to make sure AI can find them. A few small tweaks to structure and phrasing can turn your existing content into a powerful, AI-ready knowledge base.
If you’re not sure where to start, review your Help Center with your Gorgias rep or CX team. They can help you identify quick wins and show you how AI Agent pulls information from your articles.
Remember: AI Agent gets smarter with every structured doc you publish.
Ready to optimize your Help Center for faster, more accurate support? Book a demo today.
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The Power of Suggestion: Why Subtle Cues Create Better Conversations
TL;DR:
- Suggestion turns browsing into buying by gently guiding action instead of forcing it.
- Fewer, clearer choices reduce decision fatigue and help shoppers move forward with confidence.
- A well-timed prompt with a friendly tone can make automation feel like a real conversation.
- Good design earns trust by being subtle, approachable, and easy to engage with.
- Small, thoughtful cues create moments of connection that make shoppers feel understood.
Shopping today isn’t a linear funnel. It’s a fluid conversation. Browse → question → help → buy → return → repeat.
Every step is a dialogue between the shopper’s intent and the brand’s response.
But what bridges the gap between “just looking” and “I’m buying” isn’t persuasion or urgency — it’s suggestion: the subtle design, timing, and language cues that guide action without forcing it.
When done well, suggestion becomes the architecture of trust. It’s also the best way to make AI-powered experiences feel human-first, not tech-first.
This article explores how the power of suggestion — rooted in behavioral psychology and UX design — shapes modern conversational commerce.
Why suggestion matters in the age of conversational commerce
The average ecommerce shopper faces thousands of micro-decisions from the moment they land on a site. Which product? Which variant? Which review to trust? Which shipping method? Each one adds cognitive weight.
Psychologist Barry Schwartz coined the term The Paradox of Choice to describe how abundance often leads to paralysis. In his research, participants faced with too many options were less likely to make a choice and less satisfied when they did.
In ecommerce, that means overload costs conversions. When shoppers must evaluate too many variables, they hesitate, second-guess, or abandon.
Shoppers today expect empathy and ease, not persuasion. When you suggest rather than push, you signal empathy and support.
This is especially important for conversational commerce. Suggestion humanizes automation by making AI interactions feel like conversations rather than transactions.
When you push and persuade, you create a memorable experience for customers — but it’s not the kind you want them to remember.
One Reddit thread perfectly captures the problem: a user tried to cancel their Thrive Market membership and had to ask nine times before the chatbot complied.
Each time, the AI assistant tried to talk them out of it (offering deals, guilt-tripping responses, or irrelevant messages) until the customer’s frustration boiled over.
The thread exploded not just because it was mildly infuriating, but because it illustrated what customers fear most about automation: a lack of empathy.
Suggestion is how you design for trust, ease, and interaction. And for ecommerce and CX professionals, suggestion bridges browsing and buying by prompting dialogue in a gentle, psychologically sound way.
5 ways to use suggestion with agentic AI
The magic of suggestion is that it works with human psychology, not against it. It bridges the space between what a shopper wants to do and what helps them do it.
That’s the foundation of the Fogg Behavior Model, developed by Stanford’s Dr. BJ Fogg. The model states that behavior happens when three things intersect:
- Motivation — the user wants to do something.
- Ability — they can do it easily.
- Prompt — they’re nudged at the right moment.
When these three align, the likelihood of action skyrockets.
In conversational commerce, suggestion is the gentle push that turns intent into interaction.
Below are five ways to apply suggestion with agentic AI (think chat, assistants, and marketing tools) to drive trust, dialogue, and conversion.
1. Build trust with a friendly invitation
A first impression shapes the entire interaction.
A greeting like “Need help?” or “Looking for something special?” signals availability without applying pressure. It’s the digital equivalent of a store associate smiling and saying, “Let me know if you need anything.”
This works because of linguistic framing, which is a form of persuasive language that subtly shapes how people interpret intent.
- Sentences using personal pronouns (“you,” “we”) increase perceived warmth and empathy.
- Questions (vs. imperatives) activate a conversational schema in the brain, inviting a cooperative response.
- Short, low-stakes phrasing signals that engagement is voluntary.
In practice, this means:
- Replace “Start chat now” with “Need a hand finding the right fit?”
- Use punctuation and tone cues that convey friendliness.
- Let the chat invite linger rather than pop up suddenly — this gives users agency.
Take a look at Glamnetic. Its shopping assistant sits at the bottom-right corner of every page. While shoppers scroll on the homepage, a prompt appears: “Shop with AI.” It’s transparent about being an AI chat, but subtle enough to be there for shoppers when they’re ready to use it at their own leisure.
Gorgias Shopping Assistant is an easy way to do this. At the right moment, Shopping Assistant appears with a greeting such as “Need help?” or “Chat with our AI!” It’s friendly, low-pressure, optional, more “Hey I’m here if you need” than “Buy now!”
2. Make decisions easier by offering fewer choices
If you’ve ever scrolled through 80 product filters and given up, you’ve experienced choice overload. This is the Paradox of Choice in action:
More options = higher cognitive effort = lower satisfaction.
Suggestion works because it reduces mental effort. When an AI assistant limits quick-reply options to just a few (say, “Long sleeve,” “Short sleeve,” “Sleeveless”), it transforms chaos into clarity.
Each small tap provides forward momentum, a concept known as the goal-gradient effect: the closer we feel to completing a goal, the faster and more positively we act.
How can you apply this to agentic AI?
- Keep quick replies between 3–5 choices — enough to feel personalized, not overwhelming.
- Present them as progressive steps, not isolated decisions (e.g., “Show me styles” → “Show me colors” → “Add to cart”).
- Always include a “Something else” or “Other” option to preserve user autonomy.
- Refresh options dynamically based on prior selections — a technique known as choice scaffolding.
Gorgias’s Shopping Assistant does this well, surfacing only the most relevant next steps. Instead of forcing open-ended typing, it guides shoppers through mini-decisions that build confidence. Here’s an example from Okanui, showing four clear options to reply to Shopping Assistant.
3. Encourage interaction with a user-friendly design
Before a shopper reads a single word of text, their brain has already judged whether your interface feels safe to engage with.
That’s the Aesthetic–Usability Effect — when people perceive something as visually appealing, they assume it will be easier and more trustworthy to use.
Design psychologist Don Norman put it best: “Attractive things work better because they make people feel better.”
Here’s why visual subtlety matters:
- Rounded edges and soft shapes signal continuity and friendliness (the human brain associates curves with safety; sharp angles with danger).
- Muted palettes and neutral contrast lower visual stress, allowing the interface to fade into the background until needed.
- Micro-animations — like a gentle glow or slide-in — trigger attention without hijacking focus.
- Minimizable elements give users a sense of control, reducing resistance to engagement.
OSEA’s product description page is a beautiful example of unintrusive design in action. The buttons have rounded edges, the 10% offer isn’t covering other page elements, and the chat sits in the bottom-right corner, making it easily accessible if a shopper has questions about the product.
4. Match your timing to the customer’s pace
Timing is everything in suggestion-based design. Even the most thoughtful interaction will fail if it appears at the wrong moment.
That’s where the Fogg Behavior Model becomes tactical: Behavior = Motivation × Ability × Prompt
When shoppers are motivated (interested in a product) and able (engaging is easy), a well-timed prompt (chat bubble, message, or offer) turns potential into action.
But mistime it, and you risk the opposite. A chat that appears too early feels like spam. Too late, and the user’s interest window closes.
Here’s how to align the timing sweet spot:
- Use behavioral triggers: Fire prompts after meaningful engagement (e.g., 25–30 seconds on a product page, reaching 70% scroll depth, or idling for 15 seconds).
- Match prompt to context: Offer size guidance on apparel pages, warranty info near checkout, or live help on return pages.
- Respect frequency: One well-placed nudge beats five redundant ones.
- Localize timing: Adjust based on device and location. Mobile users often need faster cues due to shorter browsing sessions.
Gorgias Shopping Assistant does all of the above. Using context — such as the current page, conversational context, and cart behavior — helps the AI trigger prompts like “Need help choosing a size?” or “Have questions about shipping?”
5. Aim to educate, reassure, or inspire — not just sell
Every small suggestion — a phrase, a button shape, a pause, a tone — creates what behavioral economists call a moment of micro-trust.
Individually, these moments may feel insignificant. But together, they turn a static interface into a relationship.
When greeting, choices, design, and timing align, conversation becomes the natural outcome — not the goal. That’s what conversational commerce gets right: it reframes success from “did they convert?” to “did they connect?”
For CX teams, this shift requires designing for the emotional continuity of the experience:
- Did each prompt respect the shopper’s autonomy?
- Did the interaction feel like a two-way exchange?
- Did the system adapt to intent rather than dictate it?
We love this example from Perry Ellis to drive this tip home:
Designing for trust in an age of AI
As AI continues to shape how people shop, brands face a choice: Design for control, or design for trust.
Suggestion is the path to the latter.
The right cue, delivered at the right time, reminds people that even in automated spaces, there’s still room for empathy and understanding.
Gorgias was built on the belief that great commerce starts with conversation, not conversion.
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How to Prep for Peak Season: BFCM Automation Checklist
A no-fluff checklist to automate your support, streamline operations, and boost CX before the BFCM surge hits.
TL;DR:
- Start by cleaning up your Help Center. Update your articles based on last year’s data, using plain language and clear policy details to boost self-service.
- Use automations to streamline ticket routing and support efficiency. Set rules for tagging, escalation, and inbox views, so your team can respond faster.
- Prep your macros, AI, and staffing plan in advance. Build responses for top FAQs, train AI on the right sources, and forecast agent needs to avoid burnout.
- Automate logistics, upselling, and QA to stay ahead. From showing shipping timelines to flagging low-quality responses, automation ensures smooth operations and more revenue during peak season.
Getting ready for that yearly ticket surge isn’t only about activating every automation feature on your helpdesk, it’s about increasing efficiency across your entire support operations.
This year, we’re giving you one less thing to worry about with our 2025 BFCM automation guide. Whether your team needs a tidier Help Center or better ticket routing rules, we’ve got a checklist for every area of the customer experience brought to you by top industry players, including ShipBob, Loop Returns, TalentPop, and more.
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2025 BFCM automation checklist
- Tidy up your Help Center
- Audit your docs
- Review last year’s BFCM data to find your must-have articles
- Update your policy details
- Edit content using easy-to-understand language
- Expedite your ticket routing automations
- Set up automated ticket tags
- Create an inbox view for each category
- Set escalation rules for urgent tickets
- Set up mandatory Ticket Fields
- Prep your macros and AI agent
- Write macros for your top FAQs
- Train your AI on the right sources
- Define the limits of what AI should handle
- Forecast your BFCM staffing needs
- Use ticket volume to estimate the number of agents
- Plan extra coverage with automation or outsourcing
- Run agent training sessions on BFCM protocols
- Map out your logistics processes
- Negotiate better rates and processing efficiencies
- Automate inventory reorder points
- Build contingency plans for disruptions
- Show shipping timelines on product pages
- Maximize profits with upselling automations
- Guide shoppers with smart recommendations
- Suggest alternatives when items are out of stock
- Engage hesitant shoppers with winback discounts
- Keep support quality high with QA automations
- Automate ticket reviews with AI-powered QA
- Track both agent and AI responses
- Turn QA insights into coaching opportunities
Tidy up your Help Center
Your customer knowledge base, FAQs, or Help Center is a valuable hub of answers for customers’ most asked questions. For those who prefer to self-serve, it’s one of the first resources they visit. To ensure customers get accurate answers, do the following:
- Audit your docs
- Review last year’s BFCM data to find your must-have articles
- Update your policy details
- Edit content using easy-to-understand language
1. Audit your docs
Take stock of what’s currently in your database. Are you still displaying low-engagement or unhelpful articles? Are articles about discontinued products still up? Start by removing outdated content first, and then decide which articles to keep from there.
Related: How to refresh your Help Center: A step-by-step guide
2. Review last year’s BFCM data to find your must-have articles
Are you missing key topics, or don’t have a database yet? Look at last year’s tickets. What were customers’ top concerns? Were customers always asking about returns? Was there an uptick in free shipping questions? If an inquiry repeats itself, it’s a sign to add it to your Help Center.
3. Update your policy details
An influx of customers means more people using your shipping, returns, exchanges, and discount policies. Make sure these have accurate information about eligibility, conditions, and grace periods, so your customers have one reliable source of truth.
Personalization tip: Loop Returns advises adjusting your return policy for different return reasons. With Loop’s Workflows, you can automatically determine which customers and which return reasons should get which return policies.
Read more: Store policies by industry, explained: What to include for every vertical
4. Edit content using easy-to-understand language
Customers want fast answers, so ensure your docs are easy to read and understand. Titles and answers should be clear. Avoid technical jargon and stick to simple sentences that express one idea. To accelerate the process, use AI tools like Grammarly and ChatGPT.
No time to set up a Help Center? Gorgias automatically generates Help Center articles for you based on what people are asking in your inbox.
Expedite your ticket routing automations
Think of ticket routing like running a city. Cars are your tickets (and customers), roads are your inboxes, and traffic lights are your automations and rules. The better you maintain these structures, the better they can run on their own without needing constant repairs from your CX team.
Here’s your ticket routing automation checklist:
- Tag every ticket
- Create views for each category you need (VIP, Returns, Troubleshooting, etc.)
- Set escalation rules for urgent tickets
- Set up mandatory Ticket Fields
1. Set up automated ticket tags
Instead of asking agents to tag every ticket, set rules that apply tags based on keywords, order details, or message type. A good starting point is to tag tickets by order status, returns, refunds, VIP customers, and urgent issues so your team can prioritize quickly.
Luckily, many helpdesks offer AI-powered tags or contact reasons to reduce manual work. For example, Gorgias automatically detects a ticket’s Contact Reason. The system learns from past interactions, tagging your tickets with more accuracy each time.
2. Create an inbox view for each category
Custom or filtered inbox views give your agents a filtered and focused workspace. Start with essential views like VIP customers, returns, and damages, then add specialized views that match how your team works.
If you’re using conversational AI to answer tickets, views become even more powerful. For example, you might track low CSAT tickets to catch where AI responses fall short or high handover rates to identify AI knowledge gaps. The goal is to reduce clutter so agents can focus on delivering support.
3. Set escalation rules for urgent tickets
Don’t get bogged down in minor issues while urgent tickets sit unanswered. Escalation rules make sure urgent cases are pushed to the top of your inbox, so they don’t risk revenue or lead to unhappy customers.
Tickets to escalate to agents or specialized queues:
- Lost packages
- Damaged items
- Defective items
- Failed payments
- Open tickets without a follow-up
4. Set up mandatory Ticket Fields to get data right off the bat
Ticket Fields add structure by requiring your team to capture key data before closing a ticket. For BFCM, make fields like Contact Reason, Resolution, and Return Reason mandatory so you always know why customers reached out and how the issue was resolved.
For CX leads, Ticket Fields removes guesswork. Instead of sifting through tickets one by one, you’ll have clean data to spot trends, report on sales drivers, and train your team.
Pro Tip: Use conditional fields to dig deeper without overwhelming agents. For example, if the contact reason is “Return,” automatically prompt the agent to log the return reason or product defect.
Prep your macros and AI agent
Macros and AI Agent are your frontline during BFCM. When prepped properly, they can clear hundreds of repetitive tickets. The key is to ensure that answers are accurate, up-to-date, and aligned with what you want AI to handle.
- Write macros for your most common FAQs
- Train your AI on the right sources
- Define the limits of what AI should handle
1. Write macros for your top FAQs
Customers will flood your inbox with the same questions: “Where’s my order?” “When will my discount apply?” “What’s your return policy?” Write macros that give short, direct answers up front, include links for details, and use placeholders for personalization.
Bad macro:
- “You can track your order with the tracking link. It should update soon.”
Good macro:
- “Hi {{customer_firstname}}, you can track your order here: {{tracking_link}}. Tracking updates may take up to 24 hours to appear. Here’s our shipping policy: [Help Center link].”
Pro Tip: Customers expect deep discounts this time of year. BPO agency C(x)atalyze recommends automating responses to these inquiries with Gorgias Rules. Include words such as “discount” AND “BFCM”, “holiday”, “Thanksgiving”, “Black Friday”, “Christmas”, etc.
2. Train your AI on the right sources
AI is only as good as the information you feed it. Before BFCM, make sure it’s pulling from:
- Your Help Center with updated FAQs and policies
- Internal docs on return windows, promos, and shipping cutoffs
- Product catalogs with the latest details and stock info
- BFCM-specific resources like discount terms or extended support hours
Double-check a few responses in Test Mode to confirm the AI is pulling the right information.
3. Define the limits of what AI should handle
Edge cases and urgent questions need a human touch, not an automated reply. Keep AI focused on quick requests like order status, shipping timelines, or promo eligibility. Complex issues, like defective products, VIP complaints, and returns, can directly go to your agents.
Pro Tip: In Gorgias AI Agent settings, you can customize how handovers happen on Chat during business hours and after hours.
Forecast your BFCM staffing needs
Too few agents and you prolong wait times and miss sales. Too many and you’ll leave your team burned out. Capacity planning helps you find the balance to handle the BFCM surge.
1. Use ticket volume to estimate the number of agents
Use your ticket-to-order ratio from last year as a baseline, then apply it to this year’s forecast. Compare that number against what your team can realistically handle per shift to see if your current staffing plan holds up.
Read more: How to forecast customer service hiring needs ahead of BFCM
2. Plan extra coverage with automation or outsourcing
You still have options if you don’t have enough agents helping you out. Customer service agency TalentPop recommends starting by identifying where coverage will fall short, whether that’s evenings, weekends, or specific channels. Then decide whether to increase automation and AI use or bring in temporary assistance.
3. Run agent training sessions on BFCM protocols
Before the holiday season, run refreshers on new products, promos, and policy changes so no one hesitates when the tickets roll in. Pair training with cheat sheets or an internal knowledge base, giving your team quick access to the answers they’ll need most often.
Map out your logistics processes
Expect late shipments, low inventory, and more returns than usual during peak season. With the proper logistics automations, you can stay ahead of these issues while reducing pressure on your team.
ShipBob and Loop recommend the following steps:
- Negotiate better rates and processing efficiencies
- Automate your reverse logistics
- Connect your store, 3PL, and WMS
- Automate inventory reorder points
- Show shipping timelines on product pages
1. Negotiate better rates and processing efficiencies
Shipping costs add up fast during peak season. Work with your 3PL or partners like Loop Returns to take advantage of negotiated carrier rates and rate shopping tools that automatically select the most cost-effective option for each order.
2. Automate inventory reorder points
To maintain a steady supply of products, set automatic reorder points at the SKU level so reorders are triggered once inventory dips below a threshold. More lead time means fewer ‘out of stock’ surprises for your customers.
3. Build contingency plans for disruptions
Bad weather, delays, or unexpected demand can disrupt shipping timelines. Create a playbook in advance so your team knows exactly how to respond when things go sideways. At minimum, your plan should cover:
- Weather disruptions - Do you have a backup plan if carriers can’t pick up shipments due to storms or severe conditions?
- Carrier overloads - Which alternative carriers or routes can you switch to if primary partners are at capacity?
- Inventory shortages - How will you handle overselling, low stock alerts, or warehouse imbalances?
- Demand drop-offs - How will you reallocate inventory if BFCM sales don’t match forecasts?
4. Show shipping timelines on product pages
Customers want to know when their order will arrive before they hit checkout. Add estimated delivery dates and 2-day shipping badges directly on product pages. These cues help shoppers make confident decisions and reduce pre-purchase questions about shipping times.
Pro Tip: To keep those timelines accurate, build carrier cutoff dates into your Black Friday logistics workflows with your 3PL or fulfillment team. This allows you to avoid promising delivery windows your carriers can’t meet during peak season.
Maximize profits with upselling automations
You’ve handled the basics, from ticket routing to staffing and logistics. Now it’s time to go beyond survival. Upselling automations create an end-to-end experience that enhances the customer journey, shows them products they’ll love, and makes it easy to buy more with confidence. To put them to work:
- Guide shoppers with smart recommendations
- Suggest alternatives when items are out of stock
- Engage hesitant shoppers with winback discounts
1. Guide shoppers with smart recommendations
BFCM puts pressure on customers to find the right deal fast, but many don’t know what they’re looking for. Make it easier for them with macros that point shoppers to bestsellers or curated bundles. For a more advanced option, conversational AI like Gorgias Shopping Assistant can guide browsers on their own, even when your agents are offline.
2. Suggest alternatives when items are out of stock
No need to damage your conversion rate just because customers missed the items they wanted. Automations can recommend similar or complementary products, keeping customers engaged rather than leaving them empty-handed.
If an item is sold out, set up automations to:
- Suggest similar items like another size, color, or variation of the same product.
- Highlight premium upgrades such as a newer model or higher-value version that’s in stock.
- Cross-sell and offer bundles to keep the order valuable even without the original item.
- Notify customers about restocks by letting shoppers sign up for back-in-stock alerts.
3. Engage hesitant customers with winback discounts
Automations can detect hesitation through signals like abandoned carts, long checkout times, or even customer messages that mention keywords such as “too expensive” or “I’ll think about it.” In these cases, trigger a small discount to encourage the purchase.
You can take this a step further with conversational AI like Gorgias Shopping Assistant, which detects intent in real time. If a shopper seems uncertain, it can proactively offer a discount code based on the level of their buying intent.
Keep support quality high with QA automations
During BFCM, speed alone is not enough. Customers expect accurate, helpful, and on-brand responses, even when volume is at its highest. QA automations help you prioritize quality by reviewing every interaction automatically and flagging where standards are slipping. To make QA part of your automation prep:
- Automate ticket reviews with AI-powered QA
- Track both agent and AI responses
- Turn QA insights into coaching opportunities
1. Automate ticket reviews with AI-powered QA
Manual QA can only spot-check a small sample of tickets, which means most interactions go unreviewed. AI QA reviews every ticket automatically and delivers feedback instantly. This ensures consistent quality, even when your team is flooded with requests.
Compared to manual QA, AI QA offers:
- Full coverage: Every ticket is reviewed, not just a sample.
- Instant feedback: Agents get insights right after closing tickets.
- Consistency: Reviews are unbiased and use the same criteria across all interactions.
- Scalability: Works at any ticket volume without slowing down your team.
2. Track both agent and AI responses
Customers should get the same level of quality no matter who replies. AI QA evaluates both human and AI conversations using the same criteria. This creates a fair standard and gives you confidence that every interaction meets your brand’s bar for quality.
3. Turn QA insights into coaching opportunities
QA automation is not just about grading tickets. It highlights recurring issues, unclear workflows, or policy confusion. Use these insights to guide targeted coaching sessions and refine AI guidance so both humans and AI deliver better results.
Pro Tip: Pilot your AI QA tool with a small group of agents before peak season. This lets you validate feedback quality and scale with confidence when BFCM volume hits.
Give your ecommerce strategy a boost this holiday shopping season
The name of the game this Black Friday-Cyber Monday isn’t just to get a ton of online sales, it’s to set up your site for a successful holiday shopping season.
If you want to move the meter, focus on setting up strong BFCM automation flows now.
Gorgias is designed with ecommerce merchants in mind. Find out how Gorgias’s time-saving CX platform can help you create BFCM success. Book a demo today.
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AI Agent Keeps Getting Smarter (Here’s the Data to Prove It)
2025 was a big year for AI Agent—and the data proves just how much smarter it’s become.
TL;DR:
- AI Agent is getting more accurate every month: It’s improved 14.9% this year thanks to better LLMs, constant updates, and user feedback.
- It writes more correctly than most humans: With a 4.77/5 language score, it’s nailing grammar, tone, and clarity better than human agents.
- It’s empathetic, too: AI Agent now shows more empathy and listens better than human agents.
- Brands are gaining confidence fast: Quality scores jumped from 57% to 85% in just a few months, and CX teams are noticing.
- Customers are almost as happy with AI as with humans: AI Agent’s CSAT is just 0.6 points shy of human agents’ average CSAT.
Handing trust over to AI can be intimidating. One off-brand reply and you undo the reputation and customer loyalty you’ve worked so hard to build.
That’s why we’ve made accuracy our top priority with Gorgias AI Agent.
For the past year, the Gorgias team has been hard at work fulfilling the pressing demand for accuracy and speed. AI Agent is getting smarter, faster, and more reliable, and merchants and their customers are happier with the output.
Here’s the data.
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AI Agent delivers more accurate answers than ever
This year, AI Agent’s accuracy rose from 3.55 to 4.08 out of 5, a 14.9% improvement from January. This average score is based on CX agents' ratings of AI Agent responses in the product, on a scale of 1 to 5.
In the past year, we’ve improved knowledge retrieval, added new integrations, expanded reporting features, and asked for more feedback in-product.
We saw the steadiest leap in July, right after the release of GPT-5. AI Agent began reaching levels of consistency and accuracy that agents could trust.
AI Agent writes with more linguistic precision than humans
Clear, easy-to-understand language helps people trust what they’re reading. Website Planet found that 85% more visitors bounced from a page when typos were present. That’s why we’ve made it a priority for AI Agent to respond to customers with correct grammar, syntax, and tone of voice.
The efforts have paid off: AI Agent scores a high 4.77 out of 5 in language proficiency compared to 4.4 for human agents. The result is error-free messages that are easy to read and consistent with your brand vocabulary.
AI Agent shows that empathy can be scaled
Accuracy isn’t just about saying the right thing; it’s also about how a message lands. For that reason, we track AI Agent’s communication quality. Did it reply with empathy? Did it exhibit active listening and respond with clear phrasing?
Recently, AI Agent is even scoring slightly above humans with 4.48 out of 5 in communication, compared to 4.27. This means AI Agent captures the nuance of every message by considering the background context and acknowledging customer frustration before it gives customers a solution.
AI Agent resolves every part of a customer’s question
What happens when a ticket ends without a clear answer? Customers feel neglected and leave the chat still unsure. This can make your brand look out of touch, leaving customers with the lingering feeling that you don’t care.
But don’t worry, we built AI Agent to close that loop every time: AI Agent’s resolution completeness score sits at a perfect 1 out of 1, compared to 0.99 out of 1 for human agents.
In practice, this means customers feel cared for and understood, while your team receives fewer follow-ups, giving them more time to focus on strategic, high-priority tasks.
Read more: A guide to resolution time: How to measure and lower it
Brand confidence is on the rise
Building a great product is a two-way conversation between our engineers and the people who use it. We listen, review feedback, ship changes, and measure what improves.
From January to November 2025, AI Agent quality rose from about 57% to 85%. August was the first big step up, and September kept climbing. Brands are seeing fewer low-quality or incorrect answers and more steady decisions.
This is proof that merchants and their shoppers are witnessing the improvements we’ve been making, for the better.
Related: The engineering work that keeps Gorgias running smoothly
Shoppers are rating AI support almost as high as human support
At the end of the day, what matters is how customers feel when they talk to support. Do they trust the answer? Do they find it helpful? Are they running into more friction with AI than without it?
Our data shows that customers are appreciating AI assistance more and more. Since the start of 2025, AI Agent on live chat has gotten a CSAT score 40% closer to the average CSAT of human agents. For email, the gap has narrowed by about 8%.
The goal is to eventually achieve a gap of zero. At this point, AI’s support quality is indistinguishable from that of humans. To get there, we’re focusing on practical improvements like accuracy, clear language, complete answers, and better handoff rules.
How we measure CSAT gap: The CSAT gap is calculated by subtracting AI CSAT from human CSAT. When the number is closer to zero, AI is catching up. When it’s negative, AI is still below human results.
Reliable AI interactions start with accuracy
Behind every accurate AI reply is a team that cares about the details. AI Agent doesn’t make up answers—it follows what you teach it. The more effort your team puts into maintaining an up-to-date Help Center and Guidance, the better the customer experience becomes.
As we look ahead to 2026, we’re focused on fine-tuning knowledge retrieval logic, refining Guidance rules, and continuously learning from feedback from you and your customers.
We’re proud of the strides AI Agent continues to make, and can’t wait for more brands to experience the accuracy for themselves.
Want to see how AI Agent delivers exceptional accuracy without sacrificing speed? Book a demo or start a trial today.
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Why Faster Isn’t Always Better: The Pitfalls of Fast-Only Customer Support
Speed has become AI's main selling point in CX, but that narrow focus creates long-term problems down the line.
TL;DR:
- Fast ≠ good. Chasing faster replies without accuracy or empathy leads to frustrated customers, burned-out agents, and declining CSAT.
- Speed-only AI backfires. Quick but wrong responses damage trust and increase ticket volume.
- Train your AI like a new hire. The best results come when AI learns your tone, workflows, and policies—not when it’s treated as plug-and-play.
- Balance speed with quality. Brands like Boody, Cocorico, and TUSHY show that when AI is trained thoughtfully, teams can scale automation and keep the human touch.
- Adopt an accuracy-first mindset. The future of CX belongs to brands that prioritize reliability, empathy, and consistency over being the fastest.
Speed gets all the glory in customer support. The faster the reply, the happier the customer. That’s not always true. When CX teams chase response times at the expense of accuracy or empathy, they often end up with the opposite effect. Frustrated customers, burned-out agents, and slipping CSAT are common when speed is the only priority.
As more teams adopt AI tools that promise instant results, the risk grows. Quick responses mean nothing if they’re wrong or robotic.
In this post, we’ll unpack why “fast” doesn’t always mean “good” and how an accuracy-first approach to AI leads to better support, and stronger customer relationships in the long run.
The speed trap: why CX teams fall for it
Response time has become the go-to measure of “good” support. Dashboards light up green when messages are answered in seconds, and teams celebrate shaved-down handle times.
But focusing on speed alone can create a dangerous blind spot.
When “fast” becomes the only KPI that matters, CX leaders make speed-at-all-costs decisions. They may roll out untrained AI tools, overuse canned replies, or push agents to close tickets before solving real problems.
On paper, the metrics look great. In reality, customer sentiment quietly drops.
It’s no surprise that 86% of consumers say empathy and human connection matter more than a quick response when it comes to excellent customer experience.
Fast support might satisfy your dashboard, but thoughtful, accurate service is what satisfies your customers.
Pitfall #1: Maximizing speed and sacrificing quality
A chatbot replies instantly, but gives the wrong answer. The customer follows up again, frustrated. Now your ticket volume has doubled, your agents are backlogged, and the customer’s confidence in your brand has dropped.
That’s the hidden cost of speed-first support. When teams prioritize quick replies over correct ones, CSAT falls, costs rise, and trust erodes. Customers remember the experience, not the timestamp.
They want to feel understood and confident that their issue is solved. A fast reply that misses the mark doesn’t deliver reassurance, empathy, or clear next steps. It’s not speed they value. It’s resolution, accuracy, and a sense that someone genuinely cared enough to get it right.
Bad AI answers sting more than slow ones because they feel careless. Especially when they repeat the same mistakes. Accuracy builds credibility; speed without it breaks it.
How Boody delivers high-quality replies while maintaining speed
Boody, for example, found the balance. With AI trained on their tone of voice and workflows, they reduced response times from hours to seconds while maintaining a high CSAT score and freeing agents for meaningful work.
The bamboo apparel brand uses Gorgias AI Agent to reassure the customer that someone is on the way to help, especially for urgent situations. It’s been instrumental in collecting preliminary information for more nuanced situations, like photos and product numbers for warranty claims.
As Boody’s CX Manager, Myriam Ferraty, explained the key is using AI to provide instant low-effort answers when customers need a prompt response.
“If a customer reaches out about product feedback or issues, AI Agent prompts the customer to give us all the information we need. When an agent gets to the ticket, they can jump into solution mode right away.” —Myriam Ferraty, CX Manager at Boody
Boody found a way to avoid the “fast but frustrating” trap by pairing speed with quality, and the numbers prove it:
- 99.88% faster first-response times: Boody’s AI Agent reduced average response times from 7 hours to just 31 seconds.
- 9+ hours shorter resolution times: Within one month of implementation, resolution times dropped significantly while accuracy stayed high.
- 26% of all interactions handled by AI: Their AI agent took on repetitive queries, freeing human agents for higher-value conversations.
- 10% revenue lift from support: With agents focused on community engagement and brand experience, customer interactions began driving measurable revenue.
These results show what happen when CX teams train AI thoughtfully, it can becomes a trusted extension of the support team, instead of only increasing speed booster.
Takeaway: Fast and good is possible, but only when your AI is trained, guided, and measured for precision, not just speed.
Read more: How CX leaders are actually using AI: 6 must-know lessons
Pitfall #2: Treating AI as plug-and-play
Many CX teams expect AI to “just work” out of the box. They install a shiny new tool, flip the switch, and hope it starts solving tickets overnight. But AI isn’t a magic button. It’s a new team member. And like any new hire, it needs training, context, and feedback to perform well.
Untrained AI can quickly go off-script. It might give inconsistent answers, slip into the wrong tone, or worse, hallucinate information altogether. The consequences are confused customers, damaged trust, and more cleanup work for your human agents.
AI performs best when it’s trained on your brand voice, policies, and knowledge base. The best CX teams don’t settle for default settings or cookie-cutter templates. They invest time to train their AI. That’s what turns it from a generic chatbot into a genuine brand representative.
How Cocorico’s well-trained AI led to customer trust (and laughter)
Cocorico, a French fashion brand, shows what this looks like in practice. Instead of setting AI loose, their team invested time in teaching it how to communicate naturally and on-brand. Within just a few months, they achieved:
- 48% automation rate, handling nearly half of all customer requests.
- 22-second average first-response time, without losing personalization.
At first, Cocorico’s Ecommerce Manager, Margaux Pourrain, admitted she was hesitant to trust AI, “We were apprehensive about launching AI. On the technical side, I thought, ‘Would the AI respond professionally? Would it respond appropriately? Could it create more work by requiring constant verification?’ On the customer experience side, I was nervous it would feel impersonal.”
Her doubts didn’t last long. Once trained on Cocorico’s workflows and brand tone, AI transformed how the team engaged with customers, “AI Agent responds so personally that customers often don’t realize they’re talking to AI. We’ve even seen customers interacting playfully and joking around with Maurice.”
Takeaway: With proper training and oversight, AI can become a trusted teammate that enhances customer experience rather than diluting it.
Read more: How AI Agent works & gathers data
Pitfall #3: Losing the human touch
When CX teams chase faster replies above all else, it’s easy to forget that great support involves connection. Agents and AI start focusing on closing tickets instead of solving problems.
Speed-only goals create fast but flat experiences that technically help customers but don’t feel human.
Over-automation can strip away the warmth and personality that make a brand memorable. Customers might get an answer in seconds, but if it lacks empathy or context, trust takes a hit. Research supports that brands that prioritize emotional intelligence in support interactions see stronger loyalty and retention rates.
How TUSHY keeps their AI playful, not robotic
TUSHY, the bidet brand known for its witty tone, took a more thoughtful approach to automation. With Gorgias Shopping Assistant, pre-sale questions about compatibility, installation, and recommendations are handled automatically. This frees up human agents to focus on relationship-building conversations.
As Ren Fuller-Wasserman, TUSHY’s Senior Director of Customer Experience, explained, keeping conversations authentic was central to their approach:
“Too often, a great interaction is diminished when a customer feels reduced to just another transaction. With AI, we let the tech handle the selling, unabashedly, if needed, so our future customers can ask anything, even the questions they might be too shy to bring up with a human. In the end, everybody wins!”
That human touch has paid off. TUSHY’s Shopping Assistant mirrors their playful brand voice and delivers real results:
- +20% increase in chat conversion rate overall
- 81% higher conversion rate compared with human agents
- 13× ROI from the Shopping Assistant investment
“Shopping Assistant has been a game-changer for our team, especially with the launch of our latest bidet models,” Fuller-Wasserman said. “Expanding our product catalog has given customers more choices than ever, which can overwhelm first-time buyers. Now, they’re increasingly looking to us for guidance on finding the right fit for their home and personal hygiene needs.”
Takeaway: Automation shouldn’t erase your brand’s humanity, it should amplify it. When AI is trained to reflect your tone and values, it can boost both efficiency and emotional connection.
The smarter path forward: accuracy-first AI
The future of customer support doesn’t involve being the fastest. Instead it means being the most reliable. Accuracy-first AI reframes automation from a race to respond into a strategy to build trust.
When customers get the right answer, in the right tone, every time, they’re more likely to stay loyal, even if it takes a few seconds longer.
So what does accuracy-first AI actually look like?
- Starts with training and clear guardrails: Like any new team member, your AI needs onboarding. These guardrails include context, escalation rules, and examples of what “great” looks like.
- Learns from past tickets and feedback: Continuous improvement keeps your AI sharp and aligned with evolving customer expectations.
- Reflects your tone and knowledge base: Every response should sound like you, not a generic script.
- Complements instead of replaces human agents: AI should take the repetitive load so humans can focus on empathy, problem-solving, and connection.
Accuracy-first AI is a mindset shift. Teams that treat AI as a coachable teammate, not a plug-and-play tool, will unlock faster resolutions and higher CSAT in the long run.
Read more: Coach AI Agent in one hour a week: SuitShop’s guide
Build for accuracy, instead of speed
Speed might win you a customer’s attention, but accuracy is what earns their trust. Fast replies mean little if they’re wrong, off-brand, or robotic. The real differentiator in modern CX isn’t how quickly you respond, it’s how effectively you resolve issues and make customers feel understood.
AI should enhance your team’s expertise, not replace it. Train it on your tone, coach it like a new hire, and measure it on quality as much as efficiency.
The brands that will thrive in the AI era won’t always be the fastest. They’ll be the most reliable, human, and consistent.
Looking for AI-led support that’s fast and human? Book a demo with Gorgias to see how accuracy-first automation can elevate your support.
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Further reading
Meet Auto QA: Quality Checks Are Here to Stay
TL;DR:
- Manual QA is time-consuming—Auto QA does the heavy lifting. It frees up team leads by automatically reviewing conversations with accuracy and consistency, so they can focus on improving support.
- Auto QA scores 100% of private text conversations, whether handled by a human or Gorgias AI Agent. It evaluates support quality based on Resolution Completeness, Communication, and Language Proficiency.
- Auto QA supports multiple languages but provides feedback in English. It can assess tickets in any language supported by OpenAI’s GPT-4, ensuring global teams can benefit from automated QA.
- Start with individual meetings before a team-wide rollout of Auto QA. One-on-one conversations help address specific agent concerns and ensure a smooth transition.
Customer satisfaction scores (CSAT) have long been the go-to metric for measuring support quality, with 53% of customer experience leads relying on them. However, CSAT only tells you part of the story.
When customers rate their experience 3 out of 5, what does it really mean? Did they rate the agent’s actions or the company’s policies? Was an agent helpful or inefficient? Did they take unnecessary steps to get to the answer?
Quality assurance checks can fill these gaps, but manual QA is a heavy lift. Team leads often struggle to review more than a small sample of conversations, leaving many issues unchecked.
Auto QA redefines quality assurance for today’s support teams. It transforms QA from a manual task into an automated feedback engine that helps your team deliver excellent support, every single time.
Let's dive into how Auto QA works, how accurate its scoring is, and how you can add it to your support workflow to start improving customer conversations today.
What is Auto QA?
Gorgias Auto QA upgrades the customer service QA process by automatically evaluating 100% of private text conversations, whether handled by a human or AI Agent.
Each message is scored on metrics like Resolution Completeness, Brand Voice, and Accuracy, helping teams fix and address areas of improvement.
With an automated QA process, brands can:
- Save time: Automated quality checks help team leads focus on the most critical tickets.
- Ensure consistency: Both human agents and AI Agent are evaluated with a unified, comprehensive quality score.
- Boost performance: Agents can receive targeted coaching to provide more consistent customer experiences.
- Meet customer expectations: Customers benefit from higher-quality support with quicker resolutions and accurate responses.
How Auto QA works
Let's explore a real-life scenario: A customer reaches out about a product issue, seeking troubleshooting help. Here’s how the interaction unfolds:
Customer: "Hi, my device broke, and I bought it less than a month ago. -Kelly"
Support Agent: "Hi Kelly, please send us a photo or a video so we can determine the issue with your device. -Michael"
The ticket is eventually closed, but the customer doesn't leave a CSAT score.
In this case, Auto QA would provide the following insights:
- Communication Score: 3/5. Reason: The agent's wording could benefit from more empathy.
- Resolution Score: "Complete". Reason: The agent effectively addressed the customer's concerns.
How accurate is Auto QA’s scoring?
Auto QA uses a comprehensive scoring system that evaluates conversations on communication proficiency and knowledge accuracy.
To ensure accuracy, Auto QA only scores interactions with at least 250 characters and messages from both agents and customers. It's also smart enough to filter out automated responses, spam, and bot messages.
Auto QA automatically scores three main aspects:
- Resolution Completeness: Did the agent solve everything the customer asked about? This area is scored with a "Complete" or "Incomplete.” For instance, it correctly marks a ticket as "Complete" when a customer resolves their issue or when there's no clear question to address.
- Communication Quality: How well did the agent listen and show empathy? Uses a 1-5 scale, looking at how well your agents acknowledged a customer’s concerns and communicated the solution.
- Language Proficiency: Did the agent communicate properly? Uses a 1-5 scale to check spelling, grammar, and syntax.
For deeper feedback, certain criteria require manual scoring from team leads:
- Accuracy: How accurate was the information provided by the agent?
- Efficiency: How quickly did the agent handle the ticket? How well did they minimize the number of follow-ups?
- Internal Compliance: How closely did the agent follow your team’s internal processes and brand guidelines?
- Brand Voice: How well did the agent use brand vocabulary, greetings, sign-offs, and tone of voice?
How to integrate Auto QA into your workflow
Whether you're just starting with quality checks or transitioning from manual QA, Auto QA can seamlessly fit into your existing processes. Here's how to get started.
1. Set your standards
What does “good” look like for your team? Review Auto QA's scoring system and decide which metrics matter most for your brand, from Resolution Completeness to Brand Voice. This will help you set realistic targets for your team to work toward.
Tip: Start by prioritizing a couple of areas. This could look like prioritizing a 5/5 Resolution Completeness score while deprioritizing Brand Voice. As your team gets comfortable with Auto QA, you can ramp up to improving Brand Voice.
2. Agree on a scoring system
Since some criteria—Accuracy, Efficiency, Internal Compliance, and Brand Voice—require manual scoring, it’s best to agree on how your team will use the scoring scale.
For example, each score from 1 to 5 receives a distinct piece of feedback. Here’s what that would look for the Efficiency criteria:
- 1/5 stars: Excessive back-and-forth that could have been avoided
- 2/5 stars: Resolution took longer than necessary due to poor process
- 3/5 stars: Average handling time with some unnecessary steps
- 4/5 stars: Quick resolution with minimal back-and-forth
- 5/5 stars: One-touch resolution
3. Prepare your agents
Start rolling out Auto QA through individual meetings with agents rather than overwhelming your team with a general training session. One-on-one conversations allow you to better address each agent's specific questions and concerns. Make sure to cover the following:
- Explain that Auto QA is meant to help make conversations consistent, not police agents
- Explain the scoring criteria and what each score means
- Highlight which criteria agents should prioritize
If regular one-on-one meetings aren't part of your routine, consider introducing Auto QA during your weekly team meetings or through a dedicated training session. Just remember to leave plenty of time for questions and walk through multiple examples to ensure everyone is comfortable with the system.
4. Establish a review schedule
To solidify QA checks, create a simple routine for reviewing Auto QA insights with the Auto QA Report (navigate to Statistics > Auto QA).
- Weekly: Do a quick check of automated scores.
- Monthly: Analyze trends and patterns across conversations.
- Quarterly: Review and adjust quality benchmarks.
5. Act on insights
Once you’ve collected a substantial amount of Auto QA data, there are a few follow-up actions you can take to continue having high-quality conversations:
- Set the example by sharing high-scoring conversations in your team meetings.
- Coach agents individually by reviewing their tickets together. Celebrate high-scoring conversations and provide targeted feedback on areas for improvement. This immediate, personalized approach helps agents grow faster than general training sessions.
- Increase product and policy knowledge by refining internal guidelines on brand voice, escalation processes, and more.
Remember, Auto QA works alongside your existing processes—it doesn't replace them. Start small, focus on the metrics that matter most to your team, and scale up as you get comfortable with Auto QA.
Brands are excited about the power of Auto QA
We invited leading ecommerce brands to beta test Auto QA, and their feedback highlights how it's transforming quality assurance across support teams of all sizes.
amika's support team values the complete visibility beyond CSAT: "Auto QA dramatically widens the volume of tickets we can review," they share. "A 5-point scale only tells you so much, and relying on consumers providing feedback limits what you're able to learn from."
Peachybbies' CX team enjoys real-time improvement: "Being able to give real-time feedback is pivotal, especially during peak times," their team explains. "Auto QA catches pretty much everything I'd want a human QA agent to catch."
OSEA Malibu's managers discovered operational insights: "It helps managers understand when a macro or process is leading to incomplete conversations versus when an agent made a mistake," their support lead shares.
Bring quality into every conversation with Auto QA
By prioritizing QA, your team can identify potential problems early, reduce errors, and improve overall performance, leading to a smoother, more reliable experience for customers––and your CX team.
In the long run, brands focusing on QA can gain a competitive edge. Book a demo now to see what Auto QA can do for you.
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5 CX Metrics To Track in 2025: A Guide for Managers
There are tons of CX metrics you could be tracking. But where you spend your time is crucial as a customer experience leader.
According to recent data, these are the top five CX metrics for you to prioritize and improve on in 2025.
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Why CX metrics are essential for success
Not tracking CX metrics is like putting a loaf of bread in the oven but leaving baking time to chance. Without a set timer, you could end up with an underbaked bowl of dough or a burnt mess. Unless you have a sixth sense, it’s going to be really challenging to end up with something good.
In the same vein, metrics provide clear parameters for success. Meet or exceed them and your team is doing well; fall short and you’ll be better equipped to identify pain points and solve them.
Here are a few additional reasons why setting customer support metrics is key to success.
- Measure success and ROI. By tracking KPIs like resolution time, first response time, and CSAT, you can gauge the health of your customer support program and potentially justify investments in CX initiatives in the future.
- Identify customer and team pain points. Metrics help uncover areas where customers or your team is struggling. For example, high resolution times or low CSAT scores signal friction in the experience that you can address.
- Create accountability within your team. When everyone on your team understands what success looks like, it aligns efforts and keeps everyone focused on shared goals.
- Prioritize resources. Metrics guide CX leaders on where to allocate resources—for example, leveraging AI and automation to tackle repetitive tickets when ticket volume adds up or resolution times are getting high.
- Get proactive. Metrics reveal trends in customer behavior which can help you predict customer needs and make proactive adjustments in your CX strategy. By monitoring customer sentiment and acting on feedback, CX leaders can create more personalized and positive experiences.
Tip : AI and automation can be valuable sidekicks as you look to optimize and improve on metrics. That’s especially true for busy periods: in 2024, 70% of CX leaders relied on AI and automation during peak seasons.
Resolution time should be your main focus for 2025
Customers are done with being patient. One study found that two thirds of respondents valued speed to reply just as much as product price.
A recent survey we ran found the same thing.
In our 2024 customer expectations survey, we asked CX leads and agents which metric they used to track success. Here’s what they said:
- Resolution Time (71%)
- First Response Time (59%)
- CSAT (53%)
- Revenue or Sales Impact (41%)
- Ticket Volume (41%)
Resolution time is going to be a key differentiator for your team this year. It should be your primary focus when it comes to optimizing different facets of your customer service strategy.
Top 5 CX metrics for 2025 & how to improve them with AI
1) Resolution time
Resolution time is the average time it takes to resolve a customer request from start to finish.
How do you calculate resolution time?
To calculate resolution time, you’ll take the total resolution time within a set period and divide it by the total number of customer interactions your team tackled within that same time frame.
Average resolution time = Total resolution time in a defined period / Total number of customer interactions resolved in that period
How to use AI & automation to improve it
According to a 2023 study from Statista, 70% of support leaders noted that the customer support metrics that AI had the greatest positive effect on was resolution time.
You can use automation features to send Macros to answer common questions, or leverage AI to interact as an agent via email or chat. The instant nature of these tools means that customers won’t have to wait in a queue for your team to get to them.
For example, Wildride implemented Gorgias AI Agent to manage an influx of 1,000 tickets per week. After AI Agent took over 33% of email inquiries, the team saw a 24% decrease in resolution time. That allowed the team to focus on more complex issues, streamline their support process, and make their customers happier.
2) First Response Time (FRT)
First response time is the length of time it takes for a customer service team to send the initial reply to a customer inquiry.
How do you calculate first response time?
To calculate average first response time, take the total amount of time it took for your team to respond to initial customer requests and divide by the total number of tickets within a set time frame.
How to use AI & automation to improve it
Your team is busy––when they’re not tackling repetitive questions, they’re helping customers with complicated or high-effort requests. All of that work is going to bog down your FRT, especially during more buzzy periods like sales, new releases, or over the holidays.
By using AI to jump in to handle those more routine requests, you can significantly reduce your FRT and give your team time back to tackle more heavy-lift needs.
For example, AI Agent helped Glamnetic achieve a 91% improvement in first response time during Black Friday Cyber Monday (BFCM) 2024. They got FRT down from their pre-AI Agent time of eight minutes to 40 seconds.
Here’s what that looked like in practice:
3) Customer Satisfaction Score (CSAT)
CSAT scores show how satisfied customers are with a product, service, or interaction, typically gathered through surveys.
How is CSAT calculated?
CSAT is calculated via a five-point rating scale survey sent to customers after a support interaction, where one is the worst experience and five is the best. While it can be calculated in different ways, at Gorgias the average of all survey responses is your CSAT score.
How to use AI & automation to improve it
When customers reach out for support, they’re expecting a fast response––regardless if they have an issue or are contemplating their next purchase.
That’s why using automation or AI tools to provide that lightning quick response, even if it directs shoppers to a self-service resource, can be extremely effective in raising CSAT scores. These responses could be sent by an AI agent that responds like a human agent would or an automated Macro built to fire off pre-crafted templates to common questions.
In luxury golf brand VESSEL’s case, customers felt that the AI responses were helpful and seemed on-par with the level of support they’d expect from a human agent.
“Our customers expect almost immediate responses, and so being able to automate that, even if it's not necessarily the exact answer that they're looking for, but being able to send over information to give them the reassurance that we're looking into it or trying to find an answer, whatever it may be, that's been a huge help to our team,” says Lauren Reams, the Customer Experience Manager at VESSEL.
4) Revenue or sales impact
The direct or indirect effect of customer service or business activities on generating sales or revenue.
How do you calculate it?
There are different ways to calculate revenue generated and the sales impact of customer support, and quantifying the indirect impact can be difficult. But generally, the formula looks like this:
ROI = [ (Money earned - Money spent) / Money spent ] x 100
Resource: How to measure & improve customer service ROI
How to use AI & automation to improve it
Leveraging AI and automation can provide significant cost savings because it acts as an additional agent who can tackle repetitive questions, translating to money saved on the time it would take for human agents to manually answer those questions.
The results are tangible: by automating 48% of inquiries, Dr. Bronner's saved $5,248 in the first month, and $100K in the first year.
Jonas Paul Eyewear saw revenue influenced by AI Agent as well: the team tracked $600 of sales revenue directly to the tool after it effectively answered pre-sales support questions from shoppers.
5) Ticket volume
Ticket volume is the total number of customer service inquiries that a team receives over a specific period of time.
How do you calculate it?
The customer support tool you use will be able to calculate ticket volume for you, as it’s the total number of tickets that have come in within a set amount of time. If you don’t use a CX platform yet and are still using something like Gmail or Excel, you’ll perform this count manually.
How to use AI & automation to improve it
Set rules to trigger automated responses to common questions, or ask an AI agent to completely take them off your team’s plate.
Arcade Belts, for example, saw a 50% reduction in ticket volume by using Gorgias AI Agent.
How to get buy in to improve your CX program
Tracking CX metrics is valuable for more than just gauging your program's effectiveness. The more you improve upon your CX metrics, the more you can leverage them to prove your support function’s value within your company.
- Tie CX to revenue. Show how improvements in customer satisfaction or repeat purchase rates directly impact revenue growth.
- Show industry benchmarks. Compare your team’s stats to competitors or industry averages to demonstrate how well your support strategy is working.
- Demonstrate your team’s impact on sales and retention. Use the metrics you’ve collected to show support’s impact on converting customers asking pre-sales questions and getting repeat customers.
- Ask to expand your team’s budget. Pitch acquiring additional buy in and resources by presenting revenue generated, costs saved through tools like AI and automation, and happy customers created.
How to use metrics to evaluate AI performanceIf you want to transform customer experience for the long term, the AI tools you use should never be “set it and forget it” solutions. Just as you do with your human agents, you can use metrics to evaluate your AI agent to make sure it’s performing well. If you use Gorgias, you’ll find these metrics under the AI Agent dashboard.
To review AI Agent’s performance:
It’s also easy to retrain your AI's performance by adjusting settings like Guidance, refining the internal documents it draws from, setting up brand voice, or creating a Handover topic list to escalate certain types of tickets to human agents.
Start tracking top CX metrics
Whether you’re new to being a CX leader or you’re a seasoned pro, tracking and improving on your CX metrics will help your team stand out among the rest. A key way to improve them is to leverage AI and Automation tools, and Gorgias is here to help you do it.
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Say Hello to AI Agent on Chat: 24/7 Support for Online Stores
TL;DR:
- AI Agent on Chat automates up to 50% of chat conversations. It ensures customers get fast, context-aware answers, product recommendations, and seamless handovers to human agents when needed.
- AI Agent goes beyond automated features like Flows and article recommendations. On top of basic automation features, AI Agent can handle complex inquiries like modifying orders and providing personalized product recommendations.
- Setting up AI Agent on Chat is quick. Brands can activate AI Agent with a few clicks, improving efficiency during peak seasons and reducing the need for follow-ups.
- Updating AI Agent’s knowledge and behavior ensures the best customer experience. Businesses should refine their Help Center, set Guidance instructions, personalize AI Agent’s tone, and test responses before going live.
It’s clear that shoppers want answers fast—chat accounts for 20% of all customer support tickets.
The appeal is obvious: Chat is an easy-to-access customer service channel for quick questions and a convenient and subtle way to cross-sell complementary products.
But without the right chat tool, brands risk losing these valuable opportunities.
Introducing AI Agent on Chat, a conversational AI assistant that can automate up to 50% of chat conversations. This new feature upgrades chat by combining agent knowledge with superhuman efficiency and response times.
Now, customers can guarantee personalized interactions at any point of the shopping journey—whether they’re looking for a quick answer or a tailored recommendation.
With AI powering every interaction, one-to-one conversations become a seamless part of every customer experience.
Why Chat is better with AI Agent
Before AI Agent, customers reaching out through chat outside business hours had two options: following pre-set Flows (automated FAQ conversations) or browsing through suggested Help Center articles.
These features are great for quick answers to basic questions, but AI Agent takes support to the next level by handling more complex needs like modifying orders or offering personalized product recommendations.
With AI Agent in Chat, customers enjoy dynamic, real-time conversations available on multiple channels. AI Agent generates personalized responses that match exactly what customers ask for, automating 50% of chat interactions so agents get time back to upsell, create stronger relationships, and craft better experiences.
Related: How to optimize your Help Center for AI Agent
The key features of AI Agent on Chat
Upgrade your chat support from a basic Q&A tool into an intelligent assistant that handles customer inquiries 24/7. Here's how AI Agent makes that possible:
Real-time conversations
AI Agent responds within 15 seconds or less, offering fast responses that result in frictionless conversations. Unlike traditional chatbots, AI Agent also adapts to your brand’s unique tone of voice to enhance the customer experience and assure shoppers their questions will be taken care of.
24/7 availability
Today’s shoppers expect instant responses regardless of time zone or business hours. AI Agent on Chat means customers get the help they need, when they need it. This availability leads to higher customer satisfaction and fewer abandoned carts.
Instant product recommendations
AI Agent understands context and customer intent. Whether a shopper needs help finding the right product size or changes their mind and wants to compare features, AI Agent customizes its recommendations for each person.
Intelligent handovers
Some conversations, like technical issues or complaints, need a human touch. AI Agent recognizes these situations and smoothly transfers them to the right agent.
Using Handover topics, you can choose which types of inquiries should go straight to human agents. Then, if AI Agent lacks the confidence to provide an answer or can’t locate relevant knowledge in its database, it automatically escalates the conversation.
Read more: Handover rules
Why enable AI Agent in Chat now?
Based on Hiver’s 2024 study, 62% of customers prefer live chat to other support channels. With AI Agent in Chat, agents can cut down average response times while customers get the answers they need in one conversation with zero wait times or follow-ups.
Easy setup
AI Agent on Chat is ready to use in a few clicks. Simply connect your Shopify store and Chat widget to AI Agent, and you’re ready to resolve questions asked by visitors and loyal customers faster than you ever have.
Capture the growing demand for live support
Chat is often a customer’s first touchpoint with your brand, whether they’ve just discovered your brand or are on their third order. Meet customer expectations by being available with AI Agent on Chat. The faster you can ease their concerns, the faster they can head to checkout.
Maximize team efficiency
AI Agent makes scaling support effortless, especially during peak seasons like Black Friday. While it handles repetitive support tickets like order status and shipping questions, your team can focus on high-priority tasks like requests from VIP customers.
Eliminate the need for follow-ups
Drawing from knowledge sources like your Help Center and policy pages means AI Agent can often resolve inquiries within one conversation. No more unnecessary back-and-forths. Quick resolutions = happier and more loyal customers.
How to activate AI Agent on Chat
Ready to get started? Here’s how to activate AI Agent on Chat:
- Click Automate in the top left menu.
- Select your store from the sidebar, then click on AI Agent.
- In the Settings tab, under Chat Settings, select one or more Chat from the dropdown menu.
- Toggle Enable AI Agent on Chat on.
- Select Save Changes at the bottom of the page.
Already use AI Agent for email? No need to set up Guidance and Handover topics all over again—AI Agent will behave the same way in Chat.
Best practices for setting up AI Agent on Chat
Get the most out of AI Agent on Chat by following these best practices.
1. Prepare and optimize your knowledge base
The Help Center is AI Agent’s brain. This customer knowledge database is the key to AI Agent’s accurate and on-brand responses. To ensure your AI Agent is as trained as your human agents, include important topics in your Help Center like shipping, returns, cancellations, and account management.
No articles yet? No problem! Gorgias has 20+ article templates for you to use and modify. Or, even better, check out the AI Library for AI-generated articles based on your customer tickets.
2. Set restrictions with Guidance
AI tools perform best when you set limitations. A Guidance is the main way to control AI Agent’s behavior. It is a set of written instructions that outline how AI Agent should interact with customers, handle certain requests, and more.
We recommend publishing a Guidance on the top five questions you receive from customers.
Tip: AI Agent prioritizes Guidance above Help Center articles. Unlike Help Center articles, the content in your Guidance will not be customer-facing.
3. Personalize AI Agent's voice
The beauty of AI Agent is its ability to speak like one of your agents. Select from Friendly, Professional, or Sophisticated presets—or create a custom tone that aligns with your brand.
Need help finding your brand voice? Here are seven brand voice examples.
4. Test AI Agent’s responses before going live
Use test scenarios to see how AI Agent responds to common customer questions, such as order status, shipping questions, and return policies. To cover all your bases, test AI Agent as both a new and returning customer to make sure it delivers accurate responses no matter the customer's need.
5. Improve AI Agent’s behavior
AI Agent becomes smarter as it learns from you. Like a human agent, give your AI Agent feedback on its responses, from how it speaks, which topics it escalates, and what actions it takes in certain scenarios.
There are multiple ways to give AI Agent feedback on a ticket:
- Mark AI Agent’s message or any of the resources it used as correct or incorrect.
- Suggest that AI Agent use a different resource if a better or more correct piece of knowledge exists.
- Report an issue to the Gorgias Product team.
Try AI Agent Actions on Chat
AI Agent can also perform actions like accessing Shopify order details and executing third-party app actions, such as updating shipping addresses and order cancellations, directly in Chat.
Excited to deliver an elevated chat experience? Book a demo now to experience the power of AI Agent on Chat.
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The Gorgias & Shopify Integration: 8 Features Your Support Team Will Love
TL;DR:
Managing customer support as a Shopify store owner can feel like juggling too many tools at once.
Constantly switching tabs to look up orders, update customer information, or track returns wastes valuable time. Plus, it prevents your team from focusing on what really matters––delivering quick, personalized customer service.
Gorgias’s Shopify integration solves this. It keeps all your Shopify data in one place, so your team spends less time toggling tabs and more time helping customers. The result? Faster responses, better service, and more revenue.
Below, we break down the eight key capabilities of this integration, each paired with practical use cases to showcase its real-world value.
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1. View Shopify data in tickets
What it does: Shopify order data is displayed directly within support tickets, allowing agents to view essential details like order status, customer information, and transaction history without leaving the helpdesk.
Use case: An agent handling a “Where’s my order?” request can instantly check tracking information and update the customer.
The fashion retailer Princess Polly improved their customer experience team’s efficiency by using Gorgias's deep integration with Shopify. Agents can view and update customer and order data directly within Gorgias, eliminating the need to switch between multiple tabs.
Taking a streamlined approach led to a 40% increase in efficiency, an 80% decrease in resolution time, and a 95% decrease in first response time.
2. Perform Shopify Actions
What it does: Agents can update Shopify order and customer data with Shopify Actions right in Gorgias.
Key features:
- Create a new order: Add existing products or custom items, apply discounts, modify quantities, add notes and tags, and choose to charge taxes. Then set the order as Paid or Pending and email the invoice to the customer.
- Duplicate an order: Replicate an existing order and make adjustments as needed.
- Cancel/refund an order: Cancel or refund orders by setting quantities to refund, specifying shipping amounts to refund, providing reasons for cancellation, restocking items, and notifying the customer.
- Edit shipping address: Update the shipping address for an order.
- Insert product links: Add product links or product cards from tickets so customers can add the product to their cart quickly.
- Display the customer’s cart: View the exact items the customer has in their cart at the moment they reach out via Chat.
Use case: Agents can perform Shopify actions directly from Gorgias, such as adding products, applying discounts, updating quantities, or issuing refunds.
3. Embed customer-specific Shopify data in Macros
What it does: Create templated responses called Macros with dynamic Shopify variables to automatically incorporate customer-specific information.
Key features:
- Dynamic variables: Macros can include variables that pull real-time data from Shopify, such as order status, tracking numbers, and customer details.
- Automated actions: Beyond inserting dynamic content, Macros can perform actions like tagging tickets, setting statuses, or assigning conversations to specific agents. The automation streamlines workflows and ensures consistent handling of similar inquiries.
Use case: A customer inquires about their order. With one click, the agent uses a Macro that pulls in the order status and expected delivery date, creating a faster and more personalized response.
Take Try The World, a gourmet subscription service, needed a robust Shopify integration to handle an increasing volume of customer inquiries. By switching to Gorgias, they gained the ability to unify conversations and embed Shopify data directly into Macros. Now, agents can quickly generate personalized responses that includes order details, tracking links, and customer-specific information.
Try the World’s support team’s efficiency skyrocketed, enabling them to handle 120 tickets per day, up from 80, and reduce response times to just one business day.
4. Provide product information with Macros
What it does: Macros with embedded Shopify data let agents quickly and accurately share pre-sale information like product links, stock availability, and discount codes, helping to convert prospective customers into buyers.
Key features:
- Dynamic Shopify variables in Macros: Agents can use dynamic variables to pull real-time product information.
- Pre-built responses for common questions: Macros can include templated responses tailored for pre-sale inquiries, such as providing direct links to products or applying discount codes.
Use case: A customer asks if a specific product is available in their size and color. The agent can apply a Macro that automatically pulls the product's inventory details and includes a discount code, sending a response like this:
“Hi [customer name Macro],
Great news! The product [Shopify product information Macro] is currently in stock in the size and color you’re looking for. You can check it out here: [Product Link]. Use the code WELCOME10 at checkout for 10% off your first order! Let me know if you have any other questions!”
How it helps:
- Eliminates manual search and typing for agents.
- Ensures accurate, real-time product information for customers.
- Improves the likelihood of converting inquiries into sales.
5. Enable self-serve order management in Chat
What it does: Using Gorgias Chat, customers can track orders or manage their purchases on their own with no agent assistance needed.
Key feature:
- Order management automation: Customers can access real-time order information, including status updates and tracking details, through the chat interface. This automation reduces the volume of live chat inquiries by up to 30%.
Use case: A customer wants to check the status of their recent purchase. By accessing Chat on your website, they can enter their email and order number and receive instant updates on their order's progress, including shipping and delivery information, without waiting for an agent's response.
How it helps:
- Automates routine inquiries and frees up your support team to handle more complex issues.
- Enhances customer satisfaction thanks to immediate responses.
- Reduces the need for multiple communication channels, consolidating support interactions in one place.
6. Use Shopify variables in Rules
What it does: Rules paired with Shopify variables can automate various support tasks, such as identifying specific customer segments or tagging tickets, to boost efficiency and consistency.
Key features:
- Automated tagging: Rules can automatically tag tickets based on specific Shopify data. For instance, you can set up a Rule to tag tickets from customers with high order counts or significant total spending as "VIP."
- Prioritization of tickets: Rules can prioritize tickets that meet certain criteria, such as high-value orders or repeat customers.
Use case: A customer with a history of substantial purchases contacts support. A rule detects that the customer's total spending exceeds a predefined threshold and automatically tags the ticket as "VIP."
This tag can then trigger other workflows, such as assigning the ticket to a senior support agent or escalating its priority.
How it helps:
- Improves customer experience by prioritizing high-value customers.
- Maintains consistent service quality.
7. Track revenue with reporting
What it does: Gorgias offers comprehensive reporting that allows you to measure how your support interactions influence sales.
Key features:
- Tickets converted: Tracks the number of support tickets that led to a sale within five days of the ticket's creation.
- Conversion rate: Calculates the percentage of created tickets that resulted in sales, helping you assess the effectiveness of your support team's interactions.
- Total sales from support: Sums the revenue generated from orders associated with converted tickets, accounting for refunds and order adjustments to provide accurate figures.
These metrics are accessible under Statistics → Support Performance → Revenue in your Gorgias dashboard. You can filter the data by integration, ticket channel, tags, or specific time periods to gain detailed insights.
Use case: By analyzing Revenue Statistics, you can identify which support channels or agents are most effective in driving sales. For example, if live chat interactions have a higher conversion rate, you might allocate more resources to that channel.
Additionally, recognizing top-performing agents can inform training programs to elevate overall team performance.
For example, One Block Down, a Milan-based streetwear brand, struggled to manage a growing volume of customer inquiries across multiple platforms. By integrating Gorgias with Shopify, they centralized all customer interactions into a single platform, giving agents instant access to crucial information like order history and returns directly within tickets.
The setup allowed the team to measure the direct impact of their support efforts on revenue.
The result? An impressive 1,000% increase in support-generated revenue and a 1-hour average first response time. By connecting the dots between customer service and sales performance, One Block Down demonstrated how proactive, data-driven support can directly influence the bottom line.
How it helps:
- Quantifies the revenue generated from support interactions.
- Faster team optimization with data-driven insights.
- Understanding the correlation between support interactions and sales can help refine customer service strategies.
8. AI Agent integration
What it does: AI Agent automates Shopify actions like canceling orders, editing order details, and reshipping items.
Key features:
- Cancel Shopify order: AI Agent can automatically cancel unfulfilled orders upon customer request, restocking the items and issuing a full refund. A confirmation email is sent to the customer once the cancellation is complete.
- Edit order shipping address: When a customer needs to update their shipping address, AI Agent verifies if the order is unfulfilled, confirms the new address with the customer, and updates it in Shopify accordingly.
- Replace order item: AI Agent facilitates item replacements in orders by confirming the item to be removed and the new item to be added, checking stock availability, adjusting payments if necessary, and sending an updated order confirmation to the customer.
- Reship order for free: In cases where an order is lost in transit or arrives damaged, AI Agent can duplicate and resend the order at no additional charge.
- Remove order item: If a customer decides to remove an item from their order, AI Agent can handle the removal, restock the item in Shopify, process the refund for the removed item, and notify the customer of the updated order details.
Use case: A customer realizes they've entered an incorrect shipping address shortly after placing an order. They contact support, and AI Agent promptly verifies that the order is unfulfilled, confirms the correct address with the customer, updates the shipping information in Shopify, and sends a confirmation email—all without human intervention.
How it helps:
- Automating routine order management tasks reduces the workload on human agents.
- Quick and accurate responses to order modification requests lead to a better customer experience.
- Automated processes ensure consistency and accuracy in handling order changes, reducing the likelihood of human error.
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The Problem with Full-Screen Pop-Ups for Driving Conversions
TL;DR:
- Full-screen pop-ups disrupt the shopping experience. They frustrate visitors by interrupting their browsing and increase bounce rates, driving 72% of customers away.
- Gorgias Convert offers a non-intrusive alternative. With a chat-based widget, it engages customers naturally without interrupting their journey.
- Convert tailors messages to shopper behavior. Personalized campaigns detect browsing habits, cart details, and exit intent to deliver relevant offers at the right moment.
- Shopify brands see measurable results with Convert. Users report conversion boosts of 6-10%, improved customer satisfaction, and revenue growth, proving its effectiveness over traditional pop-ups.
Looking to grow an email list to capture leads or offer welcome incentives? These days, the default solution is to plaster a full-screen pop-up on your homepage.
It seems effective on the surface, collecting emails right off the bat, but dig deeper, and these pop-ups disrupt the shopping experience and skyrocket bounce rates—with 72% of customers exiting a website.
But how else do you get your message across?
That’s where Gorgias Convert comes in—a smarter, more customer-centric tool to drive conversions without pushing your visitors away.
Below, we’ll explore why it’s time to move on from full-screen pop-ups and how Gorgias Convert offers a better alternative for Shopify brands looking to boost engagement and revenue.
What’s wrong with full-screen pop-ups?
Pop-ups can be an effective marketing tool, but their full-screen counterpart often creates more problems than they solve. These intrusive overlays pose several challenges that can harm both user experience and your bottom line.
Disruptive experience
Full-screen pop-ups demand attention, often at the worst possible moment—like when a customer is browsing products or is just about to check out. This experience can frustrate visitors and lead them to abandon your site entirely.
High bounce rates
The BBC says every extra second a page takes to load can cost you 10% of your users—and pushy pop-ups don’t help. If your pop-ups are poorly timed or overly intrusive, visitors feel unwelcome, causing them to leave before exploring your offerings.
Lack of personalization
Traditional pop-ups are static and one-size-fits-all. They can’t adjust messaging based on where the customer is in their shopping journey or their behavior on your site.
Can be blocked
Many users employ ad blockers that filter out pop-ups altogether, meaning your message never even reaches a portion of your audience.
Why Gorgias Convert is the better alternative: 7 benefits
Gorgias Convert flips the script by offering a subtle, customer-friendly way to capture leads and drive sales without the drawbacks of full-screen pop-ups. Here’s why your Shopify brand should make the switch:
1. Non-intrusive
Gorgias Convert integrates seamlessly into your store, using a chat-based widget that feels like a natural part of the browsing experience. Using chat to double as a supporting and converting tool is less disruptive, allowing customers to explore your store at their own pace.
2. Caters to user behavior
Convert makes it easy to bring any type of campaign to life. Catch the attention of the exact shoppers you want by detecting their browsing behavior, customer profile, cart attributes, and more.
For example, the exit intent campaign is the top-performing Convert campaign—it detects when a user is about to leave and displays a discount code. It’s fully customizable, allowing you to tailor offers based on how much time they’ve spent on a page, the number of items in their cart, or if they’ve visited more than three times without making a purchase.
3. Customizable messaging
Unlike one-size-fits-all pop-ups, Convert lets you tailor your messaging based on customer behavior, order history, and engagement. For example, if a customer is browsing a specific product, Convert can offer a relevant discount or incentive tied directly to that item.
4. Encourages conversations
With Convert, you’re not just collecting an email address—you’re starting a conversation. The tool allows you to engage with customers in real-time through pre-set flows that guide them toward taking action, whether it’s signing up for your newsletter, redeeming an offer, or completing a purchase.
Related: 6 types of conversational customer service + how to implement them
5. Mobile-friendly
In 2024, smartphones were responsible for generating 68 percent of online shopping orders. To meet shoppers where they are, Convert’s chat-style interactions are optimized for mobile users. Unlike traditional pop-ups that don’t display correctly on smaller screens, Convert maintains a seamless experience for shoppers who prefer to shop on the go.
6. Integrated with Shopify and Gorgias
Using Convert means you can combine immediate assistance with smart marketing through its native integration with Gorgias and Shopify. For example, if a customer hesitates to make a purchase, you can intervene with a live chat offer or product recommendation in real-time.
The Shopify integration also allows you to generate unique discount codes that expire within 48 hours—preventing them from being shared on unauthorized coupon sites. These codes are automatically created with customizable thresholds, such as discounts for specific collections or individual users, without manual setup.
7. A/B testing made easy
Convert allows you to test different messages and incentives, giving valuable insights into what resonates most with your audience. This data-driven approach ensures your lead capture strategy evolves with shoppers over time.
Read more: How campaign messaging can increase conversions
Rave reviews from real Shopify brands
Shopify brands using Gorgias Convert have led to a conversion rate boost of 6-10% more across their website, up to a 24% click-through rate and 43% click-to-order rate, and improved customer satisfaction. By prioritizing a frictionless shopping experience, these brands are turning casual visitors into loyal customers.
Here’s what some happy brands have to say about Convert:
Haircare brand, Kreyol Essence, influenced 13% of revenue with Convert campaigns: “With Convert, we’ve not only improved our conversion rates but also created a seamless, personalized shopping experience that our customers love. It’s like having a personal assistant for each shopper. Thanks to Convert, we can interact with our customers and surface key information at the right time, turning clicks into connections."
Brands using customer service management agency, TalentPop, love how easy it is to generate revenue with Convert: “Clients are constantly surprised and delighted by how effective Gorgias Convert is for revenue generation. They especially appreciate that Convert can be used to target a diverse range of customers across the entire purchasing journey.”
In five months, yoga brand Manduka, increased revenue by 284.15% after using Convert: “Gorgias Convert has helped us make the shopping experience more intuitive. We can give a nice prompt to remind people of promotions we’re running, highlight specific product features, or just remind them we're here to help and answer questions. The chat campaigns make it easy for customers because they lead them to us, as opposed to them having to search for how to contact us for assistance.”
Goodbye full-screen pop-ups, hello Gorgias Convert
Shoppers want personalized experiences that respect their time and preferences. Full-screen pop-ups belong to an era of intrusive marketing that shoppers would rather leave in the past.
Gorgias Convert for your Shopify brand means delivering impactful interactions, more conversions, and an easy path to long-term customer loyalty.
Ready to make the switch? Start your effortless shopping journey today with Gorgias Convert. Chat with our team!
Introducing Conversational AI: The Smartest Way to Handle Chat, Actions, QA, and Insights
Today, we’re announcing our deeper investment in conversational AI for ecommerce.
"Since day one, Gorgias has been dedicated to helping ecommerce brands deliver exceptional customer experiences. We started with a helpdesk to centralize support, then introduced AI Agent to instantly resolve support questions,” says Romain Lapeyre, CEO of Gorgias.
“Now, we're taking the next leap forward with an AI Agent that powers the entire customer journey—anticipating buyer needs, boosting sales, and automating high-quality support. Today, I'm happy to announce Gorgias as the Conversational AI platform for ecommerce.”
Gorgias’s Conversational AI platform will let teams provide fast, scalable, and cost-effective support while helping them drive revenue growth. From automatic order changes and refunds to product recommendations and cross-sells, brands will be able to flawlessly combine their support and sales efforts.
The end result is an AI-powered customer journey where every customer interaction feels complete, personal, and connected, both before and after purchase.
Questions in Chat, resolved in seconds
Last year, we introduced AI Agent for email.
Some brands call their AI Agent Lisa, some call it Wally, and most treat it like a real member of the team. But this reliable support sidekick was only available to answer customers on email—until now.
Get ready for instant responses that tackle support inquiries of all sizes. Now, your customers can enjoy fast responses that keep their shopping experience as smooth as possible.
On top of improving first response times, AI Agent can play an even more critical role in unblocking sales, suggesting products, and driving upsells and cross-sells.
With responses sent in 15 seconds or less, brands can delight customers with near-instant resolutions.
Let your AI Agent take action
Actions let AI Agent perform customer requests on behalf of your support team. This includes changing shipping addresses, fetching fulfillment status, canceling orders, adding discounts, and more.
You can use a library of pre-configured Actions for popular apps like Shopify, Rebuy, Loop, and more. And you don’t need any technical skills to set them up.
With almost half of queries requiring some kind of update, Actions is your go-to for complete resolutions so you can get more accomplished.
Quality built into every support ticket
Quality checks have traditionally been manual, time-consuming, and inconsistent. Our brand new Auto QA feature changes that by automatically scoring 100% of conversations on resolution completeness and communication quality—whether from a human or AI agent.
With Auto QA, team leads can:
- Scale quality consistently and easily. Both human and AI agents follow the same quality standards, allowing for consistent, high-quality customer experiences.
- Coach smarter. Use real-time QA ratings in tickets to give agents targeted feedback.
- Track team performance. The dashboard highlights metrics by agent, showing what’s working and where to improve.
Gain clarity on your AI Agent’s impact
Support teams should be in complete control of their AI. That’s why the AI Agent Report and AI Agent Insights were created—to help you know exactly how your AI Agent is performing and contributing to your customer service operations.
The AI Agent Report provides full visibility into AI Agent’s performance, covering metrics like first response Time, CSAT, and one-touch ticket resolutions. Fully integrated into your Support Performance Statistics dashboard, the report includes:
- The percentage of tickets automated by AI Agent
- The number of tickets closed by AI Agent
- Success rates for one-touch resolutions
- How satisfied customers are with AI Agent’s responses
AI Agent Insights takes it a step further. It analyzes AI Agent’s performance data and provides you with a dashboard of recommendations, including potential automation opportunities, popular ticket intents to optimize, and knowledge base improvements.
Meet your new AI sales assistant
Soon, we’ll be expanding AI Agent's skills with the launch of Shopping Assistant, a tool designed to assist customers on their shopping journey.
Shopping Assistanthelps brands boost their sales capabilities through smart product recommendations, on-page checkout assistance, and personalized conversations. Now it's easier to reduce cart abandonment, suggest complementary products to boost average order value, and overcome pre-sale objections.
This new tool will bridge the gap between marketing and CX, ensuring brands can scale personalized interactions 24/7 without increasing headcount.
Looking ahead with conversational AI
As we continue to innovate with conversational AI, our focus remains on helping you succeed.
By combining smarter tools with valuable insights, we’re creating opportunities for you to put your customers first and build deeper connections at every touchpoint.
Join us as we pave a new way for the future of ecommerce.
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12 Ways to Upgrade Your Data and Trend Analysis With Ticket Fields
TL;DR:
- Ticket Fields make it easy to organize ticket data. They let agents collect the right information by filling out specific fields before closing a ticket.
- Conditional Ticket Fields are smart fields that adapt based on the ticket type. These fields show up only when they’re needed, helping agents capture just the right details.
- Use Ticket Fields to spot trends and improve your CX. Track things like return reasons, product feedback, or refund patterns to make smarter decisions and keep customers happy.
- Get your team up to speed with quick, practical tools. Share a best practices deck, give them a handy cheat sheet, and run a quick demo to make Ticket Fields easy to understand and use.
Your customer service conversations contain a goldmine of insight about your shoppers—like why they reached out, trends in shopper behavior, and how your products or services perform.
But how do you turn thousands of unstructured support tickets into accurate, digestible, and actionable takeaways?
Ticket Fields are the answer. They give support teams extra layers of data by labeling tickets in a much smarter way than traditional tags. With the right setup, Ticket Fields can help you uncover patterns, make smarter decisions, and highlight the value customer experience (CX) brings to your entire organization.
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What are Ticket Fields?
Ticket Fields are customizable properties that allow CX teams to collect and organize information about tickets. Agents fill in ticket fields before closing the ticket, making it much easier to scale data collection.
Ticket Fields can be mandatory, requiring an agent to populate a field before closing the ticket. They can also be conditional, only appearing when relevant to the ticket.
There are four types of Ticket Fields: Dropdown, Number, Text, and Yes/No. Here are some ways to use each:
- Return Reason (Dropdown): Track why customers are returning items, such as incorrect sizing, damaged goods, or dissatisfaction. This can help you spot product deficiencies or fulfillment errors.
- Product Feedback (Text): Collect feedback about products directly from customers. Share this data with your product team and make it easier for them to make improvements that customers ask for.
- Refund Amount (Number): Use this to identify trends, like high refund rates for a specific product, and modify your refund policies to minimize losses.
- First-Time Buyer (Yes/No): Flag whether a customer is making their first purchase. Use this to address pain points among new customers.
Why Ticket Fields are more powerful than Tags
Unlike Tags, which are single-reason and non-conditional, Ticket Fields ensure key information, such as fulfillment details or cancellation reasons, is built into a ticket.
Think of Tags as stickers added to a ticket, while Ticket Fields are part of the ticket’s DNA itself, giving you much more control and insight.
Let’s take a closer look at why Ticket Fields are far superior at collecting data than Tags:
Mandatory fields for comprehensiveness
Agents manually apply Tags, which means it’s easy to forget to tag a ticket.
Ticket Fields, however, enforce structure by allowing CX managers to decide which fields are mandatory and which are optional. This flexibility ensures that all tickets contain the same basic details.
Conditional fields for a streamlined experience and in-depth data
Ticket Fields can be conditional, meaning certain types of tickets automatically include fields that must be filled in.
How does it work? Take a look at this example:
If the Contact Reason field is Cancellation, conditional ticket fields like Cancel Reason, Did We Cancel Subscription, and Order Number must also be filled out.
Here’s how it looks in the Field Conditions settings:
No more missing context, gaps in the data, or typing N/A in a field. Support teams can capture the data they need from each ticket every time.
Ease of migration
For CX teams transitioning from other helpdesks, being able to import historical ticket data with the field information intact is significant. This preserves workflows and existing data, helping teams get set up in no time without losing crucial information.
Tags, on the other hand, should be used to:
- Sort tickets in different Views. Tags are helpful for organizing your tickets into different views to aid your workflow. For example, you can focus on all urgent tickets by creating a view that only displays tickets tagged as “Urgent.”
- Used as temporary categories for exceptions. Tags can be used to add extra detail to an existing category. For instance, if you have a field named “Subscription Type” with “Premium Plan” selected as value in the ticket, you can add a “Gift Subscription” Tag temporarily.
12 Ticket Fields every CX team should consider for better reporting
Ticket Fields are incredibly adaptable, allowing you to capture the exact data your team needs to meet your goals—whether it’s tracking product trends, choosing a shipping carrier, or increasing customer satisfaction.
Here are 12 examples of custom Ticket Fields to level up your data analysis.
1. Contact reason
Type of ticket field: Dropdown
What to do with the data: Identify common reasons customers contact you and take proactive steps to address them.
The Contact Reason ticket field is an easy way to figure out why customers reach out to your support team in the first place.
You can quickly identify trends, such as a sudden spike in return requests, and investigate whether it's a website, fulfillment, product, or service issue.
Some common contact reasons:
- Status inquiry
- Discount
- Refund
- Product question
- Feedback
Note: Gorgias AI automatically suggests contact reasons, pre-filling the field with a prediction based on message content. Agents can accept or adjust the suggestion, helping the system become smarter over time as it learns from these interactions.
2. Resolution
Type of ticket field: Dropdown
What to do with the data: Assess the effectiveness of resolutions and refine your service level agreement.
The Resolution ticket field tracks the action taken to resolve a ticket. Analyzing how your team handles tickets and identifying opportunities to improve resolutions is essential.
For example, you could analyze how often issues are resolved with replacements versus discounts. If you find replacements are overused for minor issues, you might implement a policy to provide discounts instead, helping to reduce costs without harming customer satisfaction.
Here are some values to add to the Resolution ticket field:
- Sent more information
- Replacement sent
- Discount given
- Refund
- Sent tracking order information
- No action taken
3. Feedback
Type of ticket field: Dropdown
What to do with the data: Use both positive and negative feedback to update your policies, escalation process, customer-facing resources, product, and more.
The Feedback ticket field can capture general feedback about your brand or feedback specific to your products.
This field is an excellent way to carry out product research. For example, if you’re a food brand, you can create a dropdown that categorizes feedback by sentiment, such as “Too Sweet,” “Too Salty,” “General Dislike,” and “Artificial Taste.” Once you’ve received a decent amount of feedback, you can return to the test kitchen and perfect your recipe.
4. Product
Type of ticket field: Dropdown
What to do with the data: Track product trends and prioritize improvements.
The Product field is valuable for tracking which items generate the most inquiries. If you have a large inventory, incorporating a Product ticket field can help flag which products are causing the most issues or trouble for shoppers.
If a product is the most used value, this could indicate frequent issues with the product, such as quality issues, defects, or missing information on its product page.
If a product is the least used value, it may not be generating much attention. If this is due to low sales, consider enhancing its visibility through marketing to attract more shoppers. However, being the least used value can also be good news, meaning your product performs well, and shoppers have no complaints.
Pro Tip: To understand which specific products are getting returned, add a conditional “Product” ticket field.
5. Defect
Type of ticket field: Dropdown + conditional field
What to do with the data: Identify recurring quality issues and fix root causes.
Track the most prominent defects reported by customers with a Defect ticket field. This can help you monitor product quality and adjust production, manufacturer, or supplier processes.
For deeper insights, add a conditional “Product” field to pinpoint which products experience specific defects. For example, if you’re a bag brand, you might find that a certain backpack is usually tied to a “Zipper” defect. This can be a valuable insight to pass on to your product team to alter the design or adjust your manufacturing process.
Here’s a look at the dropdown values for the Defect ticket field:
6. Cancellation reason
Type of ticket field: Dropdown
What to do with the data: Lower churn by addressing cancellation triggers.
If you’re a subscription-based business with a climbing cancellation rate, adding a Cancellation Reason ticket field can help you stop the churn. This field tracks why customers cancel orders or subscriptions. It’s a powerful way to identify patterns, such as price sensitivity or delivery delays, and to take steps to retain customers.
Cancellation reason examples:
- Too expensive
- Bad product-customer fit
- Don’t need it
- Moving to a competitor
- Poor customer service
7. Shipping carrier
Type of ticket field: Dropdown + conditional field
What to do with the data: Evaluate shipping carrier performance and improve logistics.
For any ecommerce brand, your shipping carrier is a big contributor to customer satisfaction. The faster a customer’s order gets to them, the better.
Use a Shipping Carrier ticket field to track the shipping carrier for tickets related to delivery issues. This will provide insights into which carriers perform poorly, enabling you to modify your logistics and order fulfillment processes.
Pair the Shipping Carrier field with a conditional “Shipping Issue” field to identify potential correlations. For example, if “Delayed” is a top shipping issue for a certain carrier, it may be time to change your logistics process.
8. Purchase origin
Type of ticket field: Dropdown
What to do with the data: Learn how customers find your brand and see what types of customers and issues are tied to the purchase source.
The Purchase Origin field helps you see where customers are coming from. Are they buying directly from your website? Or from social media platforms like Instagram or TikTok?
Dig deeper, and you may also spot connections between purchase origin and common issues.
For your marketing team, this data will help improve strategies at all levels, from advertising and messaging to targeting the right platforms.
9. Customer escalation
Type of ticket field: Yes/No
What to do with the data: Reduce escalations by revising escalation processes and retraining agents.
The Customer Escalation field tracks whether a ticket was escalated to a manager. It helps teams identify training needs and improve processes to reduce escalations.
As the use of AI agents increases in ecommerce customer service, having a clear view of which tickets are escalated can help pinpoint gaps in AI performance and identify scenarios that require human intervention.
Analyzing this data over time can guide updates to AI workflows and agent training, reducing the need for escalations altogether.
10. Discount percentage
Type of ticket field: Number
What to do with the data: Understand how discounts impact customer satisfaction.
The Discount Percentage ticket field tracks the percentage of a discount applied to a customer's order, offering insights into how promotions affect customer behavior.
For example, if customers using a 20% discount frequently contact support about order confusion or dissatisfaction, it might indicate unclear promotion terms or product descriptions. This data helps brands refine promotional messaging and determine whether higher discounts lead to increased ticket volumes, customer satisfaction, or sales.
11. First-time buyer
Type of ticket field: Yes/No + conditional field
What to do with the data: Improve the customer experience for brand new customers.
The First-Time Buyer field flags whether a customer is making their first purchase, making it easier to spot and support new shoppers. When a customer is marked as a first-time buyer, a conditional “Customer Sentiment” field can appear to capture how they feel about their experience.
First-time buyers often have questions about products or need recommendations to feel confident about their purchase. Pairing this ticket field with sentiment data helps to identify common pain points, preferences, and patterns among new customers so your team can finetune the customer experience and leave a lasting first impression.
12. Months in use
Type of ticket field: Number
What to do with the data: Analyze product performance over time.
The Months in Use field tracks how long customers have been using a product. It’s perfect for spotting when items start breaking down, spoiling, or losing effectiveness.
This data helps brands figure out where durability, shelf life, or packaging could be improved to keep customers happy and products performing as expected.
Who benefits from Ticket Fields?
Ticket Fields provide value across the entire CX ecosystem, from agents to decision-makers.
- Support teams: Gain a deeper understanding of shopper behavior and where issues arise from.
- Operations teams: Identify and resolve operational inefficiencies in your support, fulfillment, and feedback workflows.
- Data and tech teams: Analyze Ticket Fields reports from the support team that provide detailed customer service and product data that can inform other departments like product.
- Executives: Get visibility into CX operations, including shipping, damaged items, cancellations, and team performance, to make data-backed decisions.
How to make Ticket Fields a core part of your support process
Ticket Fields are only as powerful as the processes that support them. Follow these five steps to help your team turn support tickets into valuable data for better reporting.
1. Define your data and reporting goals
Decide what insights your team needs to improve workflows, product quality, or customer satisfaction. For example, if you want to track cancellations, set up fields like "Cancellation Reason" and "Refund Amount." Keep your Ticket Fields focused on data your team can use.
2. Set up Ticket Fields
Use Gorgias to configure Ticket Fields in a structured and easy-to-use format. Keep dropdown options concise and specific to avoid confusion. Then, run a test ticket or two to confirm the setup works smoothly for agents.
Read more: Create and edit Ticket Fields
3. Train and onboard your team
Create a presentation deck that clearly explains the purpose of every Ticket Field, the options agents can select for each field, and how the fields tie into the team’s data goals. For added visuals, include flowcharts to show when and how to use each field.
Pro Tip: Give agents a quick reference tool they can easily consult by providing a cheat sheet summarizing Ticket Field best practices.
4. Implement changes based on insights
Whether the data points to gaps in your workflows, product details, or customer education, acting on these patterns is how you drive meaningful change.
Here are some fixes, from low to high effort, that your team can implement:
- Update FAQs in your Chat Flows
- Edit automated responses
- Retrain your AI agent with new information
- Add relevant answers to your Help Center
- Optimize product pages with more details like usage instructions, ingredients, or sizing charts
- Modify product categorization on your website
- Adjust internal workflows
- Renegotiate contracts with underperforming shipping carriers
- Redesign or reformulate products
5. Review Ticket Field data in monthly meetings
Schedule a monthly meeting to review your Ticket Fields Statistics and evaluate their impact on your support workflows and customer satisfaction.
During the meeting, discuss:
- What trends do the reports reveal?
- Are agents consistently filling out each field?
- Which fields are consistently filled out and provide actionable insights?
- Have our priorities changed, making some fields less useful?
Lastly, remember to document the insights and update your team regularly to keep everyone aligned.
Drive smarter decisions with Ticket Fields
Gorgias’s Ticket Fields turn ticket data into insights you can actually use. Spot trends, improve workflows, and make faster, smarter decisions.
Are you ready to see it in action? Book a demo, and let us show you how Ticket Fields can elevate your support.
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How to Reduce CX Stress in 2025 with AI and Automation
TL;DR:
- Automate repetitive questions to give agents time back. Use tools like Help Centers, Flows, and AI agents to handle common queries so agents can take care of more complex issues.
- Lower response times with automation. Set up automated email responses, use Flows, and leverage AI Agents to reply to customers faster.
- Maintain a consistent tone of voice with AI. Automate QA processes and provide custom tone instructions to ensure every response aligns with your brand's voice.
- Self-serve returns and use chat campaigns to upsell. Use tools like Loop Returns for self-serve returns and Gorgias Convert to boost revenue with personalized upselling campaigns.
According to Salesforce research, 77% of support staff have dealt with increased and complex workflows compared to the year prior. In addition, 56% of agents have experienced burnout due to support work.
As teams transition into the next era of CX—one where almost every customer expects efficiency, convenience, and friendly and knowledgeable service –– they’ll need the support of more than just a stellar lead to avoid the stress that comes with the job.
AI and automation are valuable and impactful tools that can aid teams in providing these top-notch experiences while helping agents lower their own stress.
Here are seven ways to leverage AI and automation to increase agent productivity, meet customer expectations, and decrease burnout on CX teams.
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How to reduce stress with AI and automation
While there will always be reasons for human intervention, here are seven support challenges that AI and automation can solve for CX teams long term.
- Tackle repetitive questions
- Lower response times
- Keep a consistent tone of voice
- QA responses at scale
- Upsell customer conversations
- Let customers self-serve returns
- Address common points of confusion
1) Tackle repetitive questions
Every CX team receives repetitive questions like “where is my order” (WISMO), “can I change my shipping address,” or “what is your return policy” every single day. These questions add up over time, creating frustration and burnout for agents and longer response times for customers.
Instead, teams can leverage AI and automation to answer these questions and take time back for other essential tasks.
How to use AI and automation to reduce repetitive questions
If you use Gorgias, there are a couple of ways to put automation to work.
- Lowest effort: Create a Help Center. Help Centers are beneficial for a couple of reasons. First, they give customers an avenue for self-service. Second, they're the primary knowledge source that Gorgias AI Agent draws from. To make setup a breeze, browse 50 help center templates with included answers, all customizable to your brand’s policies.
- Medium effort: Set up Flows. Flows guide simple automated interactions that get customers the answers they need. Flows might help customers understand sizing, learn how long delivery will take, or find warranty information.
- Highest effort: Activate AI Agent. AI Agent is conversational AI that can handle repetitive tickets for teams by learning your brand’s policies, tone of voice, and specific instructions.
"Gorgias's AI Agent has been a game-changer for us, allowing us to automate nearly half of our customer service inquiries. This efficiency means we don’t need to hire additional staff to manage routine tasks, which has saved us the equivalent of two full-time positions.
—Noémie Rousseau, Customer Service Manager at Pajar
Resource: How to automate half of your CX tasks
2) Lower response times
Many customers get frustrated due to delayed support responses, especially if (they believe) they’re asking a simple question. Not only can AI and automation support by offering responses to these questions, they allow human agents to respond faster to customers who have more complex questions.
How to use AI and automation to lower response times
- Lowest effort: Use automated acknowledgment responses to reassure customers that you’ve heard them, and provide a time frame for when they can expect to hear back. This can be as simple as setting up an email to trigger each time a customer sends in a support request.
- Medium effort: Set up Flows in Chat to give customers quick, automated answers to common questions.
- Highest effort: Use AI Agent to answer customers 10x faster than your human agents.
AI Agent has been an effective tool for the team at luxe golf accessory shop VESSEL. “Now we’re able to get back to people so much faster than before,” says Lauren Reams, their Customer Experience Manager.
“We can quickly collect information – avoiding the back and forth questions like what is your name, email or shipping address. Using AI to eliminate the back and forth has been great, and getting back to customers much faster than before has been the biggest win for our team.”
3) Keep a consistent tone of voice
If customers see an inconsistent tone of voice across responses, it’ll affect your brand credibility. It also causes confusion and may create issues maintaining repeat and loyal customers.
How to use AI and automation to keep tone of voice consistent
- Lowest effort: Set up AI Agent’s tone of voice with custom instructions. While AI Agent comes with three pre-set options (Friendly, Professional, and Sophisticated), you can also provide custom Guidance for how you’d like it to sound.
- Medium effort: Use Macros or templated responses to always keep agents on brand.
- Highest effort: Conduct agent training via an automated QA system. Auto QA can provide instant feedback on agent responses to ensure they’re on brand and use the right tone of voice.
4) QA responses at scale
Manual quality assurance checks are time-consuming and often inconsistent. But they’re key to providing great support at scale while maintaining a high standard across thousands of interactions. Aside from catching any errors, a regular QA process also builds trust with customers, increases personalization, and helps agents improve over time.
How to use AI and automation for QA
Automated quality assurance can provide up to 90% accuracy, according to research by McKinsey. To ensure 100% of your customer conversations are checked, used Auto QA. This AI-powered QA tool evaluates your team's responses—AI or human—based on Resolution Completeness, Communication, and Language Proficiency.
5) Upsell customer conversations
When CX teams are bogged down with an overwhelming amount of tickets, there’s going to be a lack of time and opportunity to upsell in customer conversations. This is especially true when dealing with angry or upset customers, and during high-impact periods like BFCM.
How to use AI and automation for upselling
Activate onsite marketing campaigns with Gorgias Convert to provide product recommendations and promote current discounts, sales, or campaigns.
For example, you can use AI to promote relevant items to shoppers to increase their cart value. You might highlight items that are frequently bought together, or show a bundle that would make a great gift for someone. Research shows that these types of personalized recommendations can increase average order value (AOV) by 15%.
Resource: 5 Holiday Onsite Campaigns to Maximize Year-End Sales
6) Let customers self-serve returns
The National Retail Federation (NRF) projects that retail returns will total $890 billion in 2024. With so many brands losing money from returns, it’s essential that you find ways to mitigate them.
How to use AI and automation for returns
By switching to Gorgias, Audien Hearing saw nearly a 5% drop in return rates. And Rumpl saw $8,000 in recouped return fees by integrating Loop Returns with Gorgias.
Loop lets customers self-serve returns through a returns portal that encourages exchanges instead. It makes the entire process a breeze, and eliminates back and forth between customers and busy support teams.
7) Address common points of confusion
Many times, issues that were completely avoidable are escalated, leaving support teams with more tickets and already frustrated customers. These issues are likely common points of confusion that you can easily solve before they ever reach your customers.
How to use AI and automation to ease confusion
If you use Gorgias, here’s how you can leverage automation:
- Lowest effort: Update your Help Center to address FAQs or policies customers have found confusing in the past.
- Medium effort: Create Flows to address frequently asked questions.
- Highest effort: Set up AI Agent’s handover rules to only escalate certain topics to your human team.
“I’ve been in this role for four years and this was probably our best back to school season yet. In past years, you knew you were going to come in and be bogged down – but this year was way more seamless and much less stressful and that’s thanks to AI Agent.”
—Danae Kaminski, Customer Care Team Lead at Jonas Paul Eyewear
Get time back to do what really matters
At Gorgias, our goal is to create solutions to the real problems CX professionals face every day. Tools like AI Agent make it possible for teams to provide better customer experiences, reduce agent stress, and create more cohesive and positive working environments overall.
”Thanks to the time we've saved by automating many of our routine tasks, our team has had the chance to bond more,” says Noémie.
“We even had time for a team picnic and painted a picnic table outside! It’s been great to step away and spend time as a team occasionally, knowing that our customers are still being taken care of by the AI Agent. It’s really improved team morale.”
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