

TL;DR:
Most shoppers arrive with questions. Is this the right size? Will this match my skin tone? What’s the difference between these models? The faster you can guide them, the faster they decide.
As CX teams take on a bigger role in driving revenue, these moments of hesitation are now some of the most important parts of the buying journey.
That’s why more brands are leaning on conversational AI to support these high-intent questions and remove the friction that slows shoppers down. The impact speaks for itself. Brands can expect higher AOV, stronger chat conversion rates, and smoother paths to purchase, all without adding extra work to your team.
Below, we’re sharing real use cases from 11 ecommerce brands across beauty, apparel, home, body care, and more, along with the exact results they saw after introducing guided shopping experiences.
When you’re shopping for shoes similar to an old but discontinued favorite, every detail counts, down to the color of the bottom of the shoe. But legacy brands with large catalogs can be overwhelming to browse.
For shoppers, it’s a double-edged sword: they want to feel confident that they checked your entire collection, but they also don’t want to spend time looking for it.
How Shopping Assistant helps:
Shopping Assistant accelerates the process, turning hazy details into clear, friendly guidance.
It describes shoe details, from colorways to logo placement, compares products side by side, and recommends the best option based on the shopper’s preferences and conditions.
The result is shoppers who feel satisfied and more connected with your brand.

Results:
Big events call for great outfits, but putting one together online isn’t always easy. With thousands of options to scroll through, shoppers often want a bit of styling direction.
How Shopping Assistant helps:
Shoppers get to chat with a virtual stylist who recommends full outfits based on the occasion, suggests accessories to complete the look, and removes the guesswork of pairing pieces together.
The result is a fun, confidence-building shopping experience that feels like getting advice from a stylist who actually understands their plans.

Results:
Shade matching is hard enough in-store, but doing it online can feel impossible. Plus, when a longtime favorite gets discontinued, shoppers are left guessing which new shade will come closest. That uncertainty often leads to hesitation, abandoned carts, or ordering multiple shades “just in case.”
How Shopping Assistant helps:
Shoppers find their perfect match without any of the guesswork. The assistant asks a few quick questions, recommends the closest shade or formula, and offers smart alternatives when a product is unavailable.
The experience feels like chatting with a knowledgeable beauty advisor — someone who makes the decision easy and leaves shoppers feeling confident in what they’re buying.
Katia Komar, Sr. Manager of Ecommerce and Customer Service Operations at bareMinerals UK says, “What impressed me the most is the AI’s ability to upsell with a conversational tone that feels genuinely helpful and doesn't sound too pushy or transactional. It sounds remarkably human, identifying correct follow-up questions to determine the correct product recommendation, resulting in improved AOV. It’s exactly how I train our human agents and BPO partners.”

Results:
When shoppers are buying gifts, especially for someone else, they often know who they’re shopping for but not what to buy. A vague product name or a half-remembered scent can quickly make the experience feel overwhelming without someone to guide them.
How Shopping Assistant helps:
Thoughtful guidance goes a long way. By asking clarifying questions and recognizing likely mix-ups, Shopping Assistant helps shoppers figure out what the recipient was probably referring to, then recommends the right product along with complementary gift options that make the choice feel intentional.
It brings the reassurance of an in-store associate to the online experience, helping shoppers move forward with confidence.

Results:
Finding the right bra size online is notoriously tricky. Shoppers often second-guess their band or cup size, and even small uncertainties can lead to returns — or abandoning the purchase altogether.
Many customers just want someone to walk them through what a proper fit should actually feel like.
How Shopping Assistant helps:
Searching for products is no longer a time-consuming process. Shopping Assistant detects a shopper’s search terms and sends relevant products in chat. Like an in-store associate, it uses context to deliver what shoppers are looking for, so they can skip the search and head right to checkout.

Results:
For shoppers buying personalized jewelry, the details directly affect the final result. That’s why customization questions come up constantly, and why uncertainty can quickly stall the path to purchase.
How Shopping Assistant helps:
Shopping Assistant asks about the shopper’s style preferences and customization needs, then recommends the right product and options so they can feel confident the final piece is exactly their style. The experience feels quick, helpful, and designed to guide shoppers toward a high investment purchase.

Results:
Decorating a home is personal, and shoppers often want reassurance that a new piece will blend with what they already own. Questions about color palettes, textures, and proportions come up constantly. And without guidance, it’s easy for shoppers to feel unsure about hitting “add to cart.”
How Shopping Assistant helps:
Giving shoppers personalized styling support helps them visualize how pieces will work in their home.
Shoppers receive styling suggestions based on their existing space as well as recommendations on pieces that complement their color palette.
It even guides them toward a 60-minute virtual styling consultation when they need deeper help. The experience feels thoughtful and high-touch, which is why shoppers often spend more once they feel confident in their choices.

Results:
When shoppers discover a new drink mix, they’re bound to have questions before committing. How strong will it taste? How much should they use? Will it work with their preferred drink or routine? Uncertainty at this stage can stall the purchase or lead to disappointment later.
How Shopping Assistant helps:
Clear, friendly guidance in chat helps shoppers understand exactly how to use the product. Shopping Assistant answers questions about serving size, flavor strength, and pairing options, and suggests the best way to prepare the mix based on the shopper’s preferences.

Results:
Shopping for health supplements can feel confusing fast. Customers often have questions about which formulas fit their age, health goals, or daily routine. Without clear guidance, most will hesitate or pick the wrong product.
How Shopping Assistant helps:
Shopping Assistant detects hesitation when shoppers linger on a search results page. It proactively asks a few clarifying questions, narrows down product options, and points shoppers to the best product or bundle for their needs.
The entire experience feels supportive and gives shoppers confidence they’ve picked the right option.

Results:
Shopping for kids’ furniture comes with a lot of “Is this the right one?” moments. Parents want something safe, sturdy, and sized correctly for their child’s age. With so many options, it’s easy to feel unsure about what will actually work in their space.
How Shopping Assistant helps:
Shopping Assistant guides parents toward the best fit right away. It asks about their child’s age, room layout, and safety considerations, then recommends the most appropriate bed or furniture setup. The experience feels like chatting with a knowledgeable salesperson who understands what families actually need as kids grow.

Results:
Even something as simple as choosing a toothbrush can feel complicated when multiple models come with different speeds, materials, and features. Shoppers want to understand what matters so they can pick the one that fits their routine and budget.
How Shopping Assistant helps:
Choosing between toothbrush models shouldn’t feel like decoding tech specs. When shoppers can see the key differences in plain language, including what’s unique, how each model works, and who it’s best for, they can make a decision with ease.
Suddenly, the whole process feels simple instead of overwhelming.

Results:
Across all 11 brands, one theme is clear. When shoppers get the guidance they need at the right moment, they convert more confidently and often spend more.
Here’s what stands out:
What this means for you:
Look closely at your most common pre-purchase questions. Anywhere shoppers hesitate from fit, shade, technical specs, styling, bundles is a place where Shopping Assistant can step in, boost confidence, and unlock more sales.
If you notice the same patterns in your own store, such as shoppers hesitating over sizing, shade matching, product comparisons, or technical details, guided shopping can make an immediate impact. These moments are often your biggest opportunities to increase revenue and improve the buying experience.
Many of the brands in this post started by identifying their most common pre-purchase questions and letting AI handle them at scale. You can do the same.
If you want to boost conversions, lift AOV, and create a smoother path to purchase, now is a great time to explore guided shopping for your team.
Book a demo or activate Shopping Assistant to get started.
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TL;DR:
Rising customer expectations, shoppers willing to pay a premium for convenience, and a growing lack of trust in social media channels to make purchase decisions are making it more challenging to turn a profit.
In this emerging era, AI’s role is becoming not only more pronounced, but a necessity for brands who want to stay ahead. Tools like Gorgias Shopping Assistant can help drive measurable revenue while reducing support costs.
For example, a brand that specializes in premium outdoor apparel implemented Shopping Assistant and saw a 2.25% uplift in GMV and 29% uplift in average order volume (AOV).
But how, among competing priorities and expenses, do you convince leadership to implement it? We’ll show you.
Shoppers want on-demand help in real time that’s personalized across devices.
Shopping Assistant recalls a shopper’s browsing history, like what they have clicked, viewed, and added to their cart. This allows it to make more relevant suggestions that feel personal to each customer.
The AI ecommerce tools market was valued at $7.25 billion in 2024 and is expected to reach $21.55 billion by 2030.
Your competitors are using conversational AI to support, sell, and retain. Shopping Assistant satisfies that need, providing upsells and recommendations rooted in real shopper behavior.
Conversational AI has real revenue implications, impacting customer retention, average order value (AOV), conversion rates, and gross market value (GMV).
For example, a leading nutrition brand saw a GMV uplift of over 1%, an increase in AOV of over 16%, and a chat conversion rate of over 15% after implementing Shopping Assistant.
Overall, Shopping Assistant drives higher engagement and more revenue per visitor, sometimes surpassing 50% and 20%, respectively.

Shopping Assistant engages, personalizes, recommends, and converts. It provides proactive recommendations, smart upsells, dynamic discounts, and is highly personalized, all helping to guide shoppers to checkout.
After implementing Shopping Assistant, leading ecommerce brands saw real results:
Industry |
Primary Use Case |
GMV Uplift (%) |
AOV Uplift (%) |
Chat CVR (%) |
|---|---|---|---|---|
Home & interior decor 🖼️ |
Help shoppers coordinate furniture with existing pieces and color schemes. |
+1.17 |
+97.15 |
10.30 |
Outdoor apparel 🎿 |
In-depth explanations of technical features and confidence when purchasing premium, performance-driven products. |
+2.25 |
+29.41 |
6.88 |
Nutrition 🍎 |
Personalized guidance on supplement selection based on age, goals, and optimal timing. |
+1.09 |
+16.40 |
15.15 |
Health & wellness 💊 |
Comparing similar products and understanding functional differences to choose the best option. |
+1.08 |
+11.27 |
8.55 |
Home furnishings 🛋️ |
Help choose furniture sizes and styles appropriate for children and safety needs. |
+12.26 |
+10.19 |
1.12 |
Stuffed toys 🧸 |
Clear care instructions and support finding replacements after accidental product damage. |
+4.43 |
+9.87 |
3.62 |
Face & body care 💆♀️ |
Assistance finding the correct shade online, especially when previously purchased products are no longer available. |
+6.55 |
+1.02 |
5.29 |
Shopping Assistant drives uplift in chat conversion rate and makes successful upsell recommendations.
“It’s been awesome to see Shopping Assistant guide customers through our technical product range without any human input. It’s a much smoother journey for the shopper,” says Nathan Larner, Customer Experience Advisor for Arc’teryx.
For Arc’teryx, that smoother customer journey translated into sales. The brand saw a 75% increase in conversion rate (from 4% to 7%) and 3.7% of overall revenue influenced by Shopping Assistant.

Because it follows shoppers’ live journey during each session on your website, Shopping Assistant catches shoppers in the moment. It answers questions or concerns that might normally halt a purchase, gets strategic with discounting (based on rules you set), and upsells.
The overall ROI can be significant. For example, bareMinerals saw an 8.83x return on investment.
"The real-time Shopify integration was essential as we needed to ensure that product recommendations were relevant and displayed accurate inventory,” says Katia Komar, Sr. Manager of Ecommerce and Customer Service Operations, UK at bareMinerals.
“Avoiding customer frustration from out-of-stock recommendations was non-negotiable, especially in beauty, where shade availability is crucial to customer trust and satisfaction. This approach has led to increased CSAT on AI converted tickets."

Shopping Assistant can impact CSAT scores, response times, resolution rates, AOV, and GMV.
For Caitlyn Minimalist, those metrics were an 11.3% uplift in AOV, an 18% click through rate for product recommendations, and a 50% sales lift versus human-only chats.
"Shopping Assistant has become an intuitive extension of our team, offering product guidance that feels personal and intentional,” says Anthony Ponce, its Head of Customer Experience.

Support agents have limited time to assist customers as it is, so taking advantage of sales opportunities can be difficult. Shopping Assistant takes over that role, removing obstacles for purchase or clearing up the right choice among a stacked product catalog.
With a product that’s not yet mainstream in the US, TUSHY leverages Shopping Assistant for product education and clarification.
"Shopping Assistant has been a game-changer for our team, especially with the launch of our latest bidet models,” says Ren Fuller-Wasserman, Sr. Director of Customer Experience at TUSHY.
“Expanding our product catalog has given customers more choices than ever, which can overwhelm first-time buyers. Now, they’re increasingly looking to us for guidance on finding the right fit for their home and personal hygiene needs.”
The bidet brand saw 13x return on investment after implementation, a 15% increase in chat conversion rate, and a 2x higher conversion rate for AI conversations versus human ones.

Customer support metrics include:
Revenue metrics to track include:
Shopping Assistant connects to your ecommerce platform (like Shopify), and streamlines information between your helpdesk and order data. It’s also trained on your catalog and support history.
Allow your agents to focus on support and sell more by tackling questions that are getting in the way of sales.
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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:
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:
The start of a new year is the perfect time to give your help center the refresh it deserves. For many ecommerce brands, the help center is one of the most underused support tools—yet it's also one of the most powerful. 88% of customers already search your website for some kind of knowledge base or FAQ.
Customers expect fast answers, and a well-designed, updated help center can meet their needs while taking some weight off your support team. We’ll walk you through why refreshing matters and how to do it.
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90% of consumers worldwide consider issue resolution their top priority for customer service. A robust help center gives you the tools to meet this expectation, delivering fast and reliable solutions that simplify your customers’ lives.
A well-designed help center benefits both your customers and your team. For customers, it lets them solve problems quickly and independently. Instead of waiting for an email response or queuing for live chat, a help center empowers them to find answers on their own terms 24/7.
For your team, a refreshed help center is transformative, too. Here’s what a help center update can achieve:
In short, refreshing your help center will improve customer experience and boost efficiency across your entire customer service strategy. It’s a win-win for everyone.
Refreshing your help center doesn’t have to be overwhelming. By breaking the process into clear, actionable steps, you can transform your help center into a powerful self-service tool that delights customers and supports your team.
Here are four key steps to guide your refresh.
Before making any major changes, you need to understand where your help center currently stands. A thorough audit will help you identify areas for improvement and ensure you make targeted updates.
Here's how to start:
Dive into your help center metrics to spot underperforming content. Look at article views, time-on-page, and bounce rates. Low engagement might mean the content is unclear, irrelevant, or hard to find.
With a customer experience platform like Gorgias, you can view the performance of each article:

Customer feedback is invaluable. Use surveys or follow-up emails to ask customers what information they had trouble finding. Their responses can highlight blind spots in your help center.
At the end of each help center article, include a simple question like, "Was this content helpful?" Use the feedback to pinpoint which articles are effective and which may need improvement.

Put yourself in your customers’ shoes. Try searching for answers to common questions. Is the layout intuitive? Are the search results helpful? A smooth user experience is key to a successful help center.
Check if your articles are outdated or missing important updates, like new product features or policy changes.
Read more: How to create and optimize a customer knowledge base
Fresh, well-organized content is the backbone of a great help center. Customers rely on clear and accurate information, so investing in your content can transform your help center into a powerful self-service tool.
Here’s how to refresh your content and make it shine:
Regularly analyze support tickets to identify common and emerging questions. Integrate these into your knowledge base to address customer needs proactively and reduce incoming tickets.
Text alone isn’t always enough. Use images, GIFs, and videos to break down complex topics and make instructions easier to follow. For example, a quick explainer video can save customers time and eliminate confusion.
Princess Polly’s customer help center exemplifies what a great help center should look like. Its visually appealing design ensures that customers can quickly navigate to the information they need. Whether they’re looking for help with shipping, payments, returns, or any other issue, the intuitive layout makes the process simple and stress-free.

Gorgias lets you customize fonts, logos, and headers for your Help Center without any coding. If you want more customization, you can dip into HTML and CSS to tailor specific elements.
Ensure your content reflects your brand voice while staying approachable and customer-friendly. Consistency builds trust and reinforces your brand identity.
Need help finding your brand voice? Read AI Tone of Voice: Tips for On-Brand Customer Communication for guidance.
Review older content for inaccuracies or missing information, such as policy changes or new product details.
Use bullet points, short paragraphs, and clear headings to make articles easy to scan. Most customers skim for quick answers—design your content to match their behavior.
Even the most well-crafted help center is ineffective if customers can’t locate it. Ensuring visibility across all customer touchpoints is key to driving engagement and making self-service the first stop for support. Here’s how to do it:
Make your help center easily accessible by placing links in strategic locations, such as your website’s header, footer, and main navigation menu. Include links in transactional emails, like order confirmations, tracking updates, or shipping updates, where customers often have questions.
Optimize your help center articles with keywords your customers are likely to search for. Use clear, concise titles, meta descriptions, and headings to boost search engine visibility and help customers find answers directly from Google.
Use tools like automated chat and automated email responses to proactively surface relevant help center articles. For instance, when customers type a question in a chatbox, suggest related articles before escalating to a support agent.
Read more: Offer more self-serve options with Flows: 10 use cases & best practices
Don’t wait for customers to stumble upon your help center—promote it! Highlight it in onboarding emails, social media posts, and banners on your site.

Jonas Paul Eyewear ensures their help center is easy to access by prominently linking it in the website’s footer under the “Quick Links” section. The thoughtful placement ensures customers can quickly navigate to the help center from any page, making it a convenient resource for addressing their questions or concerns.
Read more: Boost your Help Center's visibility: Proven strategies to increase article views
Your help center isn’t just for customers—it will also level up your AI-driven support strategy. By structuring your knowledge base effectively, you enable AI tools to deliver accurate, reliable, and consistent answers to customer queries.
Here’s how to make it work:
Ensure your help center articles cover a wide range of customer questions in detail. This makes it easier for AI tools to pull relevant information and respond accurately.
Organize your content with clear headings, bullet points, and simple language. Well-structured articles are easier for AI to parse and interpret.
Use uniform terminology across articles to prevent confusion and ensure AI tools can quickly identify relevant data.
Keep your knowledge base fresh by adding new FAQs, updating outdated content, and incorporating customer feedback. Up-to-date information ensures AI tools provide answers that align with your latest products, policies, and services.
Periodically review how well your AI tools are using your help center content to address customer needs. Identify gaps in information and fine-tune articles as needed.
Dr. Bronner’s built their help center to power AI Agent, a conversational support assistant that answers both transactional and personalized customer inquiries in the same style as a human agent. Making this change helps the brand save $100,000 a year and decrease their resolution time by 74%.

💡Pro Tip: Transform your help center into an AI training powerhouse with Gorgias’s help center AI optimization guide. This guide offers actionable tips for making your knowledge base AI-ready.

By using your help center to power AI tools, you’ll improve customer self-service options and lighten the load on your support team. AI-enhanced support delivers faster resolutions, higher customer satisfaction, and a scalable approach to customer service.
Refreshing your help center isn’t just about improving customer experience—it’s a game-changer for your entire support strategy. With tools like Gorgias’s Help Center, you can empower customers to self-serve while equipping your team with the resources they need to excel.
In 2025, make your help center the cornerstone of your support operations—and watch the results speak for themselves.
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TL;DR:
This year, 71% of customer experience (CX) leaders are using AI and automation to handle the holiday shopping season. These tools, including AI agents and email autoresponders, speed up tasks like responding to customers and updating orders.
But answering tickets isn't enough. Responses must also be high-quality, whether from humans or AI. And while customer satisfaction (CSAT) is the standard measure of how successful these interactions are, they have major limits.
CSAT scores don’t tell the full story about whether agents were helpful or if they used on-brand language. These gray areas in quality lead to missed sales, higher return rates, and frustrated customers during peak periods.
AI quality assurance (QA) is changing that. In this article, we’ll see what QA looks like today, how AI can simplify the process, and how CX teams can use tools like Auto QA to improve quality across all conversations.
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Today, QA in customer support is a largely manual responsibility. Customer conversations are reviewed by CX team leads to ensure customer satisfaction and identify areas for agent coaching. Team leads evaluate agent responses against a checklist of best practices, including the proper use of language, product knowledge, consistency, and helpfulness.
However, reviewing tickets takes a long time.
QA is important, but it's hard to prioritize when customers are actively waiting for help with refunds, urgent order edits, or negative reviews. And when CX teams are under-resourced and short-staffed, it’s easy to put QA on the back burner.
What’s more, as AI plays a bigger role in responding to customers, quality assurance must evolve to ensure the quality of AI-generated responses, not just human responses.
Over time, the lack of QA in CX can hold back support teams for three reasons:
AI-powered quality assurance (QA) uses AI to automate the process of reviewing customer interactions for resolution completeness, communication, language proficiency, and more.
Instead of team leads spending hours manually sifting through tickets, AI takes over and evaluates how well tickets were resolved by agents.
Shifting this traditionally manual work to an automated process pulls teams out of the weeds and into more beneficial work like speaking to customers and upselling.

With AI QA, routine ticket reviews are not just an optional part of your customer service strategy, they become a permanent part of it. The road to greater customer trust, resolution times, and stronger product knowledge becomes easier.
Read more: Why your strategy needs customer service quality assurance
Manual QA is like trying to review a handful of tickets during an incoming flood of new customer requests. Team leads can only focus on a small sample, leaving most interactions unchecked. Without complete visibility, creating a standard across all interactions is challenging.
Now, switch over to AI QA. You don’t have to choose between QA duty or answering tickets—QA checks are automatically done. You’ll still need to monitor AI’s performance, but now there’s more time to focus on creating strategies that improve the customer experience.
Here’s how AI QA and manual QA measure up to each other:
|
Feature |
AI QA |
Manual QA |
|---|---|---|
|
Number of Tickets Reviewed |
All tickets are reviewed automatically. |
Only a small sample of tickets can be reviewed. |
|
Speed of Reviews |
Reviews are completed instantly after responses. |
Reviews are time-consuming and delayed. |
|
Consistency |
Feedback is consistent and unbiased across all tickets. |
Feedback varies depending on the reviewer. |
|
Scalability |
Scales, regardless of ticket volume. |
Struggles to keep up with high ticket volumes. |
|
Agent Feedback |
Provides instant, actionable feedback for every resolved ticket. |
Feedback is delayed and limited to a few cases. |
|
Leader Advantage |
Frees up leaders to train the team and improve workflows. |
Disadvantageous, as leaders spend most time manually reviewing tickets. |
AI quality assurance helps CX leaders move beyond manual reviews by offering fast, thorough insights into performance and customer needs. Here are seven key benefits it brings to your team.
AI QA reviews every ticket, giving CX leaders a complete view of agent performance and customer trends. Nothing slips through the cracks, so you can act on real data each and every single time.
What the team wins: Key areas to focus on to improve the customer experience.
What the customer wins: A consistent support experience where their concerns are fully addressed.
Only a third of customers highly trust businesses, and without QA checks in place, that trust only deteriorates.
AI QA feedback can highlight confusing policies or common product issues that lead to unhappy customers. With instant feedback, teams can quickly make changes and create better, consistent customer experiences.
What the team wins: Faster fixes for recurring issues.
What the customer wins: A smoother, frustration-free experience.
Agents can receive feedback that instantly highlights gaps in workflows or unclear escalation steps. This is an efficient way to resolve issues within the wider team before they become more significant problems.
What the team wins: Process issues are solved quickly.
What the customer wins: Faster resolutions with little to no delays.
AI QA evaluates both Gorgias AI Agent and human agent interactions using the same criteria. This creates a level playing field and ensures all customer interactions meet the same quality standards.
What the team wins: Fair evaluations for both AI and human responses.
What the customer wins: High-quality support, no matter who handles the ticket.
With less time spent on manual reviews, leaders can dedicate more energy to team development. Training sessions guided by AI insights help agents improve quickly and ensure the team delivers support that aligns with protocols.
What the team wins: More focused skill-building based on data.
What the customer wins: Clearer and more accurate support.
AI QA is helpful for showing agents which areas they need more training on, whether it's being better about using brand voice or polishing up on product knowledge. This leads to better support processes and stronger product understanding across the team.
What the team wins: Better support tactics and product expertise.
What the customer wins: Faster resolutions due to knowledgeable agents.
Since all tickets are reviewed, teams can feel confident they’re delivering high-quality support on a regular basis. Customers get clear, helpful answers, while agents gain insights from every ticket with AI feedback.
What the team wins: Consistent support performance.
What the customer wins: Reliable support they can trust.
AI QA analyzes tickets using predefined categories to evaluate how complete and helpful agent responses are. Let’s take a closer look at how it maintains accurate ticket reviews with an AI QA tool like Gorgias’s Auto QA.
Auto QA evaluates tickets based on three key areas: Resolution Completeness, Communication, and Language Proficiency.
For Resolution Completeness, it checks if all customer concerns were fully addressed. For example, if an agent resolves only one of two issues raised, the ticket is marked incomplete. Tickets where customers resolve issues on their own or don’t respond to follow-ups can still be graded as complete if handled appropriately.
Communication quality is scored on a scale of 1 to 5, assessing clarity, professionalism, and tone. Agents earn higher scores when they provide clear solutions and remain positive throughout the interaction.
Finally, Language Proficiency evaluates whether an agent displayed high proficiency in the language of the conversation. The score considers how well spelling, grammar, and syntax were employed.

Auto QA isn’t set in stone. Team leads can expand on AI-generated feedback by adding their comments. For example, if a resolution is graded as ‘Incomplete,’ a team lead can explain why and provide additional context. This helps clarify the evaluation for the agent and also helps the AI model improve over time.
Ready to bring the benefits of AI QA to your team? Here’s how to get started with Auto QA:
AI QA isn’t just about automating ticket reviews — it empowers CX leaders to focus on what truly matters: training and improving processes.
Leave spot-checking and inconsistent application of policies and brand voice in the past. As a built-in feature of Gorgias Automate, Auto QA makes high-quality customer interactions your brand’s standard.
Book a demo now.
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TL;DR:
Nailing customer support during BFCM is all about staying ahead of the game and making smart moves—fast.
But the real key to success lies in what you do when the rush is over. Treating BFCM as a learning opportunity allows you to refine your customer experience (CX) and set yourself up for an even better performance next year.
Without a plan for what to do after Black Friday, it’s easy to repeat mistakes or overlook key trends that could make all the difference next year.
In this article, we’ll share a simple framework to help you evaluate your BFCM performance and turn insights into actionable steps for long-term CX improvement.
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It’s best to reflect on key areas like customer service, tech performance, customer behavior, and operations right after BFCM versus waiting until late next year.
By taking a closer look now, you can spot what worked, fix what didn’t, and start applying those insights to other big sales events throughout the year—not just BFCM.
A little effort now = a lot of payoff later!
By analyzing key metrics, you can identify what worked, where your team excelled, and what areas need improvement to better prepare for future busy seasons. Key metrics include:
Tools like Gorgias’s Ticket Insights can reveal which issues—like discounts, shipping policies, or damaged orders—dominated your support tickets.

For a more comprehensive view, Gorgias’s Support Performance dashboard shows how customer service influenced sales, including tickets converted, conversion ratios, and total revenue. These insights are invaluable for understanding the connection between support efficiency and revenue growth.

Brands like Obvi, a leading supplement company, have leveraged Gorgias to enhance their support strategies.
Obvi serves a large number of shoppers seeking pre-sales guidance to choose the right supplements. By using Gorgias’s Flows and Article Recommendations, they provide instant, automated answers to frequently asked questions directly within Chat.
Here’s how it works:

To fine-tune their approach, Obvi uses data from their tickets to identify recurring customer questions. By analyzing the gaps between their initial FAQs and real customer inquiries, they adjusted their automated responses to better meet customer needs.

“We thought we knew what our FAQs were, but data from Gorgias was incredibly insightful to understand which FAQs to automate. That's one reason it's really valuable to have our Helpdesk tickets and automation features in one tool.”
—Ron Shah, CEO and Co-founder at Obvi
While marketing efforts often steal the spotlight, savvy brands know that backend systems are the unsung heroes of Black Friday and Cyber Monday.
Start by auditing critical areas such as platform downtime, checkout errors, or slow response times. These issues not only frustrate shoppers but can also lead to lost revenue and customer loyalty during your busiest shopping days of the year.
Next, evaluate how well your tools were able to manage peak volumes. Did your helpdesk, CRM, and ecommerce platforms work seamlessly together, or were there gaps in your integrations?
If switching between platforms slowed your team down or caused data silos, consider streamlining your tech stack with an all-in-one CX solution.
For example, conversational AI platforms like Gorgias enable CX teams to consolidate support, sales, and automation into a single tool. Gorgias combines Helpdesk and AI Agent to resolve customer issues efficiently, while Convert supports upselling and increasing customer lifetime value.
A streamlined, integrated platform not only boosts efficiency but also helps your CX team focus on what matters most: delivering exceptional customer experiences.
Start by reviewing product demand, buying patterns, and cart-building behaviors. Were there any unexpected customer needs or shifts in preferences? Identifying these trends can help you refine your inventory planning, marketing strategies, and product offerings.
For example, here’s a detailed breakdown of what to look for:
Use these insights to adjust inventory planning for future campaigns. Ensure you have sufficient stock of trending products and create promotional bundles for underperforming items.
Tailor future cart-building promotions to encourage higher Average Order Value (AOV). For instance, highlight complementary products or offer discounts on bundles.
Incorporate these suggestions into your product development or cross-sell strategies. Highlight related products in future campaigns to meet these emerging needs.
If you have an FAQ page or Help Center, evaluate how well it performed. Did customers find the information they needed, or did they still open tickets for common questions?
Metrics like Article Views, Number of Searches, and Click-Through Rates can show how effectively your self-service resources meet customer needs.
If customers contact support for information already in your Help Center, it may indicate unclear articles or poor visibility of resources. This means you should rewrite unclear articles, optimize search terms, and ensure Help Center links are prominently displayed across your website and emails.
BFCM is a stress test for your operations, and reflecting on how well your systems handled the surge can help you uncover critical areas for improvement.
Start by reviewing your staffing during peak periods. Did your customer service and warehouse teams feel overwhelmed, or were they adequately supported?
Questions to Ask:
Next Steps:
Preparing your team with a more flexible schedule and extra resources for high-demand areas can make all the difference.
If order fulfillment workflows slowed down or became error-prone, it may be time to optimize your processes.
Questions to Ask:
Next Steps:
Stockouts or overstock situations during BFCM can directly impact both sales and customer satisfaction.
Questions to Ask:
Next Steps:
Operational challenges often have a ripple effect on customer experience. By reflecting on these areas—staffing, fulfillment, and inventory—you can identify actionable improvements that streamline operations and create a smoother experience for both your team and your customers.
Once you've reviewed the key areas of your BFCM performance, the next step is turning those insights into actionable strategies. Here’s how to build a CX improvement plan that sets you up for long-term success.
Start by centralizing everything you’ve uncovered from your retro.
Use collaborative tools like Notion, Google Docs, or Trello to organize insights across customer service, tech performance, and operations.
And don’t just focus on observations—highlight actionable takeaways. For example, instead of noting “high contact rates,” document the underlying causes, like gaps in FAQs or unclear return policies.
If you’re feeling overwhelmed by the volume of data, let AI do the heavy lifting. Use prompts like these to quickly spot patterns:
AI tools can save you time and ensure nothing slips through the cracks as you plan your next steps.
Analyzing challenges in your CX processes can reveal quick wins and long-term improvements. Here are a few common support pain points and how to address them:
A surge in customer inquiries often signals that self-service options aren’t meeting expectations.
Solution: Add or update tools like chat widgets, Help Centers, and post-purchase emails to proactively answer common questions.
This usually points to workflow inefficiencies or a lack of team bandwidth.
Solution: Use automation to prioritize urgent tickets, deflect repetitive inquiries, and ensure smoother workflows.
Frustration with slow resolutions or insufficient empathy often leads to poor satisfaction ratings.
Solution: Invest in empathy training and implement faster resolution strategies, like automating FAQs or integrating sentiment detection tools to flag unhappy customers.
While tools like Gorgias’s AI Agent can streamline support, improper setup can lead to automation loops that frustrate customers.
Solution: Define rules for when AI should escalate to a human, feed it more comprehensive data (like updated Help Center articles), and set boundaries for topics it shouldn’t handle.

For example, even with the efficiency provided by their Helpdesk, Obvi found Black Friday and Cyber Monday to be a hectic and stressful period for their small customer support team—just one full-time agent and half of another team member’s time.
The influx of customer inquiries made it difficult to focus on more complex tickets that could save sales from unhappy customers or convert inquiries into purchases. Instead, their team was bogged down by thousands of repetitive questions, like “Where is my order?”
Automating answers to repetitive questions gave the Obvi team the room to focus on personalized and revenue-driving customer interactions, like engaging with their community of 75,000 women.
“Instantly, our CX team had time to prioritize important matters, like being active in our community of 75,000 women instead of sitting answering emails.”
—Ron Shah, CEO and Co-founder at Obvi
The extra bandwidth helped Obvi drive over 3x the purchases from support conversations compared to previous years. AI Agent also enabled their team to reach inbox zero by 6 pm—during Black Friday week!
By automating 27% of their inquiries, they not only improved their response times but also handled over 150 tickets daily with just 1.5 agents, driving 10x more sales during BFCM.
Even the smallest changes can deliver a big impact.
For example, update FAQs based on ticket trends or refine chat flows to reduce repetitive questions. Consolidating your CX tools into an omnichannel helpdesk like Gorgias can also reduce agent workload while delivering consistent customer experiences.
Repetitive inquiries—like shipping updates, return questions, or product FAQs—don’t need to consume your team’s time. Automating these workflows can significantly lighten your team’s load while keeping response times quick.
Gorgias users, for example, can automate up to 60% of support tickets with conversational AI tools like AI Agent, enabling teams to focus on higher-value interactions.
Quick wins aren’t just about streamlining support—they can also drive measurable results.
For instance, Pajar, a footwear brand, leverages AI Agent to handle common inquiries in English and French. While this is a feature they use year-round, it’s handy during holiday shopping seasons when support teams are under pressure to respond quickly.

This freed up their small team of five agents to focus on complex tickets, achieving impressive results:
With tools like AI Agent and Sentiment Detection, you can automate prioritization for tickets—such as flagging urgent issues or unhappy customers—while still maintaining a personal touch.
Peak season often highlights gaps in both team training and CX tools. Addressing these areas not only improves your team’s ability to handle high-pressure situations but also fosters a stronger customer-first mindset across your organization.
Start by leveraging the feedback you’ve collected. Your team has so much data they can review between channels like email, SMS, chat, and social media—both compliments and complaints. You need to be willing to listen to every customer’s needs.
At Love Wellness, customer feedback is treated as a daily priority.
The team has a dedicated Slack channel for feedback, where team members regularly drop insights from all touchpoints. This collaborative approach helps them get familiar with recurring themes, dissect customer needs, and work together on solutions.

The Love Wellness team recommends scheduling recurring feedback share sessions with Product or Website teams—or even inviting those teams into Gorgias to create dedicated views for feedback categories like product improvements or website issues.
Beyond tools and processes, training is crucial. Their team also emphasizes the importance of fostering a customer-first mindset at all levels:
Customer service is one of the main ways they build trust with customers, especially in the personal care and women’s health niche. That’s why the Love Wellness team created an immersive customer experience training program that involves everyone—from the company's president to its office manager.
This holistic approach ensures that every team member, regardless of their role, understands the company’s purpose and how their actions contribute to a seamless customer experience.
Your customer support team isn’t just there to clear tickets—it’s a key driver of revenue, retention, and customer lifetime value (CLV). Yet, too many teams measure success based solely on metrics like response and resolution times. While these are important, they’re only part of the story.
As Zoe Kahn, Manager of Customer Experience and Retention at Chomps, explains:
“Aiming for overly broad goals of ‘surprising and delighting’ customers without a real understanding of how support impacts the whole customer journey or business ROI is a common pitfall. Customer experience, largely driven by the support team, touches every stage of the journey—from pre-sales to post-sales—and directly influences more sales and loyalty.”
To demonstrate CX’s value, it’s crucial to track metrics that reflect your team’s true impact on the business. For example:
By focusing on these KPIs, you’ll incentivize your support team to go beyond answering questions and actively contribute to business goals. This could include suggesting products during conversations, encouraging happy customers to leave reviews, or proactively addressing issues that lead to churn.

Teams using Gorgias have even greater opportunities to prove ROI through tools like the Revenue Statistics dashboard, which tracks metrics like tickets converted into sales, conversion rates, and total revenue driven by support interactions.
“Without knowing how much money your customer experience (CX) drives, you’ll never fully understand your impact on the business or have the data needed to advocate for more resources from leadership.”
—Zoe Kahn, Chomps
The best way to close out your post-BFCM retro is by setting clear, measurable goals for next year. Use this year’s insights to create actionable targets that enhance your customer support and CX strategy:
Tools like Gorgias make it easier to turn these goals into reality. With powerful automation, integrated insights, and scalable support solutions, you can transform this year’s lessons into meaningful, lasting improvements.
Start planning now to make next year’s BFCM your smoothest—and most successful—yet!
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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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