

TL;DR:
Your AI sounds like a robot, and your customers can tell.
Sure, the answer is right, but something feels off. The tone of voice is stiff. The phrases are predictable and generic. At most, it sounds copy-pasted. This may not be a big deal from your side of support. In reality, it’s costing you more than you think.
Recent data shows that 45% of U.S. adults find customer service chatbots unfavorable, up from 43% in 2022. As awareness of chatbots has increased, so have negative opinions of them. Only 19% of people say chatbots are helpful or beneficial in addressing their queries. The gap isn't just about capability. It's about trust. When AI sounds impersonal, customers disengage or leave frustrated.
Luckily, you don't need to choose between automation and the human touch.
In this guide, we'll show you six practical ways to train your AI to sound natural, build trust, and deliver the kind of support your customers actually like.
The fastest way to make your AI sound more human is to teach it to sound like you. AI is only as good as the input you give it, so the more detailed your brand voice training, the more natural and on-brand your responses will be.
Start by building a brand voice guide. It doesn't need to be complicated, but it should clearly define how your brand communicates with customers. At minimum, include:
Think of your AI as a character. Samantha Gagliardi, Associate Director of Customer Experience at Rhoback, described their approach as building an AI persona:
"I kind of treat it like breaking down an actor. I used to sing and perform for a living — how would I break down the character of Rhoback? How does Rhoback speak? What age are they? What makes the most sense?"
✅ Create a brand voice guide with tone, style, formality, and example phrases.
Humans associate short pauses with thinking, so when your AI responds too quickly, it instantly feels unnatural.
Adding small delays helps your AI feel more like a real teammate.
Where to add response delays:
Even a one- to two-second pause can make a big difference in a robotic or human-sounding AI.
✅ Add instructions in your AI’s knowledge base to include short response delays during key moments.
Generic phrases make your AI sound like... well, AI. Customers can spot a copy-pasted response immediately — especially when it's overly formal.
That doesn't mean you need to be extremely casual. It means being true to your brand. Whether your voice is professional or conversational, the goal is the same: sound like a real person on your team.
Here's how to replace robotic phrasing with more brand-aligned responses:
|
Generic Phrase |
More Natural Alternative |
|---|---|
|
“We apologize for the inconvenience.” |
“Sorry about that, we’re working on it now.” (friendly) |
|
“Your satisfaction is our top priority.” |
“We want to make sure this works for you.” (friendly) |
|
“Please be advised…” |
“Just a quick heads up…” (friendly) |
|
“Your request has been received.” |
“Got it. Thanks for reaching out.” (friendly) |
|
“I will now review your request.” |
“Let me take a quick look.” (friendly) |
✅ Identify your five most common inquiries and give your AI a rewritten example response for each.
One of the biggest tells that a response is AI-generated? It ignores what's already happened.
When your AI doesn't reference order history or past conversations, customers are forced to repeat themselves. Repetition can lead to frustration and can quickly turn a good customer experience into a bad one.
Great AI uses context to craft replies that feel personalized and genuinely helpful.
Here's what good context looks like in AI responses:
Tools like Gorgias AI Agent automatically pull in customer and order data, so replies feel human and contextual without sacrificing speed.
✅ Add instructions that prompt your AI to reference order details and/or past conversations in its replies, so customers feel acknowledged.
Customers just want help. They don't care whether it comes from a human or AI, as long as it's the right help. But if you try to trick them, it backfires fast. AI that pretend to be human often give customers the runaround, especially when the issue is complex or emotional.
A better approach is to be transparent. Solve what you can, and hand off anything else to an agent as needed.
When to disclose that the customer is talking to AI:
For more on this topic, check out our article: Should You Tell Customers They're Talking to AI?
✅ Set clear rules for when your AI should escalate to a human and include handoff messaging that sets expectations and preserves context.
We're giving you permission to break the rules a little bit. The most human-sounding AI doesn't follow perfect grammar or structure. It reflects the messiness of real dialogue.
People don't speak in flawless sentences every time. We pause, rephrase, cut ourselves off, and throw in the occasional emoji or "uh." When AI has an unpredictable cadence, it feels more relatable and, in turn, more human.
What an imperfect AI could look like:
These imperfections give your AI a more believable voice.
✅ Add instructions for your AI that permit variation in grammar, tone, and sentence structure to mimic real human speech.
Human-sounding AI doesn’t require complex prompts or endless fine-tuning. With the right voice guidelines, small tone adjustments, and a few smart instructions, your AI can sound like a real part of your team.
Book a demo of Gorgias AI Agent and see for yourself.
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TL;DR:
You’ve chosen your AI tool and turned it on, hoping you won’t have to answer another WISMO question. But now you’re here. Why is AI going in circles? Why isn’t it answering simple questions? Why does it hand off every conversation to a human agent?
Conversational AI and chatbots thrive on proper training and data. Like any other team member on your customer support team, AI needs guidance. This includes knowledge documents, policies, brand voice guidelines, and escalation rules. So, if your AI has gone rogue, you may have skipped a step.
In this article, we’ll show you the top seven AI issues, why they happen, how to fix them, and the best practices for AI setup.
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AI can only be as accurate as the information you feed it. If your AI is confidently giving customers incorrect answers, it likely has a gap in its knowledge or a lack of guardrails.
Insufficient knowledge can cause AI to pull context from similar topics to create an answer, while the lack of guardrails gives it the green light to compose an answer, correct or not.
How to fix it:
This is one of the most frustrating customer service issues out there. Left unfixed, you risk losing 29% of customers.
If your AI is putting customers through a never-ending loop, it’s time to review your knowledge docs and escalation rules.
How to fix it:
It can be frustrating when AI can’t do the bare minimum, like automate WISMO tickets. This issue is likely due to missing knowledge or overly broad escalation rules.
How to fix it:
One in two customers still prefer talking to a human to an AI, according to Katana. Limiting them to AI-only support could risk a sale or their relationship.
The top live chat apps clearly display options to speak with AI or a human agent. If your tool doesn’t have this, refine your AI-to-human escalation rules.
How to fix it:
If your agents are asking customers to repeat themselves, you’ve already lost momentum. One of the fastest ways to break trust is by making someone explain their issue twice. This happens when AI escalates without passing the conversation history, customer profile, or even a summary of what’s already been attempted.
How to fix it:
Sure, conversational AI has near-perfect grammar, but if its tone is entirely different from your agents’, customers can be put off.
This mismatch usually comes from not settling on an official customer support tone of voice. AI might be pulling from marketing copy. Agents might be winging it. Either way, inconsistency breaks the flow.
How to fix it:
When AI is underperforming, the problem isn’t always the tool. Many teams launch AI without ever mapping out what it's actually supposed to do. So it tries to do everything (and fails), or it does nothing at all.
It’s important to remember that support automation isn’t “set it and forget it.” It needs to know its playing field and boundaries.
How to fix it:
AI should handle |
AI should escalate to a human |
|---|---|
Order tracking (“Where’s my package?”) |
Upset, frustrated, or emotional customers |
Return and refund policy questions |
Billing problems or refund exceptions |
Store hours, shipping rates, and FAQs |
Technical product or troubleshooting issues |
Simple product questions |
Complex or edge‑case product questions |
Password resets |
Multi‑part or multi‑issue requests |
Pre‑sale questions with clear, binary answers |
Anything where a wrong answer risks churn |
Once you’ve addressed the obvious issues, it’s important to build a setup that works reliably. These best practices will help your AI deliver consistently helpful support.
Start by deciding what AI should and shouldn’t handle. Let it take care of repetitive tasks like order tracking, return policies, and product questions. Anything complex or emotionally sensitive should go straight to your team.
Use examples from actual tickets and messages your team handles every day. Help center articles are a good start, but real interactions are what help AI learn how customers actually ask questions.
Create rules that tell your AI when to escalate. These might include customer frustration, low confidence in the answer, or specific phrases like “talk to a person.” The goal is to avoid infinite loops and to hand things off before the experience breaks down.
When a handoff happens, your agents should see everything the AI did. That includes the full conversation, relevant customer data, and any actions it has already attempted. This helps your team respond quickly and avoid repeating what the customer just went through.
An easy way to keep order history, customer data, and conversation history in one place is by using a conversational commerce tool like Gorgias.
A jarring shift in tone between AI and agent makes the experience feel disconnected. Align aspects such as formality, punctuation, and language style so the transition from AI to human feels natural.
Look at recent escalations each week. Identify where the AI struggled or handed off too early or too late. Use those insights to improve training, adjust boundaries, and strengthen your automation flows.
If your AI chatbot isn’t working the way you expected, it’s probably not because the technology is broken. It’s because it hasn’t been given the right rules.
When you set AI up with clear responsibilities, it becomes a powerful extension of your team.
Want to see what it looks like when AI is set up the right way?
Try Gorgias AI Agent. It’s conversational AI built with smart automation, clean escalations, and ecommerce data in its core — so your customers get faster answers and your agents stay focused.
The best in CX and ecommerce, right to your inbox

TL;DR:
Customer education has become a critical factor in converting browsers into buyers. For wellness brands like Cornbread Hemp, where customers need to understand ingredients, dosages, and benefits before making a purchase, education has a direct impact on sales. The challenge is scaling personalized education when support teams are stretched thin, especially during peak sales periods.
Katherine Goodman, Senior Director of Customer Experience, and Stacy Williams, Senior Customer Experience Manager, explain how implementing Gorgias's AI Shopping Assistant transformed their customer education strategy into a conversion powerhouse.
In our second AI in CX episode, we dive into how Cornbread achieved a 30% conversion rate during BFCM, saving their CX team over four days of manual work.
Before diving into tactics, understanding why education matters in the wellness space helps contextualize this approach.
Katherine, Senior Director of Customer Experience at Cornbread Hemp, explains:
"Wellness is a very saturated market right now. Getting to the nitty-gritty and getting to the bottom of what our product actually does for people, making sure they're educated on the differences between products to feel comfortable with what they're putting in their body."
The most common pre-purchase questions Cornbread receives center around three areas: ingredients, dosages, and specific benefits. Customers want to know which product will help with their particular symptoms. They need reassurance that they're making the right choice.
What makes this challenging: These questions require nuanced, personalized responses that consider the customer's specific needs and concerns. Traditionally, this meant every customer had to speak with a human agent, creating a bottleneck that slowed conversions and overwhelmed support teams during peak periods.
Stacy, Senior Customer Experience Manager at Cornbread, identified the game-changing impact of Shopping Assistant:
"It's had a major impact, especially during non-operating hours. Shopping Assistant is able to answer questions when our CX agents aren't available, so it continues the customer order process."
A customer lands on your site at 11 PM, has questions about dosage or ingredients, and instead of abandoning their cart or waiting until morning for a response, they get immediate, accurate answers that move them toward purchase.
The real impact happens in how the tool anticipates customer needs. Cornbread uses suggested product questions that pop up as customers browse product pages. Stacy notes:
"Most of our Shopping Assistant engagement comes from those suggested product features. It almost anticipates what the customer is asking or needing to know."
Actionable takeaway: Don't wait for customers to ask questions. Surface the most common concerns proactively. When you anticipate hesitation and address it immediately, you remove friction from the buying journey.
One of the biggest myths about AI is that implementation is complicated. Stacy explains how Cornbread’s rollout was a straightforward three-step process: audit your knowledge base, flip the switch, then optimize.
"It was literally the flip of a switch and just making sure that our data and information in Gorgias was up to date and accurate."
Here's Cornbread’s three-phase approach:
Actionable takeaway: Block out time for that initial knowledge base audit. Then commit to regular check-ins because your business evolves, and your AI should evolve with it.
Read more: AI in CX Webinar Recap: Turning AI Implementation into Team Alignment
Here's something most brands miss: the way you write your knowledge base articles directly impacts conversion rates.
Before BFCM, Stacy reviewed all of Cornbread's Guidance and rephrased the language to make it easier for AI Agent to understand.
"The language in the Guidance had to be simple, concise, very straightforward so that Shopping Assistant could deliver that information without being confused or getting too complicated," Stacy explains. When your AI can quickly parse and deliver information, customers get faster, more accurate answers. And faster answers mean more conversions.
Katherine adds another crucial element: tone consistency.
"We treat AI as another team member. Making sure that the tone and the language that AI used were very similar to the tone and the language that our human agents use was crucial in creating and maintaining a customer relationship."
As a result, customers often don't realize they're talking to AI. Some even leave reviews saying they loved chatting with "Ally" (Cornbread's AI agent name), not realizing Ally isn't human.
Actionable takeaway: Review your knowledge base with fresh eyes. Can you simplify without losing meaning? Does it sound like your brand? Would a customer be satisfied with this interaction? If not, time for a rewrite.
Read more: How to Write Guidance with the “When, If, Then” Framework
The real test of any CX strategy is how it performs under pressure. For Cornbread, Black Friday Cyber Monday 2025 proved that their conversational commerce strategy wasn't just working, it was thriving.
Over the peak season, Cornbread saw:
Katherine breaks down what made the difference:
"Shopping Assistant popping up, answering those questions with the correct promo information helps customers get from point A to point B before the deal ends."
During high-stakes sales events, customers are in a hurry. They're comparing options, checking out competitors, and making quick decisions. If you can't answer their questions immediately, they're gone. Shopping Assistant kept customers engaged and moving toward purchase, even when human agents were swamped.
Actionable takeaway: Peak periods require a fail-safe CX strategy. The brands that win are the ones that prepare their AI tools in advance.
One of the most transformative impacts of conversational commerce goes beyond conversion rates. What your team can do with their newfound bandwidth matters just as much.
With AI handling straightforward inquiries, Cornbread's CX team has evolved into a strategic problem-solving team. They've expanded into social media support, provided real-time service during a retail pop-up, and have time for the high-value interactions that actually build customer relationships.
Katherine describes phone calls as their highest value touchpoint, where agents can build genuine relationships with customers. “We have an older demographic, especially with CBD. We received a lot of customer calls requesting orders and asking questions. And sometimes we end up just yapping,” Katherine shares. “I was yapping with a customer last week, and we'd been on the call for about 15 minutes. This really helps build those long-term relationships that keep customers coming back."
That's the kind of experience that builds loyalty, and becomes possible only when your team isn't stuck answering repetitive tickets.
Stacy adds that agents now focus on "higher-level tickets or customer issues that they need to resolve. AI handles straightforward things, and our agents now really are more engaged in more complicated, higher-level resolutions."
Actionable takeaway: Stop thinking about AI only as a cost-cutting tool and start seeing it as an impact multiplier. The goal is to free your team to work on conversations that actually move the needle on customer lifetime value.
Cornbread isn't resting on their BFCM success. They're already optimizing for January, traditionally the biggest month for wellness brands as customers commit to New Year's resolutions.
Their focus areas include optimizing their product quiz to provide better data to both AI and human agents, educating customers on realistic expectations with CBD use, and using Shopping Assistant to spotlight new products launching in Q1.
The brands winning at conversational commerce aren't the ones with the biggest budgets or the largest teams. They're the ones who understand that customer education drives conversions, and they've built systems to deliver that education at scale.
Cornbread Hemp's success comes down to three core principles: investing time upfront to train AI properly, maintaining consistent optimization, and treating AI as a team member that deserves the same attention to tone and quality as human agents.
As Katherine puts it:
"The more time that you put into training and optimizing AI, the less time you're going to have to babysit it later. Then, it's actually going to give your customers that really amazing experience."
Watch the replay of the whole conversation with Katherine and Stacy to learn how Gorgias’s Shopping Assistant helps them turn browsers into buyers.
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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:
While most ecommerce brands debate whether to implement AI support, customers already rate AI assistance nearly as highly as human support. The future isn't coming. It's being built in real-time by brands paying attention.
As a conversational commerce platform processing millions of support tickets across thousands of brands, we see what's working before it becomes common knowledge. Three major shifts are converging faster than most founders realize, and this article breaks down what's already happening rather than what might happen someday.
By the end of 2026, we predict that the performance gap between ecommerce brands won't be determined by who adopted AI first. It will be determined by who built the content foundation that makes AI actually work.
Right now, we're watching this split happen in real time. AI can only be as good as the knowledge base it draws from. When we analyze why AI escalates tickets to human agents, the pattern is unmistakable.
The five topics triggering the most AI escalations are:
These aren’t complicated questions — they're routine questions every ecommerce brand faces daily. Yet some brands automate these at 60%+ rates while others plateau at 20%. The difference isn't better AI. It's better documentation.
Take SuitShop, a formalwear brand that reached 30% automation with a lean CX team. Their Director of Customer Experience, Katy Eriks, treats AI like a team member who needs coaching, not a plug-and-play tool.
When Katy first turned on AI in August 2023, the results were underwhelming. So she paused during their slow season and rebuilt their Help Center from the ground up. "I went back to the tickets I had to answer myself, checked what people were searching in the Help Center, and filled in the gaps," she explained.
The brands achieving high automation rates share Katie's approach:
AI echoes whatever foundation you provide. Clear documentation becomes instant, accurate support. Vague policies become confused AI that defaults to human escalation.
Read more: Coach AI Agent in one hour a week: SuitShop’s guide
Two distinct groups will emerge next year. Brands that invest in documentation quality now will deliver consistently better experiences at lower costs. Those who try to deploy AI on top of messy operations will hit automation plateaus and rising support costs. Every brand will eventually have access to similar AI technology. The competitive advantage will belong to those who did the unexciting work first.
Something shifted in July 2025. Gorgias’s AI accuracy jumped significantly after the GPT-5 release. For the first time, CX teams stopped second-guessing every AI response. We watched brand confidence in AI-generated responses rise from 57% to 85% in just a few months.
What this means in practice is that AI now outperforms human agents:
For the first time, AI isn't just faster than humans. It's more consistent, more accurate, and even more empathetic at scale.
This isn't about replacing humans. It's about what becomes possible when you free your team from repetitive work. Customer expectations are being reset by whoever responds fastest and most completely, and the brands crossing this threshold first are creating a competitive moat.
At Gorgias, the most telling signal was AI CSAT on chat improved 40% faster than on email this year. In other words, customers are beginning to prefer AI for certain interactions because it's immediate and complete.
Within the next year, we expect the satisfaction gap to hit zero for transactional support. The question isn't whether AI can match humans. It's what you'll do with your human agents once it does.
The brands that have always known support should drive revenue will finally have the infrastructure to make it happen on a bigger scale. AI removes the constraint that's held this strategy back: human bandwidth.
Most ecommerce leaders already understand that support conversations are sales opportunities. Product questions, sizing concerns, and “just browsing” chats are all chances to recommend, upsell, and convert. The problem wasn't awareness but execution at volume.
We analyzed revenue impact across brands using AI-powered product recommendations in support conversations. The results speak for themselves:
It's clear that conversations that weave in product recommendations convert at higher rates and result in larger order values. It’s time to treat support conversations as active buying conversations.
If you're already training support teams on product knowledge and tracking revenue per conversation, keep doing exactly what you're doing. You've been ahead of the curve. Now AI gives you the infrastructure to scale those same practices without the cost increase.
If you've been treating support purely as a cost center, start measuring revenue influence now. Track which conversations lead to purchases, which agents naturally upsell, and where customers ask for product guidance.
We are now past the point where response time is a brand's key differentiator. It is now the use of conversational commerce or systems that share details and context across every touchpoint.
Today, a typical customer journey looks something like this: see product on Instagram, ask a question via DM, complete purchase on mobile, track order via email. At each step, customers expect you to remember everything from the last interaction.
The most successful ecommerce tech stacks treat the helpdesk as the foundation that connects everything else. When your support platform connects to your ecommerce platform, shipping providers, returns portal, and every customer communication channel, context flows automatically.
A modern integration approach looks like this. Your ecommerce platform (like Shopify) feeds order data into a helpdesk like Gorgias, which becomes the hub for all customer conversations across email, chat, SMS, and social DMs. From there, connections branch out to payment providers, shipping carriers, and marketing automation tools.
As Dr. Bronner’s Senior CX Manager noted, “While Salesforce needed heavy development, Gorgias connected to our entire stack with just a few clicks. Our team can now manage workflows without needing custom development — we save $100k/year by switching."
As new channels emerge, brands with flexible tech stacks will adapt quickly while those with static systems will need months of development work to support new touchpoints. The winners will be brands that invest in their tools before adding new channels, not after customer complaints force their hand.
Start auditing your current integrations now. Where does customer data get stuck? Which systems don’t connect to each other? These gaps are costing you more than you realize, and in the future, they'll be the key to scaling or staying stagnant.
Post-purchase support quality will be a stronger predictor of customer lifetime value than any email campaign. Brands that treat support as a retention investment rather than a cost center will outperform in repeat purchase rates.
Returns and exchanges are make-or-break moments for customer lifetime value. How you handle problems, delays, and disappointments determines whether customers come back or shop elsewhere next time. According to Narvar, 96% of customers say they won’t repurchase from a brand after a poor return experience.
What customers expect reflects this reality. They want proactive shipping updates without having to ask, one-click returns with instant label generation, and notifications about problems before they have to reach out. When something goes wrong, they expect you to tell them first, not make them track you down for answers.
The quality of your response when things go wrong matters more than getting everything right the first time. Exchange suggestions during the return flow can keep the sale alive, turning a potential loss into loyalty.
Brands that treat post-purchase as a retention strategy rather than a task to cross off will see much higher repeat purchase rates. Those still relying purely on email marketing for retention will wonder why their customer lifetime value plateaus.
Start measuring post-return CSAT scores and repeat purchase rates by support interaction quality. These metrics will tell you whether your post-purchase experience is building loyalty or quietly eroding it.
After absorbing these predictions about AI accuracy, content infrastructure, revenue-centric support, context, and post-purchase tactics, here's your roadmap for the next 24 months.
Now (in 90 days):
Next (in 6-12 months):
Watch (in 12-24 months):
The patterns we've shared, from AI crossing the accuracy threshold to documentation quality, are happening right now across thousands of brands. Over the next 24 months, teams will be separated by operational maturity.
Book a demo to see how leading brands are already there.
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TL;DR:
Looking to grow an email list to capture leads or offer welcome incentives? These days, the default solution is to plaster a full-screen pop-up on your homepage.
It seems effective on the surface, collecting emails right off the bat, but dig deeper, and these pop-ups disrupt the shopping experience and skyrocket bounce rates—with 72% of customers exiting a website.
But how else do you get your message across?
That’s where Gorgias Convert comes in—a smarter, more customer-centric tool to drive conversions without pushing your visitors away.
Below, we’ll explore why it’s time to move on from full-screen pop-ups and how Gorgias Convert offers a better alternative for Shopify brands looking to boost engagement and revenue.
Pop-ups can be an effective marketing tool, but their full-screen counterpart often creates more problems than they solve. These intrusive overlays pose several challenges that can harm both user experience and your bottom line.
Full-screen pop-ups demand attention, often at the worst possible moment—like when a customer is browsing products or is just about to check out. This experience can frustrate visitors and lead them to abandon your site entirely.
The BBC says every extra second a page takes to load can cost you 10% of your users—and pushy pop-ups don’t help. If your pop-ups are poorly timed or overly intrusive, visitors feel unwelcome, causing them to leave before exploring your offerings.
Traditional pop-ups are static and one-size-fits-all. They can’t adjust messaging based on where the customer is in their shopping journey or their behavior on your site.
Many users employ ad blockers that filter out pop-ups altogether, meaning your message never even reaches a portion of your audience.
Gorgias Convert flips the script by offering a subtle, customer-friendly way to capture leads and drive sales without the drawbacks of full-screen pop-ups. Here’s why your Shopify brand should make the switch:
Gorgias Convert integrates seamlessly into your store, using a chat-based widget that feels like a natural part of the browsing experience. Using chat to double as a supporting and converting tool is less disruptive, allowing customers to explore your store at their own pace.

Convert makes it easy to bring any type of campaign to life. Catch the attention of the exact shoppers you want by detecting their browsing behavior, customer profile, cart attributes, and more.
For example, the exit intent campaign is the top-performing Convert campaign—it detects when a user is about to leave and displays a discount code. It’s fully customizable, allowing you to tailor offers based on how much time they’ve spent on a page, the number of items in their cart, or if they’ve visited more than three times without making a purchase.

Unlike one-size-fits-all pop-ups, Convert lets you tailor your messaging based on customer behavior, order history, and engagement. For example, if a customer is browsing a specific product, Convert can offer a relevant discount or incentive tied directly to that item.
With Convert, you’re not just collecting an email address—you’re starting a conversation. The tool allows you to engage with customers in real-time through pre-set flows that guide them toward taking action, whether it’s signing up for your newsletter, redeeming an offer, or completing a purchase.

Related: 6 types of conversational customer service + how to implement them
In 2024, smartphones were responsible for generating 68 percent of online shopping orders. To meet shoppers where they are, Convert’s chat-style interactions are optimized for mobile users. Unlike traditional pop-ups that don’t display correctly on smaller screens, Convert maintains a seamless experience for shoppers who prefer to shop on the go.

Using Convert means you can combine immediate assistance with smart marketing through its native integration with Gorgias and Shopify. For example, if a customer hesitates to make a purchase, you can intervene with a live chat offer or product recommendation in real-time.
The Shopify integration also allows you to generate unique discount codes that expire within 48 hours—preventing them from being shared on unauthorized coupon sites. These codes are automatically created with customizable thresholds, such as discounts for specific collections or individual users, without manual setup.

Convert allows you to test different messages and incentives, giving valuable insights into what resonates most with your audience. This data-driven approach ensures your lead capture strategy evolves with shoppers over time.
Read more: How campaign messaging can increase conversions
Shopify brands using Gorgias Convert have led to a conversion rate boost of 6-10% more across their website, up to a 24% click-through rate and 43% click-to-order rate, and improved customer satisfaction. By prioritizing a frictionless shopping experience, these brands are turning casual visitors into loyal customers.
Here’s what some happy brands have to say about Convert:
Haircare brand, Kreyol Essence, influenced 13% of revenue with Convert campaigns: “With Convert, we’ve not only improved our conversion rates but also created a seamless, personalized shopping experience that our customers love. It’s like having a personal assistant for each shopper. Thanks to Convert, we can interact with our customers and surface key information at the right time, turning clicks into connections."
Brands using customer service management agency, TalentPop, love how easy it is to generate revenue with Convert: “Clients are constantly surprised and delighted by how effective Gorgias Convert is for revenue generation. They especially appreciate that Convert can be used to target a diverse range of customers across the entire purchasing journey.”
In five months, yoga brand Manduka, increased revenue by 284.15% after using Convert: “Gorgias Convert has helped us make the shopping experience more intuitive. We can give a nice prompt to remind people of promotions we’re running, highlight specific product features, or just remind them we're here to help and answer questions. The chat campaigns make it easy for customers because they lead them to us, as opposed to them having to search for how to contact us for assistance.”
Shoppers want personalized experiences that respect their time and preferences. Full-screen pop-ups belong to an era of intrusive marketing that shoppers would rather leave in the past.
Gorgias Convert for your Shopify brand means delivering impactful interactions, more conversions, and an easy path to long-term customer loyalty.
Ready to make the switch? Start your effortless shopping journey today with Gorgias Convert. Chat with our team!

Today, we’re announcing our deeper investment in conversational AI for ecommerce.
"Since day one, Gorgias has been dedicated to helping ecommerce brands deliver exceptional customer experiences. We started with a helpdesk to centralize support, then introduced AI Agent to instantly resolve support questions,” says Romain Lapeyre, CEO of Gorgias.
“Now, we're taking the next leap forward with an AI Agent that powers the entire customer journey—anticipating buyer needs, boosting sales, and automating high-quality support. Today, I'm happy to announce Gorgias as the Conversational AI platform for ecommerce.”
Gorgias’s Conversational AI platform will let teams provide fast, scalable, and cost-effective support while helping them drive revenue growth. From automatic order changes and refunds to product recommendations and cross-sells, brands will be able to flawlessly combine their support and sales efforts.
The end result is an AI-powered customer journey where every customer interaction feels complete, personal, and connected, both before and after purchase.
Last year, we introduced AI Agent for email.
Some brands call their AI Agent Lisa, some call it Wally, and most treat it like a real member of the team. But this reliable support sidekick was only available to answer customers on email—until now.
Get ready for instant responses that tackle support inquiries of all sizes. Now, your customers can enjoy fast responses that keep their shopping experience as smooth as possible.
On top of improving first response times, AI Agent can play an even more critical role in unblocking sales, suggesting products, and driving upsells and cross-sells.
With responses sent in 15 seconds or less, brands can delight customers with near-instant resolutions.

Actions let AI Agent perform customer requests on behalf of your support team. This includes changing shipping addresses, fetching fulfillment status, canceling orders, adding discounts, and more.
You can use a library of pre-configured Actions for popular apps like Shopify, Rebuy, Loop, and more. And you don’t need any technical skills to set them up.
With almost half of queries requiring some kind of update, Actions is your go-to for complete resolutions so you can get more accomplished.

Quality checks have traditionally been manual, time-consuming, and inconsistent. Our brand new Auto QA feature changes that by automatically scoring 100% of conversations on resolution completeness and communication quality—whether from a human or AI agent.
With Auto QA, team leads can:

Support teams should be in complete control of their AI. That’s why the AI Agent Report and AI Agent Insights were created—to help you know exactly how your AI Agent is performing and contributing to your customer service operations.
The AI Agent Report provides full visibility into AI Agent’s performance, covering metrics like first response Time, CSAT, and one-touch ticket resolutions. Fully integrated into your Support Performance Statistics dashboard, the report includes:

AI Agent Insights takes it a step further. It analyzes AI Agent’s performance data and provides you with a dashboard of recommendations, including potential automation opportunities, popular ticket intents to optimize, and knowledge base improvements.

Soon, we’ll be expanding AI Agent's skills with the launch of Shopping Assistant, a tool designed to assist customers on their shopping journey.
Shopping Assistanthelps brands boost their sales capabilities through smart product recommendations, on-page checkout assistance, and personalized conversations. Now it's easier to reduce cart abandonment, suggest complementary products to boost average order value, and overcome pre-sale objections.
This new tool will bridge the gap between marketing and CX, ensuring brands can scale personalized interactions 24/7 without increasing headcount.

As we continue to innovate with conversational AI, our focus remains on helping you succeed.
By combining smarter tools with valuable insights, we’re creating opportunities for you to put your customers first and build deeper connections at every touchpoint.
Join us as we pave a new way for the future of ecommerce.
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TL;DR:
Your customer service conversations contain a goldmine of insight about your shoppers—like why they reached out, trends in shopper behavior, and how your products or services perform.
But how do you turn thousands of unstructured support tickets into accurate, digestible, and actionable takeaways?
Ticket Fields are the answer. They give support teams extra layers of data by labeling tickets in a much smarter way than traditional tags. With the right setup, Ticket Fields can help you uncover patterns, make smarter decisions, and highlight the value customer experience (CX) brings to your entire organization.
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Ticket Fields are customizable properties that allow CX teams to collect and organize information about tickets. Agents fill in ticket fields before closing the ticket, making it much easier to scale data collection.
Ticket Fields can be mandatory, requiring an agent to populate a field before closing the ticket. They can also be conditional, only appearing when relevant to the ticket.
There are four types of Ticket Fields: Dropdown, Number, Text, and Yes/No. Here are some ways to use each:

Unlike Tags, which are single-reason and non-conditional, Ticket Fields ensure key information, such as fulfillment details or cancellation reasons, is built into a ticket.
Think of Tags as stickers added to a ticket, while Ticket Fields are part of the ticket’s DNA itself, giving you much more control and insight.
Let’s take a closer look at why Ticket Fields are far superior at collecting data than Tags:
Agents manually apply Tags, which means it’s easy to forget to tag a ticket.
Ticket Fields, however, enforce structure by allowing CX managers to decide which fields are mandatory and which are optional. This flexibility ensures that all tickets contain the same basic details.
Ticket Fields can be conditional, meaning certain types of tickets automatically include fields that must be filled in.
How does it work? Take a look at this example:
If the Contact Reason field is Cancellation, conditional ticket fields like Cancel Reason, Did We Cancel Subscription, and Order Number must also be filled out.
Here’s how it looks in the Field Conditions settings:

No more missing context, gaps in the data, or typing N/A in a field. Support teams can capture the data they need from each ticket every time.
For CX teams transitioning from other helpdesks, being able to import historical ticket data with the field information intact is significant. This preserves workflows and existing data, helping teams get set up in no time without losing crucial information.
Tags, on the other hand, should be used to:
Ticket Fields are incredibly adaptable, allowing you to capture the exact data your team needs to meet your goals—whether it’s tracking product trends, choosing a shipping carrier, or increasing customer satisfaction.
Here are 12 examples of custom Ticket Fields to level up your data analysis.
Type of ticket field: Dropdown
What to do with the data: Identify common reasons customers contact you and take proactive steps to address them.
The Contact Reason ticket field is an easy way to figure out why customers reach out to your support team in the first place.
You can quickly identify trends, such as a sudden spike in return requests, and investigate whether it's a website, fulfillment, product, or service issue.
Some common contact reasons:
Note: Gorgias AI automatically suggests contact reasons, pre-filling the field with a prediction based on message content. Agents can accept or adjust the suggestion, helping the system become smarter over time as it learns from these interactions.

Type of ticket field: Dropdown
What to do with the data: Assess the effectiveness of resolutions and refine your service level agreement.
The Resolution ticket field tracks the action taken to resolve a ticket. Analyzing how your team handles tickets and identifying opportunities to improve resolutions is essential.
For example, you could analyze how often issues are resolved with replacements versus discounts. If you find replacements are overused for minor issues, you might implement a policy to provide discounts instead, helping to reduce costs without harming customer satisfaction.
Here are some values to add to the Resolution ticket field:

Type of ticket field: Dropdown
What to do with the data: Use both positive and negative feedback to update your policies, escalation process, customer-facing resources, product, and more.
The Feedback ticket field can capture general feedback about your brand or feedback specific to your products.
This field is an excellent way to carry out product research. For example, if you’re a food brand, you can create a dropdown that categorizes feedback by sentiment, such as “Too Sweet,” “Too Salty,” “General Dislike,” and “Artificial Taste.” Once you’ve received a decent amount of feedback, you can return to the test kitchen and perfect your recipe.

Type of ticket field: Dropdown
What to do with the data: Track product trends and prioritize improvements.
The Product field is valuable for tracking which items generate the most inquiries. If you have a large inventory, incorporating a Product ticket field can help flag which products are causing the most issues or trouble for shoppers.
If a product is the most used value, this could indicate frequent issues with the product, such as quality issues, defects, or missing information on its product page.
If a product is the least used value, it may not be generating much attention. If this is due to low sales, consider enhancing its visibility through marketing to attract more shoppers. However, being the least used value can also be good news, meaning your product performs well, and shoppers have no complaints.
Pro Tip: To understand which specific products are getting returned, add a conditional “Product” ticket field.

Type of ticket field: Dropdown + conditional field
What to do with the data: Identify recurring quality issues and fix root causes.
Track the most prominent defects reported by customers with a Defect ticket field. This can help you monitor product quality and adjust production, manufacturer, or supplier processes.
For deeper insights, add a conditional “Product” field to pinpoint which products experience specific defects. For example, if you’re a bag brand, you might find that a certain backpack is usually tied to a “Zipper” defect. This can be a valuable insight to pass on to your product team to alter the design or adjust your manufacturing process.
Here’s a look at the dropdown values for the Defect ticket field:

Type of ticket field: Dropdown
What to do with the data: Lower churn by addressing cancellation triggers.
If you’re a subscription-based business with a climbing cancellation rate, adding a Cancellation Reason ticket field can help you stop the churn. This field tracks why customers cancel orders or subscriptions. It’s a powerful way to identify patterns, such as price sensitivity or delivery delays, and to take steps to retain customers.
Cancellation reason examples:
Type of ticket field: Dropdown + conditional field
What to do with the data: Evaluate shipping carrier performance and improve logistics.
For any ecommerce brand, your shipping carrier is a big contributor to customer satisfaction. The faster a customer’s order gets to them, the better.
Use a Shipping Carrier ticket field to track the shipping carrier for tickets related to delivery issues. This will provide insights into which carriers perform poorly, enabling you to modify your logistics and order fulfillment processes.
Pair the Shipping Carrier field with a conditional “Shipping Issue” field to identify potential correlations. For example, if “Delayed” is a top shipping issue for a certain carrier, it may be time to change your logistics process.

Type of ticket field: Dropdown
What to do with the data: Learn how customers find your brand and see what types of customers and issues are tied to the purchase source.
The Purchase Origin field helps you see where customers are coming from. Are they buying directly from your website? Or from social media platforms like Instagram or TikTok?
Dig deeper, and you may also spot connections between purchase origin and common issues.
For your marketing team, this data will help improve strategies at all levels, from advertising and messaging to targeting the right platforms.

Type of ticket field: Yes/No
What to do with the data: Reduce escalations by revising escalation processes and retraining agents.
The Customer Escalation field tracks whether a ticket was escalated to a manager. It helps teams identify training needs and improve processes to reduce escalations.
As the use of AI agents increases in ecommerce customer service, having a clear view of which tickets are escalated can help pinpoint gaps in AI performance and identify scenarios that require human intervention.
Analyzing this data over time can guide updates to AI workflows and agent training, reducing the need for escalations altogether.
Type of ticket field: Number
What to do with the data: Understand how discounts impact customer satisfaction.
The Discount Percentage ticket field tracks the percentage of a discount applied to a customer's order, offering insights into how promotions affect customer behavior.
For example, if customers using a 20% discount frequently contact support about order confusion or dissatisfaction, it might indicate unclear promotion terms or product descriptions. This data helps brands refine promotional messaging and determine whether higher discounts lead to increased ticket volumes, customer satisfaction, or sales.

Type of ticket field: Yes/No + conditional field
What to do with the data: Improve the customer experience for brand new customers.
The First-Time Buyer field flags whether a customer is making their first purchase, making it easier to spot and support new shoppers. When a customer is marked as a first-time buyer, a conditional “Customer Sentiment” field can appear to capture how they feel about their experience.
First-time buyers often have questions about products or need recommendations to feel confident about their purchase. Pairing this ticket field with sentiment data helps to identify common pain points, preferences, and patterns among new customers so your team can finetune the customer experience and leave a lasting first impression.

Type of ticket field: Number
What to do with the data: Analyze product performance over time.
The Months in Use field tracks how long customers have been using a product. It’s perfect for spotting when items start breaking down, spoiling, or losing effectiveness.
This data helps brands figure out where durability, shelf life, or packaging could be improved to keep customers happy and products performing as expected.
Ticket Fields provide value across the entire CX ecosystem, from agents to decision-makers.
Ticket Fields are only as powerful as the processes that support them. Follow these five steps to help your team turn support tickets into valuable data for better reporting.
Decide what insights your team needs to improve workflows, product quality, or customer satisfaction. For example, if you want to track cancellations, set up fields like "Cancellation Reason" and "Refund Amount." Keep your Ticket Fields focused on data your team can use.
Use Gorgias to configure Ticket Fields in a structured and easy-to-use format. Keep dropdown options concise and specific to avoid confusion. Then, run a test ticket or two to confirm the setup works smoothly for agents.
Read more: Create and edit Ticket Fields
Create a presentation deck that clearly explains the purpose of every Ticket Field, the options agents can select for each field, and how the fields tie into the team’s data goals. For added visuals, include flowcharts to show when and how to use each field.

Pro Tip: Give agents a quick reference tool they can easily consult by providing a cheat sheet summarizing Ticket Field best practices.
Whether the data points to gaps in your workflows, product details, or customer education, acting on these patterns is how you drive meaningful change.
Here are some fixes, from low to high effort, that your team can implement:
Schedule a monthly meeting to review your Ticket Fields Statistics and evaluate their impact on your support workflows and customer satisfaction.
During the meeting, discuss:
Lastly, remember to document the insights and update your team regularly to keep everyone aligned.

Gorgias’s Ticket Fields turn ticket data into insights you can actually use. Spot trends, improve workflows, and make faster, smarter decisions.
Are you ready to see it in action? Book a demo, and let us show you how Ticket Fields can elevate your support.
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TL;DR:
According to Salesforce research, 77% of support staff have dealt with increased and complex workflows compared to the year prior. In addition, 56% of agents have experienced burnout due to support work.
As teams transition into the next era of CX—one where almost every customer expects efficiency, convenience, and friendly and knowledgeable service –– they’ll need the support of more than just a stellar lead to avoid the stress that comes with the job.
AI and automation are valuable and impactful tools that can aid teams in providing these top-notch experiences while helping agents lower their own stress.
Here are seven ways to leverage AI and automation to increase agent productivity, meet customer expectations, and decrease burnout on CX teams.
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While there will always be reasons for human intervention, here are seven support challenges that AI and automation can solve for CX teams long term.
Every CX team receives repetitive questions like “where is my order” (WISMO), “can I change my shipping address,” or “what is your return policy” every single day. These questions add up over time, creating frustration and burnout for agents and longer response times for customers.
Instead, teams can leverage AI and automation to answer these questions and take time back for other essential tasks.
If you use Gorgias, there are a couple of ways to put automation to work.

"Gorgias's AI Agent has been a game-changer for us, allowing us to automate nearly half of our customer service inquiries. This efficiency means we don’t need to hire additional staff to manage routine tasks, which has saved us the equivalent of two full-time positions.
—Noémie Rousseau, Customer Service Manager at Pajar
Resource: How to automate half of your CX tasks
Many customers get frustrated due to delayed support responses, especially if (they believe) they’re asking a simple question. Not only can AI and automation support by offering responses to these questions, they allow human agents to respond faster to customers who have more complex questions.

AI Agent has been an effective tool for the team at luxe golf accessory shop VESSEL. “Now we’re able to get back to people so much faster than before,” says Lauren Reams, their Customer Experience Manager.
“We can quickly collect information – avoiding the back and forth questions like what is your name, email or shipping address. Using AI to eliminate the back and forth has been great, and getting back to customers much faster than before has been the biggest win for our team.”
If customers see an inconsistent tone of voice across responses, it’ll affect your brand credibility. It also causes confusion and may create issues maintaining repeat and loyal customers.

Manual quality assurance checks are time-consuming and often inconsistent. But they’re key to providing great support at scale while maintaining a high standard across thousands of interactions. Aside from catching any errors, a regular QA process also builds trust with customers, increases personalization, and helps agents improve over time.
Automated quality assurance can provide up to 90% accuracy, according to research by McKinsey. To ensure 100% of your customer conversations are checked, used Auto QA. This AI-powered QA tool evaluates your team's responses—AI or human—based on Resolution Completeness, Communication, and Language Proficiency.

When CX teams are bogged down with an overwhelming amount of tickets, there’s going to be a lack of time and opportunity to upsell in customer conversations. This is especially true when dealing with angry or upset customers, and during high-impact periods like BFCM.
Activate onsite marketing campaigns with Gorgias Convert to provide product recommendations and promote current discounts, sales, or campaigns.
For example, you can use AI to promote relevant items to shoppers to increase their cart value. You might highlight items that are frequently bought together, or show a bundle that would make a great gift for someone. Research shows that these types of personalized recommendations can increase average order value (AOV) by 15%.

Resource: 5 Holiday Onsite Campaigns to Maximize Year-End Sales
The National Retail Federation (NRF) projects that retail returns will total $890 billion in 2024. With so many brands losing money from returns, it’s essential that you find ways to mitigate them.
By switching to Gorgias, Audien Hearing saw nearly a 5% drop in return rates. And Rumpl saw $8,000 in recouped return fees by integrating Loop Returns with Gorgias.
Loop lets customers self-serve returns through a returns portal that encourages exchanges instead. It makes the entire process a breeze, and eliminates back and forth between customers and busy support teams.

Many times, issues that were completely avoidable are escalated, leaving support teams with more tickets and already frustrated customers. These issues are likely common points of confusion that you can easily solve before they ever reach your customers.
If you use Gorgias, here’s how you can leverage automation:

“I’ve been in this role for four years and this was probably our best back to school season yet. In past years, you knew you were going to come in and be bogged down – but this year was way more seamless and much less stressful and that’s thanks to AI Agent.”
—Danae Kaminski, Customer Care Team Lead at Jonas Paul Eyewear
At Gorgias, our goal is to create solutions to the real problems CX professionals face every day. Tools like AI Agent make it possible for teams to provide better customer experiences, reduce agent stress, and create more cohesive and positive working environments overall.
”Thanks to the time we've saved by automating many of our routine tasks, our team has had the chance to bond more,” says Noémie.
“We even had time for a team picnic and painted a picnic table outside! It’s been great to step away and spend time as a team occasionally, knowing that our customers are still being taken care of by the AI Agent. It’s really improved team morale.”
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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.


