

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

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

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

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

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

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

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

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

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

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

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

Results:
Across all 11 brands, one theme is clear. When shoppers get the guidance they need at the right moment, they convert more confidently and often spend more.
Here’s what stands out:
What this means for you:
Look closely at your most common pre-purchase questions. Anywhere shoppers hesitate from fit, shade, technical specs, styling, bundles is a place where Shopping Assistant can step in, boost confidence, and unlock more sales.
If you notice the same patterns in your own store, such as shoppers hesitating over sizing, shade matching, product comparisons, or technical details, guided shopping can make an immediate impact. These moments are often your biggest opportunities to increase revenue and improve the buying experience.
Many of the brands in this post started by identifying their most common pre-purchase questions and letting AI handle them at scale. You can do the same.
If you want to boost conversions, lift AOV, and create a smoother path to purchase, now is a great time to explore guided shopping for your team.
Book a demo or activate Shopping Assistant to get started.
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TL;DR:
What’s the common factor between shoppers debating between products and considering a splurge? Hesitation.
Today’s shoppers are overwhelmed with choices. They don’t want to be left to figure things out on their own. They want guidance.
But most brands are missing that crucial piece of the puzzle. They lack a strategy that accompanies shoppers on their journey. A tool that encourages shoppers to proceed to checkout. And, ultimately, a customer experience devoid of a sales approach.
That’s why we built Shopping Assistant, an AI Agent that proactively engages browsers, offers context-aware product recommendations, and turns hesitation into conversions in real time.
And it’s working. Brands using Shopping Assistant are seeing a 62% uplift in conversion, 10% higher average order value, and 5x ROI.
Here’s a closer look at what’s behind the magic.
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Most traditional chatbots passively wait for questions and deliver answers that aren’t personalized to each shopper's preferences.
Unlike these bots, Shopping Assistant reads real-time signals like pages viewed, cart contents, and conversation tone. This results in a solution that not only offers support but also offers personalized, proactive selling. This enables Shopping Assistant to continuously refine and adjust its playbook, evolving with each shopper as their journey matures.
Here’s how Shopping Assistant engages with customers across the shopping journey:
Take this example below. When a customer vaguely asks “how to make up,” Shopping Assistant interprets it as a sign of interest in makeup products and recommends a starter kit.

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

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

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

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

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

“Once I added specific questions in quotes, it made a huge difference.”
SuitShop didn’t automate 100% of CX — but that’s not the point. At 30% automation (and growing), Katie gives her team more time to specialize, connect, and handle urgent or emotional conversations with care.
Here’s what Gorgias offers to help as well:
Whether you’re just getting started or trying to move beyond basic automation, Katie’s approach proves that coached AI outperforms out-of-the-box tools every time.
Want to coach your AI Agent like SuitShop? Book a demo to see how Gorgias can help you scale smarter.
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TL;DR:
At Gorgias Connect LA 2025, CX leaders from Tommy John, TUSHY, Triple Whale, and Talent Pop shared how support teams solve problems and drive revenue.
This shift, known as the support sales flywheel, doesn’t involve massive overhauls or shiny new tools. Instead, it means doing the small things exceptionally well, like picking up the phone, empowering agents to make judgment calls, and adding a personal touch where others automate.
These brands have shown that when support teams focus on consistency, connection, and conversion, the results compound. Every thoughtful interaction spins the flywheel faster, boosting loyalty, LTV, and revenue.
Ahead, we’re breaking down the most actionable takeaways so your team can start building its own support-led growth engine.
Watch the full panel here:
From scrappy install calls to AI-powered training, these CX leaders aren’t only talking about driving revenue, they’re doing it. Here’s how they’re turning support into a sales flywheel, and the tactics your team can start testing today.
“Customer service done right is actually a great source of revenue.” That’s how Tamanna Bawa, Tech Partner Manager at Triple Whale, kicked off the conversation on how data can transform CX from reactive to revenue-driving.
She advises segmenting customers based on purchase history and behavior to deliver more personalized, higher-converting interactions.
In a market where margins are razor-thin and ad costs are high, Tamanna emphasized that “incremental gains from personalization are the difference between companies that are thriving and the ones that are just surviving.”
What do you do when your hero product needs a cultural shift as much as it needs installation instructions? If you’re TUSHY, you send in your “Poop Gurus.”
Ren Fuller-Wasserman, Senior Director of CX at TUSHY, shared how her team launched a scrappy, free CX-led service that has now become a legendary video install program to help customers set up their bidets.
The real value wasn’t just tech support. As Ren put it, “It wasn’t about the actual install process, it was the encouragement they needed to change culture.” These calls sparked deeply personal moments (yes, even with cats and toddlers wandering in) and created the kind of emotional connection customers never forget.
Today, that service has evolved into a $15 paid add-on at checkout, and the customers who use it have significantly boost LTV and retention. It’s a masterclass in turning support moments into revenue through genuine human connection.
Phone support is back, and it’s becoming one of the most effective ways to turn conversations into conversions.
Ren from TUSHY swears by it. Her team uses customer phone numbers from abandoned carts to reach out directly. “You can send a hundred emails,” she said, “but a voicemail from a real person cuts through the noise.” Even if customers don’t answer, the fact that a brand called is memorable, and often enough to drive them back to checkout.
Max Wallace, the Director of CX Tommy John echoed the value of voice. His team recently implemented Gorgias Voice, using it to track conversion rates by agent. That visibility helps them identify what top performers are doing differently and replicate it across the team. “By the end of a tough call, customers often apologize for how they started. You can’t get that kind of de-escalation over email.”
In a world where inboxes are crowded and chat fatigue is real, a real voice builds real trust and real revenue.
Pro Tip: Don’t rush into phone if your other channels aren’t dialed in. “Master email and chat first. Then, start with limited phone hours. Taste it before scaling it,” said Armani Taheri, the co-founder of TalentPop.
For Max at Tommy John, revenue-driving support starts with two things: deep product knowledge and the freedom to bend the rules.
“We have five different fabrics for men’s underwear alone,” Max shared. To help customers choose the right one, agents need firsthand experience. That’s why Tommy John sends new products directly to the support team, so they can offer real, personalized recommendations like “Try Second Skin instead of Cool Cotton.”
But product knowledge is only half the equation. The other half is empowering agents to make judgment calls. Tommy John’s “Best Pair Guarantee” allows customers to try a product and get a refund or replacement if it’s not the right fit.
Agents are trained to prioritize retention, offering replacements instead of refunds, recommending better-suited products, and using their own discretion to keep customers happy.
As Max put it, “We don’t have really strict policies… we want them to use their best judgment.” That confidence translates into smoother resolutions, more cross-sells, and customers who stick around.
How do you train outsourced agents to drive revenue, without sounding like a sales team? According to Armani Taheri of TalentPop, it starts with confidence and context.
“You have to tailor-fit the training approach to each brand,” he explained. That means grounding agents in product knowledge, tone of voice, and customer journey before they ever interact with a shopper.
One of the most effective tactics is roleplaying. Armani’s team uses both live roleplays and AI-powered chat simulations to prepare agents for real conversations, pre-sales, post-sales, and everything in between. Tools like Replit and Lovable help create lightweight, brand-specific training environments agents can practice in at their own pace.
The goal isn’t to turn CX reps into hard sellers. It’s to give them the confidence and consistency to recognize revenue opportunities, and act on them in a natural, helpful way.
Ready to turn your CX team into a revenue engine? Here are some of the tools mentioned by the panelists that help make it happen:
Whether you're scaling phone support or experimenting with post-purchase outreach, the right tools make the flywheel spin faster.
They’re on the front lines with your most engaged customers, answering questions, easing doubts, and uncovering what really drives purchases. With the right tools and training, they resolve tickets and help close the sale.
With tools like Gorgias Voice, it’s easier than ever to connect the dots between conversations and conversions.
Want to see how your CX team can help drive growth?
Book a demo to see how Gorgias Voice powers sales through support.
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TL;DR:
Your CX team talks to customers every day. They know what’s confusing, driving purchases, and causing returns, because they hear it firsthand.
But all too often, those insights stay siloed in support tickets and live chat transcripts instead of informing the campaigns that shape the customer journey.
This post is here to change that. We’re breaking down the most valuable questions marketing teams should be asking their CX counterparts. When marketing and CX work together, you get more relevant messaging, smarter product positioning, and campaigns that convert.
Whether you’re planning a big seasonal push or just want to improve product education, this is where to start.
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Your CX team knows what makes shoppers hesitate. They’re the ones fielding questions like: Does this come in a larger size? Is it final sale? Will it arrive in time?
Beyond being pre-sale inquiries, they’re signals. They reveal what your customers care about most, and where your messaging may be falling short. When marketing teams tune into this, they can proactively address objections in landing pages, product detail pages (PDPs), emails, and top-of-funnel content.

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

Ask your CX team:
“Which product do customers rave about most, and what exactly are they saying?”
When customers are frustrated, it’s easy to blame the product. But in many cases, the issue isn’t quality, it’s communication.
At Shinesty, a men’s underwear brand, Molly Kerrigan, Senior Director of Retention, observed that high return rates often stemmed from unmet customer expectations.
She noted the importance of maintaining clear and consistent communication as the company grows, “We get a lot of praise from our customers, and they talk highly of our CX team after 1:1 interactions. We can’t lose that as we scale.”
Molly notes that using Gorgias AI Agent enables Shinesty’s customers to receive quick answers, freeing her team's time for more complex or sensitive issues.
Similarly, Princess Polly saw that delivering a standout customer experience meant being fast, consistent, and helpful at every stage. After switching to Gorgias, their support performance improved dramatically:
Before changing the product, try updating the messaging. Use insights from CX to rewrite descriptions, add size guides, include user-generated content, or even build a quick-fit quiz. Small tweaks help set clearer expectations and reduce unnecessary returns.
Ask your CX team:
“Which products are driving the most complaints, and what do customers wish they knew before buying?”
Confusion is a conversion killer. If a customer isn’t sure about how something works, what’s included, or whether it’s right for them, they’re more likely to bounce.
That’s why it pays to ask your CX team where customers get stuck. Is it a product feature that needs more context? A vague store policy? A missing detail on a bundle?
The good news is that most confusion is fixable. Start with the following steps:
If you’re using Shopping Assistant, you can go even further. It can detect when shoppers are hesitant and provides real-time nudges. Like an assistant who knows all your needs, Shopping Assistant automatically surfaces the questions customers are likely to ask when evaluating a product, so they’re equipped with the clarity they need to proceed to checkout.

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

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

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

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

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

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

You can also use Gorgias's Dashboard to spot emerging trends across all your channels. This custom reporting feature lets you choose from various charts that reveal high-level patterns—like the most common contact reasons or sudden spikes in ticket volume—giving marketers early insight into shifting customer sentiment and trending topics across social platforms.
Ask your CX team 💬 Which articles in our Help Center are most searched right now?
When support and marketing teams collaborate, you unlock a cycle of continuous improvement. CX teams surface the insights, marketing turns them into strategy, and both sides drive measurable results.
Here’s how to make it work:
We need to reframe CX as a proactive function that drives revenue.
Support teams already have the answers marketers are searching for. You just need the tools to tap into them. Gorgias makes that easy, with flexible reporting features, powerful AI, automated tagging, and integrations that bridge the gap between CX and marketing.
Want to connect your support data to better marketing?
Explore Gorgias’s analytics tools or book a demo to speak to a product expert about how to integrate your support strategy with marketing.
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TL;DR:
Automated responses don’t actually resolve anything. In reality, they increase customer wait time.
What a customer really wants is immediate resolution, whether they’re looking to cancel an order, change a shipping address, or pause a subscription.
So, how do you go beyond automated text responses? AI Agent Actions.
Below, we’ll go over the 7 most common customer service requests you can resolve with AI Agent Actions, so your team gets time back to strengthen customer relationships, increase revenue, and improve your CX strategy.
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AI Agent Actions are tasks AI Agent can complete for your customers, such as canceling an order or updating a shipping address.
Instead of handing it off to a human agent, AI Agent resolves the ticket by connecting to your ecommerce apps and performing the action on its own.
You get maximum control over when and how Actions are executed. Before performing the Action, AI Agent asks customers for confirmation, respecting your processes and maintaining a high level of customer service. Once an Action has been taken, you can even share feedback with your AI Agent to reinforce its behavior or finetune it further.

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

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

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

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

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

Action to use: Reship order for free
Supported apps: Shopify, ShipMonk
No customer expects a lost or damaged order. Let customers know that you have their backs by reshipping a new order free of charge. Fast resolutions during unexpected events demonstrate your commitment to customer satisfaction.
“An instant response builds confidence. We live in a world with short attention spans, so customers appreciate how quickly we can respond to their inquiries. Customers aren’t worrying unnecessarily for longer than they have to for an address change or order cancellation.”
—Mia Chapa, Sr. Director of Customer Experience at Glamnetic
Action to use: Send return shipping status
Supported app: Loop
Customers want to know that their return package is on its way to you, so they can redeem their refund. Easily send them a shipment tracking link to give them that peace of mind.
Action to use: Get order info
Supported apps: Shopify, ShipHero, ShipMonk, ShipStation, ShipBob, Wonderment
Based on Gorgias data, order status ranks among customers' top 10 questions for support teams. Reassure your customers with quick updates on their orders, including product details, shipping progress, expected delivery date, and other helpful information.
Here are a few helpful setup tips to make sure Actions run without a hitch:
If you want…
AI Agent Actions can get you there.
You’ve now seen how Actions can resolve tickets in a snap—no unnecessary handoffs, canned responses, or long response times.
Book a demo to see AI Agent Actions work in real time and start automating what you shouldn’t be doing manually anymore.
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TL;DR:
AI Agent is built to deliver fast, accurate support at scale, but like any teammate, it performs best when given clear and specific instructions.
That’s where Guidance comes in. Writing structured prompts that tell your AI Agent exactly what to do in a given scenario helps reduce escalations, speed up resolutions, and create a more consistent customer experience.
One simple, repeatable way to do that is with the “When, If, Then” framework.
In this post, we’ll show you how it works, using examples from our Gorgias Academy course, Improve AI Agent with Better Guidance.
You’ll learn how to write Guidance that results in:
Let’s break it down.
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Guidance is how you tell your AI Agent what to do. It’s a set of instructions that outlines how your AI Agent should respond in specific situations.
When Guidance is available, your AI Agent follows it first, even before checking your Help Center or website content.
That means if your Guidance is missing, unclear, or incomplete, your AI Agent might escalate the ticket, or worse, give a confusing or unhelpful response. Here’s an example:
Let’s say a customer wants to return an item. A human agent would send them a link to the return portal and explain the steps. But without that instruction in Guidance, your AI Agent might skip straight to escalation, turning a simple request into unnecessary work for your team.
That’s why clear, step-by-step Guidance is key to help your AI Agent respond the way your best support agent would.

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

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

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

TL;DR:
Rising tariffs. Shipping delays. Unpredictable price hikes. For ecommerce, it's an understatement to say the pressure is rising. If you're on the CX team, you're already facing the fire head-on — all the customer frustration, confusion, and hesitation.
CX teams are on the frontlines of support and sales. You're shaping customer trust, buying decisions, and brand loyalty.
From pre-sales conversations to loyalty programs, it’s time to rethink the customer journey, so you can turn every interaction into an opportunity to grow your revenue.
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Customer service isn’t just about reacting to problems. It can be a proactive and strategic function that helps you stabilize and even grow your revenue.
Think about it this way: you have the power to turn everyday customer moments into wins.
At every stage of the customer journey, you can turn:
This isn’t about being pushy for sales. It's about anticipating needs and putting systems in place that protect customer relationships and revenue.
As you update your CX workflow, keep these two questions in mind:
Most pre-sales hesitation is rooted in uncertainty: What’s the return policy? How much is shipping? Will this fit? Will it arrive in time?
Reduce customer effort and build confidence with automation as your CX team’s first line of defense. Anything else more complicated, your agents can take care of.
Start by setting up automated answers for the questions your team responds to every day, especially the ones that delay conversions:
There are a few ways to automate these questions in Gorgias:

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

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

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

Once you’ve identified your at-risk customers, use win-back strategies, like:
When handled thoughtfully, a churn-risk customer can become one of your strongest advocates because you showed up when it mattered most.
Don’t forget, there are already customers who love you! These loyal customers don’t just come back to buy again — they bring friends, amplify your brand, and give your business stability when you need it most.
Use customer data to identify customers who purchase frequently, spend more, or have referred others. Tag them as VIPs in your helpdesk so that their requests are prioritized.
For example, in Gorgias, you can use Customer Fields (customer labels and properties) to group your customers under:
When you know who your top customers are, you can offer more personalized service and make sure every interaction strengthens their connection to your brand.
You don’t need to offer huge discounts to let customers know you appreciate them. Small, thoughtful gestures often make the biggest impact:
If you’re using macros and automations, you can even trigger some of these surprise-and-delight actions automatically, making it easier to scale while keeping the personal touch.
We know how overwhelming uncertain times can be. It’s easy to think you need to reinvent your entire strategy just to keep up.
But the truth is, you already have what you need. You have a team that knows your customers. You have conversations happening every day that can protect, nurture, and even grow your business.
By grounding yourself in what’s already working and creating proactive systems, you can turn uncertainty into strong and steady growth.
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