

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:
AI Agent is built to deliver fast, accurate support at scale, but like any teammate, it performs best when given clear and specific instructions.
That’s where Guidance comes in. Writing structured prompts that tell your AI Agent exactly what to do in a given scenario helps reduce escalations, speed up resolutions, and create a more consistent customer experience.
One simple, repeatable way to do that is with the “When, If, Then” framework.
In this post, we’ll show you how it works, using examples from our Gorgias Academy course, Improve AI Agent with Better Guidance.
You’ll learn how to write Guidance that results in:
Let’s break it down.
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Guidance is how you tell your AI Agent what to do. It’s a set of instructions that outlines how your AI Agent should respond in specific situations.
When Guidance is available, your AI Agent follows it first, even before checking your Help Center or website content.
That means if your Guidance is missing, unclear, or incomplete, your AI Agent might escalate the ticket, or worse, give a confusing or unhelpful response. Here’s an example:
Let’s say a customer wants to return an item. A human agent would send them a link to the return portal and explain the steps. But without that instruction in Guidance, your AI Agent might skip straight to escalation, turning a simple request into unnecessary work for your team.
That’s why clear, step-by-step Guidance is key to help your AI Agent respond the way your best support agent would.

Learn more: Create Guidance to give AI Agent custom instructions
Sometimes it’s hard to know where to start when writing Guidance. The “When, If, Then” framework gives you a simple, repeatable structure to follow, so there’s no need to guess.
Taking this approach mirrors how AI Agent processes information behind the scenes. When you write clear Guidance, your AI Agent can follow it step by step, just like a support teammate would.
Let’s walk through the three parts of the framework.
Start by identifying the situation your Guidance applies to. This is the trigger or scenario. Use it as the title of your Guidance so it’s easy to find later.
Example:
Keep it simple and action-oriented. You’re setting the stage for what comes next.

Once you’ve defined the scenario, add any conditions that determine what should happen. “If” statements help your AI Agent understand what to do based on specific details, like timing, order history, or customer tags.
Example:
Use as many “if” conditions as needed to guide different outcomes. Just make sure you cover all the possibilities so your AI Agent doesn’t get stuck.
This is where you tell your AI Agent exactly what to do. Be specific and use bullet points or numbered steps to keep things clear.
Example:
The more clearly you outline the steps, the more consistently your AI Agent will perform.
The framework keeps your Guidance simple, structured, and easy to understand—for both your team and your AI Agent. When your AI Agent knows exactly what to do, it can deliver fast, accurate, and helpful responses that keep customers happy.
Say a shopper messages your store asking to return an item and you want AI Agent to send them to your return portal.
Here’s how this looks in a complete piece of Guidance:
WHEN a shopper asks to return an order:
IF the order was placed less than or equal to 15 days ago,
THEN
These nine scenarios come up constantly in ecommerce support, and they’re perfect candidates for automation. They follow predictable patterns and are quick to resolve when your AI Agent knows what to do.
Use the examples below to jumpstart your setup. Each one is written using the When, If, Then framework and can be copied directly into Gorgias.
WHEN a customer asks about their order status:
IF tracking information is available,
THEN
IF tracking information is unavailable,
THEN
WHEN a customer inquires about product sizing for [item name]:
IF the customer asks what size to get, or mentions they’re unsure about sizing,
THEN
WHEN a customer requests to change their shipping address:
IF the order has not been fulfilled,
THEN
IF the order has already been fulfilled,
THEN
WHEN a customer asks to cancel their order:
IF the order has not been fulfilled,
THEN
IF the order has already been fulfilled,
THEN
WHEN a customer asks about returning an item:
IF the return is within the allowed return window of [x] days after the order was received,
THEN
IF the return window has expired,
THEN
WHEN a customer inquires about discounts or promo codes:
IF there is an active promotion for [item name],
THEN
IF there are no active promotions for [item name],
THEN
WHEN a customer requests to pause their subscription:
IF the customer has an active subscription,
THEN
WHEN a customer asks about product restocking:
IF a restock date is available,
THEN
IF the restock date is unknown,
THEN
WHEN a customer inquires about international shipping:
IF international shipping is available,
THEN
IF international shipping is not available,
THEN
Pro Tip: Test out your Guidance by going to AI Agent > Test, and iterate as you go.
If your AI Agent isn’t following your Guidance, or it’s escalating tickets you thought it could handle, run through this quick checklist to spot the issue:
Don’t have time to write Guidance from scratch? The good news is AI can help with that, too.
AI-generated Guidance is available for all AI Agent subscribers. This feature analyzes your historical ticket data and uses it to generate ready-to-use, customizable prompts for your AI Agent.
Here’s what it does:

Clear, structured Guidance is the key to unlocking better performance from your AI Agent. With just one well-written “When, If, Then” prompt, you can reduce escalations, speed up resolutions, and give your shoppers a smoother experience.
Not sure where to start? Try writing Guidance for one common question today—like returns, order status, or promo codes. Or, if you want to go deeper, check out our free Gorgias Academy course.

TL;DR:
As ticket volume grows, even the best CX teams start running into roadblocks: limited integrations, repetitive manual work, clunky interfaces, and slower response times. You patch things together. You make it work... until you can’t.
Many growing ecommerce brands find themselves trapped in a system that demands constant workarounds just to function.
If your current customer service platform feels more like a burden than a backbone, you’re not alone—and you’re not stuck.
In this post, we’ll walk through:
There’s a tipping point most brands hit as they scale. The signs are subtle at first—maybe your agents are taking longer to respond, or the volume of customer support tickets quietly outpaces your team. Then it starts affecting revenue, customer satisfaction, and retention. Big yikes.
Left unchecked, small inefficiencies can snowball into bigger operational challenges.
Catch these warning signs before they start costing you growth:
Support teams that are always playing catch-up rarely have time to focus on higher-value work. If your inbox is constantly overflowing or first response times are creeping up, it’s likely a sign your tools aren’t scaling with your business.
That’s exactly what happened with apparel brand Psycho Bunny.
“As we grew and expanded, we needed a tool that was better suited for Shopify, easier to manage, and offered better support to help us get the most out of the tool,” said Jean-Aymeri de Magistris, VP IT, Data & Analytics, and PMO at Psycho Bunny.
If your agents are spending more time gathering context than solving problems, you’re losing time (and likely, patience) on both sides of the conversation. Fragmented tools can seriously undercut productivity.
Dr. Bronner’s experienced this firsthand, juggling Salesforce, spreadsheets, and disconnected systems.
“When I joined, we were logging calls and emails in Excel. It wasn’t scalable,” recalled Emily McEnany, Senior CX Manager at Dr. Bronner’s.
Some platforms require technical support even for small changes, such as custom workflows, new automations, or basic integrations. That may work at the start, but it becomes a bottleneck as your brand grows.
Disconnected systems strip away context, increasing the risk of mistakes. Whether it’s pulling up an order status or managing a return, agents need tools that work together, not against each other.
Every support team deals with repetitive inquiries. But without automation or self-service options, those tickets eat into your team’s time and keep you from focusing on higher-impact conversations.
Nude Project struggled to keep up with their ticket volume due to Zendesk’s lack of intuitive automation features. During Black Friday, the team received a record-high number of tickets—more than double their average volume.
“Connecting with customers through a screen is not always easy. With the high volume of messages, we need a tool that simplifies operational tasks while enabling effective communication and organization,” said Raquel J. Méndez, CX Manager at Nude Project.
Your platform should be easy for new hires to learn and for your team to evolve with. If ramping up agents takes weeks (or months), the platform might be getting in the way more than it’s helping.
Arcade Belts went through this process, trying one system, then switching back to one that better matched their needs.
“It just took a demo or two to realize what was actually going to support our team the way we needed,” their Ecommerce Coordinator, Grant, shared.
If any of these challenges sound familiar, you’re not alone.
The important part is recognizing when you’ve outgrown your current setup—and knowing that there are options out there to help you move faster.
Switching platforms isn’t just about solving today’s problems. It’s about creating space for your team to be efficient, serve customers better, and turn support from a cost center into a real growth engine.
Need to migrate to a new platform? Look for the following:
As your brand grows, support volume naturally increases.
Find a stable infrastructure that can handle that growth, has zero platform lag, and a robust engineering team that continuously makes the tool better for your needs.
To Psycho Bunny, Zendesk was a “legacy tool”—so they switched to Gorgias.
In just a few weeks, they migrated all historical conversations, tags, and Macros to Gorgias. Jean-Aymeri, their VP IT, credits Gorgias’s helpful onboarding specialists for making it effortless to integrate their apps and onboard their team onto a brand new tool.
Related: The engineering work that keeps Gorgias running smoothly
From “where’s my order” questions to return policies, prioritize AI tools that can automate repetitive inquiries.
Dr. Bronner’s implemented AI Agent to handle rising volumes of FAQs, allowing their team to focus on complex requests that require a human touch.
In just two months, they saw:
By systematizing the simple stuff, they freed up bandwidth to focus on what matters most—building relationships and solving more nuanced problems.

More brands are rethinking how support contributes to revenue. Look for a tool that combines support and sales. The most effective ones use AI to initiate upselling conversations, so your team can generate new revenue without needing to scale headcount at the same rate.
For jewelry brand Caitlyn Minimalist, which normally saw 30,000 tickets per month, AI Agent was the perfect fit. On top of answering FAQs, AI Agent also helped recommend products based on customer needs.
These conversations often begin as simple inquiries (“What should I get for my friend’s birthday?” or “What product suits me?”) and end in a purchase—handled entirely by AI. In fact, AI Agent’s conversion rates were 150% higher than the team average, proving that automation can support and sell.
The last thing scaling brands should have to worry about is relying on developers for basic changes. That includes being able to create macros and automations in-house and access key customer data without toggling across tools.
The platform should fit into your existing ecommerce stack—not fight against it.
That’s where Audien Hearing found themselves before switching to Gorgias.
“I’ve seen companies lose a lot of money because it’s not efficient,” said Zoe Kahn, former VP of CX. “You try to save money early on, but then you look at your helpdesk a year later and think, ‘Oh no, what’s happening?’”
Since switching from Richpanel, Audien Hearing’s CX team has been able to run CX on their own terms—without the bottlenecks.
They now resolve 9,000 tickets per month through self-service alone (including a customer knowledge base), cut first response times by 88%, and reduced return rates by 5%. With more time for one-on-one conversations, CSAT jumped from 80 to 86.
“But migration sounds hard.”
We get it. Moving your entire CX operation can feel intimidating. But with the right partner (and the right platform), it doesn’t have to be.
Here’s how Gorgias makes switching smooth and stress-free:
Most Gorgias customers are fully live within just a few days—ready to serve customers faster, smarter, and with less manual lift.
When fast-growing intimates brand Pepper outgrew their old CX platform, they knew they needed a system that could scale with them—without sacrificing speed or quality.
“Gladly didn’t offer any automation or inbox organization features. Our queue got really messy. We got 400 tickets a day during Black Friday, and we didn’t clear that backlog until the following Spring. We knew we couldn’t do that again,” explained Gabrielle McWhirter, CX Operations Lead at Pepper.
With Gorgias, Pepper was able to:

And the results spoke for themselves:
See how Pepper made the switch happen (and why they’re never looking back):
If you’re seeing the warning signs, here’s a quick gut check:
The right platform won’t just help your team work better. It’ll help you drive more revenue, boost customer retention, and actually make customers want to talk to you.
See what switching to Gorgias could do for your brand. Book a demo today.
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TL;DR:
Rising tariffs. Shipping delays. Unpredictable price hikes. For ecommerce, it's an understatement to say the pressure is rising. If you're on the CX team, you're already facing the fire head-on — all the customer frustration, confusion, and hesitation.
CX teams are on the frontlines of support and sales. You're shaping customer trust, buying decisions, and brand loyalty.
From pre-sales conversations to loyalty programs, it’s time to rethink the customer journey, so you can turn every interaction into an opportunity to grow your revenue.
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Customer service isn’t just about reacting to problems. It can be a proactive and strategic function that helps you stabilize and even grow your revenue.
Think about it this way: you have the power to turn everyday customer moments into wins.
At every stage of the customer journey, you can turn:
This isn’t about being pushy for sales. It's about anticipating needs and putting systems in place that protect customer relationships and revenue.
As you update your CX workflow, keep these two questions in mind:
Most pre-sales hesitation is rooted in uncertainty: What’s the return policy? How much is shipping? Will this fit? Will it arrive in time?
Reduce customer effort and build confidence with automation as your CX team’s first line of defense. Anything else more complicated, your agents can take care of.
Start by setting up automated answers for the questions your team responds to every day, especially the ones that delay conversions:
There are a few ways to automate these questions in Gorgias:

Read more: How to optimize your help center for AI Agent
Be the compass for the wandering window shoppers and browsers. They might not know exactly what to get, but with the right nudge, you can guide them toward the right product and a fuller cart.
Try these chat prompts:
Sometimes, a discount is all a customer needs to take their order to checkout. Instead of storewide promo codes, use AI to offer tailored discounts to shoppers who show strong intent to buy. This can help reduce abandoned carts and leave customers with a great impression of your brand.
Here are some of the best times to offer a discount:
If shoppers can’t quickly find what they’re looking for, they’ll leave. Real-time product recommendations help resolve indecision and increase average order value.
Examples of when real-time suggestions drive conversions:

High-intent questions are usually specific and goal-oriented — things like:
When customers ask questions that directly impact their ability to purchase, it’s a strong buying signal. If they don’t get a fast response, they’ll probably abandon their cart.
So, how do you encourage shoppers to keep shopping?
Activate chat on your website and equip it with automated features, such as Flows, and/or conversational AI, like AI Agent.
No matter what setup you choose, always have a protocol ready to hand off to a human agent when needed.
In Gorgias, you can set up Rules or use AI Agent handover rules to automatically route conversations based on specific keywords, topics, or customer behavior.

After buying, customers may want to change their order or just need reassurance that everything is on its way.
If customers feel ignored during this critical window, you risk losing their business.
The easy fix? Eliminate friction, reassure customers, and make it easy for them to stay excited about their purchase.
Customers expect full visibility into their orders. Give them full access to this information, and you'll receive fewer WISMO requests.
Integrate your helpdesk with your 3PL or shipping provider to automatically send real-time updates on order status. If customers have an account portal, give them a tracking link.
Pro Tip: If delays are expected, automate messages to let customers know ahead of time. Being proactive keeps customers informed and reduces the need for reactive support.
When something goes wrong, like a delay, a lost package, or unexpected fees, it's how you respond that matters most.
Empower your CX team to act quickly. For example:
You can also use sentiment detection to flag frustrated customers early. Gorgias has built-in customer sentiment detection that automatically identifies tones like urgent, negative, positive, or even threatening language. You can create Rules that tag these conversations and route them to the right agent for faster handling.
Read more: Customer sentiments
Just because a customer is at risk doesn’t mean you’ve lost them. Identifying and re-engaging at-risk customers is one of the highest-impact things you can do to protect revenue.
Pay attention to repeat patterns that signal dissatisfaction. Common early indicators include:
Use sentiment detection and Ticket Fields (ticket properties) to tag these signals automatically. With this data identified, you’ll start to spot patterns that can help you address issues, giving customers a reason to stay.

Once you’ve identified your at-risk customers, use win-back strategies, like:
When handled thoughtfully, a churn-risk customer can become one of your strongest advocates because you showed up when it mattered most.
Don’t forget, there are already customers who love you! These loyal customers don’t just come back to buy again — they bring friends, amplify your brand, and give your business stability when you need it most.
Use customer data to identify customers who purchase frequently, spend more, or have referred others. Tag them as VIPs in your helpdesk so that their requests are prioritized.
For example, in Gorgias, you can use Customer Fields (customer labels and properties) to group your customers under:
When you know who your top customers are, you can offer more personalized service and make sure every interaction strengthens their connection to your brand.
You don’t need to offer huge discounts to let customers know you appreciate them. Small, thoughtful gestures often make the biggest impact:
If you’re using macros and automations, you can even trigger some of these surprise-and-delight actions automatically, making it easier to scale while keeping the personal touch.
We know how overwhelming uncertain times can be. It’s easy to think you need to reinvent your entire strategy just to keep up.
But the truth is, you already have what you need. You have a team that knows your customers. You have conversations happening every day that can protect, nurture, and even grow your business.
By grounding yourself in what’s already working and creating proactive systems, you can turn uncertainty into strong and steady growth.
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TL;DR:
For many ecommerce teams, store policies are an afterthought, tucked away in the footer or buried deep in the FAQ. But they shouldn’t be.
Great customer experience (CX) starts before a customer reaches out. And with 55% of shoppers preferring self-service support, your store policies are often their first stop for answers.
In this guide, we break down the must-have policies for five key ecommerce verticals, based on real Gorgias ticket data. From shipping delays to subscription changes, you’ll learn how to prevent tickets before they happen.
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If you’re constantly fielding questions about returns, shipping times, or order changes, it’s a policy opportunity.
Well-crafted store policies are one of your CX team's most effective tools for setting expectations, building trust, and preventing support issues before they happen. When done right, they turn common friction points into effortless experiences.
When policies are vague or hard to find, customers turn to your inbox, driving up ticket volume and slowing down your support team.
Here are the most common blind spots we see:
When policies aren’t clear or easy to find, customers turn to your inbox. And that means more tickets, wait times, and pressure on your team.
Based on real data from Gorgias, these are the top 10 tickets customers send across channels like chat, contact forms, and email:
What do most of these have in common? You can address them with clear, accessible policies.
Customer expectations aren’t one-size-fits-all, and your store policies shouldn’t be either.
What shoppers expect from a fashion brand is very different from what they need from a wellness company or electronics provider.
We’ve broken down the top policy must-haves by vertical, using real-world examples from Gorgias customers and ticket data.
Use these examples as your plug-and-play guide to write better policies, reduce ticket volume, and create smoother support experiences — no matter what you sell.
When it comes to fashion, uncertainty drives tickets. “Will this fit?” “Can I return it?” “Where’s my order?” The most successful fashion brands like Princess Polly cut down on support volume by making these answers easy to find before customers ever reach out.


Consumer goods customers often want to know two things right away: “What’s it made of?” and “When will it get here?” These questions can quickly pile up in your inbox if your policies aren’t front and center.
Trove Brands, home to household favorites like BlenderBottle and Owala, solves this by proactively answering product and shipping questions across their site and emails.

At the end of each product page, BlenderBottle shares a support menu where shoppers can find information on order status and replacement parts.

Read more: What's the secret to reducing WISMO requests?
In electronics, clarity is everything. Customers want to know how to use the product, what to do if it doesn’t work, and how to get a replacement — without jumping through hoops.
Over-the-counter hearing aid company Audien Hearing nails this by creating crystal-clear support content around setup, shipping, and returns, so customers can troubleshoot confidently and independently.
Audien Hearing has clear visual policies that make it simple for shoppers to find the info they need quickly.

In the health and wellness space, trust and transparency are everything. Customers want to feel confident that the products they’re using are safe and that the support will be just as thoughtful as the product itself.
Brands like period underwear brand Saalt do this exceptionally well, pairing clear product education with empathetic policies that guide customers through everything from first use to subscription changes.
Saalt lets customers phrase questions themselves or choose from a dropdown menu.


Food and beverage customers tend to be both curious and cautious. They want to know what they’re putting in their bodies — and what to do if something goes wrong with the order.
Brands like Everyday Dose get ahead of these concerns by making their policies clear, accessible, and customer-first.
Everyday Dose lists frequently asked questions and makes it simple for customers to find important allergen and ingredient information.

Given that Everyday Dose is a mushroom supplement brand, many shoppers will likely have questions around allergens and exact ingredients. On each of their product pages, there is a clear “Read the Label” button.


Everyday Dose also has a chat which encourages customers to click through to the correct support link or to track their order.

Pro Tip: Use a conversational AI platform to handle common questions at scale. For example, Gorgias’s AI Agent can instantly respond to FAQs like “How much is shipping?” or “When will my order arrive?” — all in your brand’s voice. And when a request needs a human touch, it routes the ticket to the right agent automatically.
Even the most well-written policy won’t reduce tickets if it’s buried three clicks deep in your footer. To truly support your customers (and lighten your team’s workload), your policies need to show up in the right places, at the right moments.
Here’s how to get them in front of customers when they need them most:
Well-placed policies turn support into a self-service experience. They empower your customers to get what they need without ever opening a ticket — and that’s a win for everyone.
Clear, proactive policies do more than answer questions. They prevent tickets, build trust, and make your support team’s job easier. By tailoring your policies to your industry and placing them where customers actually need them, you turn potential friction points into smooth experiences.
Want to take it a step further? Book a demo to see Gorgias’s AI Agent handle common inquiries like shipping, returns, and product questions, across chat, email, and contact forms.
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If you're an ecommerce leader right now, you’re likely facing a new wave of uncertainty. Rising tariffs, disrupted imports, and sudden cost increases are putting pressure on your margins, and your customer relationships.
At Gorgias, we are working with thousands of brands that are grappling with tough calls: adjust prices, shift sourcing, or absorb costs to protect loyalty. And while the supply chain is where these issues start, the customer experience is where they play out.
Whether you’re a growing DTC or an enterprise brand, your customers deserve transparency. We know the pressure you're under, and we're here to help you navigate it. To help you not only manage the conversation, but lead it with clarity, empathy, and speed.
Ecommerce brands are in an impossible position right now, following the 24 hours news cycle, and waiting to see how tariffs will cut into profits and impact their business.
For customers? It can create confusion, frustration, and a flurry of angry tickets if brands aren’t proactive and transparent. But here's the truth: how your team talks about tariffs is just as important as what they say.
These moments of friction, and how you communicate these changes to your customers can be opportunities to build trust, reduce churn, and even demonstrate the real revenue power of your team. In a moment when clarity and trust are everything, the role of CX leaders is more important than ever.
Tariffs may seem like a back-end issue, but in reality, they shape front-end experiences—from product pricing and availability to fulfillment speed and satisfaction.
For ecommerce brands, especially those sourcing from China or shipping globally, these trade shifts hit close to home. Products get more expensive, shipping slows down, and some SKUs disappear altogether.
And CX teams are often the first to hear about it. The question isn’t if you should communicate tariff implications, but how.
Here’s the good news: customers don’t expect you to control global trade policy. But they do expect honesty.
What matters most right now is:
And even more specifically, your customers are likely looking for answers to three simple questions:
In times of change, trust becomes foundational. If you're not upfront about what’s happening and how it affects them, customers will fill in the blank, or worse, turn to competitors.
Tariffs are complex, but your messaging shouldn’t be. Strip out the policy jargon and explain the changes in human terms. Let customers know what’s changing, why it’s happening, and what steps you’re taking to protect their experience.
Instead of: “Due to regulatory changes impacting import duties…”
Say: “Because of new tariffs, some of our prices have gone up. Here’s why, and what we’re doing to keep costs down.”
From your Help Center to your agents to your email updates, your message should be consistent. Mismatched explanations create confusion and erode trust. Align your team on the key talking points and update scripts and automations across all customer touchpoints.
Speaking of your Help Center, now might be a great time to create an article specifically about tariffs and how you’re approaching them. The article can serve as a source of truth for your customers and your AI agents on the front lines answering questions.
Customers don’t just want the facts, they want to know you care. Acknowledge the frustration, and offer reassurance. Small gestures like a personalized note or a shipping perk can show you’re on their side.
Generic messages fall flat. Give customers details that they can rely on: Are the changes permanent? Are you absorbing part of the cost? Is a specific product impacted? When you’re upfront about the situation, and how you’re responding to it, you build credibility.
Times of uncertainty are times to cut costs, but it may also mean increased ticket volume. AI agents can help on the frontlines. But be sure to build your handovers to escalate to your team in the right moments to build trust.
Luggage brand, Beis, recently sent an email to customers that is a great example in customer-first communication. Rather than quietly raising prices or burying fees in checkout, they called it what it was: tariffs.

They explained the change clearly, why it was happening, and what customers could expect. And most importantly, they acknowledged the frustration. No spin, or vague language, just a clear message from a brand that respects its customers enough to be honest with them.
This kind of proactive messaging does more than prevent a flood of support tickets. It creates alignment between the brand and the customer. Beis didn’t make the rules but they’re navigating them with their customers, not in spite of them.
Too often, tariff policies get relegated to the FAQ page or terms and conditions. Customers typically only land there after they’re already confused or upset.
Instead, CX should treat tariffs as a key part of the customer journey and be equipped to speak about them empathetically and clearly.
Add a proactive message to your chat widget that addresses tariff-related questions before they even come up. A short note like, “You may notice some pricing changes – here’s why,” with a link to your FAQ or a specific article, helps to deflect confusion and prevents cart abandonment.
Surface timely information right where customers are most likely to look. Use your chat or search function to include a clear callout.
“Looking for information on recent pricing or shipping updates? Here’s what changed.”
This type of visibility empowers self-service, and reduces ticket volume.
Don’t leave your support team guessing. Create internal scripts with clear language on what to say (and what to avoid) when talking tariffs. Script empathy, not just compliance: Empower agents with language that acknowledges the inconvenience while reinforcing the brand's values.
Say:
Avoid:
If you’re using automation, make sure your AI Agent and autoresponders can explain tariff policies accurately and compassionately. Use macros to ensure fast, consistent replies, without sacrificing tone. Some key macro themes to create:
Each macro should strike a balance of clarity, empathy, and brand voice, offering both the what and the why.
Tariffs might be out of your control. But how you talk about them? That’s entirely in your hands.
This is your moment as a CX leader, not just to react but to lead. To turn friction into transparency, tension into trust, and confusion into connection. Because when policies change overnight and customer confidence is on the line, the brands that communicate with honesty, consistency, and care don’t just survive. They strengthen loyalty.
Your customers don’t expect perfection. They expect clarity. They expect empathy. And they expect you to show up.
At Gorgias, we’re here to make sure you can. With tools to automate answers, personalize conversations, and empower your team to deliver the kind of CX that builds long-term brand equity, even when times get tough.

TL;DR:
Chargebacks are more than a thorn in a merchant’s side — they’re a growing financial and operational threat. According to Ethoca, chargebacks are projected to more than double, from $7.2 billion in 2019 to $15.3 billion by 2026 in the U.S. alone. And while fraud plays a role, the primary reason customers file chargebacks is simpler: they feel ignored.

At Chargeflow, we recently published a comprehensive report analyzing why customers dispute chargebacks. The findings were eye-opening. While it’s true that fraud is a real concern, most chargebacks happen for a different reason: a lack of communication between merchants and customers.
Top stats from Chargeflow’s report:
When customers feel ignored or frustrated, they often turn to their bank for a solution instead of reaching out to the merchant first. Understanding these behaviors is key to preventing disputes before they escalate and cause chaos.
So, what actually drives customers to dispute charges? Here’s what the data says.
While chargebacks are often the cost of doing business, the truth is that many disputes are preventable — but only if merchants understand the root causes. We identified five key drivers behind chargebacks.
According to our research, most customers file a dispute right away after encountering an issue, leaving no opportunity to resolve the problem. Another 38% file within one to three days if they don’t receive a timely response.
Why? Customers assume the fastest way to get their money back is by filing a chargeback, especially if they receive no response from the merchant.
We found that 80% of customers never receive a follow-up after filing a chargeback. Additionally, 64% of customers state immediate communication is crucial, yet many businesses fail to reach out.
Why? Customers expect businesses to be proactive. When they don’t hear back quickly, they assume the merchant won’t help, making a chargeback seem like the best option.
98% of customers report a neutral to highly satisfactory experience when filing chargebacks, and only 12% are denied.

Why? Many customers believe chargebacks are faster and easier than dealing with merchants directly, especially if return policies are unclear.
The most common reason for filing a chargeback is “product not received” (35% of the cases). Other common reasons included:
Why? When customers don’t receive clear shipping updates or experience delivery delays, they assume their order won’t arrive and file a chargeback rather than waiting.
Friendly fraud occurs when a cardholder makes a legitimate purchase but later disputes the charge as fraudulent or unauthorized, leading their card issuer to reverse the payment.
Our research found that:

According to our State of Chargebacks report, 79% of chargebacks are actually friendly fraud, meaning they were filed for invalid reasons.
Why? Many customers mistakenly believe that a chargeback is just another way to request a refund, rather than a process intended for fraud or merchant failure.
📌 The takeaway: Most chargebacks aren’t actual fraud, but rather a result of customer confusion, impatience, or poor communication from merchants.
Merchants who want to stop chargebacks before they happen need a two-part strategy:
Chargebacks result from slow response times, poor communication, and unresolved issues, not fraud. Adopting AI-driven customer support and chargeback automation allows businesses to significantly reduce disputes and retain more revenue.
Many chargebacks happen because customers don’t receive a fast enough response. In fact, 52% say they will dispute a charge if the response time is too slow. AI-powered chatbots provide real-time support, resolving issues before they escalate.
Customers expect updates regarding orders and refunds, but often don’t receive them. 80% of customers report never hearing from a merchant after filing a chargeback.
Automated order updates, refund confirmations, and proactive notifications keep customers informed, reducing unnecessary disputes.
Customers expect round-the-clock support, but most businesses can’t provide live assistance. AI-powered ticketing and automation ensure every customer receives help, regardless of the time zone or urgency.
The result? Fewer chargebacks, faster resolutions, and increased customer satisfaction.
It’s impossible to please every customer. On average, chargebacks take 50 days to resolve successfully. Focus your energy on retaining high-value, long-term customers.
Lost inquiries take on average 15 days to resolve, and lost chargebacks take 38 days. Prioritize cases based on impact.
Advanced automated ticketing systems can route inquiries and prioritize urgent cases.
Ensure customer service teams have quick-response templates to speed their resolutions.
“Product not received” was the most cited reason for delivery-related chargebacks. Work closely with carriers and third-party suppliers to improve fulfillment and reduce disputes.
Use automated tools for real-time analytics, enhanced communication, and proactive alerts, which will reduce response times.
Successfully tackling chargebacks requires both proactive customer support and automated dispute management. That’s why Gorgias and Chargeflow work so well together to give merchants a comprehensive defense against disputes.
Post-purchase automation isn’t just about reducing customer support workload or quick replies. It's about finding the most effective ways to increase customer loyalty and prevent disputes.
Learn more about how AI-driven automation enhances post-purchase experiences here.
As you know, chargebacks are costly, frustrating, but most importantly, preventable. Our research shows that most chargebacks don’t stem from fraud, but from poor communication, slow response times, and customer uncertainty.
By prioritizing fast, AI-driven customer support and automated chargeback management, merchants can resolve issues before they escalate, improve customer experience, and protect their revenue.
With Gorgias handling proactive customer support and Chargeflow managing chargeback disputes, merchants get a powerful, end-to-end prevention system that ensures fewer chargebacks, higher dispute win rates, and, at the end of the day, happier customers.
Don’t let chargebacks drain your revenue. Take control today with faster, smarter automation.
Download Chargeflow’s full Psychology of Chargebacks Report to dive deeper into the data and start preventing disputes before they happen.

TL;DR:
When customer service teams are at their busiest, they need a helpdesk that keeps up. That’s exactly why our Site Reliability Engineering (SRE) team has been working behind the scenes to make the Gorgias platform faster than ever.
Over the past year, we've made remarkable improvements to our platform to eliminate bottlenecks, speed up data retrieval, and reduce incidents. For you, this means fewer disruptions, faster load times, and a more reliable helpdesk experience.
Here's how we did it.
Our platform relied on a single, shared database connection pool to manage all queries. Think of it as having just one pipe handling all the water flowing through your house — when too much water rushes in at once, the whole system backs up.
In practice, this meant a single surge in database requests could clog the entire system. When lower-priority background tasks got stuck, they could prevent high-priority operations (like loading tickets or running automations) from working properly. This would cause the entire helpdesk to slow down or, worse, become completely unresponsive.
Using PgBouncer, a tool that manages database connections and reduces the load on a server, we implemented multiple connection pools. Instead of relying on a single pipeline to stream all requests, we created separate "pipes" for different requests.

Like how road traffic picks up again after an exit, routing our database traffic into separate connection pools makes sure high-priority customer interactions don’t lag behind automated background tasks.
This solution is future-proof. In the event that a lower-priority task is delayed in one connection pool, other functionalities of the helpdesk will continue working because of the remaining connection pools.
The results speak for themselves:
We've eliminated incidents caused by connection pool issues in the helpdesk completely. This reduced major helpdesk outage incidents by around four per year and maintained an average uptime of over 99.99%.
As Gorgias grew to over 15,000 customers, so did the volume of data. We’re talking data from tickets, integrations, automations, and many more. The combination of more users and data meant slower searches within the helpdesk.
However, the amount of data was not the problem — it was how our data was organized.
Imagine this: An enormous storage room full of file cabinets containing every piece of data. Sure, those file cabinets kept data organized, but you would still need to spend time searching through the entire room, running up and down aisles of cabinets, to find your desired file. This method was cumbersome.
We needed a more efficient way to keep our data easy to find, especially as more customers used our platform.
The answer was database partitioning — breaking our large datasets into smaller, more manageable segments. Using Debezium, Kafka, and Kafka-connect JDBC, all managed by Terraform, we migrated over 40TB of data, including 3.5 billion tickets, without a moment of downtime for our merchants.
Instead of a giant room with thousands of file cabinets, we divided that giant room into 128 smaller rooms. So now, instead of looking for a file in one room, you know you just need to go into room number 102, which has a much smaller area to search.
This approach allows our system to quickly pinpoint the location of data, significantly reducing the time it takes to find and deliver information to users.
Additionally, database maintenance has become more efficient. Some of the partitions can probably sit without needing to be changed at all. We just have to maintain the partitions that are getting new files, which cuts down on maintenance time.
Better database partitioning provides several benefits:
When incidents occurred in the past, our response process was inconsistent, leading to delays in resolution. It was sometimes unclear who should take the lead, what immediate actions were required, and how to effectively communicate with affected customers.
Additionally, post-incident reviews varied in quality, making it difficult to prevent similar issues from happening again. We needed a standardized framework to address incidents in a timely fashion.
To streamline incident management, we introduced a replicable, automated process:
With our improved incident management process:
With more brands catching on to how essential a solid CX platform is, our team's got our work cut out for us. Here's what's on the way:
Gorgias will inevitably face new challenges in performance — no system is completely immune to downtime.
But we've built our architecture with the future in mind, and it’s more resilient than ever as more and more brands realize the power of conversational AI CX platforms.
The result? A platform you can count on to help you deliver exceptional customer service, without technical issues getting in the way.
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TL;DR:
Shoppers aren’t just open to AI — they’re starting to expect it.
According to IBM, 3 in 5 consumers want to use AI as they shop. And a McKinsey study found that 71% expect personalized experiences from the brands they buy from. When they don’t get that? Two-thirds say they’re frustrated.
But while most brands associate AI with support automation, its real power lies in something bigger: scaling personalization across the entire customer journey.
We’ll show you how to do that in this article.
Before AI can personalize emails, recommend products, or answer support tickets, it needs one thing: good data.
That’s why one of the best places to start using AI isn’t in sales or support — but in enriching your customer data. With a deeper understanding of who your customers are, what they want, and how they behave, AI becomes a personalization engine across your entire business.
Post-purchase surveys are gold mines for understanding customers — but digging through the data manually? Not so fun.
AI can help by analyzing survey responses at scale, identifying trends, and categorizing open-ended customer feedback into clear, actionable insights. Instead of skimming thousands of answers to spot what customers are saying about your shipping times, AI can surface those insights instantly — along with sentiment and behavior signals you might’ve missed.
Try this prompt when doing this: "Analyze 500 open-ended post-purchase survey responses. Identify the top 5 recurring themes, categorize customer sentiment (positive, neutral, negative), and surface any trends related to product quality, delivery experience, or customer support."
One of AI’s biggest strengths? Spotting intent.
By analyzing things like page views, cart activity, scroll behavior, and previous purchases, AI can identify which shoppers are ready to buy, which ones are likely to churn, and which just need a little nudge to move forward.
This doesn’t just apply to email and retargeting. It also works on live chat, in real time.
Take TUSHY, for example.
To eliminate friction in the buying journey, TUSHY introduced Shopping Assistant — a virtual assistant designed to guide shoppers toward the right product before they drop off.
Instead of letting potential customers bounce with unanswered questions, the AI Agent steps in to offer:

With a growing product catalog, TUSHY realized first-time buyers were overwhelmed with options — and needed help choosing what would work best for their home and hygiene preferences.
“What amazed us most is that the AI Agent doesn’t just help customers choose the perfect bidet for their booty — it also provides measurement and fit guidance, high-level installation support, and even recommends all the necessary spare parts for skirted toilet installations. It’s ushering in a new era of customer service — one that’s immediate, informative, and confidence-boosting as people rethink their bathroom habits.”
—Ren Fuller-Wasserman, Sr. Director of Customer Experience at TUSHY
AI also helps you see the road ahead.
Instead of looking at retention and loyalty metrics in isolation, AI can help you forecast what’s likely to happen next and where to focus your attention.
By segmenting customers based on behaviors like average order value, order frequency, and churn risk, AI can identify revenue opportunities and weak spots before they impact your bottom line.
All you need is the right prompt. Here’s an example you can run using your own data in any AI tool:
Prompt: “Analyze my customer data to forecast revenue by segment. Break customers into at least three groups based on behavior patterns like average order value, purchase frequency, and churn risk.
For each segment, provide:
Here’s what a result might look like:
Instead of flying blind, you’re making decisions with clarity — and backing them with data that scales.
When used strategically, AI becomes a proactive sales agent that can identify opportunities in real-time: recommending the right product to the right shopper at the right moment.
Here’s how ecommerce brands are using AI to drive revenue across every part of the funnel.
Your prices shouldn’t be static — especially when your competitors, inventory, and customer behavior are anything but.
AI-powered tools like Shopping Assistant help brands automatically adjust pricing based on shopper behavior. The goal is to make the right offer to the right customer.
For example:
With dynamic pricing, you can protect your margins and boost conversions — without relying on blanket sales.
AI-powered chat is no longer just a glorified FAQ. Today, it can act as a real-time shopping assistant — guiding customers, boosting conversions, and helping your team reclaim time.
That’s exactly what Pepper did with “Penelope,” their AI Agent built on Gorgias.
With a rapidly growing product catalog (22 new SKUs in 2024 alone), Pepper knew shoppers needed help discovering the right products. Customers often had questions about styles, materials, or sizing, and if they didn’t get answers right away, they’d abandon carts and move on.
Instead of hiring more agents to keep up, Pepper deployed Penelope to live chat and email.
Her job?
“With AI Agent, we’re not just putting information in our customer’s hands; we’re putting bras in their hands... We’re turning customer support from a cost center to a revenue generator.”
—Gabrielle McWhirter, CX Operations Lead at Pepper

Let’s look at how Penelope performs on the floor:
A shopper asked about the difference between two wire-free bras. Penelope broke down the styles, support level, and fabric in plain language — then followed up with personalized suggestions based on the shopper’s preferences.
Using Gorgias Convert chat campaigns, Pepper triggers targeted messages to shoppers based on behavior. If someone is browsing white bras? Penelope jumps in and offers assistance, often leading to faster decisions and fewer abandoned carts.
If a customer adds a swimsuit top to their cart, Penelope suggests matching bottoms. No full-screen popups, no awkward sales scripts — just thoughtful, helpful guidance.
Penelope also handles WISMO tickets and return inquiries. If a shopper is dealing with a sizing issue, Penelope walks them through the return process and links to Pepper’s Fit Guide to make sure the next purchase is spot on.

By implementing AI into chat, Pepper saw a 19% conversion rate from AI-assisted chats, an 18% uplift in AOV, and a 92.1% decrease in resolution time.
With Penelope handling repetitive and revenue-driving tasks, Pepper’s team now has more time to offer truly personalized touches — like virtual fit sessions that have turned refunds into exchanges and even upsells.
Bundling is a proven tactic for increasing AOV — but most brands still rely on subjective judgment calls or static reports to decide which products to group.
AI can take this a step further.
Instead of just looking at what’s bought together in the same cart, AI can analyze purchase sequences. For example, what people tend to buy as a follow-up 30 days after their first order. This gives you powerful clues into natural buying behavior and bundling opportunities you might’ve missed.
If you’re looking to explore this at scale, you can use anonymized sales data and feed it into AI tools to surface patterns in:
Try this prompt:
"Analyze this spreadsheet of order data and identify product bundle opportunities. Look for: (1) products frequently purchased together in the same order, (2) items commonly bought as a second purchase within 30 days of the first, and (3) patterns in high-value or high-frequency product pairings. Provide insights on the most promising bundles and why they might work well together."
Just make sure you’re keeping customer data anonymous — and always double-check the insights with your team.
Related: Ecommerce product categorization: How to organize your products
AI isn’t just here to deflect tickets. From quality assurance to proactive outreach, AI can elevate the entire support experience — on both sides of the conversation.
Manual QA is slow, selective, and often feels like it’s chasing the wrong tickets.
That’s where Auto QA comes in. Instead of reviewing just a handful of conversations each week, Auto QA evaluates 100% of private messages, whether they’re handled by a human or an AI agent.
Every message is scored on key metrics like:
It gives support leaders a full picture of how their team is performing, so they can coach with clarity, not just gut feeling.
Here’s what brands can do with automated QA:
Let’s walk through a real example.
Customer: “Hi, my device broke, and I bought it less than a month ago.”
Agent: “Hi Kelly, please send us a photo or a video so we can determine the issue with your device.”
Auto QA flags this interaction with:
Reactive support is table stakes. AI takes it a step further by anticipating issues before they happen — and proactively helping customers.
Let’s say login errors spike after a product update. AI detects the surge and automatically triggers an email to affected customers with a simple fix. No need for them to dig through help docs or wait on chat — support meets them right where they are.
Proactive AI can also be used for:
This saves the time of your agents because the AI will spot problems before they turn into tickets.
Your customers are telling you what they think. AI just helps you hear it more clearly.
By analyzing reviews, support tickets, post-purchase surveys, and social comments, AI can spot sentiment trends that might otherwise fly under the radar.
For example:
Related: 12 ways to upgrade your data and trend analysis with Ticket Fields
Whether you’re enriching customer data, making smarter product recommendations, triggering dynamic pricing, or proactively resolving support issues, AI gives your team the power to scale personalization without sacrificing quality.
With Gorgias, you can bring many of these use cases to life — from AI-powered chat that drives conversions to automated support that still feels human.
And with our app store, you can tap into additional AI tools for data enrichment, direct mail, bundling insights, and more.
Personalized ecommerce doesn’t have to mean more work. With the right AI tools in your corner, it means smarter work — and better results.
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