

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:
At Gorgias, we’ve embraced the concept of high talent density, introduced by Netflix co-founder and CEO Reed Hastings in No Rules Rules, as a foundation of how we operate. The idea is simple: a team is at its best when every member is highly skilled and performing at their peak.
I’ll walk you through exactly how we’ve built a workplace that prioritizes talent density by breaking down what the concept means, how it shapes our hiring process, and how we keep Gorgias a rewarding environment to grow in.
High talent density refers to having a team where each member is highly skilled and performs at their best. When a group consists of top performers, their collective effectiveness increases. Hastings notes, "Talented people make one another more effective."
For example, in a team of five exceptional employees, each individual's high performance elevates the group's overall success. If there is even one underperformer, a team's effectiveness decreases by 30 to 40 percent.
We follow three pillars to maintain and grow high talent density. These pillars guide how we build and sustain a team of exceptional performers at Gorgias.
To bring this to life, we’ll use an analogy of colors to represent different types of performers in our talent pool:

Let’s take a closer look at how we practice each of these pillars below.
Every manager wants to hire someone exceptional, but even with the best intentions, it doesn’t always work out.
To clarify, we’re looking for someone great to do the job now but has the potential to grow and stay strong as the company evolves.
Here’s how we approach it.
Let’s be upfront: great talent often comes with a higher price tag.
The first step in building high talent density is offering competitive pay. Exceptional people expect to be compensated for their contributions, and rightly so.
A single outstanding hire, even if paid 50% more than two average employees, often delivers far greater results.
This is especially true in creative roles, where the impact of a single talent can be worth that of several others. It’s certainly not easy to prioritize compensation when resources are tight, but talented people are an investment — and talent is usually expensive.
Related: How we built an international SAAS salary calculator for our distributed team
Great candidates don’t always come knocking on your door. The best talent is often already employed, not actively looking for a new role.
To hire the best, we go beyond applications and invest heavily in proactive sourcing.
At Gorgias, we rely on scorecards and standardized feedback forms to assess every applicant fairly and thoroughly. We also include role-specific assessments or assignments as part of the process.
While some argue that take-home tasks are no longer standard, we’ve found them invaluable. A strong interview doesn’t always translate into strong performance, and these assignments often reveal critical insights into a candidate’s true capabilities.
Referrals are another piece of the puzzle. A-players tend to know and recommend other A-players. While leveraging referrals, we also keep a close eye on maintaining diversity to make sure everyone gets the same chance.
Performance isn’t static. Someone who was a top performer last year might not meet expectations today, especially as the company grows and their role evolves.
To stay objective, we pair performance reviews with bi-yearly cross-evaluation talent reviews. Cross-evaluations provide a broader perspective, helping managers see beyond potential biases and assess whether a top talent has changed in performance quality.
These regular evaluations ensure we’re always aware of who is meeting expectations and who may need support or a more difficult conversation.
While Netflix's philosophy is to immediately separate with employees when they underperform, we believe in a more empathetic approach that follows our company’s core value of being 100% honest.
At Gorgias, we train managers to deliver clear, actionable feedback so team members always know where they stand and how they can improve. To us, honesty means being thoughtful, encouraging, and focused on helping people grow.
We also use Performance Improvement Plans (PIPs) as a tool for growth. We don’t simply view them as compliance tools, but as opportunities for employees to get back on their feet. In fact, 50% of our PIPs result in team members regaining performance.
Sometimes, despite feedback and coaching, parting ways becomes the best option for both the employee and company. When that happens, we believe in making the transition as respectful and fair as possible.
Offering a strong severance package not only supports employees during their transition but also empowers managers to make tough decisions confidently. It reflects our shared responsibility and ensures we treat people with dignity, even when their time with us comes to an end.
When a company grows, employees need to match that pace to keep delivering at a high level. This requires consistent learning and development to meet the challenges of each new stage.
Growth doesn’t happen by accident. As Daniel Coyle explains in The Talent Code, greatness isn’t born; it’s grown through “deep practice.”
To encourage growth, Gorgias managers hold career conversations every six weeks, focusing on the “3Es”: education, exposure, and experience. These discussions identify growth areas, leverage networks, and clarify the steps team members can take to excel.
We also reward our top performers with opportunities beyond financial incentives. From double learning stipends to travel experiences and executive mentorships, these rewards keep our “dark green” talents motivated and engaged.
Read more: Why we don’t increase salaries based on performance
In the pursuit of high talent density, results are important, but so is maintaining a positive, team-oriented environment.
A top performer with a toxic attitude can harm the environment you’re working hard to build. For that reason, we hire and nurture people who align with our values, show respect for others, and contribute to a collaborative culture. Both the what (talented employees) and the how (exemplary behavior) matter.
I believe this is one of the toughest topics when it comes to talent management.
Top performers are eager to work hard and prove their worth. Oftentimes, they approach work intensely and passionately. However, too much intensity can lead to exhaustion. And, of course, tired employees can’t deliver well.
That’s why managing pressure is crucial to maintaining high talent density. Introducing programs and initiatives that support the well-being of your employees helps prevent stress and burnout.
We take a tailored approach to prevent burnout, recognizing that one size doesn’t fit all. Having strong management training and great HRBPs (HR Business Partners) are the most impactful pieces. They help uncover the underlying issues of burnout: lack of vacation time, heavy workload, personal challenges, or misalignment.
Once the issues are clear, we provide the right tools to help. This could include coaching, training, enhanced benefits, or adjusted workloads.
We use specific metrics to gain insights into the effectiveness of our talent management strategies and refine our approach as needed.
Here are the metrics we track to evaluate talent density:
By regularly tracking these metrics, we can see where we may be falling short — whether that’s being slow to part ways with low performers, struggling to attract great talent, or losing top performers unnecessarily.
The ultimate goal of having strong talent density is to build a well-performing organization.
After each talent review, HRBPs will work hand in hand with managers to refine the organizational chart. They identify opportunities for improvement, such as promoting top talent, adjusting scopes of responsibility, or making changes to strengthen the team.
Ultimately, you should always make sure that your top performers are leading the most critical and top-priority initiatives.

In my role as VP of People at Gorgias, I’ve seen how fast growth fuels the resources and opportunities needed to attract and develop exceptional talent. High performers thrive in environments with big goals and fast results, but it’s up to us to create the right conditions for them to succeed.
Sustaining high talent density takes dedication and humility. It means holding ourselves to high standards while being transparent. While we’ve made great strides, there’s always more to learn and refine.
As we continue this journey, let us remain humble, acknowledging that there is always room for growth and improvement.

TL;DR:
Scaling great customer support is often seen as a challenge, especially when ticket volumes climb and customer expectations rise. But for CX leads and executives, it’s essential to recognize that support isn’t just a cost center—it’s a profit driver. Exceptional customer support builds loyalty, drives repeat business, and creates upselling opportunities, directly boosting revenue.
That’s where Gorgias comes in. In this blog, we’ll show you how brands like Rumpl, TalentPop, Stylest, and Baby Gold have turned their support challenges into measurable wins with the power of automation and smart tools.
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Obvi was leaving money on the table. Without phone support, they faced challenges like subscription drop-offs and missed upsell opportunities. Voice as a support channel wasn’t on their radar, so valuable revenue streams slipped through the cracks. Plus, they lacked a proactive strategy to retain subscriptions.
By integrating Gorgias’ omnichannel support tech, Obvi transformed their customer experience. They introduced a personalized, phone-based support system tailored to upselling and subscription retention, and partnered with Aventus’ Learning Management System (ALMS) to give their agents expert training.
The result?
A customer support system that delivered exceptional service while boosting revenue.
Results achieved:
With Gorgias and phone support, Obvi unlocked the potential of voice to grow their business and deepen customer loyalty.
During peak seasons like back-to-school, Jonas Paul Eyewear struggled to keep up with the sheer volume of customer inquiries. The small customer care team was overwhelmed with repetitive questions, leading to slower response times and increased stress. They needed an efficient solution to handle the increased load while maintaining excellent service.
By partnering with Gorgias, Jonas Paul Eyewear transformed their customer service operations. AI Agent automated responses to common queries like prescription details and return policies, freeing up their team to focus on more complex issues.
An integration with Aircall allowed agents to handle phone calls directly within Gorgias, with access to customer interaction history and Shopify data. A Klaviyo integration streamlined inquiries related to home try-on kits and orders. Together, these tools created a customer-focused experience.
Results achieved:
"With faster responses and more proactive support through AI, we are seeing happier customers, which obviously translates into more retention and more brand loyalty. Overall with the improvement in first response time, we've really seen an uptick in customer satisfaction and less of an escalation in tickets."
—Lynsay Schrader, Lab and Customer Service Senior Manager at Jonas Paul Eyewear
As Dr. Bronner's business grew, so did their customer support challenges. The limitations of their previous system, Salesforce, made it difficult for their small customer experience (CX) team to handle increasing inquiries, especially repetitive questions. As a result, customers experienced longer response times, and the brand needed a more effective solution.
By switching to Gorgias, Dr. Bronner's transformed their customer support operations. They implemented AI Agent to automate routine inquiries, allowing their team to focus on more complex, personalized interactions.
The addition of a comprehensive Help Center empowered customers to find answers independently. At the same time, integrations with Shopify, Aircall, and Loop Returns streamlined the management of orders, returns, and voice communications — all within a single platform.
Results achieved:

"Our CX team is small, which is why leaning into automation was so crucial for us. We were really at a turning point at the beginning of the year, and we knew that we had to make a change. We had to make our tools work for us, not against us. Gorgias was a huge opportunity, and we decided to jump in head first. Within the first 30 days, we were able to automate 30% of customer interactions and are now up to 45%."
—Emily McEnany, Senior CX Manager at Dr. Bronner’s
Peak seasons like winter, Black Friday, and Cyber Monday brought immense pressure to Pajar’s small customer service team of five agents. With high ticket volumes and a bilingual customer base (English and French), maintaining quick response times and delivering excellent service became a major challenge. They needed a solution to streamline operations and keep their customers happy.
Partnering with Gorgias proved to be a game-changer. Pajar implemented AI Agent to handle common inquiries in both English and French, freeing their team to focus on complex tickets. Automation reduced repetitive tasks, improving team efficiency, while Gorgias’ 30-in-30 onboarding program helped them quickly hit their automation goals.
Results achieved:

"We were nervous to get started at first, but as soon as we had the implementation call it was a huge weight off of our shoulders — we knew it was going to be great. And we were right. The first day we turned it on, we started seeing results right away."
—Noémie Rousseau, Customer Service Manager at Pajar
LSKD, a popular Australian activewear brand, struggled to keep up with a high volume of customer inquiries during peak periods. Their previous system couldn’t handle repetitive queries efficiently, leading to slower response times and an overburdened support team. To maintain their commitment to excellent customer service, they needed a smarter solution.
Gorgias delivered. By implementing AI Agent, LSKD automated responses to common questions, enabling their team to focus on complex, high-value interactions. Automation streamlined workflows, reducing manual tasks, while integration with Shopify provided instant access to customer order data. LSKD could respond faster and more accurately, improving the overall customer experience.
Results achieved:

"Gorgias AI Agent is going to be a game-changer for us during BFCM. With the ability to provide immediate, personalized responses, we’re confident it will not only reduce the volume of repetitive inquiries but also ensure our community feels supported during the busiest time of the year.”
—Kailey Burton, Community Experience Head Coach at LSKD
Baby Gold, a jewelry brand known for its personalized pieces, faced growing challenges in meeting customer demands for quick and efficient support. Their existing customer service system lacked the automation needed to manage repetitive inquiries, leading to slower response times and an increased workload for their team.
They needed a solution to improve efficiency and meet customer expectations for rapid assistance.
AI Agent autonomously resolved customer email tickets by learning the brand’s unique policies and voice while automation reduced manual tasks. Easy integration with their existing systems provided agents with instant access to customer data, enabling quicker, more accurate responses and improving overall efficiency.
Results achieved:
"I feel that nowadays, people expect quick responses and rapid assistance. AI and tools such as AI Agent are perfect to meet these expectations."
—Sindi Melgar, Customer Service Manager at Baby Gold
Psycho Bunny, a bold menswear brand known for its edgy take on classic styles, faced a challenge: how to maintain a stellar customer experience while scaling their multi-million dollar business. With a focus on improving key performance indicators (KPIs) and customer satisfaction (CSAT), they needed a solution to boost efficiency without adding to their customer support team’s workload.
Psycho Bunny implemented AI Agent to handle routine customer inquiries, such as order status, returns, and exchanges, freeing up human agents to focus on more complex, high-value interactions.
With automation managing 26% of tickets and integration with existing systems, Gorgias provided the tools to streamline operations and deliver exceptional service, all from one unified platform.
Results achieved:
"I already love Gorgias because its email and chat capabilities are ahead of the competition, so I trust Gorgias to also build the best AI agent. And having all our CX tools within the same system is important—I don’t want yet another dashboard to check."
—Tosha Moyer, Senior Customer Experience Manager at Psycho Bunny
Stylest, a swimwear brand, set its sights on a big goal: to boost visitor engagement and convert more casual browsers into loyal customers. They wanted to increase sales and highlight their best-selling styles while providing an enjoyable shopping experience.
To achieve this, Stylest partnered with ECOM DEPARTMENT and implemented Gorgias Convert, an onsite marketing tool designed to optimize customer interactions and drive conversions. With Convert, they launched targeted campaigns that effectively guided visitors toward completing their purchases without disrupting the shopping experience.
Results achieved:
TalentPop, a customer service management agency serving ecommerce brands, set out to expand its client base and elevate its service offerings. To achieve these goals, they needed a partner that could align with their go-to-market strategies, provide innovative tools, and help attract new business.
TalentPop tapped into Gorgias’s robust platform and co-selling initiatives to acquire mutual customers.
They received tailored guidance to plan forward-thinking strategies, looking 1–2 years ahead, while maintaining a high standard of service delivery. Access to essential tools and operational support allowed TalentPop to streamline processes, boost efficiency, and increase revenue from customer support services.
Results achieved:
"Gorgias has been instrumental in TalentPop’s growth from the start of our partnership. They have provided key prospect opportunities, supported us in winning accounts, and invested in TalentPop by bringing on best-in-class customer service agents to support their teams."
—Olivia Parker, Senior Partnerships Manager at TalentPop
Rumpl’s manual, 3PL-dependent returns process was time-consuming and inefficient, with resolutions taking 2–3 weeks. A reliance on shared Excel sheets created operational bottlenecks during busy periods and frustrated customers.
By integrating Loop Returns with Gorgias, Rumpl automated and streamlined their returns process. Customers could manage returns and exchanges via an automated portal in the Gorgias chat widget. Self-service tools and automated communications reduced manual workloads, while centralized support within Gorgias improved efficiency and visibility.
Results achieved:
"The Gorgias/Loop integration has been really useful for us. Being able to view return info in Gorgias, then open that return in Loop with one click, makes it super easy to navigate and resolve any issues the customer might have."
—Jacob Cantu, Senior Customer & People Experience Manager at Rumpl
Great customer support goes beyond answering questions. It involves building trust, driving loyalty, and turning everyday interactions into opportunities for growth. From streamlining returns to automating repetitive tasks, brands like Rumpl, TalentPop, Stylest, and Baby Gold show how the right tools can transform support into a revenue-driving powerhouse.
With Gorgias, you can work smarter, resolve issues faster, and create exceptional experiences that keep your customers coming back.
Want to see how Gorgias can help you scale your support and grow your business? Book a demo today and discover the tools that will take your customer experience to the next level.
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TL;DR:
Tone of voice—and a strong brand personality—have become essential components of exceptional customer service.
As many brands introduce AI to automate customer service interactions, the challenge of ensuring that AI is helpful looms. Part of that helpfulness means speaking to customers in a way that connects with them, not alienates them.
That’s why implementing AI that uses your brand’s signature tone of voice has never been so important.
This post will explore why tone of voice matters in customer service and provide insights on how AI can effectively replicate brand voice, with tips on implementing it successfully.
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Through a customer service lens, tone of voice is the style, word choice, and general vibe of how your brand speaks when it communicates with customers. Tone of voice is one of the key components of brand identity, so the tone of voice a support team uses will always align with its greater brand.
According to Statista, 64% of customers prefer making purchases from companies that create experiences tailored to their needs and wants. A consistent tone of voice does just that, building trust, creating better relationships between customers and brands, and making experiences more personal.
On the flip side, brands that don’t prioritize tone of voice — especially when it comes to AI — will see robotic tones cause a loss of customer trust.
51% of customers share concerns that brands that use AI won’t connect them to a human. But if you choose the right AI tools that leverage your brand’s information and use it effectively, you can train it to mimic your unique voice — sometimes to the point where customers don’t even know that it’s the AI talking.
That’s true for the CX team at toddler carrier brand Wildride.
”An influencer emailed us saying, 'I really love you guys,' and our AI Agent replied, 'Love you too,' with heart emojis, which was really funny. It was just like an email from me and my other team members,” says Amber van den Berg, their Head of Customer Experience.
Wildride trusts Gorgias AI Agent to manage a high volume of tickets while still providing each customer with a great experience.
📚 Further reading: How Wildride automated 33% of email tickets with AI Agent
AI Agent uses a few key components to mimic tone of voice, including LLMs (Large Language Models) to form human-like responses, guidance from you, and the internal resources you provide it.
“We’ve had customers respond to AI Agent thinking they were speaking to a real person. That’s how elevated the response was from AI,” says Emily McEnany, Senior CX Manager at Dr. Bronner’s.

You can absolutely train AI to match your brand's specific voice and style. Here are a couple of tips that will help you be successful:
If your brand has an established voice and tone, make sure that you either have internal documents that detail it or can describe it accurately in a couple of paragraphs.
You’ll use that information to help train the AI, so it’s essential that it’s up-to-date and accurate.
If you don’t have an established tone, now is a great time to generate your brand voice. Review customer conversations and the copy on your website. Chat with your marketing team and even your brand’s founder to get a clear picture of what it is or what you’d like it to be.
Here’s a quick-start guide for how to find your tone of voice:
Most AI-powered tools will allow you to set up some sort of guidance around how they interact with customers. If you use Gorgias AI Agent, you’ll be able to set specific tone of voice parameters. Choose from three pre-built options—Friendly, Professional, Sophisticated—or Custom to give it your own instructions.
For example, jewelry brand Baby Gold uses an upbeat, friendly, warm, and personable tone. They would likely choose the Friendly option, which is the go-to option for many teams.
“Sometimes agents forget personal details to call out when communicating with our customers, like birthdays or weddings,” says Sindi Melgar, their Customer Service Manager.
“But I noticed on a few different occasions where the AI Agent is highlighting these things and is saying, congratulations on your wedding! Just the tone of voice that Michelle is able to adopt is definitely on brand for us.”
If you’re looking to provide your own specific guidelines, create custom guidance like Wildride did below:

📚 Recommended reading: How to customize AI Agent with 7 brand voice examples
In general, you should always keep an eye on how your AI tool is answering questions to ensure that it’s providing accurate responses and that your customers aren’t getting frustrated. Combing through responses manually can be overwhelming, so that’s why Gorgias offers an AI Feedback feature.
In the ticket sidebar you’ll find a summary of the response AI Agent provided, including why it responded the way it did and the resource it pulled the response from.

Then, give feedback by using the 👍 or 👎 icons to mark AI Agent’s response as correct or incorrect. AI Agent uses this feedback to improve responses over time.
📚 Recommended reading: How to coach AI Agent and give feedback
Any time you add new policies or update existing ones, make sure you add them to your helpdocs and Macros, which are the main resources the AI is going to draw from.
The more consistently you can go in and provide the AI direct feedback on each response, the more easily AI will nail your unique tone.
Your brand’s tone of voice makes a huge impact on the relationships you build with customers. Combining your unique brand voice with AI means you’ll provide more personalized responses and resolve customer issues faster.
“We were hesitant at first, but AI Agent has really picked up on our brand’s voice,” says Lynsay Schrader, Lab and Customer Service Senior Manager at Jonas Paul Eyewear. “We’ve had feedback from customers who didn’t even realize they were talking to an AI.”
Gorgias AI Agent is the go-to tool for AI-driven customer support that aligns with brand tone.
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TL;DR:
Forrester’s 2024 Customer Experience Index reports that 39% of brands’ customer experience (CX) quality has declined over the past year.
It can be challenging to get a full understanding of how your team—and AI, if you use it—are truly performing.
This is true even with metrics like CSAT.
“A 5-point scale only tells you and your agents so much, and relying on consumers providing feedback further limits what you’re able to look at and learn from,” says Kayla Oberlin, Senior Manager of Customer Experience at amika.
Quality Assurance (QA) is becoming a more crucial component of a customer experience strategy, especially one that prioritizes customer happiness.
We’ll cover the importance of customer service QA, best practices, tools, and tips to implement QA effectively.
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In the CX context, QA (Quality Assurance) refers to reviewing customer conversations to improve your support team’s performance and enhance customer satisfaction. QA ensures a consistent and satisfying customer journey across touchpoints, including your website, support channels, and social media.
Aside from accuracy issues, a manual quality assurance process is:
The solution isn’t for CX teams to skip the QA process altogether but to automate it.
According to research from McKinsey, “A largely automated QA process could achieve more than 90 percent accuracy—compared to 70 to 80 percent accuracy through manual scoring—and savings of more than 50 percent in QA costs.”
With an automated QA process, brands can:
According to Statista, 94% of customers are more likely to purchase again after receiving top-notch support. Quality assurance ensures that every customer gets the same experience, and provides agents with the feedback to learn and stay on-brand with each resolution.
At its core, QA:

Addressing errors early is important, as even small mistakes can harm customer trust and create lasting negative impressions. QA tools can prevent mistakes because of better coaching and training. This can stop misinformation in its tracks –– and from escalating into bigger problems down the line.
QA makes sure that all customer touchpoints, like calls, emails, live chat, and even AI responses, are handled with the same level of care. This is especially helpful when training new team members, introducing new products or policies, or during high-traffic periods.
Consistent and reliable experiences build customer trust and loyalty. If you were to reach out to a brand and have an amazing experience the first time but a bad experience the next, you’d probably question which experience was the norm.
Top-notch experiences that happen time and time again tell your customers that you’ll always be there to help. This can boost repeat sales and even referrals: According to Statista, 82% of customers recommend a brand after a great experience.
Aside from increasing happiness and making customers feel heard and appreciated, personalized support also affects your bottom line. Statista notes that 80% of businesses found that providing personalized customer experiences led to increased spending for consumers.
With QA, teams are able to rate and review all tickets instead of spot-checking. This provides them with a:
Whether it’s lowering resolution times, introducing a knowledge base, or adding AI Agent to your team, making continuous improvements will help you stay ahead of the competition.
Implementing a QA program (especially if you can automate it) is one of those additions that provides you with the refinements you need on a resolution-to-resolution level.
QA best practices include:
As you set out to integrate a Quality Assurance process into your CX program, first establish benchmarks for various metrics and KPIs. These benchmarks help track and evaluate the performance of QA as you implement it.
If you don’t already track customer support metrics, CSAT, first response time (FRT), resolution time, and net promoter score (NPS) are great ones to start with.
💡Tip: If you use Gorgias, you’ll find your current support performance statistics in the Statistics menu. Make sure that you can see back at least six months. Then, compare an equal time frame for post-QA implementation.
While it might sound a bit “meta” to monitor your quality assurance (which is already monitoring your support responses), it’s still worth noting.
Ensure that your QA process works smoothly, helps your metrics rather than hurts them, and provides actual helpful feedback to your agents.
The simplest way to maintain your support quality standards is to use an automated QA tool. Automating the QA process lets CX teams get deeper insights into agent strengths and areas for improvement, and captures deeper insights than a CSAT score could.
Understanding how customers feel will allow you to fine-tune your processes and ensure you’re delivering a consistent and high-quality experience. Here are a few ways to collect feedback:
Lack of resources, ineffective training, poor communication between team members, not having the right tools, and doing everything manually are some of the challenges you can encounter when adding a QA process.
Here are a couple of solutions we recommend:
By prioritizing QA, your team can identify potential problems early, reduce errors, and improve overall performance, leading to a smoother, more reliable experience for customers –– and your CX team.
In the long run, brands that focus on QA can gain a competitive edge, building stronger relationships with customers and driving sustainable growth. Book a demo now.
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Let's talk about something that often gets overlooked in ecommerce: what happens after someone hits that "Place Order" button. You might think the hard part's over once you've made the sale, but here's the thing the post-purchase experience can make or break your relationship with customers.
In today's competitive online marketplace, those relationships are everything — especially considering that loyal customers spend an average of 67% more per purchase than new customers.
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Providing an excellent post-purchase customer experience can turn one-time customers into loyal advocates who are more likely to make repeat purchases and recommend your brand to others.
When someone buys from your store, they're not just getting a product — they're starting a relationship with your brand.
A great post-purchase experience shows customers you actually care about their satisfaction beyond just making the sale. 90% of U.S. customers say that an immediate customer service response is "important" or "very important.”

When you nail this part, something magical happens: one-time shoppers transform into passionate advocates who not only come back for more but can't help telling others about their amazing experience with your brand.
Having accessible support and an efficient and easy returns process may make the difference between a happy customer and an unsatisfied one.
Trust is everything in online shopping. When customers feel supported after making a purchase, they're much more likely to give you the benefit of the doubt if something goes wrong down the line.
It's like building a friendship: every positive interaction adds another layer of trust. And that trust translates directly into repeat business and glowing recommendations.
The post-purchase support experience makes a huge difference in building that trust. In fact, 96% of customers say excellent customer service builds trust.
Great post-purchase support can actually help reduce your return rates. By addressing concerns quickly and providing clear information upfront, you can prevent many returns before they happen.
This can save you money on shipping and restocking and create a smoother experience that keeps customers happy and your business healthy.
Automation eliminates manual tasks, freeing up your team to focus on more strategic initiatives. By automating repetitive tasks, you can improve efficiency and productivity, allowing your team to focus on more value-added activities.
You can automate everything from customer support to returns and exchanges to your order tracking and more. Besides meeting customers' straightforward needs, automation allows you to focus your team's energy on solving bigger problems and strengthening customer relationships.
Automation helps ensure consistency across all your post-purchase processes.
When customers know they can count on a reliable experience every time they shop with you, it builds confidence in your brand.
Plus, fewer mistakes mean happier customers and less time spent fixing problems.
Speed matters in today's world, and automation helps you deliver faster, more personalized responses to customer needs.
Whether it's instant order updates or quick responses to questions, automation helps you meet and exceed customer expectations. The result? More satisfied customers who feel valued and understood.
Here are some ways to automate the post-purchase experience:
Streamline the returns process with automated return labels, tracking, and updates. Use ReturnGO to automate this process, saving time and reducing manual errors. With automated returns, you can provide a hassle-free experience for customers, encouraging them to return to your store in the future.
Automated returns can help to improve the customer experience by making the returns process easier and more convenient. 65% of customers say the speed and ease of refunds affect where they choose to shop.
By automating tasks such as generating return labels and tracking packages, you can reduce the time and effort required for customers to return items.
Think about it from their perspective — if returning an item is hassle-free, they'll feel more confident buying from you in the future. It's like having a safety net that makes customers more comfortable taking chances on new products.
In today's fast-paced world, customers expect quick and efficient support. Using a customer experience platform like Gorgias, you can manage all your customer support tickets in one place, making it easier to provide fast, accurate help when people need it.
By centralizing your post-purchase support, you can manage support tickets more efficiently, respond to customer inquiries quickly, and provide the most up-to-date information. This centralized approach can hugely improve response times.
Nobody likes being left in the dark about their order. Automated post-purchase notifications keep your customers informed every step of the way - from order confirmation to delivery and returns. Using tools like ReturnGO, you can send personalized updates that make customers feel looked after. This is essential for building customer loyalty.
Keeping customers informed about their orders can help reduce customer anxiety. When customers know what to expect, they’re less likely to worry about their purchase and are more likely to keep buying from you again and again.

To truly streamline your post-purchase customer service, if you connect your returns management system with your customer support system, you really bring all of the pieces of a puzzle together.
When these two systems are in sync, you can create a smooth workflow that makes things easier for both your team and your customers.
By automating tasks like creating support tickets and processing returns, you can save time and create a more reliable, efficient system that helps you serve customers better. No more jumping back and forth between systems to check on a return when a customer reaches out about it.
The ReturnGO-Gorgias integration makes this happen seamlessly, with features like:

The ReturnGO-Gorgias integration makes it easy for your team to manage returns and communicate with customers without having to jump between systems to hunt for information.
So, there you have it! In the world of online shopping, how you handle the after-purchase experience can be just as important as making the sale in the first place.
By automating your post-purchase process, you can create a seamless and satisfying customer experience.
Tools like ReturnGO and Gorgias can help you create the kind of experience that builds customer loyalty.
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TL;DR:
People are only able to identify AI-generated content 46.9% of the time. That’s less than half the time!
In the ecommerce customer service industry, this is just one reason teams are getting more comfortable with using AI.
Better language processing abilities mean AI can be a better extension of CX teams, relieving agents of repetitive questions, like where is my order?, while speaking in a way that’s familiar and delightful to customers.
Upholding a strong brand voice should be one of your top priorities in CX. With Gorgias AI Agent, you can choose AI Agent’s exact tone of voice, from sophisticated to fun. Below, check out seven AI Agent brand voice examples from real customer conversations.
“We’ve had customers respond to the AI thinking they were speaking to a real person. That’s how elevated the response was from AI.”
—Emily McEnany, Senior CX Manager at Dr. Bronner’s
Tone of Voice refers to how AI Agent communicates with your customers. In Gorgias, you can select from three pre-built tone options:
Or, you can create a custom tone, keeping your brand guidelines, style guide, and target audience in mind.
Note: AI Agent and Tone of Voice are only available to Gorgias Automate subscribers.
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Explore how effectively AI Agent adapts to seven distinct tones in the examples below. First, we’ll show you what a preset AI Agent tone option sounds like, then we’ll move on to six examples using custom instructions.
Feel free to copy and paste our provided instructions to set up your AI Agent with the custom tone of your choice, or, even better, take some inspiration to create your own.
A friendly AI Agent is the go-to for most CX teams. A Friendly tone of voice is outgoing and welcomes inquiries with enthusiasm. If you were to imagine the model support agent, they would speak like this.
The Friendly tone of voice is available by default in AI Agent’s settings.
Here’s how an AI Agent with a Friendly tone of voice responds to a customer asking for samples and coupons:

Now, we move away from AI Agent’s default Tone of Voice options and toward the vast possibilities of the Custom option.
If you prefer your AI Agent get to the point in as few words as possible, create a Custom tone of voice that breaks up text into separate lines, limits paragraphs to two to three sentences, and keeps responses short.
💡 Tip: Access a custom tone of voice by going to Automate > AI Agent > Settings > Tone of Voice > Custom. A text field will appear where you can write your instructions.

Tone of voice instructions:
Acknowledge the customer's feelings by briefly repeating their initial concern(s). Break text up, don’t send entire paragraphs, and keep responses short and easy to read. Keep interactions brief but filled with empathy. We are not long-winded. Keep an informative tone while remaining professional, clear, and easy for customers to follow. Insert links where needed. Don't use too many adjectives when expressing empathy. Never tell the customer to email support or contact our customer service team.
Here’s how an AI Agent with a direct and brief tone of voice responds to a customer who wants to cancel their order:

Who says support agents can’t have personality? Bring some fun into your conversations by creating a custom tone of voice that allows your AI Agent to use emojis and exclamation points.
Tone of voice instructions:
Greet with first name only. Acknowledge the customer's feelings by repeating their initial concern(s). Be concise and provide shorter responses, try to keep your responses to a few sentences. Use a warm, positive, and engaging—like chatting with a helpful, considerate friend. Sign off with "Best Regards". Avoid jokes or comments related to sensitive topics. Make the customer feel like a friend. You can include approved emojis for a personal touch and exclamation points. Approved emojis to use: 💞🫶✨🥰💖🎀💓💘🥳💗💕💯 You should recognize and celebrate personal milestones mentioned by customers, making the interaction feel more personal. After the customer's initial message, there's no need to restate their issue in follow-up responses.
Here’s how an AI Agent with a fun tone of voice responds to a customer asking about exchanging their damaged product:

Customer support often gets a bad rep. Customers anticipate long response times and unpleasant interactions. Flip customer expectations by giving your AI Agent a calming and comforting voice that can instantly fix negative experiences.
💡 Tip: Brands in the wellness and baby industry would do well to use a comforting tone of voice for their AI Agent.
Tone of voice instructions:
Our brand embodies the role of a nurturing parent, promoting happiness, growth, and well-being while creating moments of joy and inspiration. Stay genuine and reflect childlike wonder without being overly sentimental. We maintain a positive and supportive tone, offering a safe, comforting space. Avoid admitting fault or apologizing. Be shorter in replies. Do not offer replacements. Do not give out phone numbers.
Here’s how an AI Agent with a comforting tone of voice responds to a customer asking about exchanging their damaged product:

Give your AI Agent a laid-back, “we’ve got your back” vibe that feels like chatting with a buddy. This tone keeps things casual, approachable, and like you’re ready to tackle any issue together.
Tone of voice instructions:
Sound like a gym bro. Speak casually and friendly. Be eager to help. However, do not go overboard with puns or stereotypical phrases. You may use the following emojis: 🤙💪🏋️ End responses with "Stay awesome,"
Here’s how an AI Agent with a bro-y tone of voice responds to a customer asking about glove sizing:

If your brand isn’t afraid to lean into humor and puns, this tone will definitely connect with your audience. Let your AI Agent use wit and clever wordplay to keep conversations lighthearted and customers smiling at their screens.
Tone of voice instructions:
Speak in bee and honey puns and use colorful emojis. Use at least one emoji per message. Keep your messages brief. Sign off with a different pun in every conversation. If a customer is upset or needs urgent help, avoid puns.
Here’s how an AI Agent with a punny tone of voice responds to a customer asking about suit sizes:

In all of our examples, AI Agent responses can easily be mistaken for one of your human agents. But if, for any reason, you want to change that by making your AI Agent sound robotic — it’s possible.
Tone of voice instructions:
Sound like a robot. Make robot sounds and puns. Use short, direct, and easy-to-read sentences.
Here’s how an AI Agent with a robotic tone of voice responds to a customer asking about exchanging their damaged product:

Like a chameleon, AI Agent adapts to your brand voice. Whether it’s friendly, professional, or a custom tone, you can be sure that every interaction aligns with your brand’s identity.
With AI Agent on your side, you have the power to make each conversation feel authentic. Take it from Psycho Bunny’s Senior Customer Experience Manager Tosha Moyer who says, “The overall tone is good, and its responses are really excellent.”
Ready to see AI Agent’s excellence for yourself? Book a demo and discover how AI Agent can be a permanent part of your team.
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This episode’s featured guest is Nik Sharma, the CEO at Sharma Brands. He works with founders and executives of a wide variety of brands to launch their digital platform, develop an acquisition and retention strategy, expand their channels, and optimize their revenue. He has worked with big brands such as Bill Blass, Roc Nation, and Haus, and he is on the podcast today to discuss the importance of customer service.
Customer service is a brand’s frontline of defense. They are the first to know when something is wrong, broken, or if anything can be done better. By identifying the needs, concerns, and issues of the customer faster than anyone else, they can also fix or address problems before it gets any bigger and becomes damaging to the company. For example, when Nik was working with Judy, an emergency kit brand, there was an issue with their discount code. It simply was not working but no one knew until an online shopper got in contact with customer service. Immediately, the code was fixed and although Judy must have lost several potential customers during the mistake, they could have lost far more if customer service were not there to receive and respond to the matter.
It is important to keep the customer happy. If it is their first time ordering from a brand and they have a less than stellar experience, they are most likely not going to order again. They will not give any of the company’s second products a try, such as the more expensive purchases or subscriptions. That is why customer service is there to pacify the consumer and their issues, acting as a prevention method to any bad experiences. By offering even simple solutions from a technical standpoint, such as dealing with refunds or providing a shipping label, the customer is excited that the brand provided them with a solution.
Through this excitement and acknowledgement, an intimate relationship is created between the brand and customer. The customer feels valued as the brand understands and emphasizes with them. They recognize that they will be taken care of and as more customers begin to feel the same way, a community is built. Every company talks about wanting to build a community and all the strategies that it will take to do so, but the easiest and fastest way to accomplish that is by just having an efficient customer support team. Even a simple third-party logistics team can give a significant boost to a brand by providing front-line workers for customers.
It is not an exaggeration to say that customer service is the most vital piece of a brand. Nik has seen firsthand what good customer service can do and how much feedback, both positive and negative, it can receive. By offering world-class customer experiences, it can boost businesses to new heights and maximize profits. To speak to Nik and to get a further insight into the importance of customer service, he can reached via text at 917-905-2340.

