

TL;DR:
The way shoppers buy online has shifted and customers are at the center.
They no longer want to scroll through product pages, dig through FAQs, or wait 24 hours for an email reply. They open a conversation, ask a specific question, and expect a useful answer in seconds. Brands that can’t deliver these experiences at scale are seeing customer hesitation turn into abandoned carts and lost revenue.
This shift has a name: conversational commerce. It's the practice of using real-time, two-way conversations as your primary sales channel, through chat, AI agents, messaging apps, and voice.
What started as an experiment for early adopters has become a key growth lever, with 84% of ecommerce brands treating conversational commerce as a strategic pillar this year vs. last year.

We surveyed 400 ecommerce decision-makers across North America, the U.K., and Europe to understand how conversational commerce and AI are reshaping the ecommerce landscape. These findings are complemented by aggregated and anonymized internal Gorgias platform data from 16,000+ ecommerce brands.
The State of Conversational Commerce in 2026 trends report breaks down all of the findings, including five key trends shaping the ecommerce landscape.
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A few years ago, adding an AI chatbot to your site that could provide tracking links and Help Center article recommendations was a differentiator. Today, it's table stakes. McKinsey found that 71% of shoppers expect personalized experiences, and 76% get frustrated when they don't get them.
Right now, most ecommerce professionals use AI, with 93% having used it for at least 1 year. Enthusiasm is accelerating quickly, with only 30% of ecommerce professionals rating their excitement for AI at 10/10 in April 2025. Similarly, while AI adoption rose steadily year over year, it reached a clear peak in 2026.

The use cases driving this adoption are practical and high-volume:

These are the tickets that flood brands’ inboxes every day. AI agents resolve them instantly, without pulling teams away from conversations that actually require human judgment.
Explore AI adoption and use case data in more depth in the full report.
The traditional ecommerce funnel, visit site, browse products, add to cart, check out, is losing ground. Shoppers now discover products on Instagram, ask questions via direct message, and complete purchases without ever visiting a website.

Conversational AI is actively increasing revenue, with 79% of brands reporting that AI-driven interactions have increased sales and conversion in their business.

The practical implication is that every channel is becoming a storefront. Creating personalized touchpoints with customers earlier in the journey, through proactive engagement, is impacting the bottom line.
Read the full report to explore how AI conversions have increased QoQ by industry.
Pre-purchase hesitation is one of the biggest conversion killers in ecommerce. A shopper lands on your product page, has a question about sizing or compatibility, can't find the answer quickly, and leaves. That's a lost sale that had nothing to do with your product.
Conversational AI changes that dynamic. When a shopper can ask a question and get an accurate, personalized answer in real time, the friction disappears.
Brands using Gorgias saw this play out at scale in 2025. When AI Agent recommended a product, 80% of the resulting purchases happened the same day, and 13% happened the next day.

Brands are further accelerating the buying cycle through proactive engagement. On-site features such as suggested product questions, recommendations triggered by search results, and “Ask Anything” input bars drove 50% of conversation-driven purchases during BFCM 2025.
Explore how AI is collapsing the purchase cycle in Trend 3 of the report.
There's a persistent narrative that AI is making CX teams redundant. The data tells a different story. 62% of ecommerce brands are planning to grow their teams, not cut them. But the scope of those teams is changing.

New roles are emerging around AI configuration and quality assurance. Teams are investing in technical members to write AI Guidance instructions, develop tone-of-voice instructions, and continuously QA results.
CX teams are also bridging the gap between support goals and revenue goals, as the two functions increasingly overlap.

The result is CX teams that are more technical than they were before. Agents who once spent their days answering repetitive tickets are now spending that time on higher-value work: complex escalations, VIP customer relationships, and improving the AI systems and knowledge bases that handle the volume.
Learn more about the evolution of CX roles in Trend #4.
Despite increasing AI adoption, data shows that ecommerce brands shouldn’t strive for 100% automation. Winning brands are building systems in which AI handles repetitive tier-1 tickets, and humans handle complex, sensitive cases.

AI handles speed and scale. It resolves order-tracking requests at 2 a.m., processes return-eligibility checks in seconds, and answers the same shipping question for the thousandth time without compromising quality.
Human agents handle conversations that require context, empathy, or decisions that fall outside the standard playbook. There are several topics where shoppers still prefer human support.

Successful hybrid systems require continuous iteration, meaning reviewing handover topics, Guidance, and reviewing AI tickets on a weekly basis.
Discover how leading brands are balancing human and AI systems in Trend #5.
The 2026 trends are about expansion and standardization. The 2030 predictions are about what comes next.

Voice-based purchasing is the biggest bet on the horizon. Only 7% of brands currently use voice assistants for commerce, but 89% expect it to be standard by 2030. The vision is a customer who can reorder a product, check their subscription status, or manage a return entirely over the phone.
Proactive AI is the other major shift. Rather than waiting for a customer to reach out, AI will anticipate needs based on browsing behavior, purchase history, and where someone is in their relationship with your brand. Think of it as the digital equivalent of a sales associate who remembers what you bought last time and knows what you're likely to need next.
Explore where ecommerce brands are allocating their AI budgets in the full report.
The brands winning in 2026 are creating smart, scalable systems where AIhandles volume and humans handle nuance. They’re treating every conversational channel as an opportunity to serve and sell.
The data is clear: AI adoption is accelerating, customer expectations are rising, and the revenue impact of getting this right is measurable.
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TL;DR:
In 2025, chat’s growth outpaced email by 2.5x quarter over quarter. Chat has become our most powerful customer experience tool for how shoppers discover products, ask questions, and decide to buy.
We knew it needed an upgrade, so we reimagined the entire experience from the ground up.
The result is 36% more engagement with product recommendations, nearly 2.25x more shoppers add-to-cart, and 7.3% more customer engagement.
In this post, we'll walk you through our thinking, what’s new in Chat, and how brands are already seeing big gains.
Chat has outpaced email support. Today’s shoppers prefer the speed of quick chat conversations over email. And when shoppers make a new move, we watch, listen, and move with them.
This behavioral shift isn’t happening in isolation. It aligns with the rise of conversational commerce and proves a universal move toward real-time conversations in ecommerce.
In fact, the signals were already there. Two years of building AI Agent showed us just how much design shapes behavior. The interface is the experience, and we knew that pushing chat experiences to closely resemble human interactions would transform how shoppers engage.
Our new and updated chat brings that vision to life. We believe that shopping is moving from static pages to conversations. This new update is built for how people actually want to shop.
The new design turns live chat into an interactive shopping surface made for modern shoppers. We've brought together multiple ways for shoppers to jump into chat, added clickable replies instead of typing, browsable product cards right in the conversation, and quick cart access.
Let's walk through what's new.
Chat now comes in a softer color palette that adapts to your store’s branding. We removed message bubbles in favor of an airy design that brings in the familiarity of speaking to your favorite conversational AI assistant. Every interaction now has the breathing room for deeper conversation and personalization.

It’s now easier for shoppers to get an answer with quick reply buttons and suggested questions in Chat. This replaces the tree-based flows of the previous Chat, removing the need to follow a fixed path. Shoppers can find answers faster without typing text-heavy explanations.

Browsing and buying within Chat is now possible. Previously, it only supported product links that would open in a new page. With the upgrade, you can view item details without leaving the conversation. Shoppers can browse, compare products, and add to cart in one place.

We’re keeping the context by removing the external redirects. The new interface lets shoppers browse product recommendations right in chat. View key product details, images, descriptions, variants, and pricing without opening a new tab.

Chat adds clickable questions on product pages — like “Is this true to size?” or “What’s the difference between shades?” — designed to match what a shopper is likely wondering in the moment. These context-aware prompts help remove buying hesitation before shoppers even think to ask.

Chat adds instant access to shopper actions, like a cart button and an orders button for returning customers. Shoppers can jump straight to their cart or check on an existing order without waiting for an agent to give them a status update.

Every update in Chat drives performance. We didn’t simply give it a makeover, we also fine-tuned its underlying mechanics.
When product suggestions are easy to browse, shoppers interact with them more. The new product cards make shopping feel natural, allowing customers to explore items at their own pace. That convenience led to a 36% increase in engagement with recommended products.
Chat keeps the entire shopping journey inside the conversation, from browsing and asking questions, to adding to cart and checking out. This new layout removes the usual tab-switching between chat and the website. Less friction has led to more than double add-to-cart actions than before the redesign.
Chat's cleaner design and contextual entry points make it easier for shoppers to start a conversation. With suggested questions on product pages and quick reply buttons, more visitors are choosing to engage earlier in their journey. This has resulted in a 7.3% lift in chat engagement.
Conversational commerce has moved from concept to reality. Chat makes it part of the everyday shopping experience, letting shoppers browse, ask questions, compare products, and check out in one interaction. It brings the ease of the in-person shopping experience into the digital world.
We built Chat to redefine the shopping experience. We hope you see it reflected in your customers’ journeys.
Book a demo to see what's possible with the new experience.
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TL;DR:
A year ago, ecommerce brands were still debating whether AI was worth the investment. That debate is over. Today, nearly every ecommerce professional uses AI to do their job.
The shift isn't just about adoption. It's about what AI is used for and how brands measure its impact. Support automation was the entry point. Now, AI is embedded across the full operation, from product recommendations to inventory control to real-time shopping conversations.
In our 2026 State of Conversational Commerce Report, we break down trends on AI usage among 400 ecommerce decision-makers and 16,000+ ecommerce brands using Gorgias.
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If we rewind 12 months ago, the industry was still split on AI. Some ecommerce professionals were excited, but most were still hesitant. In 2024, 69% of ecommerce professionals used AI in their roles. By 2025, that number reached 77%. In 2026, it hit 96%.

The confidence numbers back it up. 71% of brands say they are confident using AI for ecommerce, and 73% are satisfied with its business impact.
In early 2025, only 30% of ecommerce professionals rated their excitement for AI at 10/10. Today, zero percent of respondents describe themselves as hesitant about AI.

Using AI in ecommerce is not new. In fact, it dates back to the 1980s with the invention of algorithms and expert systems. And if you’ve ever leveraged similar product recommendations or chatbots, you’ve already integrated AI into your ecommerce stack.
Modern AI is far more sophisticated.
With the rise of agentic commerce and conversational AI, brands began leveraging AI agents to automate the processing of repetitive support tickets. That’s still happening today, but the scope has expanded beyond the support queue.

Ecommerce brands are deploying AI across every layer of their operation:
When brands were asked which channels contribute most to their AI success, conversational channels dominated. Social media messaging led at 78%, followed by SMS at 70%, and website live chat at 51%. Shoppers want fast, personal conversations, and AI is the best way to deliver that at scale.
Learn more about AI adoption, perception, and use case trends in the full 2026 Conversational Commerce Report.
For decades, customer support success meant fast response times and high satisfaction scores. Those are still important indicators of success, but leading brands are adding revenue-focused metrics to their dashboards.
91% of brands still track CSAT as a measure of AI's impact. But 60% now include AOV as a top indicator, and higher-revenue brands earning $20M+ are focusing on metrics like total operating expenses, cost per resolution, incremental revenue, and one-touch ticket rate.

AI can now start a conversation, ease customer doubts, sell, upsell, and recover abandoned carts in a single conversation. When you’re only measuring CSAT, you’re ignoring the real ROI of conversational AI investment.
Virtual shopping assistants now proactively engage shoppers, adapt to their needs in real time, and offer contextual product recommendations and upsells. When the moment calls for it, they can close the deal with a targeted discount.
Gorgias brands using AI Agent's shopping assistant capabilities nearly doubled their purchase rates and converted 20–50% better than those using AI Agent for support only.
Orthofeet, the largest provider of orthopedic footwear in the US, is a concrete example of this in practice. Using Gorgias, they achieved:
The data tells a clear story: AI has evolved beyond a tool for handling tier 1 support tickets. It’s a core part of your revenue generation strategy.
57% of brands are already using AI for 26–50% of all customer interactions, and 37% expect that share to rise to 51–75% within the next two years. The brands building toward that range now are the ones who will have the operational advantage when it matters most.
The practical question isn't whether to invest in AI. It's where to focus first. Based on where brands are seeing the most impact, three priorities stand out:
Want to go deeper on the full 2026 conversational commerce trends? Read the complete report for data across every major AI use case in ecommerce.
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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:
Your AI sounds like a robot, and your customers can tell.
Sure, the answer is right, but something feels off. The tone of voice is stiff. The phrases are predictable and generic. At most, it sounds copy-pasted. This may not be a big deal from your side of support. In reality, it’s costing you more than you think.
Recent data shows that 45% of U.S. adults find customer service chatbots unfavorable, up from 43% in 2022. As awareness of chatbots has increased, so have negative opinions of them. Only 19% of people say chatbots are helpful or beneficial in addressing their queries. The gap isn't just about capability. It's about trust. When AI sounds impersonal, customers disengage or leave frustrated.
Luckily, you don't need to choose between automation and the human touch.
In this guide, we'll show you six practical ways to train your AI to sound natural, build trust, and deliver the kind of support your customers actually like.
The fastest way to make your AI sound more human is to teach it to sound like you. AI is only as good as the input you give it, so the more detailed your brand voice training, the more natural and on-brand your responses will be.
Start by building a brand voice guide. It doesn't need to be complicated, but it should clearly define how your brand communicates with customers. At minimum, include:
Think of your AI as a character. Samantha Gagliardi, Associate Director of Customer Experience at Rhoback, described their approach as building an AI persona:
"I kind of treat it like breaking down an actor. I used to sing and perform for a living — how would I break down the character of Rhoback? How does Rhoback speak? What age are they? What makes the most sense?"
✅ Create a brand voice guide with tone, style, formality, and example phrases.
Humans associate short pauses with thinking, so when your AI responds too quickly, it instantly feels unnatural.
Adding small delays helps your AI feel more like a real teammate.
Where to add response delays:
Even a one- to two-second pause can make a big difference in a robotic or human-sounding AI.
✅ Add instructions in your AI’s knowledge base to include short response delays during key moments.
Generic phrases make your AI sound like... well, AI. Customers can spot a copy-pasted response immediately — especially when it's overly formal.
That doesn't mean you need to be extremely casual. It means being true to your brand. Whether your voice is professional or conversational, the goal is the same: sound like a real person on your team.
Here's how to replace robotic phrasing with more brand-aligned responses:
|
Generic Phrase |
More Natural Alternative |
|---|---|
|
“We apologize for the inconvenience.” |
“Sorry about that, we’re working on it now.” (friendly) |
|
“Your satisfaction is our top priority.” |
“We want to make sure this works for you.” (friendly) |
|
“Please be advised…” |
“Just a quick heads up…” (friendly) |
|
“Your request has been received.” |
“Got it. Thanks for reaching out.” (friendly) |
|
“I will now review your request.” |
“Let me take a quick look.” (friendly) |
✅ Identify your five most common inquiries and give your AI a rewritten example response for each.
One of the biggest tells that a response is AI-generated? It ignores what's already happened.
When your AI doesn't reference order history or past conversations, customers are forced to repeat themselves. Repetition can lead to frustration and can quickly turn a good customer experience into a bad one.
Great AI uses context to craft replies that feel personalized and genuinely helpful.
Here's what good context looks like in AI responses:
Tools like Gorgias AI Agent automatically pull in customer and order data, so replies feel human and contextual without sacrificing speed.
✅ Add instructions that prompt your AI to reference order details and/or past conversations in its replies, so customers feel acknowledged.
Customers just want help. They don't care whether it comes from a human or AI, as long as it's the right help. But if you try to trick them, it backfires fast. AI that pretend to be human often give customers the runaround, especially when the issue is complex or emotional.
A better approach is to be transparent. Solve what you can, and hand off anything else to an agent as needed.
When to disclose that the customer is talking to AI:
For more on this topic, check out our article: Should You Tell Customers They're Talking to AI?
✅ Set clear rules for when your AI should escalate to a human and include handoff messaging that sets expectations and preserves context.
We're giving you permission to break the rules a little bit. The most human-sounding AI doesn't follow perfect grammar or structure. It reflects the messiness of real dialogue.
People don't speak in flawless sentences every time. We pause, rephrase, cut ourselves off, and throw in the occasional emoji or "uh." When AI has an unpredictable cadence, it feels more relatable and, in turn, more human.
What an imperfect AI could look like:
These imperfections give your AI a more believable voice.
✅ Add instructions for your AI that permit variation in grammar, tone, and sentence structure to mimic real human speech.
Human-sounding AI doesn’t require complex prompts or endless fine-tuning. With the right voice guidelines, small tone adjustments, and a few smart instructions, your AI can sound like a real part of your team.
Book a demo of Gorgias AI Agent and see for yourself.
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TL;DR:
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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TL;DR:
What’s the common factor between shoppers debating between products and considering a splurge? Hesitation.
Today’s shoppers are overwhelmed with choices. They don’t want to be left to figure things out on their own. They want guidance.
But most brands are missing that crucial piece of the puzzle. They lack a strategy that accompanies shoppers on their journey. A tool that encourages shoppers to proceed to checkout. And, ultimately, a customer experience devoid of a sales approach.
That’s why we built Shopping Assistant, an AI Agent that proactively engages browsers, offers context-aware product recommendations, and turns hesitation into conversions in real time.
And it’s working. Brands using Shopping Assistant are seeing a 62% uplift in conversion, 10% higher average order value, and 5x ROI.
Here’s a closer look at what’s behind the magic.
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Most traditional chatbots passively wait for questions and deliver answers that aren’t personalized to each shopper's preferences.
Unlike these bots, Shopping Assistant reads real-time signals like pages viewed, cart contents, and conversation tone. This results in a solution that not only offers support but also offers personalized, proactive selling. This enables Shopping Assistant to continuously refine and adjust its playbook, evolving with each shopper as their journey matures.
Here’s how Shopping Assistant engages with customers across the shopping journey:
Take this example below. When a customer vaguely asks “how to make up,” Shopping Assistant interprets it as a sign of interest in makeup products and recommends a starter kit.

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

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

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

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

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

“Once I added specific questions in quotes, it made a huge difference.”
SuitShop didn’t automate 100% of CX — but that’s not the point. At 30% automation (and growing), Katie gives her team more time to specialize, connect, and handle urgent or emotional conversations with care.
Here’s what Gorgias offers to help as well:
Whether you’re just getting started or trying to move beyond basic automation, Katie’s approach proves that coached AI outperforms out-of-the-box tools every time.
Want to coach your AI Agent like SuitShop? Book a demo to see how Gorgias can help you scale smarter.
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