

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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TL;DR:
What’s the common factor between shoppers debating between products and considering a splurge? Hesitation.
Today’s shoppers are overwhelmed with choices. They don’t want to be left to figure things out on their own. They want guidance.
But most brands are missing that crucial piece of the puzzle. They lack a strategy that accompanies shoppers on their journey. A tool that encourages shoppers to proceed to checkout. And, ultimately, a customer experience devoid of a sales approach.
That’s why we built Shopping Assistant, an AI Agent that proactively engages browsers, offers context-aware product recommendations, and turns hesitation into conversions in real time.
And it’s working. Brands using Shopping Assistant are seeing a 62% uplift in conversion, 10% higher average order value, and 5x ROI.
Here’s a closer look at what’s behind the magic.
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Most traditional chatbots passively wait for questions and deliver answers that aren’t personalized to each shopper's preferences.
Unlike these bots, Shopping Assistant reads real-time signals like pages viewed, cart contents, and conversation tone. This results in a solution that not only offers support but also offers personalized, proactive selling. This enables Shopping Assistant to continuously refine and adjust its playbook, evolving with each shopper as their journey matures.
Here’s how Shopping Assistant engages with customers across the shopping journey:
Take this example below. When a customer vaguely asks “how to make up,” Shopping Assistant interprets it as a sign of interest in makeup products and recommends a starter kit.

Where traditional bots reset with every message, Shopping Assistant does the opposite. It has built-in context-aware intelligence that remembers what shoppers have clicked, viewed, and added to their cart during a session.
This enables natural, relevant, and persuasive conversations that truly resonate with each shopper. It goes beyond reading messages and observes behavior to adapt its responses.
That means it knows if someone has:
With plenty of context to work with, Shopping Assistant is not only smarter but also more profitable than the average chatbot. It drives more conversions with product recommendations and lifts average order value with timely upsells based on what’s been added to the cart or viewed.
Here’s what it looks like in action: When a customer engages through a product page, Shopping Assistant recommends a matching outfit, suggesting it’s aware of alternate product variants and the customer's likely interest in that style.

Promotions are powerful, but they’re not one-size-fits-all.
With Shopping Assistant, merchants can define their discount strategy to align with their brand. These strategies can range from offering no deals to using aggressive promotions.
Once the strategy is set, Shopping Assistant waits for hesitation and customer intent to trigger a discount, firing it at the most conversion-worthy moment.
Shopping Assistant initiates conversations. It’s built to engage shoppers, spotting when they linger or show signs of confusion, stepping in with timely, personalized help.
Every second counts in ecommerce. If a shopper pauses on a product page or is left scrolling through an endless search results page, Shopping Assistant detects it in real-time and reaches out with a relevant prompt like:
Here’s how Shopping Assistant reduces drop-off, builds confidence, and drives faster decision-making in three different ways.
Shopping Assistant automatically triggers commonly asked questions depending on the product currently being viewed. In one click, shoppers can get the answer to the question they’re curious about. This combats hesitation caused by a lack of information, resulting in more confident conversions.
When shoppers land on the homepage, it’s easy to become overwhelmed and not know where to navigate. The Ask Anything Input provides an easy way to start a conversation with Shopping Assistant and get the guidance they need.
Shopping Assistant can refine its response to the customer based on the page context. For example, when the customer is on a product page, Shopping Assistant knows exactly what product is being asked about.
Shopping Assistant can step in to offer pinpointed help based on a shopper’s search query. Instead of scrolling through a results page, Shopping Assistant triggers a message based on what the shopper entered, offering an easier and faster way to find what they need.
Shopping Assistant’s suggestions are rooted in real context: what the shopper has viewed, added to cart, or asked about. Whether they’re exploring a specific product line or revisiting a category they’ve shown interest in, Shopping Assistant delivers relevant upsells and complementary items that make sense for the customer.
This personalized approach to upselling increases cart size without feeling forced—it’s smart, seamless, and sales-driven.
Shopping Assistant can even turn vague product questions into upsell opportunities. By asking questions, it learns more about an individual to come up with recommendations that best fit their preferences.
Shopping Assistant is transforming the way shoppers engage and helping ecommerce brands sell more effectively. Through smarter conversations and real-time personalization, it turns every interaction into an opportunity to convert, build trust, and drive revenue.
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TL;DR:
The most coachable team member on your support team might not be human.
Brands that want to keep up with rising customer expectations are turning to AI to help meet demand. But as SuitShop’s Director of Customer Experience, Katie Eriks, will tell you, great results don’t come from flipping a switch.
They come from coaching.
Since implementing Gorgias AI Agent, SuitShop has reached a 30% automation rate, all while maintaining a lean CX team and giving every customer the tailored experience they expect (literally and figuratively).
“I consider myself its boss,” said Katie, who runs the entire coaching process solo. With under an hour of weekly maintenance now, SuitShop’s AI Agent runs efficiently, accurately, and on-brand.
Katie spoke at Gorgias Connect 2025 to share exactly how she got there. You can watch her full session below:
When brands think about automation, they often imagine flipping a switch and watching repetitive tasks vanish. But in practice, it’s not that simple, at least not if you care about customer experience.
Gorgias encourages brands to treat their AI Agent like a junior teammate — someone you onboard, train, observe, and coach over time.
Brands that do this well are already seeing massive gains:
For SuitShop, automation was about creating space for their small team to focus on specialized service. Space to scale without scaling headcount. And space to do it all without losing their voice.

Katie and her team had been longtime Gorgias users, but when they turned on AI Agent in August 2023, the results were unremarkable. The responses weren’t inaccurate, but they weren’t helpful enough either.
What Katie learned was to “Be hands-on early. Use downtime to train. And never stop refining.”
So she got to work, not by replacing the tool, but by going deeper into it. Here are her coaching tips:
Katie made herself the sole point of contact for training and QA. That might sound like a lot, but over time, it became a light lift.
“At this point, it’s definitely less than one hour per week,” she said. “In the beginning, it was more time-consuming because I needed to create help center articles and Guidance regularly. Now I’ve got it down to a pretty quick thumbs-up, thumbs-down kind of process.”
Katie uses Monday mornings to review AI Agent tickets from over the weekend, when fewer human agents are available and AI takes the lead.
Read more: Why your strategy needs customer service quality assurance
Unlike many retail brands, SuitShop’s busiest time isn’t the holiday rush — it’s wedding season in the summer and fall. So when things quieted down in December, Katie used that time strategically.
She temporarily turned off the AI Agent to regroup.
“I decided to turn it off and really beef up our Help Center,” she explained. “I went back to the tickets I had to answer myself, checked what people were searching in the Help Center, and filled in the gaps.”
She built out content with a mix of blog knowledge, internal macros, and ChatGPT. Once she felt confident the content base was solid, she turned AI back on.
Read more: How to optimize your Help Center for AI Agent
Once SuitShop’s foundational content was in place, Katie didn’t just sit back and hope for the best. Instead, she built a repeatable feedback loop grounded in data — one that helped her spot opportunities for improvement before they became issues.
Rather than combing through tickets at random, Katie created custom views inside Gorgias to zero in on the most impactful coaching moments:
To keep all of this actionable, Katie logs insights in a shared spreadsheet that functions as a live to-do list. Every row includes:
These insights are also available in Gorgias’s dashboard, where you can identify the top issues customers had.

“Sometimes I do it all in the moment. Other times I’ll log it and come back later when I can take the time to do it right.”
By combining frontline feedback with structured ticket views, Katie turned scattered QA into a consistent coaching system — one that ensures SuitShop’s AI Agent keeps getting smarter every week.
One of Katie’s most effective strategies comes from her own team.
Like many CX leads, she noticed that some agents consistently resolved tickets in a single touch. That pattern, Katie realized, wasn’t just a win for customers, it was a roadmap for an AI-driven support strategy.
Her teammate Tacy quickly became her go-to signal for what the AI Agent needed to learn next.
“I pull her tickets often to see what she’s responded with. It helps AI learn from her directly.”
By reviewing Tacy’s ticket history, Katie identified standard replies that didn’t yet exist as macros or Guidance. If Tacy was writing the same sentence repeatedly or copy-pasting a reply manually, that meant it could (and should) be taught to the AI Agent.
She also tracked Tacy’s macro usage rate. If Tacy frequently used a macro for a certain issue, but other agents weren’t, it flagged an opportunity to standardize responses across the team and the AI.
The key insight? If it only takes one touch for a human to answer, the AI can be trained to do it too.
These small efficiency wins added up quickly, especially during peak season, when the ability to automate just a few extra conversations per day created meaningful breathing room for the rest of the team.
Related: How to automate half of your CX tasks
Automation without brand voice feels robotic. Katie made sure SuitShop’s AI Agent sounded like a natural extension of the team, and that started with a name: Max.
“We get replies like, ‘Thanks Max!’ from customers who think it’s a real person.”
Using AI Agent’s tone of voice settings, Katie went deep on personalization. She customized everything from sentence structure and greeting format to whether or not emojis and exclamation marks should be used (they shouldn’t, in SuitShop’s case).

Her AI Agent instructions include clear direction on:
Katie also made sure she instructed AI Agent to acknowledge customer emotions — especially frustration — and to offer reassurance when things went wrong.
And because AI responses are written at lightning speed, she regularly reviewed messages to ensure they didn’t come off as cold or abrupt, especially in sensitive situations like delayed wedding orders or size issues close to the event date.
In the workshop, Katie walked through two real support tickets where AI missed the mark and how she used those moments to improve.
In one case, a customer asked a common question: “The navy suit I’m looking at says ‘unfinished pant hem.’ Will the pants need to be hemmed?”
Despite having help articles and macros explaining this exact issue, AI Agent responded: “I don’t have the information to answer your question.”
That was a red flag.
Katie immediately stepped in to coach the agent by:
“I like to write a short internal note, so if I see that ticket again, I know exactly how I coached it.”
In another case, AI Agent was incorrectly handing off a sizing question about jacket sleeve length. Katie realized that a previous broad handover topic ("sizing and fit questions") was causing confusion by flagging issues that the AI should have been able to handle.
So she deleted the handover topic and replaced it with a clear guidance article — complete with example questions, macros, and links to sizing resources.

“Once I added specific questions in quotes, it made a huge difference.”
SuitShop didn’t automate 100% of CX — but that’s not the point. At 30% automation (and growing), Katie gives her team more time to specialize, connect, and handle urgent or emotional conversations with care.
Here’s what Gorgias offers to help as well:
Whether you’re just getting started or trying to move beyond basic automation, Katie’s approach proves that coached AI outperforms out-of-the-box tools every time.
Want to coach your AI Agent like SuitShop? Book a demo to see how Gorgias can help you scale smarter.
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TL;DR:
Vanessa Lopez, VP of Customer Experience at Recharge, recently led a workshop that outlined how brands can transform one-off interactions into rich subscription journeys that increase opt-ins, reduce churn rate, and boost lifetime value (LTV).
Here’s what we learned.
There are many different ways that you can offer subscriptions. Here’s a rundown of the most common.
The most common subscription type is “Subscribe and save.” Instead of making a one-time purchase, customers subscribe to a product and receive it on a different cadence, whether that's weekly, bi-weekly, monthly, or quarterly.

For example, Apothékary offers a Subscribe and Save option for its herbal remedies where shoppers get a discounted rate if they subscribe every one, two, or three months.
Subscription boxes ship to customers monthly. Shoppers subscribe over a course of time, like every quarter, six months, or year. For example, CrunchLabs offers a prepaid Build Box option for kids and adults who want to tinker like engineers.

Meal kits are weekly food delivery services that either include pre-packaged ingredients to cook a dish or fully cooked dishes.
For brands that are selling higher-cost or unique items, subscriptions to purchase the same product over and over might not be the best way to gain subscribers.
The better option is a curated box, also known as a "subscribe and delight" or “mystery” box. It’s a unique way to cater to customers who prefer trying out different products, rather than receiving the same product on a recurring basis.

For example, premium snack box brand Bokksu specializes in shipping Japanese snacks. Rather than packing the same treats each month, the brand curates different items with every package. This creates both excitement and differentiation each time a customer gets a delivery.
Subscriptions are the original relationship between a brand and its customer. In fact, subscribers drive three times more value than the one-time buyer. That's because a one-time purchase is really just that—a moment in time—while subscriptions are a journey.
“When you have a customer and they subscribe, you get to see that moment they fell in love with your brand,” says Vanessa. “You get to see when they have those moments where they made you a part of their routine. Every time they engage with you and purchase something new, you learn their rhythms. You learn their preferences. It's impossible to do that with one-time buyers for the most part.”
Subscribers drive three times more value than the one-time buyer, and that's because a one-time purchase is really just that—a moment in time—while subscriptions are a journey.
Subscribers can only drive growth if you can get those customers to subscribe in the first place. This is what Recharge does: it takes customer interactions and turns them into a customer journey, allowing you to act on those signals in a personal way at scale.
It all starts the moment a shopper browses a product. Each touchpoint is an opportunity to turn that shopper into a subscriber—from the product description page to the subscription widget to checkout.
Vanessa’s tip? Make subscriptions the default option on a product description page. When you present customers with the better and more convenient option, and they see this information at the right time, they're more likely to subscribe.
Now, it’s time to test. Here's a checklist you can follow to A/B test your subscription journey:
When customers see the right information at the right time, they're more likely to subscribe. That's because it's the better and the more convenient option.
Let's say you have a customer who starts on a product description page. They decide not to subscribe—no worries. You can catch them in the cart.
When they add a product to their cart, you can upsell them with different subscription benefits so they know what they're missing out on. Do it again when they review their cart, and then again when they go to checkout, showing them complementary products that they might be interested in.
And don’t forget to take advantage of that post-purchase "your order is confirmed" high—offer customers cross-sell products, complementary products to their order, or similar items to what they've purchased in the past.
By creating multiple touchpoints for conversion, you’ll increase the possibility that they’ll make a purchase.
Set up automations in the subscription tool –– like Recharge –– you use. That means adding on upsell and cross-sell tools, and perfecting the times they trigger for customers. Test out different copy and cross-sell/upsell offers to see what resonates the most.
Just as important as acquiring customers is keeping them around.
The Recharge team names three core customer moments that might actually diverge from what brands expect to happen in the customer journey:
And while they might seem like hiccups in the process, these moments are actually hero moments. They’re moments that give you the opportunity to actually win those customers back.
For browsing shoppers, educational and informational resources are the best way to meet their needs, hesitations, and objections.
For regular subscribers, it’s providing them with direct control over their subscription, whenever they want.
The goal is to reach customers where they already are and respond instantly to their needs in a personalized way.

Gorgias’s Shopping Assistant does exactly that—meeting customers where they are by answering customer questions and even initiating conversations based on browsing activity.
This AI sales tool detects a shopper's intent, cart contents, and browsing behavior to initiate conversations, recommend products, and even send discounts as they make a decision.
Modern bidet brand TUSHY saw a 20% increase in chat conversion rate after implementing the tool.
Decide how you’d like to leverage AI and automation to meet customers where they are. That might be by providing a phone number that customers can interact with via SMS, or implementing a tool like Shopping Assistant to strike up conversational AI chats. Using AI and automation will help you better meet your customers where they are and at scale.
Rather than using AI to come up with problems your brand can solve, Vanessa recommends looking at the challenges your brand has already seen with subscriptions.
The key is to view AI as a tool that drives three core areas:
Vanessa says the most effective strategy starts with leveraging AI-powered tools, such as Recharge’s Concierge SMS.
Typically, SMS tools use template auto responses like, "How do you want to manage your subscription? Type one to cancel, type two to skip." But these aren’t compelling enough for customers to respond. What if they want to do something that doesn't fit in those two options?
Concierge SMS enables brands to build stronger relationships with their customers through conversations powered by pre-trained AI. It personalizes SMS support with customers, so relationships can expand into loyalty.
Implement an AI-driven subscription management tool that allows customers to interact and ask questions via SMS, rather than only being able to confirm or deny upcoming shipments.
Gorgias and Recharge are a powerful combination when it comes to integrating subscription management with top-notch customer support.
With Recharge, efficiently convert one-time buyers into subscribers, retain subscribers through intelligent interventions, and connect every customer touchpoint into one cohesive journey.
With Gorgias, sell more and resolve support inquiries with conversational AI.
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TL;DR:
At Gorgias Connect LA 2025, CX leaders from Tommy John, TUSHY, Triple Whale, and Talent Pop shared how support teams solve problems and drive revenue.
This shift, known as the support sales flywheel, doesn’t involve massive overhauls or shiny new tools. Instead, it means doing the small things exceptionally well, like picking up the phone, empowering agents to make judgment calls, and adding a personal touch where others automate.
These brands have shown that when support teams focus on consistency, connection, and conversion, the results compound. Every thoughtful interaction spins the flywheel faster, boosting loyalty, LTV, and revenue.
Ahead, we’re breaking down the most actionable takeaways so your team can start building its own support-led growth engine.
Watch the full panel here:
From scrappy install calls to AI-powered training, these CX leaders aren’t only talking about driving revenue, they’re doing it. Here’s how they’re turning support into a sales flywheel, and the tactics your team can start testing today.
“Customer service done right is actually a great source of revenue.” That’s how Tamanna Bawa, Tech Partner Manager at Triple Whale, kicked off the conversation on how data can transform CX from reactive to revenue-driving.
She advises segmenting customers based on purchase history and behavior to deliver more personalized, higher-converting interactions.
In a market where margins are razor-thin and ad costs are high, Tamanna emphasized that “incremental gains from personalization are the difference between companies that are thriving and the ones that are just surviving.”
What do you do when your hero product needs a cultural shift as much as it needs installation instructions? If you’re TUSHY, you send in your “Poop Gurus.”
Ren Fuller-Wasserman, Senior Director of CX at TUSHY, shared how her team launched a scrappy, free CX-led service that has now become a legendary video install program to help customers set up their bidets.
The real value wasn’t just tech support. As Ren put it, “It wasn’t about the actual install process, it was the encouragement they needed to change culture.” These calls sparked deeply personal moments (yes, even with cats and toddlers wandering in) and created the kind of emotional connection customers never forget.
Today, that service has evolved into a $15 paid add-on at checkout, and the customers who use it have significantly boost LTV and retention. It’s a masterclass in turning support moments into revenue through genuine human connection.
Phone support is back, and it’s becoming one of the most effective ways to turn conversations into conversions.
Ren from TUSHY swears by it. Her team uses customer phone numbers from abandoned carts to reach out directly. “You can send a hundred emails,” she said, “but a voicemail from a real person cuts through the noise.” Even if customers don’t answer, the fact that a brand called is memorable, and often enough to drive them back to checkout.
Max Wallace, the Director of CX Tommy John echoed the value of voice. His team recently implemented Gorgias Voice, using it to track conversion rates by agent. That visibility helps them identify what top performers are doing differently and replicate it across the team. “By the end of a tough call, customers often apologize for how they started. You can’t get that kind of de-escalation over email.”
In a world where inboxes are crowded and chat fatigue is real, a real voice builds real trust and real revenue.
Pro Tip: Don’t rush into phone if your other channels aren’t dialed in. “Master email and chat first. Then, start with limited phone hours. Taste it before scaling it,” said Armani Taheri, the co-founder of TalentPop.
For Max at Tommy John, revenue-driving support starts with two things: deep product knowledge and the freedom to bend the rules.
“We have five different fabrics for men’s underwear alone,” Max shared. To help customers choose the right one, agents need firsthand experience. That’s why Tommy John sends new products directly to the support team, so they can offer real, personalized recommendations like “Try Second Skin instead of Cool Cotton.”
But product knowledge is only half the equation. The other half is empowering agents to make judgment calls. Tommy John’s “Best Pair Guarantee” allows customers to try a product and get a refund or replacement if it’s not the right fit.
Agents are trained to prioritize retention, offering replacements instead of refunds, recommending better-suited products, and using their own discretion to keep customers happy.
As Max put it, “We don’t have really strict policies… we want them to use their best judgment.” That confidence translates into smoother resolutions, more cross-sells, and customers who stick around.
How do you train outsourced agents to drive revenue, without sounding like a sales team? According to Armani Taheri of TalentPop, it starts with confidence and context.
“You have to tailor-fit the training approach to each brand,” he explained. That means grounding agents in product knowledge, tone of voice, and customer journey before they ever interact with a shopper.
One of the most effective tactics is roleplaying. Armani’s team uses both live roleplays and AI-powered chat simulations to prepare agents for real conversations, pre-sales, post-sales, and everything in between. Tools like Replit and Lovable help create lightweight, brand-specific training environments agents can practice in at their own pace.
The goal isn’t to turn CX reps into hard sellers. It’s to give them the confidence and consistency to recognize revenue opportunities, and act on them in a natural, helpful way.
Ready to turn your CX team into a revenue engine? Here are some of the tools mentioned by the panelists that help make it happen:
Whether you're scaling phone support or experimenting with post-purchase outreach, the right tools make the flywheel spin faster.
They’re on the front lines with your most engaged customers, answering questions, easing doubts, and uncovering what really drives purchases. With the right tools and training, they resolve tickets and help close the sale.
With tools like Gorgias Voice, it’s easier than ever to connect the dots between conversations and conversions.
Want to see how your CX team can help drive growth?
Book a demo to see how Gorgias Voice powers sales through support.
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TL;DR:
Your CX team talks to customers every day. They know what’s confusing, driving purchases, and causing returns, because they hear it firsthand.
But all too often, those insights stay siloed in support tickets and live chat transcripts instead of informing the campaigns that shape the customer journey.
This post is here to change that. We’re breaking down the most valuable questions marketing teams should be asking their CX counterparts. When marketing and CX work together, you get more relevant messaging, smarter product positioning, and campaigns that convert.
Whether you’re planning a big seasonal push or just want to improve product education, this is where to start.
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Your CX team knows what makes shoppers hesitate. They’re the ones fielding questions like: Does this come in a larger size? Is it final sale? Will it arrive in time?
Beyond being pre-sale inquiries, they’re signals. They reveal what your customers care about most, and where your messaging may be falling short. When marketing teams tune into this, they can proactively address objections in landing pages, product detail pages (PDPs), emails, and top-of-funnel content.

At luxury jewelry store Jaxxon, Director of Customer Experience Caela Castillo saw firsthand how important it is to address these questions early.
“Chat used to be a support tool for repetitive questions and problem-solving, but now AI Agent takes care of that for us,” she said. Once those friction points were handled upfront, the CX team could focus on more meaningful conversations, and conversions improved.
And when AI recommended the wrong products? Conversions dropped. It was a clear signal that relevance matters, especially before the sale.
Ask your CX team:
“What do customers most often need to know before they buy, and how can we answer that earlier in the journey?”
Your best-selling product isn’t always your hero product. Sometimes, it’s that under-the-radar item that customers can’t stop talking about. The one that shows up again and again in reviews, chats, and post-purchase surveys.
The insight is gold for marketers. The key is to find out why people love it. Is it the fit? The feel? The results?
At online fashion brand, Princess Polly, Alexandria shared that her team expected Gen Z shoppers to lean on AI for recs, but what really influenced them was customer feedback. Reviews, not bots, built trust. That’s why campaigns built around real customer language and experiences often outperform the most polished product copy.
Shopping Assistant can turn those rave reviews into real-time action. It highlights top products using your Shopify product catalog to make personalized recommendations, proactively assists shoppers by using behavior signals, and even offers tailored discounts when they’re ready to convert. That means less guesswork, greater relevance, and an easier path to purchase.

Ask your CX team:
“Which product do customers rave about most, and what exactly are they saying?”
When customers are frustrated, it’s easy to blame the product. But in many cases, the issue isn’t quality, it’s communication.
At Shinesty, a men’s underwear brand, Molly Kerrigan, Senior Director of Retention, observed that high return rates often stemmed from unmet customer expectations.
She noted the importance of maintaining clear and consistent communication as the company grows, “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.”
Molly notes that using Gorgias AI Agent enables Shinesty’s customers to receive quick answers, freeing her team's time for more complex or sensitive issues.
Similarly, Princess Polly saw that delivering a standout customer experience meant being fast, consistent, and helpful at every stage. After switching to Gorgias, their support performance improved dramatically:
Before changing the product, try updating the messaging. Use insights from CX to rewrite descriptions, add size guides, include user-generated content, or even build a quick-fit quiz. Small tweaks help set clearer expectations and reduce unnecessary returns.
Ask your CX team:
“Which products are driving the most complaints, and what do customers wish they knew before buying?”
Confusion is a conversion killer. If a customer isn’t sure about how something works, what’s included, or whether it’s right for them, they’re more likely to bounce.
That’s why it pays to ask your CX team where customers get stuck. Is it a product feature that needs more context? A vague store policy? A missing detail on a bundle?
The good news is that most confusion is fixable. Start with the following steps:
If you’re using Shopping Assistant, you can go even further. It can detect when shoppers are hesitant and provides real-time nudges. Like an assistant who knows all your needs, Shopping Assistant automatically surfaces the questions customers are likely to ask when evaluating a product, so they’re equipped with the clarity they need to proceed to checkout.

TUSHY, a modern bidet brand, faced similar challenges. As bidets aren't mainstream in North America, shoppers often had concerns about product compatibility and installation. They’d ask questions like:
Without immediate answers, many potential buyers would abandon their purchase. To address this, TUSHY implemented Shopping Assistant, providing instant support. Taking this approach resulted in an 81% higher chat conversion rate compared to human agents and a 13x return on investment.
“The Shopping Assistant has been a game-changer for our team, especially with the launch of our latest bidet models. Expanding our product catalog has given customers more choices than ever, which can overwhelm first-time buyers. Now, they’re increasingly looking to us for guidance on finding the right fit for their home and personal hygiene needs,” said Ren Fuller-Wasserman, Sr. Director of Customer Experience at TUSHY.
Ask your CX team:
“Where do customers get confused most often—and how can we clear that up sooner?”
Your CX team picks up on patterns that analytics sometimes miss. They hear which items customers ask about in the same chat, which products get added to carts together, and which pairings people reorder time and time again.
That intel is a goldmine for bundling and upselling. It helps you build smarter campaigns that feel relevant and drive real value.
Zoe Kahn, owner of Inevitable Agency and former VP of Retention and CX at Audien Hearing, emphasizes the importance of using AI to enhance customer interactions.
“A lot of that revenue was potentially missed revenue because these were customers sitting on the site, asking questions about the products, and wanting an answer now so they could purchase…Now, AI can answer those questions immediately and convert those customers.”
With Shopping Assistant, you can act on these insights in real time. It will surface personalized product pairings, bundle suggestions, or accessories based on customer behavior. All before they hit the checkout page.

Returns cut into your margins and chip away at trust. Most of the time, they’re not caused by poor-quality products. They happen because expectations weren’t met.
Your CX team already knows which items come back the most and why. Maybe the color doesn’t match the photos. Perhaps the fit runs small, or the product description left out a crucial detail.
Instead of pushing the product harder, reframe how you present it. Add real customer photos. Include fit notes or a sizing chart. Call out anything that might surprise the customer post-purchase. A little clarity upfront goes a long way in reducing returns and boosting retention.
At Pepper, an intimates brand specializing in bras for small-chested bodies, they recognized the importance of pre-sale education. When customers have sizing questions, their AI Agent, Penelope, can provide immediate assistance.
“Penelope takes the information we give her and responds better than a Macro. She tailors it so that it sounds like a natural conversation between two people,” said Gabrielle McWhirter, CX Operations Lead at Pepper.
By proactively providing instant support, Pepper improved customer satisfaction and saw an 18% uplift in average order value.
Ask your CX team:
“Which products get returned the most—and what could we do upfront to change that?”
Before you launch your next campaign, start with a quick sync with your CX lead. They already know what your customers need to hear. You just have to ask.
From fixing messaging gaps to surfacing the right products at the right time, these insights help you connect with customers in personal, timely, and relevant ways.
Tools like Shopping Assistant make it easier than ever to act on this data in real time. You can turn CX knowledge into dynamic recommendations, personalized nudges, and smarter discounts.
Ready to see how you can improve your online shopping experience? Book a demo to see how Gorgias Shopping Assistant engages customers in real-time.

TL;DR:
Today’s best marketing starts with your customers.
According to Forrester’s 2024 research, “Customer-obsessed organizations reported 41% faster revenue growth, 49% faster profit growth, and 51% better customer retention than those at non-customer-obsessed organizations.”
Support teams interact with hundreds or thousands of customers every week, collecting valuable insights in the process. This voice of the customer (VOC) data is a goldmine for marketers, but it too often stays siloed among CX teams.
Ahead, we’ll break down how ecommerce brands can tap into CX insights to drive better marketing.
CX can play a crucial role in driving growth, but many brands aren’t leveraging it for marketing insights yet.
When connected to marketing, CX becomes a proactive engine that fuels better segmentation, sharper messaging, smarter campaigns, and more personalized content.
Support functions collect objections, complaints, compliments, and pre-purchase questions. When you capture and apply those insights, your marketing can target the precise roadblocks—and key sales differentiators—customers care about.
Here’s how to turn CX insights into a high-impact marketing strategy, with real examples from brands using Gorgias.
When you want to sharpen your brand messaging, there’s no better place to look than your support inbox. Your support inbox is a rich resource full of information specific to your brand and your customers.
Tools like Gorgias Ticket Insights help surface recurring themes, top questions, and friction points across all conversations. By analyzing these patterns, marketers can identify the exact words customers use to describe problems, questions, or product feedback and then reflect that language across ads, landing pages, and emails.
Spikes in tickets around specific topics (sizing, shipping timelines, and materials, for example) are insights marketers can use to update and improve corresponding content.
This can increase confidence and conversion on key pages.
By incorporating the same terminology and phrasing customers use in support conversations, brands can also increase resonance across ads, emails, and social media. Messaging that mirrors the customer’s language builds trust and helps audiences feel understood.
Ask your CX team 💬 What product issues or themes have emerged this quarter?

For example, cordless heating cushion brand Stoov® used Ticket Fields in Gorgias to understand and resolve a ticket spike. By figuring out that some customers were dissatisfied with the battery life of its core product offering, the team was able to add an optional upsell. For €20, shoppers now have the option to purchase a larger battery.
The results were meaningful: the brand saw 50% of customers opt for this battery, resulting in a 10% increase in average order value (AOV). And while the team saw a significant increase in revenue, they saw no increase in support ticket volume.
Most marketers rely on transactional data—like past purchases or time since last order—to build audience segments. But support data reveals a whole new layer of context: behavior, concerns, sentiment, and urgency.
Tools like Gorgias’s Ticket Insights and Ticket Fields allow CX teams to customize different properties attached to tickets. Agents can fill these out to capture data more accurately.
Here’s how these types of tools work: tickets come with a mandatory field for return reasons, product feedback, contact reason, etc. Before the agent closes the ticket, they use a dropdown menu to fill out the ticket field.
Studying support interactions helps answer key questions around why customers are getting in touch. This data can provide marketing teams with a way to build smarter segments for campaigns or personalized journeys.
For example, if one product is getting a large amount of inquiries, marketing teams could segment customers interested in those products and launch pre-sales education campaigns.
Fashion brand Psycho Bunny switched from Zendesk to Gorgias to improve access to reporting tools that surfaced customer patterns and support trends.
“By cross-referencing our Gorgias data with insights around basket size, product performance, and store performance, we can inform broader business decisions. For example, we can see if a certain store location generated more tickets or how many incoming queries are about a certain product,” says Jean-Aymeri de Magistris, VP IT, Data & Analytics, and PMO at Psycho Bunny.
By integrating insights like these with marketing workflows, teams can build more relevant segments that improve retention and engagement.
Ask your CX team 💬 Which customer segments are most likely to churn or repurchase?
Chat campaigns are proactive messages that trigger based on real-time behavior and context. You can use CX trends to design campaigns that directly address common objections, answer FAQs, or deliver tailored offers.
Start by reviewing your most common pre-purchase questions with your CX team. Then, create chat prompts that address those concerns exactly where they arise. For example, a sizing guide prompt on product pages or a shipping FAQ in the cart.
Make sure your message feels helpful and not overly salesy. Conversational AI assistants like AI Agent can also tailor responses in real-time, helping customers get what they need without leaving the page.

Pepper, a size-inclusive bra brand, put this into practice by combining their AI Agent (named Penelope) with targeted chat campaigns to guide shoppers through one of their most common friction points: sizing. Thanks to insights from their support team, Pepper created messaging that helped customers find the right fit instantly. The result was an 18% uplift in average order value.
“With AI Agent, we’re not just putting information in our customers’ hands; we’re putting bras in their hands. With Penelope on board, we’re turning customer support from a cost center to a revenue generator,” says Gabrielle McWhirter, CX Operations Lead at Pepper.
Ask your CX team 💬 How are customers reacting to recent promotions or launches?
When shoppers hesitate at checkout, it’s often because they don’t have the information they need.
Tapping into support conversations allows CX teams to identify common objections. They can then share those insights with marketing to refine product messaging, improve product pages, ads, and marketing campaigns.
Use customer service data to identify the top three objections customers have before converting. These might be concerns about sizing, compatibility, delivery time, or product setup. Then, pair that knowledge with a proactive AI sales tool like Shopping Assistant to offer timely answers that move shoppers closer to purchase.
For example, TUSHY, a modern bidet company, found that many prospective customers were hesitant because they weren’t sure how difficult the installation would be. By using a real-time shopping assistant to address these concerns directly on-site, TUSHY was able to guide shoppers past uncertainty.

Ask your CX team 💬 What are the top three reasons customers contact us before they buy?
If you want to know what content your customers actually need, your Help Center holds the answers. Real customer questions are found right in Help Center search queries and article analytics.
By tracking which articles are most viewed, most searched, and most frequently updated, marketers can spot common knowledge gaps and fill them with high-value content.
Start by reviewing your Help Center Statistics to see which articles are performing well, which ones are underutilized, and what terms customers are searching for.
If an article about “returns policy” is getting a spike in views, that’s your cue to simplify the policy or preempt questions with a dedicated email campaign. Marketing teams could also use this insight to build FAQ-rich landing pages, preempt questions in email flows, or even turn top-performing help content into organic blog posts or performance ad copy.

You can also use Gorgias's Dashboard to spot emerging trends across all your channels. This custom reporting feature lets you choose from various charts that reveal high-level patterns—like the most common contact reasons or sudden spikes in ticket volume—giving marketers early insight into shifting customer sentiment and trending topics across social platforms.
Ask your CX team 💬 Which articles in our Help Center are most searched right now?
When support and marketing teams collaborate, you unlock a cycle of continuous improvement. CX teams surface the insights, marketing turns them into strategy, and both sides drive measurable results.
Here’s how to make it work:
We need to reframe CX as a proactive function that drives revenue.
Support teams already have the answers marketers are searching for. You just need the tools to tap into them. Gorgias makes that easy, with flexible reporting features, powerful AI, automated tagging, and integrations that bridge the gap between CX and marketing.
Want to connect your support data to better marketing?
Explore Gorgias’s analytics tools or book a demo to speak to a product expert about how to integrate your support strategy with marketing.
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TL;DR:
Doing nothing when there’s rapid change happening in an industry is risky business.
Right now, according to our latest report, 2025 Ecommerce Trends, 77.2% of ecommerce professionals are already using AI in their day-to-day work. What happens if you’re part of the 22.8% that isn’t?
Inaction is action—one that’s a quiet drain on revenue, resources, and reputation.
Every minute spent on manual work is a minute your competitors are focusing on higher-value customer interactions, improving CX, testing offers, and scaling campaigns.
And the cost of falling behind is compounding fast. Here’s what you’re losing when you pass on AI.
As support volume grows, so does the cost of inefficiency.
Nearly 80% of CX professionals say AI saves them time. In fact, 83.9% of support leaders using AI in Gorgias say it has made their teams more efficient.
Trove Brands experienced this firsthand:
If AI can handle 70% of your support tickets, your team finally has the time—and headspace—to focus on the 30% that actually builds trust, drives repeat revenue, and improves the customer experience.
Hot take: AI isn’t impersonal. Not using it is.
In 2024, nearly one-third of CX leaders worried AI would make interactions feel less human. A year later, that number dropped by half.
Why? Brands started to see that AI wasn’t hurting the customer experience, it was removing friction from it.
For sensitive or personal products—think wellness supplements, intimate gifts, or anything a shopper might feel awkward asking about—AI creates space for honesty without judgment. And that can change the outcome entirely.
“Too often, a great interaction is diminished when a customer feels reduced to just another transaction,” said Ren Fuller-Wasserman, Senior Director of Customer Experience at TUSHY. “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, everyone wins.”
It’s a powerful point, especially for brands where discretion matters. AI removes that barrier.
You're losing trust if your support experience still makes customers hesitate. For many, that means being able to get an answer without needing to explain themselves first.
Every unanswered pre-sale question or missed upsell is revenue slipping through your fingers.
Product recommendations alone have the potential to increase revenue by up to 300%, boost conversion rates by 150%, and drive 50% higher AOV. But those results don’t come from hoping customers find what they need. They come from proactively guiding them.
That’s where AI comes in.
With Gorgias AI Agent and automation features, for example, Kirby Allison
“Our favorite features are definitely Flows and Article Recommendations. They drive so much automation for us. Shoppers get answers to their questions by themselves—what’s the right size hanger, where is my order, what shoe polish would you recommend, etc,” said Addison Debter, Head of Customer Service.

Flows let Kirby Allison surface up to six commonly asked questions directly in the chat widget. When clicked, each one opens a relevant help article—no agent needed.

Auto responses also allowed the team to handle common inquiries like sizing, shipping, and order tracking before a human ever steps in.

If your support team isn’t set up to handle pre-sale conversations at scale, the cost isn’t just in time. It’s in all the revenue you never realize you’re missing.
It might sound counterintuitive, but AI gives your team more space to be human.
The myth that AI replaces agents is still floating around in some circles, but the reality inside fast-growing ecommerce teams looks different.
In fact, AI frees up time for your team to focus on what they do best: solving complex problems, building relationships, and creating moments that actually drive loyalty.
SuitShop is a perfect example of this in action. When the team adopted AI Agent, they paired automation with intentional escalation:
“We’re helping customers feel confident during some of the most important moments in their lives—weddings, proms, job interviews, and everything in between. Naturally, my biggest concern with introducing AI was: ‘Will customers feel like they’re getting the same level of care from AI?’ But learning that AI Agent would pull knowledge from our Help Center articles and Macros, which are already written in our brand voice, made me feel more confident,” said Katy Eriks, Director of Customer Experience.
AI was able to handle common pre-sale questions like shipping timelines and product availability, while human agents stepped in for customizations, wedding-specific questions, and tailored styling support.
The goal wasn’t to remove the human element. It was to give their agents the time and context to show up more meaningfully.
In just one year, AI adoption among Gorgias users jumped from 69.2% in 2024 to 77.2% in 2025.
Excitement is rising, too: 55.3% of ecommerce professionals now rate their interest in AI as 8–10 out of 10, up from 45.6% the year prior.
AI is no longer in its experimental phase. It’s the standard, baked into everyday workflows across ecommerce.
If you’re still on the sidelines, 2026 is going to feel like a catch-up game.
The good news? You don’t have to overhaul everything to get started.
So while we’re on the topic of speed, let’s walk through how to start implementing AI for your brand.
You don’t need to automate everything on day one. The best CX teams start small, pick the right entry points, and give AI the same level of care you’d give a new team member. Here’s how to roll out AI in a way that actually works:
When searching for a new AI tool to help you manage CX, look for one that:
Price matters, but it shouldn’t be your only filter.
Also, AI should make your team feel more capable. If it feels like a bolt-on or requires constant developer help, it’s going to create friction, not solve it.
The most successful AI implementations all have one thing in common: someone owns it.
“One of our CX Managers spent 30–40 hours a week building and refining AI. That ownership was critical,” said Sarah Azzaoui, VP of Customer Experience at Clove, when she was explaining how her team first got started with AI.
What many people don’t realize is that AI isn’t going to be perfect out of the gate. AI takes real time and intention to build out. Assigning a clear point person—or better, a small squad—ensures someone is tracking performance, making optimizations, and flagging edge cases.
No one knows your customer conversations better than your support team. They see the full range of questions, tone, friction points, and emotional nuance every day.
Bringing them into the AI rollout early helps you:
This step also builds trust. If your agents feel like AI is something being done with them instead of to them, adoption is smoother and the outcomes are better.
One of the biggest mistakes brands make with AI is trying to do too much, too soon. AI rollout should feel like a phased launch, not a switch flip.
Start in a test environment if your platform allows for it. Roll out automation in stages—by topic, channel, or ticket type—and QA every step of the way.
We suggest beginning with high-volume, low-complexity tickets like:
Platforms like Gorgias offer tools like Auto QA that track whether AI responses hit the right tone, offer accurate answers, and resolve issues effectively. Use those tools to catch gaps early and monitor performance over time.
That slow, deliberate rollout pays off in performance. At Psycho Bunny, AI Agent now automates 30% of customer tickets, with custom messaging that reflects their brand tone and processes.
Once you’re ready to scale, you’ll feel more confident that the simple queries are handled correctly while you start to train the AI on more nuanced questions.
For example, Gorgias’s Guidance feature gives AI access to non-public SOPs so it knows how to respond or when to escalate.
“The Guidance feature is so important,” said Tosha Moyer, Senior Customer Experience Manager at Psycho Bunny. “We have a lot of processes that we definitely don’t want described in a customer-facing article, but we want AI Agent to be able to access that information and manage tickets accordingly.”
Even the best AI platform can’t succeed without solid inputs.
Before you roll out, take a hard look at your help docs and macros:
Think of this step as training your AI. The stronger your internal content library, the more helpful and brand-aligned your AI will be across every channel.
Whether you disclose AI usage is up to you, but be intentional.
Some brands choose anonymity for a more seamless experience. Others find that transparency builds trust, especially when something goes wrong.
What matters most is that your approach aligns with your brand tone and customer expectations—and that clear escalation paths are in place if a conversation needs a human.
Research shows that 85% of consumers want companies to share their AI assurance practices before rolling out AI-powered experiences. Customers are open to AI. But they expect clarity when it counts.
Once you’ve built the foundation, scaling AI across your CX org becomes a lot easier.
“We started with cancellations. Now we’re rolling out warranty claims, retention campaigns, and more,” said the team at Trove Brands.
After proving value with one or two ticket types, look for opportunities to expand:
The goal is to implement smarter automation that makes your team more effective and your customers more supported.
The best CX teams aren’t choosing between AI and human agents. They’re choosing both and building stronger systems because of it.
“It’s not human agents vs. AI,” said the team at Clove. “Our team helped shape the AI strategy—and that changed everything.”
But ignoring AI? That comes at a cost. And it’s not just inefficiency. It’s:
It’s time to build it into your workflows. Not just as a helper, but as a core part of your team.
Start using Gorgias AI Agent to reduce ticket load, recapture revenue, and deliver the kind of support that actually feels personal.
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TL;DR:
Automated responses don’t actually resolve anything. In reality, they increase customer wait time.
What a customer really wants is immediate resolution, whether they’re looking to cancel an order, change a shipping address, or pause a subscription.
So, how do you go beyond automated text responses? AI Agent Actions.
Below, we’ll go over the 7 most common customer service requests you can resolve with AI Agent Actions, so your team gets time back to strengthen customer relationships, increase revenue, and improve your CX strategy.
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AI Agent Actions are tasks AI Agent can complete for your customers, such as canceling an order or updating a shipping address.
Instead of handing it off to a human agent, AI Agent resolves the ticket by connecting to your ecommerce apps and performing the action on its own.
You get maximum control over when and how Actions are executed. Before performing the Action, AI Agent asks customers for confirmation, respecting your processes and maintaining a high level of customer service. Once an Action has been taken, you can even share feedback with your AI Agent to reinforce its behavior or finetune it further.

Pro Tip: Unlike Guidance, which tells AI Agent how to respond in a conversation, Actions determine what happens. It’s the difference between saying “I’ll refund your order” and doing it.
Related: How AI Agent works & gathers data
Ready to resolve requests in seconds? Activate these pre-built Actions in Gorgias to keep your team efficient and your customers happy.

Action to use: Update shipping address
Supported apps: Shopify, ShipMonk, ShipHero, ShipStation
Incorrect shipping addresses lead to costly re-shipments, delays, and even refunds. Catch errors early to keep customers satisfied and excited about their order.

Why do you need this Action?
The reality is your agents aren’t available 24/7. Unless you hire a team to cover night and weekend shifts (which is unlikely), requests will be missed. AI Agent fills in that gap, handling time-sensitive issues when your team is off the clock. Missing them isn’t just about poor customer experience—it can also lead to extra costs, like reshipping orders.
Action to use: Cancel order
Supported apps: Shopify, ShipMonk, ShipHero, ShipStation
Perhaps a customer ordered the wrong item, chose the wrong size, used the wrong card, or simply changed their mind. Allow them to quickly cancel their order and receive a refund in one go.

“Actions responds to tickets within about 30 seconds and is available 24/7. Regardless of when a customer places their order, the likelihood of quickly catching and canceling the order has increased by 70% since we started using Actions. It’s an exceptional result."
—Jon Clare, VP of Customer Service at Trove Brands
Actions to use:
Supported app: Shopify
It happens—shoppers order the wrong size or color and want to change their order immediately. Regardless of the reason, make their new decision easy to implement. Quick, accessible order updates prevent returns, lost revenue, and, most importantly, customer disappointment.
Here’s what the replace order item setup looks like in Gorgias:

Pro Tip: If you have unique workflows, you can create advanced, multi-step Actions and connect to your tools beyond our default integrations. This option requires some tech know-how (like custom HTTP requests), so feel free to bring in your developers for assistance.
Actions to use:
Supported apps: Stay AI, Recharge, Subscriptions by Loop, Skio, Seal Subscriptions
Subscriptions shouldn’t be all or nothing. Let customers skip a shipment or pause their subscription, so they can come back when they’re ready. Giving them full control lets them manage their subscription on their own terms, reducing churn rate in the process.
Here’s how AI Agent handles a skip shipment request:

Action to use: Reship order for free
Supported apps: Shopify, ShipMonk
No customer expects a lost or damaged order. Let customers know that you have their backs by reshipping a new order free of charge. Fast resolutions during unexpected events demonstrate your commitment to customer satisfaction.
“An instant response builds confidence. We live in a world with short attention spans, so customers appreciate how quickly we can respond to their inquiries. Customers aren’t worrying unnecessarily for longer than they have to for an address change or order cancellation.”
—Mia Chapa, Sr. Director of Customer Experience at Glamnetic
Action to use: Send return shipping status
Supported app: Loop
Customers want to know that their return package is on its way to you, so they can redeem their refund. Easily send them a shipment tracking link to give them that peace of mind.
Action to use: Get order info
Supported apps: Shopify, ShipHero, ShipMonk, ShipStation, ShipBob, Wonderment
Based on Gorgias data, order status ranks among customers' top 10 questions for support teams. Reassure your customers with quick updates on their orders, including product details, shipping progress, expected delivery date, and other helpful information.
Here are a few helpful setup tips to make sure Actions run without a hitch:
If you want…
AI Agent Actions can get you there.
You’ve now seen how Actions can resolve tickets in a snap—no unnecessary handoffs, canned responses, or long response times.
Book a demo to see AI Agent Actions work in real time and start automating what you shouldn’t be doing manually anymore.
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