

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
You’re seconds away from hitting “buy now,” but one last question nags at you: does this shade actually match my skin tone? You open a live chat, only to be met with a bot that pastes a help-center article. So you close the tab.
Today’s shoppers crave immediacy and authenticity. They expect real answers, not ticket numbers. Yet too many ecommerce brands still rely on static FAQs, delayed email replies, or chatbots that feel anything but conversational. The result is often missed sales, frustrated customers, and eroding loyalty.
Conversational commerce bridges that gap. By meeting customers where they are, in real time and on their terms, brands can turn every interaction into an opportunity to build confidence and connection.
In this post, we’ll explore how leading ecommerce brands use Gorgias to strengthen trust and loyalty through real-time conversations across the entire customer journey, from discovery to delivery and beyond.
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Conversational commerce is the blending of conversation and shopping. Instead of forcing customers to navigate pages, FAQs, or documents, brands engage shoppers in real time through natural, two-way dialogue. This usually takes place over:
Unlike traditional live chat, you meet customers wherever they are. Conversational commerce easily switches across channels (chat, SMS, Instagram, WhatsApp, etc.) while preserving context, tone, and personalization.
The goal is to make every interaction feel as natural as a text with a friend, but with the power to guide a purchase, resolve an issue, or suggest a product.
So, how are top brands putting conversational commerce into practice to build real trust? Let’s dive into four examples.
Imagine browsing foundation shades late at night, unsure which one will suit your skin tone. That hesitation is often enough to make a shopper abandon their cart.
That was the challenge for bareMinerals. More than half of their incoming support tickets were product questions. Many of them were about shade matching, formulation updates, or discontinued SKUs.
They needed a way to replicate the helpfulness of a beauty advisor you can call on as you browse a store.
So bareMinerals brought in Shopping Assistant, an AI-powered virtual beauty consultant built to answer product-discovery questions in real time.
It integrates with their Shopify catalog (so it never suggests out-of-stock items), trained on the nuances of context, product benefits, and discontinued color conversions.
Here’s what happened within 30 days:
Takeaway: By offering real-time, contextual product guidance that mirrors an in-store consultant, bareMinerals eliminated guesswork, reduced returns, and strengthened trust before a single purchase is finalized.
One of the most anxiety-inducing moments for any shopper? Waiting for their order. Questions like “Has my order shipped yet?” or “Where’s my package?” often lead to multiple back-and-forth contacts, burdening support and testing customer patience.
Underwear brand Tommy John experienced this firsthand. Their CX team felt the strain of repetitive, predictable post-order questions, which could be better spent on complex cases. The team needed an automated fix without a huge lift, and so they adopted AI Agent.
AI Agent handled the bulk of their routine tickets, pulling from order data and pre-configured guidance to reply instantly without agent involvement.
See how AI Agent instantly jumped in to help a customer who needed to change their address:

The impact was immediate:
Takeaway: Post-purchase communication is a trust moment. Fast, accurate, and proactive responses reassure customers that their order matters.
Returns are often a brand’s biggest trust test. When a customer navigates through the hassle of a return, they’re watching closely: Is this going to be smooth and transparent, or frustrating and impersonal?
Orthofeet, a leading orthopedic footwear brand knew this too well. Before Gorgias, their CX stack was disjointed, a combination of Freshdesk, Dialpad, and outsourced chat. As they grew, this meant tickets piled up without central visibility. They needed a tool that gathered every piece of context in one place.
That’s when they implemented AI Agent. As AI Agent handled tier-1 queries, like validating return eligibility under Orthofeet’s policy and directing customers to the returns portal, agents gained more time to focus on VIP customers, nuanced issues, and phone conversations.

The results were powerful:
Takeaway: Conversational commerce helps you blend technology and humanity to deliver scalable, emotionally resonant support. Even when things go wrong, a thoughtful conversational experience can repair, rather than erode, trust.
Conversational commerce can create selling moments inside conversations you already have with shoppers.
Arc’teryx, known for its technical outdoor gear, wanted to guide customers choosing between products like the Beta AR and Beta SL jackets. With Shopping Assistant, they turned real-time product questions into opportunities to upsell, cross-sell, and educate.
When shoppers linger on a page or ask for comparisons, the AI offers quick, tailored recommendations, suggesting the right jacket, complementary layers, or accessories. The result? More confident buyers and higher-value orders.
The results speak volumes:
Takeaway: Smart, conversational prompts transform everyday chats into meaningful sales moments, proving support channels can drive revenue, not just resolve tickets.
Every conversation is a chance to earn (or lose) trust. Whether it’s helping a shopper find their perfect shade, tracking an order, or smoothing out a return, conversations can turn moments of uncertainty into opportunities for connection.
Brands like bareMinerals, Tommy John, Orthofeet, and Arc’teryx prove that conversational commerce builds stronger relationships, higher retention, and measurable revenue.
The future of ecommerce will revolve around conversations that create trust at every click.
If you want to see how Gorgias can bridge support and sales for you, book a demo today.
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TL;DR:
We recently unveiled the latest upgrades to Gorgias Helpdesk during Moments that Matter: Meet the Modern Helpdesk.
The event was hosted by Bora Shehu, VP of Product Design, with updates from John Merse (VP of Product), Fraser Bruce (Senior Solutions Consultant), Nicole Simmen (Senior Manager, Customer Implementation), and a customer story from Michael Duran (Operations Manager, Authentic Brands).
From quality of life improvements to brand new features, here’s what’s waiting for you in Gorgias.
Watch the full presentation here:
Agents shouldn’t have to dig for context. Every conversation now comes with Ticket Summaries. Whether an agent has jumped into a ticket mid-conversation or is dealing with a new customer, these AI-generated summaries tell the whole story in no time.
We’ve also given the Customer Timeline a makeover. Now, you can glance at past tickets and order updates in one clean view. Plus, a dedicated Order View lets agents dive into past purchases without leaving the ticket or opening a new tab.

Agents have always had visibility into customer history, but now that context is easier to act on.
Ticket Fields automatically tags tickets with AI-detected reasons, whether that’s shipping questions or product feedback, to help organize your conversations more effectively.
Then, add in another layer of data using Customer Fields (in beta) to note whether you’re speaking to a longtime, VIP customer or a customer with a history of high returns.
All of this data can be funneled into your ticket reports, making it easier for your team to discover new insights about your products, support quality, and more.

Taking your brand global doesn’t have to mean hiring a whole new team or spending extra on a localization tool. AI-powered translations (in beta) will soon be available on the helpdesk.
Finally, your team will be able to support customers in any language in real-time. Customers write in their native language, agents respond in theirs, and the exchange feels natural on both sides.

How many times has an urgent ticket been buried at the bottom of your inbox? The new Priority Scoring system prevents that by automatically labeling tickets as Low, Normal, High, or Critical based on your Rules.
For example, you might label a negative Facebook comment with threatening sentiment as ‘High,’ or bump high-value shoppers to the top with a ‘Critical’ label. This ensures your team always sees the conversations that need the most attention, so no sensitive issue slips through the cracks.
Now in beta, our flow-based IVR (interactive voice response) system lets teams on Gorgias Voice build customized call journeys for every type of conversation. Route customers through interactive menus, segment them based on their data, or direct them to voicemail, and schedule SMS follow-ups and callbacks.
To match agent availability, you can set business hours per phone number and per channel across storefronts. Teams also have more flexibility with ring strategies (ring available agents all at once or one at a time), wrap-up time between calls, and faster availability refreshes.

We understand that CX teams need more than surface-level KPIs—they need to know what’s actually driving performance, revenue, and retention.
With Dashboards, you can build reports focused on CX data you care about, from agent performance to product return trends. Then, filter by store or sub-brand to zoom in on the details each team is responsible for.
We’re also introducing the Human Response Time metric to show how quickly your team responds to escalations from AI Agent. This gives you a clear sign of what issues require human attention, how fast they’re resolved, and whether you need to adjust staffing.

Leave the moving to us—we now manage migrations in-house. Depending on your plan, our Implementation team will transfer emails, customers, macros, and more for you. Combined with 99.99% uptime, switching platforms is smoother, faster, and more reliable than ever.
For accelerated performance, consider our 50-in-50 implementation program, which aims to resolve 50% of your ticket volume using AI Agent within 50 days.
Enterprise customers receive a dedicated Enterprise CSM, optimization workshops, and 24/7 support to get the most out of Gorgias from day one.
Our teams are hard at work changing the landscape of customer experience. Here’s what’s on the Gorgias Product Roadmap:
Our latest helpdesk updates make it easier than before to create memorable customer moments.
As Bora Shehu, our VP of Product Design, said, “We hope that the tools we’re building help you spend less time on robotic work, and more time on impactful human work that grows your businesses through the power of conversations.”
If you’re not on Gorgias yet and want to see what’s possible, book a demo today.
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TL;DR:
While your competitors are still making customers wait days for email replies, the smartest brands are having conversations that close sales in real time.
Instead of forcing customers to search through FAQs or go through an automation loop, conversational commerce lets you have instant chats through live chat, messaging apps, and even AI assistants.
In this guide, we’ll explain conversational commerce, where it delivers the most value, and how to start using it to drive revenue and improve CX without overwhelming your team.
Conversational commerce means using real-time, two-way conversations as your storefront. Rather than bottling up questions in FAQ pages or forcing customers to wait for your support team to respond, you can instantly connect via:
Maybe someone is on your product page and asks a question like, “Does this jacket run large?”. Through chat, they get an instant answer, increasing the chance of a sale. Or a shopper receives personalized recommendations via WhatsApp and checks out, all without leaving the app.
These channels allow you to meet customers where they already are, effortlessly. When paired with AI chatbots, you can deliver fast, accurate responses 24/7, even while your team is off the clock. That means better experiences for your customers and more sales captured for your brand.
Conversational commerce bridges the gap between shopping and support. It turns your support team (and AI tools) into revenue drivers by helping shoppers feel seen, heard, and ready to buy.
Conversational commerce means bringing your storefront into the flow of conversation, wherever that happens for your customers.
Here’s where those conversations typically happen:
This is a chat widget on your site, often in the bottom right corner, where shoppers can ask questions and receive immediate answers from a human agent or automation.
It’s a quick path to support or purchase, which one agent can manage multiple chats from simultaneously, boosting efficiency and keeping things personal.
These smart helpers use Natural Language Processing (NLP) to understand what shoppers mean beyond what they type. They guide customers through questions, offer product suggestions, handle FAQs, and can sometimes complete transactions right in the chat, even handling post‑purchase support like order status or returns.
Natural Language Processing (NLP): The processing of understanding and interpreting natural language using computers. NLP is used in tasks such as sentiment analysis, summarization, speech recognition, and more.
Think WhatsApp, Facebook Messenger, WeChat, and SMS—the apps where customers already spend their time in their day-to-day. Instead of sending them to shop on your website, you bring the shopping to them. Answer their questions, provide recommendations, and win purchases in a channel they already trust.
Voice assistance isn’t limited to smart speakers like Siri and Alexa anymore.
Now, AI voice support lets brands deliver natural conversations over the phone, without needing a massive contact center team. These AI voice agents can:
AI-powered voice support combines the human feel of a phone call with the speed and accuracy of automation. It's especially useful for high-ticket products, customers who prefer calling, or peak season overflow when your human team is maxed out.
Conversational commerce isn’t a CX buzzword. When done right, it directly impacts your bottom line.
Here’s how it pays off for ecommerce brands:
When customers can ask questions and get answers in real time, whether it's sizing info, shipping details, or help choosing between products, they’re far more likely to hit “buy.”
Success story: Clothing brand Tommy John generated $106K+ in sales in just two months through conversation-led upselling and cross-selling, with a 15% conversion rate.
Conversational commerce tools like AI agents help offload the repetitive support tasks, including answering questions like “Where’s my order?” or “What’s your return policy?”
With that time back, agents get time back to:
Instead of getting buried in basic tickets, your team gets to do the work that really moves the needle for your customers and your business.
Related: Every successful marketing campaign starts with a customer question
The right nudge at the right moment, like a personalized recommendation from an AI shopping assistant, can turn a single item into a full cart. You can also recover more abandoned checkouts by re-engaging customers directly through chat or a messaging app.
Read more: You’re missing out on sales without an AI shopping assistant—here’s why
Conversational commerce lets you meet customers with a human (or human-like) touch. When your brand is helpful, fast, and easy to talk to, shoppers remember and return.
In the long run, that means better customer retention, higher lifetime value, and more organic growth through word of mouth.
Conversational commerce shines brightest when the stakes are high or when the moment is just right.
Here are the critical moments where a real-time conversation can make all the difference:
A customer’s on your product page, they’ve added an item to their cart, but are hesitating. Maybe they’re unsure about sizing, shipping time, or which variation to choose. This is where a quick, helpful chat, automated or human, comes in and becomes the difference between bounce and conversion.
Pro tip: Use proactive chat prompts based on page behavior to start the conversation before the shopper leaves.
After a customer hits “place order,” expect more questions to roll into your inbox. Where’s my order? How do I track it? What’s your return policy? Post-purchase excitement—and anxiety—is normal, and a smart AI agent helps you get ahead of these questions while putting customers at ease.
Black Friday. Holiday rush. Product drops. These are prime opportunities to boost revenue—but they also flood your support team. Conversational commerce tools help you scale without sacrificing quality, keeping shoppers happy and sales flowing.
If you sell skincare, supplements, tech, or anything that requires a bit of education, your customers likely need guidance before they commit. A personalized conversation helps them find the right fit and feel more confident in their purchase.
Conversational commerce sounds exciting, and it is. But before you dive in, it’s worth thinking through a few key factors to set your team (and your customers) up for success.
You don’t need a full-blown chatbot army on Day 1. Start with your highest-impact touchpoints, like pre-sale FAQs or WISMO questions, and layer in automation over time. The goal is to generate clear ROI early, then expand once you see traction.
Here’s how to gradually implement automation into your CX process:
The goal isn’t to automate everything, it’s to automate smartly so your team can spend time where it counts: high-touch sales, VIP support, and strategic growth.
Do you have in-house agents ready to handle live chat? Or do you need automation to handle the bulk of it? Make sure your setup aligns with your team’s bandwidth.
Pro tip: Tools like Gorgias AI Agent and Shopping Assistant can handle the support and sales heavy lifting, making them perfect for lean CX teams.
Your customers aren’t just on your website. They’re messaging on Instagram, browsing via mobile, or checking their texts. To deliver great conversational commerce, you’ll want to show up in the places your shoppers already use.
Pro tip: Don’t spread your efforts too thin. Start with the channel that aligns with your goals and customer behavior, live chat, SMS, or social DMs, and build from there.
Ready to make conversational commerce part of your CX strategy? You don’t need to overhaul your tech stack or hire a whole new team. With Gorgias, you can start fast, stay lean, and scale smart.
Here’s how:
Gorgias AI Agent is designed to take repetitive tickets off your team’s plate, from “Where’s my order?” to “How do I make a return?” It understands natural language, pulls in relevant customer data, and responds in seconds—all using your brand’s approved knowledge.
The result is faster responses, fewer tickets, and more time back for your team.

While AI Agent, covers the support front, Shopping Assistant is your digital salesperson. It engages high-intent shoppers in real time, recommends the right products, and even upsells or cross-sells based on what the customer is browsing.
Whether it’s helping someone choose the perfect shade or nudging them to complete their cart, Shopping Assistant is designed to increase AOV and reduce abandonment.

Every time a shopper lands on your site, scrolls through Instagram, or replies to a shipping update, they’re opening the door to a conversation. The brands that show up quickly, helpfully, and with the right message, are the ones winning loyalty and revenue.
With AI Agent, you can automate accurate responses to common questions, giving your team time back without sacrificing customer experience. And with Shopping Assistant, you can turn those conversations into conversions, offering personalized recommendations, upsells, and discounts based on shopper intent.
You don’t need a massive team or months of setup to start. Just the right tools, and a strategy built for your customers.
Book a demo and learn how Gorgias helps you turn every conversation into an opportunity to grow.
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TL;DR:
Every delayed reply, missed ticket, or frustrated customer costs more than just satisfaction—it hits revenue, loyalty, and your brand reputation. That’s why more and more brands are investing in AI helpdesks to automate the tedious parts of their job.
But with so many options on the market, choosing the right AI helpdesk can feel overwhelming. Should you prioritize conversational AI? Multi-channel support? No-code customization? Or pricing that scales with your team?
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We’ve reviewed the 10 best AI helpdesks available in 2025, evaluating them across AI capabilities, ease of use, integrations, analytics, and pricing.
Helpdesk |
AI Features |
Main Strength |
Potential Limitation |
Best For |
Starting Price |
|---|---|---|---|---|---|
Gorgias |
AI Agent, Shopping Assistant, Auto QA |
Multi-channel ecommerce support, AI shopping assistant |
Ecommerce-focused |
Scaling and enterprise ecommerce brands |
$10/month per agent |
Zendesk |
Copilot, AI triage, Zendesk QA |
Enterprise-grade omnichannel support |
Can be complex for smaller teams |
Large enterprises like banks and airlines |
$25/month per agent |
Intercom |
Fin AI, Fin Tasks, Fin Insights |
Conversational AI, proactive support |
Higher learning curve for complex workflows |
SaaS and mid-to-large businesses |
$39/month per agent |
Gladly |
Gladly Hero, Sidekick Chat, Sidekick Voice |
Conversation-centric support, loyalty focus |
Complex implementation onboarding process |
Customer-focused businesses that prioritize loyalty |
Custom pricing |
Kustomer |
AI Agents for Reps, AI Agents for Customers |
CRM-centric support |
Unintuitive and laggy user interface |
Mid-to-large enterprises |
$89/month per agent |
Tidio |
Lyro AI Agent |
Easy-to-use automation for small teams |
May not scale for large enterprise workflows |
Small to mid-sized ecommerce/service businesses |
Free, $29/month per agent |
Freshdesk |
Freddy AI |
Affordable multi-channel support |
Advanced AI limited to higher tiers |
SMBs and mid-market companies |
$18/month per agent |
Ada |
Ada Voice, Ada Email |
Self-service chat automation |
Basic features cost extra |
Large enterprise businesses |
$499/month |
Siena |
Customer Service Agent, Reviews Agent, Siena Memory |
Automated support |
Lack of visibility into support and AI performance |
Mid-market ecommerce and SaaS |
$500/month |
Yuma |
Support AI, Sales AI, Social AI |
Self-service & automation for growing teams |
Limited integrations with broader sales stacks |
Established ecommerce brands |
$49/month per agent |
To create this list, we evaluated each platform based on a combination of functionality, AI capabilities, usability, and industry applicability.
Our goal was to provide a resource that CX leaders, ecommerce managers, and support teams can rely on when choosing a helpdesk that fits their business needs.
Here’s how we approached the evaluation:
By following this methodology, we created a balanced, objective view of each helpdesk, highlighting what makes them unique, their strengths, limitations, and who will benefit most from them.
Gorgias is an AI helpdesk designed for ecommerce brands, helping teams streamline support while boosting both efficiency and personalization.
By unifying all customer touchpoints—email, chat, social media, voice, and SMS—into a single dashboard, Gorgias allows support teams to manage interactions without toggling between platforms.
Unlike most helpdesks, its AI capabilities go beyond basic automation. In addition to support, its AI can influence sales by assisting, recommending, and upselling to customers based on their shopping behavior.
Best for: Scaling startups and mature ecommerce enterprises looking to expand support capacity without increasing headcount
Potential limitations: Gorgias is focused primarily on ecommerce brands, which means it may be less suitable for companies that don’t use ecommerce platforms.
Pricing: Starts at $10/month, with advanced AI features available as an add-on.
Main features:
AI features:
Zendesk is a widely adopted AI helpdesk solution that caters to teams of all sizes, from small businesses to large enterprises. It’s known for its robust ticketing system, extensive integrations, and customizable workflows, making it a versatile choice for teams across industries.
Best for: Non-ecommerce enterprises and businesses like airlines and banks
Potential limitations: Advanced AI features and enterprise-level plans can be expensive for smaller teams, and some users report that customization for niche workflows can be time-consuming.
Pricing: Starts at $25/month per agent, with advanced AI features and enterprise options available on higher tiers.

Main features:
AI features:
Intercom combines live chat, messaging, and AI automation into a single platform that focuses on proactive customer engagement. Its conversational AI makes it easy for teams to interact with customers in real time, while its automation tools help reduce response times and increase efficiency.
Best for: SaaS companies, software companies, and mid-market teams
Potential limitations: Companies looking for a plug-and-play AI solution will need to invest time in setting up Intercom. Customers report a steep learning curve when creating workflows, organizing users, and implementing new automations.
Pricing: Starts at $39/month per seat. Fin AI is available as a standalone product for $0.99 per resolution (50 resolutions per month minimum) if you have an existing helpdesk.

Main features:
AI features:
Gladly is a customer service platform built around the concept of conversation-centric support, treating every customer interaction as a continuous dialogue rather than isolated tickets.
Best for: Customer-focused brands that prioritize personalized, ongoing conversations over transactional support—especially retail, financial services, and subscription businesses that want to strengthen loyalty.
Potential limitations: Smaller teams may find it more than they need, and advanced customization can require professional services.
Pricing: Available on request, with plans typically tailored to enterprise support teams and scaled based on users and features.

Main features:
AI features:
Kustomer is a CRM-centric AI helpdesk that integrates customer support and relationship management in one platform. Its AI capabilities allow teams to automate repetitive tasks, route tickets intelligently, and gain insights into customer history, making it ideal for businesses with complex support workflows.
Best for: Mid-to-large enterprises that prioritize powerful, custom reporting
Potential limitations: Users report an unintuitive and laggy interface, which can slow down large support teams that handle high support volumes.
Pricing: Starts at $89/month per seat, with AI features available as add-ons.

Main features:
AI features:
Tidio is an AI-powered live chat and messaging platform built for small to mid-sized businesses looking to combine automation with personalized support. Its ease of setup and affordability make it a strong choice for teams new to AI helpdesks.
Best for: Small to mid-sized ecommerce or service-based businesses looking for an easy-to-use AI chat solution to automate FAQs
Potential limitations: May not scale well for large enterprise businesses.
Pricing: A free plan is available, with paid plans starting at $29/month per agent and AI features as add-ons.

Main features:
AI features:
Freshdesk is a helpdesk platform that combines AI automation, omnichannel support, and workflow management. It’s known for ease of use and affordability, making it popular among SMBs and mid-market companies.
Best for: SMBs and mid-market companies looking for an affordable, easy-to-implement AI helpdesk
Potential limitations: Some advanced AI functionality is limited to higher-tier plans. Large enterprises may require additional configuration to fully leverage AI features.
Pricing: Plans start at $18/month per agent, with AI capabilities and advanced automation available on higher tiers.

Main features:
AI features:
Not ready to move helpdesks? These standalone AI tools plug into your existing helpdesk to add automation, self-service, and conversational support.
Ada is focused on conversational automation, enabling teams to provide self-service solutions that reduce ticket volume while improving response times.
Its no-code interface makes it accessible for non-technical teams, and its AI capabilities allow for personalized customer interactions at scale.
Best for: Large enterprise businesses looking to reduce support tickets through chat-based support
Potential limitations: Basic features that are free on competitor platforms cost extra on Ada, which limits smaller businesses looking for an all-in-one solution.
Pricing: Starts at $499/month for essential AI features. Higher-tier plans are available on request.

Main features:
AI features:
Siena is focused on providing automated support for rapidly growing ecommerce and SaaS brands. With an emphasis on efficiency and self-service, Siena helps teams reduce ticket volume and respond faster, while giving managers visibility into performance metrics.
Best for: Mid-market ecommerce and SaaS companies that want to combine automation with insights
Potential limitations: Lacks clear visibility into AI performance, which can keep support teams in the dark about support performance and customer satisfaction.
Pricing: Starts at $500/month with automated tickets at $0.90 each.

Main features:
AI features:
Yuma is focused on conversational automation and self-service solutions. It is designed to reduce agent workload while providing fast, personalized responses, making it appealing to growing ecommerce teams.
Best for: Established ecommerce brands looking to integrate sophisticated conversational AI alongside their current helpdesk
Potential limitations: Limited integrations with broader sales stacks mean brands prioritizing sales will have a hard time creating a smooth workflow.
Pricing: Starts at $350/month for 500 resolutions, with higher-tier plans for more resolutions.

Main features:
AI features:
The best AI helpdesk makes support efficient, personalized, and scalable.
Here’s a quick checklist of what to look for when evaluating an AI helpdesk:
|
Feature |
What It Is |
Benefit to CX Team |
|---|---|---|
|
Smart ticket management |
AI that deflects repetitive tickets and routes complex issues to agents via macros, recommendations, and copilots |
Frees up time for higher-value tasks like customer retention and streamlined experiences |
|
Self-service workflows |
Automated execution of order edits, address changes, refunds, and cancellations—whenever customers ask |
Eliminates time spent on repetitive requests while offering 24/7 support |
|
Multi-channel support |
All-in-one platform consolidating email, chat, SMS, social media, and phone interactions |
Eliminates the need to switch between platforms while giving customers a variety of contact options |
|
Sales and upselling capabilities |
AI that analyzes shopper behavior and delivers targeted assistance, product recommendations, and offers |
Maximizes revenue impact for CX teams by directly influencing customer buying decisions |
|
User-friendly AI controls |
Intuitive tools and toggles for adjusting AI behavior through knowledge bases |
Allows teams to test and deploy AI quickly without technical expertise |
|
Performance insights |
Dashboards displaying performance metrics, support KPIs, revenue impact, plus custom reporting |
Maintains support quality while providing scalable insights that grow with your business |
|
AI learning and improvement |
Quality assurance features that improve AI through feedback, corrections, and knowledge updates |
Enables accurate responses that lead to consistent support quality and increased customer satisfaction |
The future of customer support is AI-driven, and the tools you choose today will define the efficiency, responsiveness, and satisfaction of your support team tomorrow.
If it's still early in your AI helpdesk journey, we have additional resources to help you learn more from the pros before getting started:

TL;DR:
You don’t need more software—just better usage: Atidiv transforms existing tools like Gorgias into engines for efficiency, growth, and retention.
If you’re like most ecommerce brands, you’ve invested in great tools like Gorgias to streamline support, automate workflows, and deliver personalized experiences at scale. But here’s the hard truth: Having the tools doesn’t mean you’re using them well.
We see it all the time. Gorgias is live, Macros are written, a few Rules are set, and then… chaos. Tags go unused, dashboards lack insight, and your agents are still drowning in tickets.
That’s why leading brands aren’t just buying tech, they’re partnering with teams who know how to use it. That’s where Atidiv comes in.
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Gorgias is a powerful platform. Out of the box, it gives you:
But without the right people using these tools effectively, it’s just noise. Atidiv’s CX specialists are trained Gorgias power users, and they make sure every feature works hard for your brand.
Here’s how Atidiv leverages Gorgias to drive real results:
Atidiv agents don’t just respond to tickets, they tag every interaction with purpose.
This turns your inbox into a live dashboard of customer sentiment, product feedback, and emerging trends, no extra software required.
Atidiv writes and maintains Macros that go beyond “Thanks for reaching out.”
These aren’t just canned replies—they’re crafted CX responses built to scale.

Enhance your Macros with tags, snooze rules, Shopify actions, and other dynamic variables.
Every Atidiv client gets a customized Gorgias dashboard. It’s built by Atidiv’s Team Leads to track what matters:
No more wondering if your support is working, now you know.
We use Gorgias Rules to route tickets, send auto-replies, and tag intents, reducing ticket clutter by up to 30%.
The result? Agents spend more time on high-impact conversations and less time chasing tracking numbers.

Run your support on autopilot with Gorgias Rules that automatically trigger based on your chosen conditions.
A fast-growing superfood brand came to Atidiv with Gorgias already live, but underutilized. They were answering tickets manually, tracking performance in spreadsheets, and dealing with repeat questions daily.
Within 30 days, Atidiv helped them:
And no, they didn’t need to buy any new tools.
Most brands think their next CX win will come from another app or integration. But the real unlock often comes from better use of what they already have.
That’s what Atidiv offers:
You don’t need to overhaul your tech stack. You need a team that can turn Gorgias into a strategic engine for support, growth, and insight.
Atidiv makes it possible, with trained agents, experienced leaders, and a deep understanding of what Gorgias can do when used to its full potential.
→ Want to get more out of the tools you already have? Let’s talk about how Atidiv + Gorgias can transform your support operation.

TL;DR:
If you’ve been side-eyeing AI and wondering if it’s just hype, you’re not alone. A lot of CX leaders were skeptical, too:
“I used to be the loudest skeptic,” said Amber van den Berg, Head of CX at Wildride. “I was worried it would feel cold and robotic, completely disconnected from the warm, personal vibe we’d worked so hard to build.”
But fast forward to today, and teams at Wildride, OLIPOP, bareMinerals, and Love Wellness are using AI to do more than just deflect tickets. They’re…
Here are six lessons you can steal from the brands doing it best.
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We need to get one point across clearly: AI isn’t about replacing your support team.
For brands with lean CX teams, burnout is a serious problem. And it’s one of the biggest reasons AI adoption is accelerating.
“I was constantly seeing the same frustrating inquiries—sponsorship asks, bachelorette party freebies, PR requests… 45% of our tickets were these kinds of messages,” said Nancy Sayo, Director of Consumer Services at global beauty brand, bareMinerals.
“Once I realized AI could handle them with kindness and consistency without pulling in my team, I was sold.”

Instead of thinking of AI as a replacement, think of it as an enhancement.
It’s about making sure your CX team doesn’t burn out answering the same five questions 50 times a day.
With Gorgias AI Agent, Nancy’s team now uses automation to absorb the high-volume, low-conversion noise, freeing up their seasoned agents to focus on real revenue-driving moments.
“We use AI to handle low-complexity tickets. And we route higher-value customers to our human sales team—people who’ve been doing makeup for over a decade and really know what they’re doing.”
TL;DR? The smartest teams use AI to take the weight of repetitive tickets (“Do you ship internationally?” “Can I get free samples?”) off their shoulders so agents can focus on conversations that build trust, drive loyalty, and increase LTV.
While you can get started with AI quickly for simple queries, we don't recommend using it “out of the box.” And honestly, that’s a good thing.
Brands that “set it and forget it” are missing the point. Because if you want AI to sound exactly like your brand—not like every other chatbot on the internet—you need to give it the same context you’d give a new hire.
Amber van den Berg, Head of Customer Experience at baby carrier brand Wildride, wrote out detailed tone guidelines, including:

“Lisa, our AI agent, is basically a super well-trained intern who never sleeps. I give her the same updates I give my human team, and I review Lisa’s conversations every week,” said Amber. “If something feels off-brand, too robotic, or just not Wildride enough, I tweak it.”
The feedback never stops, and that’s what makes Lisa so effective.
Related: Meet Auto QA: Quality checks are here to stay
Even when AI gets it right, customers might not always feel like it did. Especially if the tone of voice is off or if your customer base just isn’t used to automation.
“Our CSAT was low at first,” said Nancy Sayo of bareMinerals. “Even if the response was accurate and beautifully written, our older customers just didn’t want to interact with AI.”
So Nancy’s team adapted. Rather than giving customers a blunt “no” to product requests, they restructured the flow:
“If someone asked for free product, we’d say, ‘We’ll send this to the team and follow up.’ Then, 3-5 days later, the AI would close the loop. It softened the blow and made customers feel heard—even if the answer didn’t change.”
That simple tweak raised CSAT and created a better customer experience without requiring a human to step in.
Inside Gorgias, teams like bareMinerals review AI performance weekly, not just to catch mistakes, but to optimize for tone, satisfaction, and brand feel. They use:
AI gives you the flexibility to test, tweak, and tailor your approach in a way traditional support channels never could.

Too many CX teams still treat AI like a glorified autoresponder. But the most forward-thinking brands are using it to guide shoppers to checkout.
“Our customers often ask: ‘Which carrier is better for warm weather?’ or ‘Will this fit both me and my taller partner?’” said Amber van den Berg, Head of CX at Wildride. “Lisa doesn’t just answer—she gives context, recommends features, and highlights small touches like the fact that a diaper fits in the side pocket.”
With Gorgias Shopping Assistant, brands can turn AI into a proactive sales assistant—answering product questions in real time, referencing what’s in the customer’s cart, and nudging them toward the best option with empathy.
Great support doesn’t stop at the inbox. At Love Wellness, CX is the connective tissue between ecommerce, product, and marketing.
“We meet quarterly with our CX and ecommerce teams to review top questions, objections, and patterns,” said Mckay Elliot, Director of Amazon at Love Wellness. “That feedback goes straight into product development and PDP optimizations on both DTC and Amazon.”
But it’s not just a quarterly ritual. Feedback sharing is embedded in the culture, and they do this with a Slack channel dedicated to customer feedback.
Dropping in insights is part of the team’s daily and weekly responsibilities. It helps everyone stay close to the content, and it sparks real collaboration on what we can improve. They then use those insights to improve ad messaging and content.

Your team has so much data they can review between channels like email, SMS, chat, and social media—both compliments and complaints. You need to be willing to listen to every customer’s needs.
Read more: Why customer service is important (according to a VP of CX)
One of the biggest mistakes brands make with AI? Trying to do too much, too soon.
Rolling out AI should feel like a phased launch, not a switch flip. The best results come from starting simple, testing often, and iterating as you go.
“We started with one simple question—‘Do you ship internationally?’—and built from there,” said Amber van den Berg of Wildride.
“And if it doesn’t work? You can always turn it off,” added Anne Dyer, Sr. Manager of CX & Loyalty Marketing at OLIPOP. “The key is to test, review, and keep iterating. AI should enhance your human experience, not replace it.”

If your helpdesk supports it, start in a test environment to preview answers before going live. Then roll out automation gradually by channel, topic, or ticket type and QA every step of the way.
For most brands, the best starting point is high-volume, low-complexity tickets like:
You don’t need to solve everything on day 1. Just commit to one question, one channel, and one hour per week. That’s where real momentum starts.
Related: Store policies by industry, explained: What to include for every vertical
Most CX teams are used to tracking classic metrics like ticket volume and CSAT. But when AI enters the mix, your definition of success shifts. It’s not all about how fast you handle tickets anymore—it’s about how customers feel after conversations with AI, team efficiency, and the quality of every interaction.
Here are the metric CX teams used to track without AI—and what they track now with AI:
|
Metrics Tracked Before AI |
Metrics Tracked After AI |
|---|---|
|
Total ticket volume |
% of tickets resolved by AI |
|
Average first response time |
Response time by channel (AI vs. human) |
|
CSAT (overall) |
CSAT + sentiment on AI-resolved tickets |
|
Tickets per agent/hour |
Time saved per agent + resolution quality |
|
Burnout rate or turnover |
Agent satisfaction or eNPS |
AI isn’t here to replace your CX team. It’s here to free them up, so they can focus on deeper, more meaningful conversations that build loyalty and drive revenue.
So if you’re on the fence, start small. Train it. Review weekly. Build the muscle.
You’ll be surprised how quickly AI becomes your favorite intern.
If you want more tips from the experts featured today, you can:

TL;DR:
If your CX team is juggling a dozen different tools just to answer one support ticket, you’re not alone. According to our 2025 Ecommerce Trends report, 42.28% of ecommerce professionals use six or more tools every day. Plus, nearly 40% spend $5,000–$50,000 annually on their tech stack.
That’s a lot of money and a lot of tabs.
It’s no wonder “tech stack fatigue” is setting in. But while many brands are ready to simplify, there’s still hesitation around consolidation. The biggest fear is that all-in-one tools are too rigid or basic to handle the complexity of a growing business.
But the truth is, consolidation doesn’t mean compromise. When done right, it means clarity, speed, and control. It also means fewer tools, smoother workflows, and faster customer support.
Let’s bust some myths and show you what smart consolidation looks like.
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One of the biggest blockers to consolidation is compatibility. Fifty-two percent of ecommerce professionals said they hesitate to consolidate because they’re worried about tools not playing nicely together.
That hesitation makes sense. In the past, “all-in-one” tools meant being locked into a single provider’s ecosystem, with limited integrations and rigid workflows. For CX teams managing fast-moving ops and dozens of tools, from email and returns to reviews and subscriptions, the idea of losing flexibility is a non-starter.
Modern support platforms have moved away from monolithic systems and toward modular API-friendly designs that give brands control instead of constraints.
If you choose the right platform, consolidation doesn’t lead to a loss of functionality. Instead, it means getting a better-connected system that works smarter.
Just ask Audien Hearing who uses Gorgias’s open API to create an integration with its warehouse software to manage returns directly in Gorgias instead of a shared Google spreadsheet.
They also combine the power of Gorgias Voice with an integration to Aircall to resolve thousands of questions a day. This integration enables agents to access customer and order data directly from Gorgias while on a call—staying in one workspace.
“It's amazing that we're able to create any custom solutions we want with Gorgias's open API. Gorgias is way more than a typical helpdesk if you utilize the features it offers,” says Zoe Kahn, VP of Retention and Customer Experience at Audien Hearing.

Read more: The Gorgias & Shopify integration: 8 features your support team will love
Another common hesitation around consolidation is the risk of putting all your eggs in one basket. If everything runs through one tool, what happens when something breaks or you need to pivot?
It’s understandable, many teams worry that one tool can’t possibly do everything well. Maybe it won’t support their preferred channels, or the automation will be too limited. Or maybe they’ve been burned by a platform that promised too much and delivered too little.
In reality, consolidating gives CX teams more freedom, not less.
Instead of stitching together half a dozen tools and hoping they sync, teams using a single, well-integrated platform gain:
Under one system, your team doesn’t have to jump between tabs anymore. They can just focus on helping customers, quickly and consistently.
Take it from Osea Malibu, a seaweed‑infused skincare brand that transformed their support quality assurance process using Gorgias Auto QA. Their manual QA system was time-consuming and couldn’t scale as ticket volume surged. But the switch made impressive improvements:

“Gorgias Auto QA saved me so much time. What used to take over an hour now only takes 15 minutes a week, and I no longer have to worry about spreadsheets.” —Sare Sahagun, Customer Care Manager at Osea Malibu
On paper, consolidation sounds smart. But 47.6% of ecommerce professionals say cost is a barrier, and 40.3% worry about the time it takes to implement a new system.
Sticking with a fragmented stack isn’t exactly cheap or quick, either. Between training new agents, managing multiple vendors, and patching together tools that don’t fully sync, the hidden costs add up fast.
It’s not actually consolidation that drains your resources—it’s complexity. And with Gorgias, simplifying pays off fast.
Trove Brands is a standout example. After centralizing their support with Gorgias, they implemented AI-powered order cancellation workflows and saw:

Related: The hidden cost of not adopting AI in ecommerce
The biggest benefit of fewer tools is efficiency. It’s also a direct line to real business impact.
Constant tab-switching and duplicate data entry mean way too much time spent managing platforms instead of helping customers.
When you consolidate your tech stack, your team spends less time learning new systems, chasing down info, or waiting for one tool to sync with another.
Instead, they get everything they need in one place, faster replies, smoother workflows, and happier customers.
And that all adds up to better CSAT, lower churn, and a support team that’s finally free to focus on what matters.
Gorgias is built specifically for ecommerce brands, with features that reflect the way CX teams actually work.
As Shopify’s only Premier Partner for customer support, we offer a native integration that pulls in key order data and context automatically, so agents have everything they need without switching platforms. That means conversations, AI, automation, revenue data, and reporting are in one place.
Our open app ecosystem allows you to connect to 100+ tools like Shopify, Klaviyo, Yotpo, and Recharge in just a few clicks. Need more customization? Our add-ons, like AI Agent and Voice let you level up at your own pace.
Whether you're handling hundreds of tickets a week or scaling globally, Gorgias adapts—so you don’t have to keep reinventing your support stack every six months.
Dr. Bronner’s, a globally recognized organic soap and personal care brand, made the switch from Salesforce to Gorgias to keep up with growing support demands, and it paid off fast.
Here are the results they saw with Gorgias:
“We don’t get boxed out because we only work with Gorgias tools. Gorgias deeply understands the needs of CX, Shopify, and orders and how those tools work together so that it’s really easy for us to work across the board throughout those tools and that didn’t exist in our last setup at all,” says Emily McEnany, Senior CX Manager at Dr. Bronner’s.
If you’re still stitching together half a dozen tools to handle support, it might be time to ask: Is your tech stack helping you or holding you back?
With Gorgias, you get centralization and flexibility, so your team can move faster, serve better, and scale smarter.
Book a demo or dive into the full 2025 Ecommerce Trends report to see how other brands are rethinking their stacks.
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TL;DR:
Shoppers aren’t always going to reach out and ask the questions they have, especially if they’re going to have to wait for a response from a CX team.
That means you’re losing sales to friction, indecision, or information gaps.
In 2025, the average cart abandonment rate is 70.19%. But if you can find an AI tool that doubles as a support and sales agent, it could make all the difference.
Gorgias’s Shopping Assistant, for example, has brought a 62% uplift in conversion rate for brands that implement it.
Ahead, learn where you can leverage an AI shopping assistant to increase conversions and craft better purchase experiences.
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An AI shopping assistant is a chat tool powered by AI to provide pre-sales support for shoppers. It can answer questions, make product recommendations, and help guide shoppers in the right direction if they’re stuck.
Gorgias's Shopping Assistant is a powerful, hyper-personalized AI tool built for Shopify brands. Unlike other AI tools, Shopping Assistant starts conversations with customers, not the other way around. It’s uniquely tailored for each customer by tracking browsing behavior during each session and remembering what shoppers say, keeping conversations natural and recommendations relevant.
It’ll also chat with shoppers in your own brand voice, as its responses are pulled right from the knowledge you feed it.
The stages of the customer journey where common drop-off points occur for brands that lack proactive support include:
There’s a big chance that shoppers—especially first-timers—have questions, but aren’t willing to wait for a human to get back to them. And when your CX team is off the clock? Customers will likely leave altogether.
An AI shopping assistant can help you engage customers right away, even outside your business hours.
Bra brand Pepper uses Gorgias Shopping Assistant to help shoppers find their perfect size. When it detects hesitation, Shopping Assistant points customers to the sizing guide.
This proactive approach creates an easy path for conversation and sets the precedent that any questions will be answered immediately, providing a better––and less confusing––experience.

“With Shopping Assistant, we’re not just putting information in our customers’ hands; we’re putting bras in their hands,” says Gabrielle McWhirter, CX Operations Lead at Pepper.

For shoppers in the Discovery stage, using a Shopping Assistant boosts clicks and time on site and reduces bounce rate. It does this by surfacing specific questions on relevant product pages. Pepper boosted their conversion rate by 19% with Gorgias Shopping Assistant.
Read more: How Pepper’s AI Agent automates 54% of support and converts 19% of conversations
In a retail environment, a salesperson can give shoppers recommendations by asking a few questions, especially if they’re unsure of what to buy.
AI shopping assistants have the ability to mirror those in-person shopping experiences by interacting with customers in real-time to help them find their perfect match.
Shoppers can give as much (e.g., “Help! What dress is suitable for a wedding reception?”) or as little information as they’d like, and the AI shopping assistant will do the rest.
It’s possible even for questions that are slightly vague, like a customer who types in “how to make up” without any other context:

For example, jewelry shop Caitlyn Minimalist uses Shopping Assistant to recommend products, engaging interested customers and bringing them closer to a purchase.

“As a result of Shopping Assistant, we've seen a measurable lift in AOV through more meaningful customer interactions,” says Anthony Ponce, Head of Customer Experience at Caitlyn Minimalist.
“Our clients are provided the right information at the right time, creating a seamless experience that builds trust and drives confident purchases."
According to data from Gorgias, email is the highest volume support channel, with ~25% of that tied to pre-sales. AI shopping assistants tackle these pre-sales asks and also upsell by recommending complementary products. This can lead to a boost in average order value (AOV) and conversion rate.
Read more: How Caitlyn Minimalist uses Shopping Assistant to turn single purchases into jewelry collections
The main reasons customers abandoned a cart in 2025 include:
An AI shopping assistant can mitigate or resolve these issues. They resolve crucial questions—like delivery time or return policies—that need in-the-moment answers. By alleviating pre-sale concerns, they give customers the confidence to make a purchase.
For example, bidet brand TUSHY leverages Shopping Assistant to answer questions about toilet compatibility that might flush a pending sale.

Aside from quelling customer concerns, Shopping Assistant can also send discount codes to close deals. Unlike general discount codes you find across the internet, these discounts are uniquely generated for each customer, keeping them engaged and on your site.
AI shopping assistants can reduce cart abandonment rate and increase conversion rate. Gorgias Shopping Assistant adjusts to your sales strategy by sending customers discount codes that can be the final nudge to checkout.
Most AI tools are built just for support. They deflect tickets and answer FAQs, but they’re not built to sell.
Shopping Assistant proves that support teams can also drive revenue by upselling, suggesting exchanges, and giving shoppers the confidence to try a brand for the first time (or to give it another shot).
Gorgias’s AI Shopping Assistant uses context-based decision making and looks for specific behavioral signals:
|
Feature |
Traditional Chatbot |
AI Shopping Assistant |
|---|---|---|
|
Deflect tickets |
✅ |
✅ |
|
Answer frequently asked questions |
✅ |
✅ |
|
Upselling |
❌ |
✅ |
|
Proactively reaching out to offer support |
❌ |
✅ |
|
Use context-based signals to guide shoppers to checkout |
❌ |
✅ |
Ultimately, the cost of not adopting AI can be higher than the investment of implementing it. 77.2% of ecommerce professionals use AI to improve their work. Why not extend those benefits to your customers?
AI Shopping Assistants help you create better customer experiences overall. These tools help reduce customer effort, increase average order value, save would-be-lost sales, and create more customer touchpoints.
Hire the always-on Shopping Assistant that never misses a sale.
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