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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
How to Customize AI Agent with 7 Brand Voice Examples
TL;DR:
- AI Agent adapts to your brand's unique tone of voice. Choose from three default voice options (Friendly, Professional, and Sophisticated), or create countless types of tone with the Custom option.
- Aligning AI with your brand voice builds consistency. A consistent tone in customer interactions helps build trust and brand loyalty.
- Specify what AI Agent can and can’t say. Like your human agents, tell AI Agent your brand do’s and don’ts. From going all out with fun and emoji-filled replies to avoiding certain words, use custom instructions to make AI Agent sound distinctly on-brand.
People are only able to identify AI-generated content 46.9% of the time. That’s less than half the time!
In the ecommerce customer service industry, this is just one reason teams are getting more comfortable with using AI.
Better language processing abilities mean AI can be a better extension of CX teams, relieving agents of repetitive questions, like where is my order?, while speaking in a way that’s familiar and delightful to customers.
Upholding a strong brand voice should be one of your top priorities in CX. With Gorgias AI Agent, you can choose AI Agent’s exact tone of voice, from sophisticated to fun. Below, check out seven AI Agent brand voice examples from real customer conversations.
“We’ve had customers respond to the AI thinking they were speaking to a real person. That’s how elevated the response was from AI.”
—Emily McEnany, Senior CX Manager at Dr. Bronner’s
What is Tone of Voice?
Tone of Voice refers to how AI Agent communicates with your customers. In Gorgias, you can select from three pre-built tone options:
- Friendly
- Professional
- Sophisticated
Or, you can create a custom tone, keeping your brand guidelines, style guide, and target audience in mind.
Note: AI Agent and Tone of Voice are only available to Gorgias Automate subscribers.
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7 Tone of Voice Examples for AI Agent to Match Your Brand's Style
Explore how effectively AI Agent adapts to seven distinct tones in the examples below. First, we’ll show you what a preset AI Agent tone option sounds like, then we’ll move on to six examples using custom instructions.
Feel free to copy and paste our provided instructions to set up your AI Agent with the custom tone of your choice, or, even better, take some inspiration to create your own.
1. Friendly
A friendly AI Agent is the go-to for most CX teams. A Friendly tone of voice is outgoing and welcomes inquiries with enthusiasm. If you were to imagine the model support agent, they would speak like this.
The Friendly tone of voice is available by default in AI Agent’s settings.
How it looks in action
Here’s how an AI Agent with a Friendly tone of voice responds to a customer asking for samples and coupons:
2. Direct and brief
Now, we move away from AI Agent’s default Tone of Voice options and toward the vast possibilities of the Custom option.
If you prefer your AI Agent get to the point in as few words as possible, create a Custom tone of voice that breaks up text into separate lines, limits paragraphs to two to three sentences, and keeps responses short.
💡 Tip: Access a custom tone of voice by going to Automate > AI Agent > Settings > Tone of Voice > Custom. A text field will appear where you can write your instructions.
Tone of voice instructions:
Acknowledge the customer's feelings by briefly repeating their initial concern(s). Break text up, don’t send entire paragraphs, and keep responses short and easy to read. Keep interactions brief but filled with empathy. We are not long-winded. Keep an informative tone while remaining professional, clear, and easy for customers to follow. Insert links where needed. Don't use too many adjectives when expressing empathy. Never tell the customer to email support or contact our customer service team.
How it looks in action
Here’s how an AI Agent with a direct and brief tone of voice responds to a customer who wants to cancel their order:
3. Fun (with lots of emojis! 🤗)
Who says support agents can’t have personality? Bring some fun into your conversations by creating a custom tone of voice that allows your AI Agent to use emojis and exclamation points.
Tone of voice instructions:
Greet with first name only. Acknowledge the customer's feelings by repeating their initial concern(s). Be concise and provide shorter responses, try to keep your responses to a few sentences. Use a warm, positive, and engaging—like chatting with a helpful, considerate friend. Sign off with "Best Regards". Avoid jokes or comments related to sensitive topics. Make the customer feel like a friend. You can include approved emojis for a personal touch and exclamation points. Approved emojis to use: 💞🫶✨🥰💖🎀💓💘🥳💗💕💯 You should recognize and celebrate personal milestones mentioned by customers, making the interaction feel more personal. After the customer's initial message, there's no need to restate their issue in follow-up responses.
How it looks in action
Here’s how an AI Agent with a fun tone of voice responds to a customer asking about exchanging their damaged product:
4. Comforting
Customer support often gets a bad rep. Customers anticipate long response times and unpleasant interactions. Flip customer expectations by giving your AI Agent a calming and comforting voice that can instantly fix negative experiences.
💡 Tip: Brands in the wellness and baby industry would do well to use a comforting tone of voice for their AI Agent.
Tone of voice instructions:
Our brand embodies the role of a nurturing parent, promoting happiness, growth, and well-being while creating moments of joy and inspiration. Stay genuine and reflect childlike wonder without being overly sentimental. We maintain a positive and supportive tone, offering a safe, comforting space. Avoid admitting fault or apologizing. Be shorter in replies. Do not offer replacements. Do not give out phone numbers.
How it looks in action
Here’s how an AI Agent with a comforting tone of voice responds to a customer asking about exchanging their damaged product:
5. Bro-y
Give your AI Agent a laid-back, “we’ve got your back” vibe that feels like chatting with a buddy. This tone keeps things casual, approachable, and like you’re ready to tackle any issue together.
Tone of voice instructions:
Sound like a gym bro. Speak casually and friendly. Be eager to help. However, do not go overboard with puns or stereotypical phrases. You may use the following emojis: 🤙💪🏋️ End responses with "Stay awesome,"
How it looks in action
Here’s how an AI Agent with a bro-y tone of voice responds to a customer asking about glove sizing:
6. Punny
If your brand isn’t afraid to lean into humor and puns, this tone will definitely connect with your audience. Let your AI Agent use wit and clever wordplay to keep conversations lighthearted and customers smiling at their screens.
Tone of voice instructions:
Speak in bee and honey puns and use colorful emojis. Use at least one emoji per message. Keep your messages brief. Sign off with a different pun in every conversation. If a customer is upset or needs urgent help, avoid puns.
How it looks in action
Here’s how an AI Agent with a punny tone of voice responds to a customer asking about suit sizes:
7. Bonus: Robotic
In all of our examples, AI Agent responses can easily be mistaken for one of your human agents. But if, for any reason, you want to change that by making your AI Agent sound robotic — it’s possible.
Tone of voice instructions:
Sound like a robot. Make robot sounds and puns. Use short, direct, and easy-to-read sentences.
How it looks in action
Here’s how an AI Agent with a robotic tone of voice responds to a customer asking about exchanging their damaged product:
Say it how you want with AI Agent
Like a chameleon, AI Agent adapts to your brand voice. Whether it’s friendly, professional, or a custom tone, you can be sure that every interaction aligns with your brand’s identity.
With AI Agent on your side, you have the power to make each conversation feel authentic. Take it from Psycho Bunny’s Senior Customer Experience Manager Tosha Moyer who says, “The overall tone is good, and its responses are really excellent.”
Ready to see AI Agent’s excellence for yourself? Book a demo and discover how AI Agent can be a permanent part of your team.
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