

TL;DR:
Conversational commerce finally has a scoreboard.
For years, CX leaders knew support conversations mattered, they just couldn’t prove how much. Conversations lived in that gray area of ecommerce where shoppers got answers, agents did their best, and everyone agreed the channel was “important”…
But tying those interactions back to actual revenue? Nearly impossible.
Fast forward to today, and everything has changed.
Real-time conversations — whether handled by a human agent or powered by AI — now leave a measurable footprint across the entire customer journey. You can see how many conversations directly influenced a purchase.
In other words, conversational commerce is finally something CX teams can measure, optimize, and scale with confidence.
If you want to prove the value of your CX strategy to your CFO, your marketing team, or your CEO, you need data, not anecdotes.
Leadership isn’t swayed by “We think conversations help shoppers.” They want to see the receipts. They want to know exactly how interactions influence revenue, which conversations drive conversion, and where AI meaningfully reduces workload without sacrificing quality.
That’s why conversational commerce metrics matter now more than ever. This gives CX leaders a way to:
These metrics let you track impact with clarity and confidence.
And once you can measure it, you can build a stronger case for deeper investment in conversational tools and strategy.
So, what exactly should CX teams be measuring?
While conversational commerce touches every part of the customer journey, the most meaningful insights fall into four core categories:
Let’s dive into each.
If you want to understand how well your conversational commerce strategy is working, automation performance is the first place to look. These metrics reveal how effectively AI is resolving shopper needs, reducing ticket volume, and stepping into revenue-driving conversations at scale.
The two most foundational metrics?
Resolution rate measures how many conversations your AI handles from start to finish without needing a human to take over. On paper, high resolution rates sound like a guaranteed win. It suggests your AI is handling product questions, sizing concerns, shade matching, order guidance, and more — all without adding to your team’s workload.
But a high resolution rate doesn’t automatically mean your AI is performing well.
Yes, the ticket was “resolved,” but was the customer actually helped? Was the answer accurate? Did the shopper leave satisfied or frustrated?
This is where quality assurance becomes essential. Your AI should be resolving tickets accurately and helpfully, not simply checking boxes.
At its best, a strong resolution rate signals that your AI is:
When resolution rate quality goes up, so does revenue influence.
You can see this clearly with beauty brands, where accuracy matters enormously. bareMinerals, for example, used to receive a flood of shade-matching questions. Everything from “Which concealer matches my undertone?” to “This foundation shade was discontinued; what’s the closest match?”
Before AI, these questions required well-trained agents and often created inconsistencies depending on who answered.
Once they introduced Shopping Assistant, resolution rate suddenly became more meaningful. AI wasn’t just closing tickets; it was giving smarter, more confident recommendations than many agents could deliver at scale, especially after hours.

That accuracy paid off.
AI-influenced purchases at bareMinerals had zero returns in the first 30 days because customers were finally getting the right shade the first time.
That’s the difference between “resolved” and resolved well.
The zero-touch ticket rate measures something slightly different: the percentage of conversations AI manages entirely on its own, without ever being escalated to an agent.
This metric is a direct lens into:
More importantly, deflection widens the funnel for more revenue-driven conversations.
When AI deflects more inbound questions, your support team can focus on conversations that truly require human expertise, including returns exceptions, escalations, VIP shoppers, and emotionally sensitive interactions.
Brands with strong deflection rates typically see:
If automation metrics tell you how well your AI is working, conversion and revenue metrics tell you how well it’s selling.
This category is where conversational commerce really proves its value because it shows the direct financial impact of every human- or AI-led interaction.
Chat conversion rate measures the percentage of conversations that end in a purchase, and it’s one of the clearest indicators of whether your conversational strategy is influencing shopper decisions.
A strong CVR tells you that conversations are:
You see this clearly with brands selling technical or performance-driven products.
Outdoor apparel shoppers, for example, don’t just need “a jacket” — they need to know which jacket will hold up in specific temperatures, conditions, or terrains. A well-trained AI can step into that moment and convert uncertainty into action.
Arc’teryx saw this firsthand.

Once Shopping Assistant started handling their high-intent pre-purchase questions, their chat conversion rate jumped dramatically — from 4% to 7%. A 75% lift.
That’s what happens when shoppers finally get the expert guidance they’ve been searching for.
Not every shopper buys the moment they finish a chat. Some take a few hours. Some need a day or two. Some want to compare specs or read reviews before committing.
GMV influenced captures this “tail effect” by tracking revenue within 1–3 days of a conversation.
It’s especially powerful for:
In Arc’teryx’s case, shoppers often take time to confirm they’re choosing the right technical gear.
Yet even with that natural pause in behavior, Shopping Assistant still influenced 3.7% of all revenue, not by forcing instant decisions, but by providing the clarity people needed to make the right one.
This metric looks at the average order value of shoppers who engage in a conversation versus those who don’t.
If the conversational AOV is higher, it means your AI or agents are educating customers in ways that naturally expand the cart.
Examples of AOV-lifting conversations include:
When conversations are done well, AOV increases not because shoppers are being upsold, but because they’re being guided.
ROI compares the revenue generated by conversational AI to the cost of the tool itself — in short, this is the number that turns heads in boardrooms.
Strong ROI shows that your AI:
When ROI looks like that, AI stops being a “tool” and starts being an undeniable growth lever.
Related: The hidden power and ROI of automated customer support
Not every metric in conversational commerce is a final outcome. Some are early signals that show whether shoppers are interested, paying attention, and moving closer to a purchase.
These engagement metrics are especially valuable because they reveal why conversations convert, not just whether they do. When engagement goes up, conversion usually follows.
CTR measures the percentage of shoppers who click the product links shared during a conversation. It’s one of the cleanest leading indicators of buyer intent because it reflects a moment where curiosity turns into action.
If CTR is high, it’s a sign that:
In other words, CTR tells you which conversations are influencing shopping behavior.
And the connection between CTR and revenue is often tighter than teams expect.
Just look at what happened with Caitlyn Minimalist. When they began comparing the results of human-led conversations versus AI-assisted ones over a 90-day period, CTR became one of the clearest predictors of success. Their Shopping Assistant consistently drove meaningful engagement with its recommendations — an 18% click-through rate on the products it suggested.
That level of engagement translated directly into better outcomes:
When shoppers click, they’re moving deeper into the buying cycle. Strong CTR makes it easier to forecast conversion and understand how well your conversational flows are guiding shoppers toward the right products.

Discounting can be one of the fastest ways to nudge a shopper toward checkout, but it’s also one of the fastest ways to erode margins.
That’s why discount-related metrics matter so much in conversational commerce.
They show not just whether AI is using discounts, but how effectively those discounts are driving conversions.
This metric tracks how many discount codes or promotional offers your AI is sharing during conversations.
Ideally, discounts should be purposeful — timed to moments when a shopper hesitates or needs an extra nudge — not rolled out as a one-size-fits-all script. When you monitor “discounts offered,” you can ensure that incentives are being used as conversion tools, not crutches.
This visibility becomes particularly important at high-intent touchpoints, such as exit intent or cart recovery interactions, where a small incentive can meaningfully increase conversion if used correctly.
Offering a discount is one thing. Seeing whether customers use it is another.
A high “discounts applied” rate suggests:
A low usage rate tells a different story: Your team (or your AI) is discounting unnecessarily.
This metric alone often surprises brands. More often than not, CX teams discover they can discount less without hurting conversion, or that a non-discount incentive (like a relevant product recommendation) performs just as well.
Understanding this relationship helps teams tighten their promotional strategy, protect margins, and use discounts only where they actually drive incremental revenue.
Once you know which metrics matter, the next step is building a system that brings them together in one place.
Think of your conversational commerce scorecard as a decision-making engine — something that helps you understand performance at a glance, spot bottlenecks, optimize AI, and guide shoppers more effectively.
In Gorgias, you can customize your analytics dashboard to watch the metrics that matter most to your brand. This becomes the single source of truth for understanding how conversations influence revenue.
Here’s what a powerful dashboard unlocks:
Some parts of the customer journey are perfect for AI: repetitive questions, product education, sizing guidance, shade matching, order status checks.
Others still benefit from human support, like emotional conversations, complex troubleshooting, multi-item styling, or high-value VIP concerns.
Metrics like resolution rate, zero-touch ticket rate, and chat conversion rate show you exactly which is which.
When you track these consistently, you can:
For example, if AI handles 80% of sizing questions successfully but struggles with multi-item styling advice, that tells you where to invest in improving AI, and where human expertise should remain the default.
Metrics like CTR, CVR, and conversational AOV reveal the inner workings of shopper decision-making. They show which recommendations resonate, which don’t, and which messaging actually moves someone to purchase.
With these insights, CX teams can:
For instance, if shoppers repeatedly ask clarifying questions about a product’s material or fit, that’s a signal for merchandising or product teams.
If recommendations with social proof get high engagement, marketing can integrate that insight into on-site messaging.
Conversations reveal what customers really care about — often before analytics do.
This is the moment when the scorecard stops being a CX tool and becomes a business tool.
A clear set of metrics shows how conversations tie to:
When a CX leader walks into a meeting and says, “Our AI Assistant influenced 5% of last month’s revenue” or “Conversational shoppers have a 20% higher AOV,” the perception of CX changes instantly.
You’re no longer a support cost. You’re a revenue channel.
And once you have numbers like ROI or revenue influence in hand, it becomes nearly impossible for anyone to argue against further investment in CX automation.
A scorecard doesn’t just show what’s working, it surfaces what’s not.
Metrics make friction obvious:
Metric Signal |
What It Means |
|---|---|
Low CTR |
Recommendations may be irrelevant or poorly timed. |
Low CVR |
Conversations aren’t persuasive enough to drive a purchase. |
High deflection but low revenue |
AI is resolving tickets, but not effectively selling. |
High discount usage |
Shoppers rely on incentives to convert. |
Low discount usage |
You may be offering discounts unnecessarily and losing margin. |
Once you identify these patterns, you can run targeted experiments:
Compounded over time, these moments create major lifts in conversion and revenue.
One of the biggest hidden values of conversational data is how it strengthens cross-functional decision-making.
A clear analytics dashboard gives teams visibility into:
Suddenly, CX isn’t just answering questions — it’s informing strategy across the business.
With the right metrics in place, CX leaders can finally quantify the impact of every interaction, and use that data to shape smarter, more profitable customer journeys.
If you're ready to measure — and scale — the impact of your conversations, tools like Gorgias AI Agent and Shopping Assistant give CX teams the visibility, accuracy, and performance needed to turn every interaction into revenue.
Want to see it in action? Book a demo and discover what conversational commerce can do for your bottom line.
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When Rhoback introduced an AI Agent to its customer experience team, it did more than automate routine tickets. Implementation revealed an opportunity to improve documentation, collaborate cross-functionally, and establish a clear brand tone of voice.
Samantha Gagliardi, Associate Director of Customer Experience at Rhoback, explains the entire process in the first episode of our AI in CX webinar series.
With any new tool, the pre-implementation phase can take some time. Creating proper documentation, training internal teams, and integrating with your tech stack are all important steps that happen before you go live.
But sometimes it’s okay just to launch a tool and optimize as you go.
Rhoback launched its AI agent two weeks before BFCM to automate routine tickets during the busy season.
Why it worked:
Before turning on Rhoback’s AI Agent, Samantha’s team reviewed every FAQ, policy, and help article that human agents are trained on. This helped establish clear CX expectations that they could program into an AI Agent.
Samantha also reviewed the most frequently asked questions and the ideal responses to each. Which ones needed an empathetic human touch and which ones required fast, accurate information?
“AI tells you immediately when your data isn’t clean. If a product detail page says one thing and the help center says another, it shows up right away.”
Rhoback’s pre-implementation audit checklist:
Read more: How to Optimize Your Help Center for AI Agent
It’s often said that you should train your AI Agent like a brand-new employee.
Samantha took it one step further and recommended treating AI like a toddler, with clear, patient, repetitive instructions.
“The AI does not have a sense of good and bad. It’s going to say whatever you train it, so you need to break it down like you’re talking to a three-year-old that doesn’t know any different. Your directions should be so detailed that there is no room for error.”
Practical tips:
Read more: How to Write Guidance with the “When, If, Then” Framework
For Rhoback, an on-brand Tone of Voice was a non-negotiable. Samantha built a character study that shaped Rhoback’s AI Agent’s custom brand voice.
“I built out the character of Rhoback, how it talks, what age it feels like, what its personality is. If it does not sound like us, it is not worth implementing.”
Key questions to shape your AI Agent’s tone of voice:
Once Samantha started testing the AI Agent, it quickly revealed misalignment between Rhoback’s teams. With such an extensive product catalog, AI showed that product details did not always match the Help Center or CX documentation.
This made a case for stronger collaboration amongst the CX, Product, and Ecommerce teams to work towards their shared goal of prioritizing the customer.
“It opened up conversations we were not having before. We all want the customer to be happy, from the moment they click on an ad to the moment they purchase to the moment they receive their order. AI Agent allowed us to see the areas we need to improve upon.”
Tips to improve internal alignment:
Despite the benefits of AI for CX, there’s still trepidation. Agents are concerned that AI would replace them, while customers worry they won’t be able to reach a human. Both are valid concerns, but clearly communicating internally and externally can mitigate skepticism.
At Rhoback, Samantha built internal trust by looping in key stakeholders throughout the testing process. “I showed my team that it is not replacing them. It’s meant to be a support that helps them be even more successful with what they’re already doing," Samantha explains.
On the customer side, Samantha trained their AI Agent to tell customers in the first message that it is an AI customer service assistant that will try to help them or pass them along to a human if it can’t.
How Rhoback built AI confidence:
Read more: How CX Leaders are Actually Using AI: 6 Must-Know Lessons
Here is Rhoback’s approach distilled into a simple framework you can apply.
Watch the full conversation with Samantha to learn how AI can act as a catalyst for better internal alignment.
📌 Join us for episode 2 of AI in CX: Building a Conversational Commerce Strategy that Converts with Cornbread Hemp on December 16.
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TL;DR:
In 2024, Shopify merchants drove $11.5 billion in sales over Black Friday Cyber Monday. Now, BFCM is quickly approaching, with some brands and major retailers already hosting sales.
If you’re feeling late to prepare for the season or want to maximize the number of sales you’ll make, we’ll cover how food and beverage CX teams can serve up better self-serve resources for this year’s BFCM.
Learn how to answer and deflect customers’ top questions before they’re escalated to your support team.
💡 Your guide to everything peak season → The Gorgias BFCM Hub
During busy seasons like BFCM and beyond, staying on top of routine customer asks can be an extreme challenge.
“Every founder thinks BFCM is the highest peak feeling of nervousness,” says Ron Shah, CEO and Co-founder of supplement brand Obvi.
“It’s a tough week. So anything that makes our team’s life easier instantly means we can focus more on things that need the time,” he continues.
Anticipating contact reasons and preparing methods (like automated responses, macros, and enabling an AI Agent) is something that can help. Below, find the top contact reasons for food and beverage companies in 2025.
According to Gorgias proprietary data, the top reason customers reach out to brands in the food and beverage industry is to cancel a subscription (13%) followed by order status questions (9.1%).
Contact Reason |
% of Tickets |
|---|---|
🍽️ Subscription cancellation |
13% |
🚚 Order status (WISMO) |
9.1% |
❌ Order cancellation |
6.5% |
🥫 Product details |
5.7% |
🧃 Product availability |
4.1% |
⭐ Positive feedback |
3.9% |
Because product detail queries represent 5.7% of contact reasons for the food and beverage industry, the more information you provide on your product pages, the better.
Include things like calorie content, nutritional information, and all ingredients.
For example, ready-to-heat meal company The Dinner Ladies includes a dropdown menu on each product page for further reading. Categories include serving instructions, a full ingredient list, allergens, nutritional information, and even a handy “size guide” that shows how many people the meal serves.

FAQ pages make up the information hub of your website. They exist to provide customers with a way to get their questions answered without reaching out to you.
This includes information like how food should be stored, how long its shelf life is, delivery range, and serving instructions. FAQs can even direct customers toward finding out where their order is and what its status is.

In the context of BFCM, FAQs are all about deflecting repetitive questions away from your team and assisting shoppers in finding what they need faster.
That’s the strategy for German supplement brand mybacs.
“Our focus is to improve automations to make it easier for customers to self-handle their requests. This goes hand in hand with making our FAQs more comprehensive to give customers all the information they need,” says Alexander Grassmann, its Co-Founder & COO.
As you contemplate what to add to your FAQ page, remember that more information is usually better. That’s the approach Everyday Dose takes, answering even hyper-specific questions like, “Will it break my fast?” or “Do I have to use milk?”

While the FAQs you choose to add will be specific to your products, peruse the top-notch food and bev FAQ pages below.
Time for some FAQ inspo:
AI Agents and AI-powered Shopping Assistants are easy to set up and are extremely effective in handling customer interactions––especially during BFCM.
“I told our team we were going to onboard Gorgias AI Agent for BFCM, so a good portion of tickets would be handled automatically,” says Ron Shah, CEO and Co-founder at Obvi. “There was a huge sigh of relief knowing that customers were going to be taken care of.”
And, they’re getting smarter. AI Agent’s CSAT is just 0.6 points shy of human agents’ average CSAT score.

Here are the specific responses and use cases we recommend automating:
Get your checklist here: How to prep for peak season: BFCM automation checklist
With high price reductions often comes faster-than-usual sell out times. By offering transparency around item quantities, you can avoid frustrated or upset customers.
For example, you could show how many items are left under a certain threshold (e.g. “Only 10 items left”), or, like Rebel Cheese does, mention whether items have sold out in the past.

You could also set up presales, give people the option to add themselves to a waitlist, and provide early access to VIP shoppers.
Give shoppers a heads up whether they’ll be able to cancel an order once placed, and what your refund policies are.
For example, cookware brand Misen follows its order confirmation email with a “change or cancel within one hour” email that provides a handy link to do so.

Your refund policies and order cancellations should live within an FAQ and in the footer of your website.
Include how-to information on your website within your FAQs, on your blog, or as a standalone webpage. That might be sharing how to use a product, how to cook with it, or how to prepare it. This can prevent customers from asking questions like, “how do you use this?” or “how do I cook this?” or “what can I use this with?” etc.
For example, Purity Coffee created a full brewing guide with illustrations:

Similarly, for its unique preseasoned carbon steel pan, Misen lists out care instructions:

And for those who want to understand the level of prep and cooking time involved, The Dinner Ladies feature cooking instructions on each product page.

Interactive quizzes, buying guides, and gift guides can help ensure shoppers choose the right items for them––without contacting you first.
For example, Trade Coffee Co created a quiz to help first timers find their perfect coffee match:

The more information you can share with customers upfront, the better. That will leave your team time to tackle the heady stuff.
If you’re looking for an AI-assist this season, check out Gorgias’s suite of products like AI Agent and Shopping Assistant.
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TL;DR:
Conversational AI changes how ecommerce brands interact with customers by enabling natural, human-like conversations at scale, helping reduce customer churn.
Instead of forcing shoppers through rigid menus or making them wait for support, conversational AI understands questions, detects intent, and delivers instant, personalized responses.
This technology powers everything from customer service chatbots to voice assistants, helping brands automate repetitive tasks while maintaining the personal touch customers expect.
For ecommerce specifically, it means handling order inquiries, providing product recommendations, and recovering abandoned carts — all without adding headcount.
Conversational AI is a type of artificial intelligence that allows computers to understand, process, and respond to human language through natural, two-way conversations. This means your customers can ask questions in their own words and get helpful answers that feel like they're talking to a real person.
Unlike basic chatbots that only recognize specific keywords, conversational AI actually understands what your customers mean. It can handle typos, slang, and complex questions that have multiple parts. The AI learns from every conversation, getting better at helping your customers over time.
Think of it as having a super-smart team member who never sleeps, never gets frustrated, and remembers every detail about your products and policies. This AI team member can chat with customers on your website, answer questions through social media, or even handle phone calls.
Conversational AI works because several smart technologies team up to understand and respond to your customers. Each piece has a specific job in making conversations feel natural and helpful.
Natural Language Processing (NLP) is the foundation that breaks down human language into pieces a computer can understand. This means when a customer types "Where's my order?" the AI can identify the important words and grammar structure.
Natural Language Understanding (NLU) figures out what the customer actually wants. This is the smart part that realizes "Where's my order?" means the customer wants to track a shipment, even if they phrase it differently like "I need to check my package status."
Natural Language Generation (NLG) creates responses that sound human and helpful. Instead of robotic answers, it crafts replies that match your brand's voice and provide exactly what the customer needs to know.
The dialog manager keeps track of the entire conversation. This means if a customer asks a follow-up question, the AI remembers what you were just talking about and can give a relevant answer.
Your knowledge base stores all the information the AI needs to help customers. This includes your return policy, product details, shipping information, and any other facts your team would use to answer questions.
Conversational AI follows a simple three-step process that happens in seconds. Understanding this process helps you see why it's so much more powerful than old-school chatbots.
When a customer sends a message or asks a question, the AI first needs to understand what they're saying. For text messages from chat, email, or social media, the system breaks down the sentence into individual words and analyzes the grammar.
For voice interactions like phone calls, the AI uses speech recognition to turn spoken words into text first. Modern systems handle different accents, background noise, and natural speech patterns without missing a beat.
Once the AI has the customer's words, it needs to figure out what they actually want. The system looks for the customer's intent — their goal or what they're trying to accomplish.
For example, when someone asks "Can I return this sweater I bought last week?" the AI identifies the intent as wanting to make a return. It also pulls out important details like the product type and timeframe.
The AI also uses context from earlier in the conversation. If the customer mentioned their order number earlier, the AI remembers it and can use that information to help with the return request.
After understanding what the customer wants, the AI creates a helpful response. It might pull information from your knowledge base, personalize the answer with the customer's specific details, or generate a completely new response using generative AI.
The system also checks how confident it is in its answer. If the AI isn't sure about something or if the topic is too complex, it knows to hand the conversation over to one of your human agents.
Different types of conversational AI work better for different situations in your ecommerce business. Understanding these types helps you choose the right solution for your customers and team.
Chatbots are the most common type you'll see on websites and messaging apps. Early chatbots followed strict scripts — if a customer's question didn't match the script exactly, the bot would get confused and give unhelpful answers.
Modern AI-powered chatbots understand natural language and can handle much more complex conversations. The best systems combine both approaches: using simple rules for straightforward questions and AI for everything else.
These chatbots work great for answering common questions about shipping, returns, and product details. They can also help customers find the right products or guide them through your checkout process.
Voice assistants bring conversational AI to phone support and other voice channels. These aren't the old phone trees that made customers press numbers to navigate menus.
Instead, customers can speak naturally and get helpful answers right away. Voice assistants can look up order information, explain your return policy, or even process simple requests like address changes.
This works especially well for customers who prefer calling over typing, or when they need help while their hands are busy.
Read more: How Cornbread Hemp reached a 13.6% phone conversion rate with Gorgias Voice
AI agents are the most advanced type of conversational AI. Unlike chatbots that mainly provide information, AI agents can actually take action on behalf of customers.
These systems connect to your other business tools like Shopify, your shipping software, or your returns platform. This means they can do things like:
Copilots work alongside your human agents, suggesting responses and pulling up customer information to help resolve issues faster.
Read more: How AI Agent works & gathers data
Conversational AI delivers real business results for ecommerce brands. The benefits go beyond just making your support team more efficient — though that's certainly part of it.
24/7 availability means you never miss a sale or support opportunity. Customers can get help at 2 a.m. or during holidays when your team is offline. This is especially valuable for international customers in different time zones.
Instant responses prevent cart abandonment and customer frustration, improving first contact resolution. When someone has a question about sizing or shipping, they get an answer immediately instead of waiting hours or days for an email response.
Personalized interactions at scale drive higher average order values. The AI can recommend products based on what customers are browsing, their purchase history, and their preferences, just like your best salesperson would.
Cost efficiency comes from handling repetitive questions automatically. Your human agents can focus on complex issues, VIP customers, and revenue-generating activities instead of answering the same shipping questions over and over.
Multilingual support helps you serve global customers without hiring native speakers for every language. The AI can communicate in dozens of languages, opening up new markets for your business.
Certain moments in the shopping experience create the biggest opportunities for conversational AI to drive results. Focus on these high-impact use cases first.
Pre-purchase questions are your biggest conversion opportunity. When someone is looking at a product but hasn't bought yet, quick answers about sizing, materials, or compatibility can close the sale. The AI can also suggest complementary products or highlight features the customer might have missed.
Order tracking makes up the largest volume of support tickets for most ecommerce brands. Customers want to know where their package is, when it will arrive, and what to do if there's a delay. AI handles these WISMO requests instantly by pulling real-time tracking information.
Returns and exchanges can be complex, but AI excels at the initial screening. It can check if an item is eligible for return, explain your policy, and start the return process. For straightforward returns, customers never need to wait for human help.
Cart recovery works best when it's immediate and personal. AI can detect when someone abandons their cart and reach out through chat or email with personalized messages, discount offers, or answers to common concerns that prevent purchases.
Post-purchase support keeps customers happy after they buy. The AI can send order confirmations, provide care instructions, suggest related products, and handle simple issues like address changes.
Getting started with conversational AI doesn't require a complete overhaul of your systems. The key is starting with clear goals and building your capabilities over time.
The best automation opportunities are found in your tickets. Look for questions that come up repeatedly and have straightforward answers. Common examples include order status, return policies, and basic product information.
Set realistic goals for your first phase. You might aim to automate 30% of your tickets or reduce average response time by half. Track metrics like:
Not all conversational AI platforms understand ecommerce needs. Look for a platform that integrates directly with Shopify and your other business tools. This connection is essential for pulling real-time order data, customer history, and product information.
Your platform should come with pre-built actions for common ecommerce tasks like order lookups, return processing, and subscription management. This saves months of custom development work.
Make sure you can control the AI's behavior through clear guidance and rules. You need to be able to set your brand voice, define when to escalate to humans, and update the AI's knowledge as your business changes.
Start your implementation by connecting your Shopify store to give the AI access to order and customer data. Don’t forget to integrate the rest of your tech stack like shipping software, returns platforms, and loyalty programs.
Launch with a few core use cases like order tracking and basic product questions. Monitor the AI's performance closely and gather feedback from both customers and your support team. Use this data to refine the AI's responses and gradually expand its capabilities.
The best approach is iterative — start small, learn what works, and build from there.
While conversational AI offers significant benefits, you need to be aware of potential challenges and plan for them from the start.
Accuracy concerns arise when AI systems provide incorrect information or "hallucinate" facts that aren't true. Prevent this by using platforms that ground responses in your verified knowledge base and product data rather than generating answers from scratch.
Brand voice consistency becomes critical when AI represents your brand to customers. Set clear guidelines for tone, style, and messaging. Test the AI's responses regularly to ensure they align with how your human team would handle similar situations.
Data privacy requires careful attention since conversational AI handles sensitive customer information. Choose platforms with strong security measures, data encryption, and compliance with regulations like GDPR. Look for features like automatic removal of personal information from conversation logs.
Over-automation can frustrate customers when complex issues require human empathy and problem-solving. Design clear escalation paths so customers can easily reach human agents when needed. Train your AI to recognize when a situation is beyond its capabilities.
Integration complexity can slow down implementation if your chosen platform doesn't work well with your existing tools. This is why choosing an ecommerce-focused platform with pre-built integrations is so important.
The brands winning with conversational AI start with clear goals, choose the right platform, and iterate based on real performance data. They don't try to automate everything at once. They focus on high-impact use cases that deliver real results.
Ready to see how conversational AI can transform your ecommerce support and sales? Book a demo with Gorgias — built specifically for ecommerce brands.
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TL;DR:
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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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.
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.
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.
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:
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:
Rank |
Ticket Topic |
% of Escalations |
|---|---|---|
1 |
Order status |
12.4% |
2 |
Return request |
7.9% |
3 |
Order cancellation |
6.1% |
4 |
Product - quality issues |
5.9% |
5 |
Missing item |
4.6% |
6 |
Subscription cancellation |
4.4% |
7 |
Order refund |
4.1% |
8 |
Product details |
3.5% |
9 |
Return status |
3.3% |
10 |
Order delivered but not received |
3.1% |
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:
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.
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.
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
A structured layout helps both AI and shoppers find the right step faster, without confusion or escalation.
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:
This logic helps AI know what to do and how to explain the answer clearly to the customer.
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.
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:
Example: “If your return meets our policy, request your return label here.”
That extra step keeps the conversation moving and prevents unnecessary escalations.
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:
A consistent tone keeps your Help Center professional, helps AI deliver reliable responses, and creates a smoother experience for customers.
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 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.

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.


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’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 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
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.
Break up long text blocks and use descriptive headers (H2s, H3s) so readers and AI Agent can instantly find the right section.
Spell out what happens in each scenario. This logic helps AI Agent decide the right next step without second-guessing.
Make sure your Help Center includes complete, structured articles for high-volume issues like order status, returns, and refunds.
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.
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.
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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Customers who use chat support are 2.8 times more likely to convert than those who don’t. Despite its proven impact, misconceptions around chat’s limited scope — reducing it to only live interactions — persist, creating a missed opportunity for the online stores that could benefit from it the most.
The reality is chat is a versatile tool that can adjust to company needs, whether it’s a self-service tool that runs on its own, a channel for providing live support, or both.
For ecommerce businesses on the fence about incorporating chat into their customer service operations, we're here to clear up five of the most common myths about chat’s functions, costs, and benefits. After that, we’ll lay out a five-step guide to efficiently set up chat so you can start delighting customers now.
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Live chat is real-time communication that allows customers to interact with a customer service representative instantly. It's the digital equivalent of walking into a store and speaking directly with an employee.
On the other hand, chat is more than just live interactions; it includes automated responses that ensure customers receive support, even without agents. This hybrid approach allows businesses to deliver 24/7 customer support.
Chat solutions, like Gorgias Chat, blend live chat's on-demand nature with automation and AI. Chat allows businesses to provide support regardless of time zone and staff availability.
Confusion about what chat can do often discourages businesses from leveraging the powerful customer service tool. Below, we’ll be myth-busting five common misconceptions about chat to reveal its true potential.
Contrary to popular belief, chat can be a cost-effective solution to operate customer service. Brands can earn 10x more revenue by implementing chat and, in turn, operate a smaller support team. Support agents can be costly, so using chat to deflect tickets can be a quick way to optimize both time and budget.
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Chat's usefulness transcends business size and breaks down silos in customer service by allowing customers to get answers on their own time. As a customer service tool, any business engaging with customers can benefit greatly from it to tackle pre-sales questions and resolve issues efficiently.
As previously mentioned, chat can handle both live and automated interactions, which means no agents are required to manage it. Online stores can set up chat on their websites, allowing it to run 24/7. Businesses can decide whether to enable live chat or keep it fully automated.
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Related: Customer service outsourcing: why, when, and how
Due to automation-based conversations in chat, ticket volume does not necessarily increase when customers use chat. A ticket is only created when a customer converses with a live agent. Unlike using social media as a support channel, chat empowers customers to self-serve and resolve issues on their own.
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Contrary to popular belief, chat has a positive impact on customer satisfaction. Based on Gorgias data, brands experienced a 1% increase in CSAT when using automation, including chat. The improved satisfaction can be attributed to the efficiency of automated answers and the absence of wait times.
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While email remains a staple, chat offers immediate engagement in the shopping flow that can create opportunities for upselling. For example, an on-site campaign toolkit like Gorgias Convert becomes a seamless extension of your sales and support strategy with the ability to recommend products within chat.
Since chat simplifies the process of reaching out, it is also easier for companies to build trust with their customers. The fewer hurdles customers have to jump over to get an answer, the more readily they will trust your brand.
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Read more: You’re doing it wrong: better ways to use email as a customer service channel
Now that you know chat isn’t expensive and can give you a great return on investment, you can start making the most of it. Here’s the optimal way to set up chat in four, simple steps.
A study from the University of Göttingen found that customers value clarity on whether they're conversing with a bot or a human agent. Their satisfaction did not dwindle when issues went unresolved, knowing they were interacting with a chatbot.
You can add “Bot” to your chat name on Gorgias whenever automated messages are sent. Enabling this improves the customer experience by letting them know exactly who they are talking to.
In addition, customizing your chatbot avatar to your company logo instead of leaving it as the default robot avatar adds a personal touch. If live chat is enabled, uploading individual profile photos for your agents will help customers feel more comfortable since they’re able to associate a face with the agent they’re talking to.
Frequently asked questions can quickly dominate your inbox, but with Quick Responses, you can offer fully automated answers. This allows you to provide customer service on an international scale without worrying about increasing agent workload.
Gorgias Automate upgrades your customer experience with an entire automation toolkit that includes Quick Responses in Chat. You can display up to six Quick Responses at a time, providing customers with immediate answers to their questions.
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While many assume live chat needs to be available for extended hours, the truth is that live chat hours can be tailored to what suits your brand best, even if that's just one hour a day. The key is to clearly communicate when an agent will respond to customers outside of these hours.
Customers prefer live chat because of the lack of wait times, so if you’re offering live chat, be sure your agents meet customer expectations by answering chat conversations in 30 seconds. Strengthening customer relationships is crucial to building trust and, therefore, increasing your ecommerce retention rate. On Gorgias, setting your business hours will directly update how Chat appears to customers.
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A help center is a database of articles that range from frequently asked questions and guides to video tutorials and policies. On Gorgias, Chat can use your Help Center articles to enrich automated answers with detailed information. For instance, fashion and apparel stores can create a sizing guide article, which Chat can then reference, guiding customers directly to the information they need.
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Gorgias Automate enabled luxury luggage company July to handle the equivalent workload of three extra agents. With tools like Chat, July went from handling repetitive queries to focusing on more significant customer issues. This significant change enhanced their support efficiency and customer satisfaction.
Want to become a success story? Discover how Gorgias Automate can streamline your support workflow and elevate customer experience. Book a demo today.

Since ChatGPT was introduced in November 2022, customer service automation has stormed its way into almost every industry, including ecommerce. This leap in technology has paved the way for companies to increase their support efficiency dramatically, as demonstrated by the buy-now-pay-later service Klarna, which recently resolved two-thirds of customer service chats with AI.
The business gains arising from automation are evident. Faster and smarter tools mean less time handling mundane tasks and more time improving the customer journey with meaningful conversations, personalized experiences, and seamless upselling opportunities.
At Gorgias, our mission is to elevate customer experiences with automated solutions. To determine the impact, we analyzed data from over 14,000 merchants who use automation compared to those who do not.
Our data revealed a 36% increase in repeat purchases, a 37% reduction in first response time, a 52% reduction in resolution time, a 27% decrease in the ticket-to-order ratio, and a 1% increase in CSAT when automation is used.
These compelling results assert our belief in automation as the next, inevitable step for scaling support teams.
“AI is going to help us transform ourselves into deeper thinkers by taking over simple, standardized functions” —Ron Shah, CEO and Co-founder at Obvi
Before automation, customer service teams scrambled to hire more agents as their customer bases grew. When Black Friday and other peak seasons arrived, hiring more agents was the Band-Aid fix. Today, companies are opting for leaner support teams as automation allows them to do more with less. The benefit? Teams can scale and improve the quality of service without temporarily bringing on new staff.
Automation works like a junior support agent but at a higher efficiency. It can handle frequently asked questions like where is my order? and customize responses according to brand voice. So, as repetitive tasks are handled in the background, agents can focus on more complex tickets, such as product-specific questions or technical issues that require troubleshooting.
“Before, agents had to handle it all. Now, they rarely take a ticket about frequently asked questions. They’re only handling escalations, special product-related questions, and things like that.” —Caela Castillo, Director of Customer Experience, Jaxxon
The flexibility of automation makes it the ideal tool for personalized customer service. Aside from being a keyboard shortcut or macro, automation can be a hands-off assistant that can engage customers and influence as much as 25% of revenue.
At Gorgias, automation is at the core of our products, powering almost every feature in Helpdesk, Automate, and Convert. It allows merchants to deliver delightful and personalized customer interactions across various channels and touchpoints in the customer journey.
While automation is only one of many factors, we’ve found it to positively impact support performance metrics. Based on our data, merchants who used automation saw clear improvements in repeat purchase rates, response times, resolution times, tickets per order, and CSAT scores.
Retaining customer loyalty is challenging even when brands launch loyalty programs, as customers are discouraged by the effort required to receive rewards. However, Gorgias data shows that simply using automation can increase repeat purchase rates. Within 28 days, merchants who automated up to 20% of tickets increased their repeat purchase rate by 8 points.
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Yoga apparel brand Manduka used Gorgias Convert's on-site campaigns to influence customers to purchase multiple products. The campaign convinced shoppers to hit a $100 order total for free shipping by recommending small additional items they may be interested in. Their campaign brought in nearly $12,000, proving that automation can directly affect revenue.
“We want to be able to target our repeat customers who have purchased a lot, and say, ‘Welcome back! Here's a new product that would go wonderfully with the item you bought last time.’ It would be a wonderful translation of the in-person retail experience where staff know what you like, so they can assist you better.” —Jessica Botello, Customer Service Manager at Manduka
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Automated responses resolve tickets in zero seconds and result in faster first response times. On average, merchants using automation respond 37% faster than ones who don’t automate customer service.
Responding to customers as quickly as possible is especially important during busy seasons like Black Friday and Cyber Monday so that revenue-generating questions don’t get pushed to the backlog. The customer experience team at health supplement brand Obvi was able to drive 3x more purchases from support conversations compared to previous years.
Faster response times also mean agents are able to make stronger connections with customers. For Obvi’s CX team, it translated to more time to engage with their vibrant Facebook community:
“Instantly, our CX team had time to prioritize important matters, like being active in our community of 75,000 women instead of sitting answering emails.” —Ron Shah, CEO and Co-founder at Obvi
When customer tickets are automated, resolution times improve dramatically. Merchants using automation resolved tickets 52% faster than those without.
Automation is especially helpful in answering pre-sales questions. High-end luggage retailer July deflected 450 tickets a month immediately after activating Quick Responses, one-click FAQs that live in Chat. Their Head of Operations and CX, Alex Naoumidis, notes that setup was “so easy, with a huge payoff.”
This significant efficiency gain ensures customers are well-educated about their products, leaving agents time to personalize the rest of the customer journey.
As automated responses provide quick solutions to customer issues, customers need to contact support less. Based on our data, brands that automate 10% or more of their tickets see a decrease in billable tickets per order. Brands with little to no automation do not see a significant improvement in the ticket-to-order ratio.
For apparel brand Shinesty, automating more than 10% of tickets greatly decreased the number of tickets per order by 27%. Self-serve tools like interactive conversations called Flows and Article Recommendations enabled customers to solve issues relating to discounts, subscription policies, and returns on their own.
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“Automate would be useful for any ecommerce company that needs to lower their ticket counts, or wants to provide a more consistent experience.” —Molly Kerrigan, Senior Director of Retention at Shinesty
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Thirty days after setting up automation in Gorgias, brands enjoyed a 1% increase in CSAT score, a 4.51 score compared to 4.46 for non-automating brands. Even though satisfaction only nudged an inch, the positive effects reached support teams, improving agent morale and team alignment.
Molly Kerrigan, Senior Director of Retention at Shinesty, emphasizes the importance of preserving quality customer interactions during growth, "We get a lot of praise from our customers, and they talk highly of our CX team after 1:1 interactions. We can’t lose that as we scale."
Since Gorgias provides in-depth conversation analytics, CX teams are finally able to see their impact.
“Tracking customer satisfaction scores in Gorgias is a really big help to us. Before, we didn't know if we were doing well or not, but now we can see people like the service we provide. We use the KPI tracking data for internal monthly meetings to review performance and see where we can improve,” says Deja Jefferson, Customer Experience Manager at Topicals.
Clearly, balancing automation with personalization significantly improves the customer journey. Given that customers with positive customer experiences are 2.7 times more likely to do repeat business, the value of automation is unmistakable.
AI progress has advanced in a short amount of time. But to remind you, this is only the beginning of what automation and AI can do in customer service. We envision AI as a constant work in progress, meant to intake information until it is capable enough to handle more complex tasks. This means agents will spend more time building strong customer connections and finding ways the business can grow.
Gorgias is at the forefront of this evolution, developing automation and AI-driven solutions like an AI-generated Help Center, an AI Agent, a generative AI assistant that autonomously answers customer questions, and an Interaction Quality Score to measure and report on AI-customer interactions. Gorgias aims to transform how support teams and customers interact with AI, paving the way for more impactful customer experiences on a human scale.
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TL;DR:
The Help Center is more than a database to make the lives of your agents and customers easier. It's also an ingenious way of creating brand awareness. By enhancing your Help Center's visibility, you carve new pathways for shoppers to discover your brand while solidifying your brand's reliability with loyal followers.
This guide delves into practical methods for increasing your article views and turning your Help Center into a dynamic hub with Gorgias. We’ll look at the basics of a Help Center, how to structure it based on statistics and SEO, and how to share it across multiple channels.
A Help Center is a knowledge database of articles addressing common questions about your products, services, and brand. It empowers customers to find solutions on their own without needing to contact your customer service team.
A Help Center can include how-to articles, policies, answers to frequently asked questions, and more. Each article can also be supplemented with images, GIFs, and videos to better guide customers toward solutions.

Boosting your Help Center's visibility involves two key elements: understanding customer concerns to create relevant content and using SEO to increase article views.
Focusing on your customers' specific needs and questions allows you to provide articles that directly address their concerns.
Let’s delve into the two strategies you can use with Gorgias.
The first step to creating Help Center articles is understanding your customers’ problems. Identifying their concerns ensures your content aligns with what questions need clarification.
Here are five ways to uncover customer concerns with Gorgias Statistics:
Tags are labels for categorizing tickets by topic or customer intent. Regularly reviewing tags helps identify common customer inquiries. Generally, the more a tag is used, the greater the need for clarity on that topic.
On Gorgias, navigate to Statistics -> Ticket Insights -> Tags to see tag usage frequency. This view gives you an overview of popular tags. You can also adjust the view by filtering by app integration, channel, and date range.
💡 Pro Tip: The most frequently used tags can help inform what articles you should include in your Help Center. Based on the screenshot below, it would be smart to create articles about FAQs and a Price Match policy.

Intent Statistics provide valuable insights into why customers contact support. By analyzing these statistics, you can understand the primary reasons behind customer queries.
On Gorgias, go to Statistics -> Ticket Insights -> Intents to review the usage frequency of different customer intents.
This feature provides a clear bar graph view of customer concerns that are frequently mentioned in messages. You can also change the view using filters such as channel and date range.

Another way to learn about your customers’ concerns is by looking at contact reasons. On Gorgias, Contact Reason is an AI-powered feature that identifies a ticket's contact reason from its message content. Reasons could range from cancellations and refunds to shipment issues and feedback.
The Contact Reason is conveniently located at the top of each ticket, as shown in the image below.

While positive CSAT scores are gratifying, it's the negative feedback that truly helps improve your customer support.
To view Satisfaction scores on Gorgias, navigate to Statistics -> Support Performance -> Satisfaction. This section provides details on surveys sent, response rates, average ratings, and response distribution over three months.
💡 Pro Tip: For deeper insights into CSAT scores, filter for scores of 3 stars or below. Analyzing lower ratings and their accompanying comments will help you pinpoint the exact topics your Help Center articles should address.


Checking the performance of your articles can be the key to adding relevant articles to your Help Center while avoiding unnecessary topics.
On Gorgias, you can find individual article performance by going to Statistics -> Help Center -> Performance by articles. Articles are sorted from most viewed to least.
Here’s how to use article performance data to write relevant articles:
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SEO (Search Engine Optimization) isn't solely for your primary webpages. It's equally crucial for Help Center articles. Using SEO tactics in Help Center articles boosts their online visibility, but most importantly, they allow you to turn visitors into customers.
Here are some effective SEO strategies to apply:
Using relevant and related keywords in an article can boost search visibility. Customers won’t always use the same search query, so anticipating their word usage will help capture all types of customers looking for your content.
On Gorgias, you can find out what keywords customers are searching for under Statistics -> Help Center -> Help Center searches.

Here’s how to leverage search result data:
💡 Pro Tip: Don’t forget to incorporate relevant keywords into your article titles, subheadings, and excerpts. There are two benefits to this: they make it easier for customers to quickly scan your content and enhance your brand's discoverability in search engines.

Again, data plays a crucial role in making your support and Help Center the ultimate resources. On Gorgias, the "Performance by articles" section allows you to track how well each article performs. Articles are sorted by view count, ratings, and the dates they were last updated.

Here’s how you can leverage the following types of articles:
Internal links are hyperlinks that point to other articles in your Help Center, creating a network of related content. This tactic helps to proactively address questions customers might not have considered, effectively reducing the load on your support team.
To effectively increase the visibility of your Help Center articles, consider leveraging a variety of communication channels:
Remember, a well-optimized Help Center is a powerful tool in building brand awareness and customer loyalty.
Do more with an AI-powered Help Center with the power of Gorgias Automate. Discover how our advanced tools can streamline your support processes and improve customer satisfaction. Book a demo today.
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TL;DR:
At Gorgias, we're avid believers in transparency. You'll find us documenting processes diligently, asking for feedback frequently, and addressing concerns openly. This may be surprising and even unconventional to most, but after witnessing its long-term benefits on employee satisfaction and engagement, our team is set on continuing the practice.
As a natural next step in our commitment to openness, we decided to make our People Resources available to everyone. These resources include documents and processes that outline how we operate at Gorgias, including how we approach the compensation process, performance reviews, and more.
We invite you to delve into our resources, whether you’re a founder or a job seeker.
Our decision to share our People Resources is driven by a vision that sets new standards for transparency in evolving corporate practices.
By opening up our resources to the public, Gorgias positions itself as an innovator and thought leader in the industry. Allowing our processes to be read and critiqued by others outside of the company gives way to perspectives we may not have considered.
We view our People Resources as living documents and as we drive discussions about transparent work culture, the opinions and critiques of others will be a constant source of value for us to continue improving our processes.
For other organizations, accessing Gorgias' People Resources serves as a blueprint for building a positive and engaging workplace. By publicizing our processes, we hope to guide companies to create safer and more honest work environments, which in turn will improve employee satisfaction globally.
Our People Resources encompass a wide range of materials, including documents, processes, and additional resources. Here's what you'll find:
Read more: Why we don't increase salaries each year based on performance
Our People Resources are designed with a wide audience in mind, ensuring that anyone interested in building a positive team environment can find value. Here's who can benefit:
You can find our public People Resources on Notion.
If you're inspired by what you see and want to join our growing team, we invite you to check out our current job openings.
We look forward to welcoming you to Gorgias, where we will continue building a transparent and innovative workplace.

TL;DR:
While there’s a common concern that automation might alienate customers with responses that miss the mark, it turns out that 73% of customers have higher expectations for personalized experiences when advanced tech is involved.
Not only do customers expect automation and AI in customer service, but they also believe that brands should make the most out of them.
Luckily, helpdesk tools like Gorgias have found the right balance between automation, personalization, and human touch. The only thing left for CX agents to do is to use automation strategically.
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Automation and AI are distinct, just like live chat versus chatbots. AI, such as ChatGPT, evolves in real-time from interacting with and learning from input data, while automation follows set rules for routine tasks without understanding natural language.
Automation is highly customizable — it won’t spew out an inappropriate sentence unless you tell it to. If you’re still hesitant about automating your support, here are four automation myths debunked below.
The tone and style of your automated messages are entirely within your control, thanks to the customizable nature of automation. This flexibility ensures that your brand's unique voice shines through, allowing for a tailored approach that aligns with your ecommerce strategy.
If we’re talking about AI, we’ve also come a long way from generic chatbot responses. In fact, a 2019 Stanford University report found that AI computational power doubled every 3.4 months. The result? Humans are only correct 60% of the time when guessing if they’re talking to AI or a real person.
In reality, automation is highly adaptable and can incorporate customer data, brand voice, and plenty of dynamic variables to create powerful communications for personalized customer service.
Learn more: How Manduka used personalized, on-site campaigns and earned $70k
While automation enhances efficiency, it works best in tandem with human insight rather than as a complete replacement for human agents. Customer service thrives when there is a route back to human support.
Yes, customers appreciate the ease of connecting to a fellow human, but they also value speed — something automation excels at compared to humans.
Learn more: How Luksusbaby boosted 66% first response time with 45% automation
A customer-centric helpdesk trained on AI is the most effective way to have rapid and authentic customer interactions. A tool like Gorgias enables you to scale your customer service operations by connecting your ecommerce store. Gorgias learns customer conversations and data and automates simple processes like responding to repetitive tickets and refunding orders.
To effectively implement customer service automation, always remember to add a human touch to make customers feel comfortable. More importantly, not all customer interactions are suitable for automated responses so automate strategically.
Here are five ways to implement personalized automation with Gorgias, from automating responses to using website chat and creating a help center.
Skip the mental work of reading a frequently asked question and thinking of a response. Auto-responses will do both for you in the background while you complete other high-priority tasks.
How to implement:
Note: Manually follow up on complaints or technical issues. Using auto-responses on these sensitive issues may escalate them and cause more customer frustration.

AI is excellent at answering simple inquiries, but sometimes customers will ask questions that need a human’s problem-solving skills. Include a route to a live agent to address this. Allowing AI and agents to work in tandem is an effective way to improve customer satisfaction.
How to implement:
Note: Don’t trick customers into thinking they’re speaking to an agent when they’re speaking to AI. Customers are more likely to trust you when you set clear expectations from the start.

Make personalization a part of the customer journey to create friendly experiences on a large scale. Without tailored communications, you’ll likely frustrate 76% of your customers due to irrelevant recommendations and marketing campaigns.
How to implement:

According to a survey of 3,000 consumers, 56% would repurchase from a retailer that provides personalization. For this reason, create an automated action, also known as a rule, that labels tickets from VIP customers. Prioritizing VIP needs will allow your team to strengthen loyalty and drive repeat purchases.
How to implement:

The responsiveness of AI depends on the knowledge you feed it. To accelerate automation’s efficiency, provide it with resources from your knowledge base or help center. In 2020, organizations reported a reduction of up to 70% in call, chat, and email inquiries after implementing a chatbot or virtual customer assistant.
How to implement:

Read more: 9 types of customer self-service
Setting up automation without the right tools can detract from personalization efforts. Gorgias Automate remedies this by equipping CX teams with features like Autoresponders, self-service Order Management, Quick Responses in Chat, and Article Recommendations. Elevate customer experiences and grow your customer relationships by booking a demo with Gorgias today.
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Last September, Gorgias hosted CX-All Star: Episode 1, a webinar presented by a superstar panel of customer experience leaders in the DTC industry. From the health and wellness space to the tech sphere, experts Eli Weiss, Amanda Kwasniewicz, Deja Jefferson, and Ren Fuller-Wasserman gathered years of experience and wasted no time sharing their top strategies, tips, and a-ha moments with fellow attendees.
One hour wasn't long enough to reveal all their expert tricks, but it was definitely enough to help fellow CXers rethink their strategy. If you weren't able to attend the event, these were the top four lessons we learned from CX All-Star: Episode 1.
Amanda Kwasniewicz, the VP of Customer Experience at Love Wellness, emphasizes how CX should be the core of any business. "[CX] has a finger on the pulse of everything we do, whether we're just on the receiving end or whether we're executing it."
To emphasize CX's far-reaching impact, Amanda introduced a company-wide policy where every new employee spends six weeks working directly with support tickets and customers. This immersive approach to CX was so successful that non-CX team members, from marketing to finance, were able to help the CX team during a hectic inbox day when Love Wellness migrated platforms.
Read more: Why customer service is important, according to a VP of CX
"I think CX is often viewed as a call center, a revenue driver—and we're missing the core part that it's a feedback machine. It's like a feedback treasure trove. So, if you can think about it as all three of those things, that's what it is. It really is about the experience."
—Amanda Kwasniewicz, VP of Customer Experience at Love Wellness
"Brands are either notoriously anti-having a big CX team, or they're very straightforward. Either one of those extremes is dangerous," says Eli Weiss, VP of Retention Advocacy at Yotpo. The balance lies in building a team of passionate learners willing to grow.
Our experts agree that product knowledge can be taught through training, but soft skills like empathy, creativity, and passion are intrinsic. Eli notes that asking questions like "Why CX?" helps determine if a candidate will stick around. Amanda notes these team members often become superstar hires for other departments because of the breadth of their knowledge and skills.
Related: Hiring for customer service
“[LinkedIn] is how I've gotten a lot of people early on. I just looked at brands that crush it and said, 'Stay exactly where you are. I just need 2 hours.' Those 2 hours will usually give you what you as a founder can do in six, because somebody that's doing it all day is probably really good at figuring out how to put a move on it.”
—Eli Weiss, VP of Retention Advocacy at Yotpo
"If people can understand and learn the product they're selling and they can educate the customer, I think that's really valuable," says Deja Jefferson, Manager of Customer Insights at skincare brand Topicals. That's why she takes a diverse approach to product knowledge onboarding.
At Topicals, new hires don't only have to pore over lengthy documents to learn about skincare products. They get their hands dirty by speaking to experts in the product team, reading cheat sheets, and talking to customers about personal skin concerns. This multifaceted strategy is inclusive to all types of learners and leads to agents becoming true experts.
Read more: Customer service training: what to cover + how to do it
"People who are passionate about what they're doing and about helping customers [will] figure out the rest."
—Deja Jefferson, Customer Insights Manager at Topicals
Ren Fuller-Wasserman, Head of Customer Experience at bidet brand TUSHY, empowers her team to go above standard protocols to create memorable or, as her team calls it, mensch (Yiddish for a person of integrity) moments. These are exceptional CX moments that can't be found in the onboarding manual, things like sending handwritten notes, personalized texts, and replacing items without question.
However, as with all things, it's also valuable to understand that mistakes happen. Ren likens the trial-and-error nature of customer experience to building a plane as it's being flown — it won't be perfect. She notes that protocols are important guidelines, but it's also worthwhile to allow your team to be mensch and decide, where do I need to follow the protocols here?
"There are incredible opportunities to make moments that matter, but only if your team has the agency to do so."
—Ren Fuller-Wasserman, Head of Customer Experience at TUSHY
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Imagine leaving your angriest customers to spar with an automated script in your website’s chat window. Now picture your support team reading “Where is my order?” for the hundredth time and glancing at the clock, only to find six hours left in the workday.
Who do you think is more frustrated?
Luckily, you won’t have to answer that, because these are completely avoidable problems. Once you learn the important distinctions between chatbot software and live chat software, you’ll understand how to use them both more effectively and lower blood pressures across the board.
Chatbots rely completely on automation and artificial intelligence (AI) while live chat software connects customers with human agents via a real-time chatbox. A third option, self-service chat, is an appealing alternative.
To determine which solution(s) is best for your business, let’s compare chatbots and live chat software and go through the top use cases for each.
Live chat support connects customers with human support agents who can answer their questions and assist them with any issues. When a customer opens the chat box on a live chat support solution, they are connected with a real person from the company's customer support department.
Support agents then use live chat messaging to address customer inquiries and walk customers through the solution to their problem.
Interested in getting live chat software? Check out one of these lists for tailored recommendations:
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Unlike live chat software, chatbot software doesn’t connect customers with human agents. Instead, chatbot software connects customers with a chatbot that utilizes AI and machine learning to provide natural language answers to common questions.
Automation assists customers with less complex issues and provides quick answers. Chatbot technology enables companies to reduce their average response time, and frees up support agents to focus on more complex queries.
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When comparing chatbots with live chat solutions, it's important to recognize that each category offers its own unique advantages. Many companies choose to employ both live chat and chatbot apps on their ecommerce websites.
With that in mind, let's explore the strengths of each solution.
One of the biggest advantages of chatbot solutions is the fact that they allow for immediate responses to customer inquiries. Live chat solutions can also help companies reduce their wait times, though not to the same degree.
According to data from HubSpot, 90% of customers rate an "immediate" response as important or very important when contacting customer service, with 60% of customers defining "immediate" as 10 minutes or less.
With a chatbot app, offering immediate response times to customer queries is a much more attainable goal. Best of all, these immediate response times are a 24/7 offering for customers, whereas live chat agents may not always be on the clock.
The problem with relying solely on chatbots to reduce customer wait times is the fact that even the best and most intelligent chatbots are often unable to resolve complex issues. Chatbots are excellent at pulling information from internal databases to answer common questions, such as providing the status of a customer's order or editing it.
But for uncommon questions or complex issues, a chatbot alone may not be sufficient. Because they can only handle one thing at a time, it can take forever before you get all of your questions resolved.
Many companies use chatbots alongside live chat support. This allows businesses to offer both immediate responses, as well as more in-depth support for complex issues.
For example, a customer may first be connected with a chatbot that provides instant responses to their query and assists with gathering initial information. If the chatbot determines the customer's question or issue is too complex to resolve, the customer is then connected to a support agent via live chat.
This combination is an ideal solution for many companies, allowing them to quickly resolve common issues without the need for a live chat agent. At the same time, customers have the option to speak with a real person in cases where assistance from a chatbot alone isn’t sufficient.
While chatbot apps can help reduce customer service wait times and the number of customer service reps needed, many customers prefer speaking with a person.
A CGS study found that 86% of customers would rather interact with a human agent than a chatbot. Further, 71% of customers say that they would be less likely to purchase from a brand that did not have real customer service representatives available.
Chatbots have come a long way toward replicating natural language and determining customer intent for better customer engagement. Today, the best chatbot applications can come quite close to sounding like actual human beings.
Chatbots leverage AI and machine learning to deliver personalized responses, as opposed to only “canned” responses, and can better serve your customers.
Even the most advanced chatbots still fall short of a live representative when it comes to delivering a personalized, human touch. They’re also lacking when it comes to handling more complex questions or customer issues.
Once again, a combination of automation and live chat support is typically the best approach.

Chatbots and live chat applications have unique advantages when it comes to delivering consistent and accurate responses to customer queries.
Chatbots are excellent at delivering consistent, on-brand messaging. They can be programmed to systematically follow templates or scripts to provide a consistent customer service experience.
When working with human customer support agents, this high degree of consistency can be a little more difficult to achieve.
While live chat support may not offer the same consistency as chatbots, human support agents do tend to be more accurate when determining the intent of the customer they are assisting.
For example, a simple spelling error can sometimes confuse chatbots, whereas a human customer support agent would be much more likely to look past the error and correctly figure out what the customer needs.
A human agent is also much more likely than a chatbot to accurately interpret questions that are worded strangely.
For companies that are choosing between chatbots and live chat support, it’s a question of whether they’d like to prioritize consistency or accuracy. This is yet another reason why a combination of chatbots and live chat support is often the best solution.
More chat features to provide self-service support without the bots
Many of the issues your website visitors have with bad chatbots involve their mimicry of support from real people. It’s easy to tell when you’re chatting with a robot, but it’s not always made clear to you by the chat widget.
But there’s a third chat option that you should consider in addition to live chat and chatbot software.
Self-service chat options make it clear to your customers that they are receiving automated help. By presenting menus instead of imitating a human conversation, self-service customer support empowers customers to find the answers they need on their own.
It’s a win-win, because the customers get the answers they need in real time, at any hour. And your team can focus on support tickets that are more important to the business.
Here are a few ways self-service chat options can work.
Up to 30% of incoming customer service tickets are shipping status requests. With self-service order management in the chat widget, customers are empowered to make these queries on their own — providing fast answers and reducing your support tickets.
These automated options are easy to add with Gorgias. This self-service adds buttons to the chat widget to automatically:
Quick service with chat automation provides quick, responsive customer service, which means better customer experience and a positive impact on revenue.
Barcelona-based shoe brand ALOHAS added self-service order management flows with Gorgias after experiencing a high chat volume. This allowed customers to find information on their own without a human needing to respond.
Here’s how a “track order” request looks in action:

When using a chat widget, you’ll notice the same questions come up again and again. You can satisfy those FAQs by adding quick answer flows into the chat widget.
These automations can be set up in the widget for questions like:
These automations can be customized for whatever FAQs are most relevant to your ecommerce store.
Here’s how it looks, for example, when an ALOHAS customer wants to find out more about the brand’s shipping policy.

Luxury jewelry brand Jaxxon has used these self-service quick responses with great success. The customer service team found themselves overwhelmed with customer questions and unable to respond as quickly as desired.
Jaxxon upgraded their live chat widget with Gorgias Automate with Quick Responses for customers. The result, combined with using Gorgias’ helpdesk, reduced live chat volume by 17% and lifted the on-site conversion rate by 6%.

Even when a customer chooses to type out a question, automation can be used to provide quick, customized service through the chat widget.
Gorgias can detect questions that come in through chat and provide automatic answers using Rules and Macros.
Here’s how the flow works:
The best part is this can not only be used for chat, but for responses to tickets coming in through other communication channels like email, social media, and SMS.
With Gorgias, you can make sure your chat widget isn’t missing a single ticket, even if your customer support team is offline.
First, you can set up your business hours to correspond with when you have live chat available. This will show up on your site’s chat widget by either showing the current status as online or offline.
From there, you can create automated responses for whether you’re offline or online. During business hours, this message can tell customers you’ve received their request and give a time by which they can expect a response.
After business hours, the responder can tell customers that although you’re offline, they can expect a response during the next day’s business hours via email.

You can also use a contact form which turns a chat into an emailed ticket. This is great to use after-hours and to make sure chat requests don’t get lost overnight.
The use of automation within customer service is multifaceted. As we discussed earlier, a human touch is critical for many customers, and speaking with an automated chatbot can be a turn-off. However, automation certainly has its place in the customer service process.
On the customer’s side, starting with self-service chat helps them receive quicker customer support at scale — a more satisfying experience. On your team’s side, automation allows for sorting, segmenting, and prioritizing tickets.
When self-service chat can’t solve an issue, someone from your support team can easily step into the conversation. You can use Macros — scripts that automatically bring in the customer’s information — to scale the human touch on your support team.
So in reality, it’s not automation vs human support. These are two complementary tools that work better together. And the result is a stronger and faster customer experience for your website visitors, which can increase your conversion rate by as much as 12%.
Still not convinced? In 2021, brands using the Gorgias chat widget generated an average of $38,702 from conversations involving chat. We have a whole post on live chat statistics that can help illustrate the impact our chat widget can have on your business.
If you’re an ecommerce business looking for an all-in-one customer support solution that includes live chat support and AI-powered chatbots, Gorgias is your one-stop shop.
Our algorithms are trained on hundreds of millions of ecommerce tickets, so you can be sure your customers are getting the right responses every time.
Plus, you can manage both live chat and chatbot conversations in the same dashboard that you use for all your other channels, including phone, email and major social media platforms. Bring in chat from other channels, including Facebook Messenger. We’ll even be supporting Whatsapp in early 2023.
Our customer support platform is available for Magento, Shopify, and BigCommerce users.
Read more about our chat offerings by clicking here.

TL;DR:
You know what customers love? When their problems are solved on the first try.
Being able to resolve issues right away is a clear sign that your support team is on the right track to provide great customer experiences.
To maintain that level of excellence and efficiency, you’ll need to understand first contact resolution (FCR) rate.
In this article, we’ll deep dive into first contact resolution rate. You’ll learn how to calculate and monitor FCR, how to increase your FCR for better customer experiences, and look at what other metrics to monitor alongside FCR.
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First contact resolution rate is a metric that measures the percentage of customer support tickets that your agents resolve on the first interaction.
Generally, this measurement is used in call centers, but it’s also considered one of the most essential customer support metrics in ecommerce.
Like a lot of customer support metrics, FCR also goes by a few names, like:
Whichever name you prefer, the goal of the measurement is the same: understand how efficient your team is at resolving customer issues.
Time-consuming interactions erode trust over time and drive customers to shop with the competition.
According to The Effortless Experience, 96% of shoppers with a high-effort experience feel disloyal to brands afterward.
By aiming to solve customer issues from the very first interaction, you can combat the escalation of poor customer experiences and use positive interactions to improve loyalty and satisfaction, gain repeat customers, and boost revenue to meet your bottom line.
Let’s walk through the formula to figure out your FCR and look at an example. Then, we’ll unpack some challenges behind the FCR metric to make it as useful for your support agents as possible.

The formula to calculate first contact resolution rate is:
(Number of support tickets resolved on first contact / total number of resolved support tickets) x 100 = FCR rate %
The goal is to have an FCR percentage that’s as close to 100% as possible. A higher FCR indicates how successful you are at solving tickets at the first interaction without follow-up questions from customers.
Here’s what calculating FCR looks like using real numbers:
(15,000 tickets solved on first contact / 20,000 total resolved tickets) x 100 = 75% FCR
That means, on average, your team can solve 75% of support tickets on the first try.
First contact resolution is a fantastic starting point to improve your support team’s resolution time. But, like most customer support metrics, FCR has some limitations.
Simply knowing your first contact resolution rate doesn’t give you the whole story.
A low FCR means you aren’t solving most problems on the first try but it doesn’t explain the root causes.
You’ll need to track other metrics that look into customer interactions more qualitatively, like customer satisfaction (CSAT).
Second, a high FCR isn’t an automatic indicator of a successful support strategy. The challenge lies in accurately categorizing tickets resolved in one interaction. This process can be complicated by instances where automated responses may be quick but unhelpful.
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Here are four tactics you can use now to improve FCR performance and your customer experiences.
Your agents are your front line, and it’s important they’re armed with customer service scripts to resolve common issues efficiently. Scripts are pre-written responses that agents can use to avoid typing the same answers over and over again.
At Gorgias, we call scripts Macros. Gorgias allows you to personalize each Macro with customer information pulled from your integrated ecommerce platforms like Shopify and WooCommerce.
Deja Jefferson, CX and Consumer Insights Manager at skincare brand Topicals uses Macros “to help maintain brand voice while handling a high volume of customer service tickets.” As a result of this automation tactic, her team influenced 72% more revenue.
💡 Pro Tip: Exceptional customer experience depends on a robust customer service training program. Keep agent knowledge fresh with a knowledge base or Help Center of scripts. This way, agents can continuously upskill or grab information whenever they need it.
At Gorgias, we’ve found that automation increases both FCR and sales.
An automation tool like Gorgias Automate can help resolve up to 30% of incoming tickets. With features like Quick Responses and Article Recommendations, customers can get answers to their questions without waiting to speak to an agent.

For example, luxury shoe and garment care retailer Kirby Allison used Gorgias Automate to deflect 30% of incoming tickets and boosted revenue from support by 46%.

Chances are, a bulk of your tickets can be answered by customers themselves. In fact, 88% of U.S. customers expect a customer self-service portal according to a 2022 Statista survey.
On Gorgias, we solve this issue by giving merchants the ability to create a Help Center.
A Help Center is an article database that includes information commonly sought by shoppers, like product information, policies (like shipping, returns, or order cancellations), and billing and payment information.

Below, Loop Earplugs makes the customer experience seamless by linking to their FAQs in the top navigation bar of their website.

Resolving your low-priority tickets quickly is a surefire way to improve your FCR. It would be a full-time job if you had to manually prioritize and categorize your tickets.
With a helpdesk like Gorgias, you can automatically categorize incoming tickets into low-, medium-, and high-priority based on customizable parameters called Rules. Better yet, Gorgias can take care of routing high-priority tickets to your most experienced agents to maintain customer retention.

For example, snack brand Chomps created a Rule that tagged customer tickets with an “Urgent” tag if their message included phrases like “cancel order,” “wrong,” or “update my address.”

To give deeper context to your customers’ shopping experiences, it’s important to use FCR alongside other customer success metrics and KPIs.
Let’s look at how FCR works with key customer support metrics, like Customer Contact Rate, Average Response Time, Average Resolution Time, and Unresolved Ticket Rate.
Customer contact rate (CCR) looks at the percentage of customers who ask for help over a given time. It's an important metric that gives you a snapshot of your company's overall health.
Calculating CCR in combination with FCR will help you see how many people need support versus how effective your team is at deflecting lower-priority tickets.
Average response time (AVT) or average reply time measures how long your support team takes to respond to a customer message.
90% of shoppers agree that an immediate response is important when they have a support request, so it’s crucial that you have as low an AVT as possible.
The longer your response time, the longer it’ll take to get to a resolution. That’s why it’s useful to calculate AVT with FCR together. It’ll help show you the time it takes for an agent to respond, getting you even closer to a lightning-fast solution.
Average resolution time (ART) is similar to FCR in that it looks at your support team’s ability to resolve customer issues.
The difference with ART is that the metric looks at your team’s average ability to resolve issues, not just the first time.
A benefit of calculating ART is that you can understand how efficiently your team resolves higher-priority issues, like complicated returns, customer retention rates, or problems with loyal shoppers.
Unresolved ticket rate (UTR) lets you track and measure abandoned conversations and tickets that could not be solved.
It’s critical to calculate UTR because unresolved tickets are a key indicator of unhappy customers — and unhappy customers can negatively impact your bottom line.
Calculating UTR can help you find gaps in your support strategy by locating tickets where a resolution is difficult and working to build a resolution for similar problems in the future.
If you’re stuck manually calculating first contact resolution, you’ll never have time to improve your strategy.
That’s where Gorgias comes in. Gorgias Helpdesk automatically tracks and measures data like FCR so that you can focus on optimizing your strategy to provide a more positive customer experience.
Sign up for Gorgias or book a demo to track and improve your first contact resolution rate today!

