

TL;DR:
Helpdesk 2.0 starts with the people who use it most: the agents.
We spent time understanding customer support from the agent's seat. What do they reach for constantly? What slows them down? What does a better workday look like?
Everything we found is in this brand-new update.
Conversational commerce is the new standard.
In customer support, this means customers expect context to remain intact wherever they reach out, whether a conversation starts on social, moves to email, or ends on a call.
This new approach to support has also changed the agent's role. Recurring tickets, like order status checks, shipping updates, and returns, are now handled by AI. What lands in the agent inbox are edge cases that require human judgment and troubleshooting, or tickets that require the full picture.
However, the original Helpdesk was built for a different era of support.
Context was separated across views rather than built into the conversation itself. It's something one in five Gorgias customers flagged, through support tickets, NPS surveys, and conversations with our team. So, we got to work.
Helpdesk 2.0 is the result.
Here's a look at everything that changed.
Conversations have a natural rhythm, one that’s already found in every messaging tool we use. We brought that same layout into the helpdesk.
Say goodbye to the 2000s email interface and hello to chat bubbles. This updated design changes how quickly you can orient yourself and resolve the ticket in one go.

Chats with customers now look like real conversations, using the speech bubble style you’re familiar with on popular messaging apps.
Checking a customer's history used to mean leaving the conversation, an extra step that interrupted what should have been a smooth workflow.
Now, past conversations open in a sidebar next to the active conversation. You can view a customer’s full history, search through their timeline, and open prior tickets without going to a new page.

Check past conversations, orders, and customer details in the brand-new Customer Timeline.
Order information is easier to reference than ever. Open a ticket, and you instantly see the customer's recent orders, marked with product images and invoice details at a glance. Need to dig deeper? Click on an order, and the expanded information appears in the same panel.
For teams using custom integrations, apps are fixed in a quick-access integration menu on the right.

See order details, product images, and totals at a glance on the right panel, without leaving the conversation.
You shouldn't have to dig through a thread to figure out what AI already tried. Now you don't have to.
When AI Agent escalates a conversation, it includes a concise handover summary that mentions the issue, what actions were taken, and why it was passed to your team.

Escalated tickets include a brief AI-generated handover summary, marked in yellow, for quick reference.
We restructured and simplified the navigation. The left sidebar organizes everything into clear categories: Inbox, AI Agent, Marketing, and Analytics, so anyone on your team knows exactly where to go.
To quickly update your knowledge base or adjust a workflow, both now live right in the sidebar. For teams managing multiple stores, switching between them is just as straightforward, accessible from the sidebar, so agents can move between inboxes without breaking their flow.

Agents can switch between stores and their corresponding inboxes directly from the left menu.
Support comes down to the person on the other end of the conversation. We built Helpdesk 2.0 is to make sure they have everything they need to show up for that moment.
The best way to see the difference is to work in it. Start a free trial today.
TL;DR:
Industry benchmarks for ecommerce are hard to come by. Most of what's out there is self-reported, survey-based, or too aggregated to be usable. Teams are left wondering whether their AI adoption is on par with industry standards or if their response times are costing them revenue.
That's a gap we're in a unique position to close.
Gorgias processes millions of customer conversations across thousands of ecommerce brands every day. This has given us a rare, unfiltered view into how the industry operates. But until now, we’ve kept those insights largely internal.
Today, we're making it public with the Ecom Lab.
The result is years of first-party data from thousands of ecommerce brands, packaged into findings that give teams a real foundation to build their strategy on.
The Ecom Lab is Gorgias's public research hub for ecommerce. It publishes insights and reports on AI adoption, support performance, financial impact, and industry trends.
The goal is simple: give teams a real baseline to measure against and to uncover the industry's inner workings.
Metrics that actually move decisions.
The Ecom Lab publishes metrics that matter to ecommerce professionals, including AI adoption rates, first response times, CSAT scores, conversion rates, and ticket intents, all broken down by brand size, GMV tier, and industry vertical.
For the first time, teams can see exactly where they stand in comparison to the broader market.
AI is Everywhere reveals why roughly 4 in 5 ecommerce brands still haven't deployed AI in customer-facing support.
Stop Benchmarking Against the Average argues that support teams should benchmark response times against their specific industry vertical rather than the overall average.
Most Brands are Overpaying for Support breaks down the actual cost of support ticket volume and what happens when AI handles the load.
The best in CX and ecommerce, right to your inbox

TL;DR:
The page-based shopping experience dominated for decades. Customers would search, browse, compare, abandon, get retargeted, return, and eventually buy (sometimes).
That journey is no longer the only option.
Shoppers are turning to chat, messaging, and AI-powered tools to find what they need. Instead of clicking through product pages or reading static FAQs, they ask questions, have back-and-forth conversations, and get answers that move them closer to a purchase in real time. The path to checkout has changed, and the brands that recognize this are pulling ahead.
Read our 2026 State of Conversational Commerce Report to learn more about conversation commerce trends from 400 ecommerce decision-makers and 16,000+ ecommerce brands using Gorgias.
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The traditional shopping journey was a solo experience. A shopper had a need, searched for options, browsed across sessions, and eventually made a decision — often days later, after being retargeted multiple times. Support only entered the picture after the purchase.

The conversation-led journey collapses that timeline:
What used to take days now takes minutes. Discovery, evaluation, and purchase happen in a single thread.
79% of brands agree that AI-driven conversational commerce has increased sales and purchase rates in their business. When brands were asked to rank the highest-return areas:
Those numbers reflect something important: the value of conversation compounds. Faster support reduces friction. Better retention raises lifetime value. More confident shoppers buy more often and spend more per order.
The brands seeing the biggest returns aren't just using AI to deflect tickets. They're using it to create one-to-one shopping experiences at scale.
Looking at AI-only influenced orders across key verticals like Apparel and Accessories, Food and Beverages, Health and Beauty, Home and Garden, and Sporting Goods, the growth across a single year was significant.





Across industries, ecommerce brands saw AI step into conversations, reduce shopper hesitation, and drive higher QoQ conversion rates.
Learn more about AI-powered revenue generation in the full 2026 Conversational Commerce Report.
84% of brands say the strategic importance of conversational commerce is higher than it was a year ago. 82% agree it will be mainstream in their sector within two years.

That shift is registering at the leadership level because of what conversational commerce does to the buying experience. Creating one-to-one touchpoints earlier in the journey drives higher AOV, shorter buying cycles, and stronger purchase rates. Shoppers who get real-time answers to their questions are more confident.
TUSHY, known for eco-friendly bidets and bathroom essentials, is a useful example of what happens when you take conversational commerce seriously.
Bidets aren't an impulse purchase. Shoppers have real questions about fit, compatibility, and installation. Those questions used to go unanswered until the CX team could respond, often after the customer had abandoned the cart.
TUSHY used Gorgias's AI Agent and shopping assistant capabilities to automate pre-sales support. AI Agent engaged shoppers in real-time conversations, addressed their concerns directly, and built confidence at the moment of highest intent.
This resulted in a 190% increase in chat-based purchases, a 13x return on investment, and twice the purchase rate of human agents.
You don't need to overhaul your entire operation to start seeing results. The most effective approach is to start where the impact is clearest and expand from there.
A few places to begin:
Want to see the full picture of where conversational commerce is headed in 2026? Read the full report to explore the data, trends, and strategies shaping the next era of ecommerce.
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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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Four months ago, our analysts were dealing with a barrage of questions. "What's our ARR by segment?" "Build me a dashboard for this quarter's pipeline." Quick asks piled up behind complex deep dives. Stakeholders waited for answers that should have taken seconds, and analysts spent their time fielding requests instead of doing the strategic work that creates the most value.
Today, anyone at Gorgias can ask a question in plain language and get an accurate, contextualized response in seconds. Not from a colleague or dashboard, nor from a generic answer from the internet. But a response built on our business context. We call it Cortex, our flagship internal AI agent.
In two months, Cortex went from an idea to fielding thousands of questions every week, recommending actions across the business, and deprecating the need for manual dashboard creation. While most companies right now are treating AI as an initiative — at Gorgias, AI is already part of how we work. 72% of Gorgias employees use Cortex each week, and that number is only growing.
We didn’t achieve this by simply plugging a large language model into our stack. LLMs are a critical part of the equation, but they aren't the driving force — it’s everything else under the hood: the infrastructure, context, platform architecture, and the team that brings it all together.

The instinct across many companies today is to start with the model, pick a provider to solve a specific challenge, or invest heavily in getting the data right. All reasonable starting points, but most of them solve for one use case. Underneath that approach is a framing problem: seeing AI as an initiative — something you assign and measure. Seeing AI as another tool your company uses versus how your company operates.
We started somewhere different. Every company is built on four pillars: customers, people, product, and decisions. AI investments tend to place heavy emphasis on the first three. We started with the fourth. Our bet was that if we built everything around the need to make effective decisions first, asking what Gorgias needed to know to operate well, then our AI would become dramatically more powerful.
Cortex is our flagship internal AI agent, and the product where we established the tenets that now run through everything else we build: composable and modular infrastructure, governed context, and accessible from wherever decisions happen. Cortex lives in Slack, as well as across LLM vendors, in its own browser extension, and even on its own dedicated internal site.
Cortex doesn’t stop at answering questions. It can read and write to Notion, file Linear tasks, create HTML apps, automate signal delivery, and more. It operates across every layer of our stack, from dashboards to data pipelines, because we designed it as one integrated system. It is this connection that adds remarkable depth to what people can ask, and what they get in return.

A Sales Lead is pitching and asks Cortex for the full picture of the merchant. In a customized PDF, Cortex lists coverage gaps, pre-sale intent signals, and product fit options. Everything the sales lead needs to walk in with confidence.
A Senior Product leader asks, "How are we performing against OKR #1, and what can my team do to help accelerate it?" Cortex returns a full ARR breakdown, projected end-of-month attainment, segment-level findings, and connects it all back to company-level strategies. A suite of recommendations customized to the leader, the performance, and the signals that bridge how they can support our goals. The kind of answer that used to take someone a week to put together.
These aren't simple lookup queries. They require deep business context spanning multiple areas. Cortex handles these because its Decision Engine gives it the information to reason against governed data, metric definitions, and business context, turning a generic answer into a credible one.
Overnight, teams have built Cortex into how they work. They’re spending less time searching and more time finding answers, not because they were told to, but because Cortex reduced the distance between question and decision.
Cortex’s modular infrastructure allows us to experiment and add new capabilities freely. We’ve already built two more internal AI agents made for entirely different use cases, but using the same Decision Engine as Cortex.
GAIA, our internal experimentation AI Agent, helps our customers identify opportunities in their AI Agent Guidance design. It takes institutional knowledge across our teams and turns it into a scalable system that drives automation and value to our customers. Our CEO, Romain Lapeyre, has been its most vocal advocate since day one.
When we needed a platform for investor readiness and board preparation, we built Oracle. Our board decks and talk tracks are informed and built with the same AI, and our numbers are validated every step of the way.
We’re continuing to expand new AI agents internally, exploring how they can create value for customers and our own teams.
When AI handles thousands of analytical questions each week, the highest-value work for a data team shifts permanently. Late 2025, we repositioned from a Data Analytics function into a Decision Intelligence function — a structural change in what we own and how we operate.
Today, our analysts focus on the most sensitive, complex, and forward-looking decisions and analyses. They partner more deeply with stakeholders by driving next steps from signals. They're even building entirely new capabilities that didn't exist in their role descriptions months ago. Things like AI skills for Cortex, context curation, and insight and recommendation delivery. The role of the analyst hasn't diminished. It's expanded to encompass the most meaningful work an analyst can do: driving outcomes and ensuring those decisions can achieve them.

Our business support model has changed, too. Instead of embedding analysts and dedicated engineers within functional teams, we align capacity to the highest-impact company objectives and move fluidly across them. This model works even better because Decision Intelligence brings together both analytics and engineering teams under one roof.
Elliot Trabac leads our Data, Context and AI Engineering teams. The Decision Engine, Cortex, GAIA, and the platforms I've described exist because of the infrastructure his team innovated and built from the ground up. Noemie Happi Nono leads our Decision Strategy and Operations team, driving decision outcomes with stakeholders, advancing the development of Cortex skills and capabilities, and pushing into new areas of analysis every day.
Together, they're shaping what a modern data function looks like when AI becomes a standard building block for how a company operates.
The question of ROI is long gone. AI has opened the floodgates to more trusted and meaningful signals than ever. The natural next evolution is Proactive Intelligence, signals surfaced toward what you need to know, before you ask. And we're already building this because our architecture is designed to support it.
In the coming weeks, members of the Decision Intelligence team will go deeper into themes I've touched on here. Yochan Khoi, a Senior Analytics Engineer on our team, recently published a technical walkthrough of our context layer and will go further into building context strategies that scale. Others will cover infrastructure, analytical partnerships, evolving data assets into decision assets, and the cost and efficiency gains that make sustained AI investment viable.
AI hasn't changed the most important element of data and analytics functions — delivering outcomes — but it has raised the bar for what it looks like and how far we can take it. We’re just getting started.

Last few months we got lots of feedback about our extension and found to our delight that most people are satisfied, but still a few recurrent issues came up:
We listened and now we're presenting:
WYSIWYG editors for the web are notoriously buggy and are just difficult to develop.
I have yet to see one that is bug free. There are few venerable editors that do a good job like TinyMCE, FKEditor or CKEditor.. but they are big and all have edge cases that break the intended formatting and add a lot of garbage html.
There are newer good quality editors in town such as Redactor. The one that got my attention and finally landed in Gorgias is this wonderful editor called which is super lightweight, uses modern content-editable (no i-frames) and 'just works' most of the time. That's not to say it's perfect, but it's good enough and I'm satisfied with it's direction in terms of development.
Enjoy it and as always send us bug-reports or feedback on: support@gorgias.com

TL;DR:
How much of AI Agent can you actually control? The answer is more than most people expect.
AI Agent has several distinct control layers — what it knows, how it speaks, which topics it handles, which ones it passes to your team, and what actions it can take on a customer's behalf. Each layer is configurable in plain language, directly inside your Gorgias settings.
This article walks through each control, what it does, and what good configuration looks like in practice.
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AI Agent allows you to configure four inputs: Guidance, tone of voice and language, handover topics and exclusions, and knowledge sources.
Each one controls a different dimension of AI Agent's behavior. Together, they determine what AI Agent knows, how it communicates, what it will and won't handle, and where it draws its answers from.
Guidance is the highest-priority input in AI Agent's knowledge hierarchy. When information exists in both a Guidance and another source — like a Help Center article or a connected URL — AI Agent always follows the Guidance first.
It's designed for rules and behavioral instructions, not just answers. Good examples of what belongs in a Guidance:
You can add up to 100 Guidance, and each one can be as specific as your policies require.
Be specific. Vague instructions produce vague behavior. "Handle returns politely" leaves AI Agent to interpret what that means. A more useful Guidance looks like this:
"For return requests: confirm the order number, check whether the item is within the 30-day return window, and if eligible, send the prepaid return label link. If outside the window, explain the policy and hand over to a human agent."
Nothing left to chance. When writing Guidance, focus on the situation and the desired outcome.
Keep it current with Guidance Opportunities. Over time, AI Agent detects recurring questions it could not confidently answer and surfaces them as suggested new Guidance in your dashboard. Review, edit to match your policies, then approve or dismiss. Nothing is added without your sign-off.
Read more: How to write Guidance with the “when, if, then” framework
Tone of voice is a separate setting from Guidance and knowledge. It controls how AI Agent communicates, the register, the warmth, the vocabulary, rather than what it says or what it does.
You have four options:
Custom is where brands with specific voice guidelines should spend time. Describe your communication style the same way you'd brief a copywriter: words and phrases that fit your brand, what to avoid, how to handle emotionally charged conversations. Emoji usage and phrases your team always or never uses can all go here.
Two things to keep separate as you configure this:
Tone usually takes a few iterations to get right. Use the test conversation feature, found under AI Agent > Test, to simulate customer conversations and verify how AI Agent sounds before it goes live.
Learn more: Customize AI Agent's tone of voice
Handover topics and exclusions give you explicit control over which conversations AI Agent handles and which go straight to your human team. Both live in the Handover and Exclusion section of your AI Agent settings.
Handover topics are subjects AI Agent is always instructed to pass to a human, even if it has relevant information. You add them in plain language. Some examples worth considering for most stores:
Exclusions work differently. Using the "Prevent AI Agent from answering" Rule, you can tell AI Agent to ignore certain tickets entirely, based on a tag, a sender's email address, or specific words in the message. These tickets stay in the queue for your human agents without AI Agent touching them.
You can also toggle whether AI Agent tells the customer it is handing them over, or does so silently. Both options are available in the same section.
Note that AI Agent hands over automatically in some situations regardless of configuration, including when it cannot find a relevant answer, when a response does not pass its internal quality check, and when a customer asks to speak to a human.
Read more: Customize how AI Agent hands over to your team
AI Agent's answers are grounded entirely in the sources you connect. It won't speculate beyond them, and if it cannot find a relevant answer, it hands over instead of guessing.
The sources you can connect are:
Start by connecting what you already have. Gaps will surface quickly through handovers in the inbox or through Guidance Opportunities flagging unanswered questions. Adding a URL or uploading a document is usually faster than writing a Guidance for every scenario.
Learn more: Onboard AI Agent with knowledge sources
AI Agent runs on email, chat, and SMS. None are on by default. You enable each one manually. Turning a channel off doesn’t affect your configuration.
Email is where most brands start. AI Agent handles incoming tickets, filters spam, and pulls from your knowledge sources and Shopify data to reply with context. Anything it cannot resolve gets handed over with the full conversation attached.
Chat is faster and more transactional. Customers tend to ask shorter, more immediate questions — order status, return eligibility, quick policy checks. AI Agent adapts automatically, writing shorter and more conversational replies on chat than it would on email.
SMS requires a separate add-on subscription. It is the most tone-sensitive channel, so configure your tone of voice carefully and test thoroughly before enabling AI Agent here.
There is no required order for activation. Most brands pick the channel with the highest ticket volume and clearest policies, then expand. Switching a channel off is a simple toggle. Nothing gets deleted.
Before enabling AI Agent on any channel, test it first. Gorgias has a built-in test conversation feature that lets you simulate customer interactions without affecting real tickets, reporting, or customers. Go to AI Agent > Test.
Step 1: Start with your hardest tickets. Skip the generic questions. Test the scenarios that made you hesitant in the first place — complex product questions, return edge cases, sensitive topics on your handover list. If AI Agent handles these well, you can activate with confidence.
Step 2: Test each channel separately. AI Agent adapts its response style by channel. Shorter on chat, more detailed on email. A response that reads well on email may feel too long on chat, so configure the channel in the test settings to match the one you are evaluating.
Step 3: Check your handovers. Send a message containing the language or scenario you want escalated. Confirm AI Agent passes it to your team rather than attempting a response. Do this for every topic on your handover and exclusion list.
Step 4: Test your tone. Run several conversations before settling on your tone configuration. Try emotionally charged messages, not just neutral ones. Tone usually takes a few rounds to get right.
Test conversations do not count toward your automated interaction billing. Iterate freely.
Some tickets should never be handled by AI. Not because AI Agent cannot generate a response, but because the situation calls for a human regardless.
There are two types of escalation to understand: the ones AI Agent does automatically, and the ones you configure yourself.
Automatic escalations. These are built in and can’t be turned off. AI Agent hands over automatically when it lacks confidence in an answer, when it can’t find relevant content in its knowledge sources, when it detects customer anger or frustration, and when a customer explicitly asks to speak to a human.
Every response also passes through an internal QA step — a second AI model measures confidence, and if the response does not meet the threshold, it is not sent.
Configured escalations. These are yours to define. Two tools handle this.
Handover topics tell AI Agent to always pass a conversation to a human on a specific subject, even if it has relevant information. Add them in plain language in your AI Agent settings. Good candidates for most stores:
Exclusions go further. Using the "Prevent AI Agent from answering" Rule, you can tell AI Agent to ignore certain tickets entirely, based on tags, sender email addresses, or specific words in the message. These tickets never get touched by AI Agent at all.
Route escalations to the right place. When AI Agent hands over, configure which tag, team, or queue the ticket routes to. A return escalation goes to fulfilment. A billing dispute goes to a senior agent. Escalated tickets should never land in a generic inbox.
Learn more: Security and privacy FAQ for Gorgias AI Agent
Configuration is not a one-time task. The brands who get the most out of AI Agent check in regularly, flag what is not working, and update its knowledge as policies and products change. Here is a simple review checklist to run through on a monthly basis, or after any major policy or product update.
Most of the configuration covered in this article applies to every store. This section is for brands in categories where the stakes of an incorrect or out-of-scope response are higher. Skim to your vertical and take what applies.
You now know exactly what you can control, and there is more of it than most brands expect. The next step is seeing it configured for your store specifically.
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TL;DR:
Intercom built its reputation as a customer messaging tool for SaaS companies. As it shifted toward enterprise, many ecommerce brands found themselves paying more for features they didn't need — and missing the ones they did. This guide covers the 15 best Intercom alternatives, evaluated specifically for ecommerce brands on Shopify and beyond.
Intercom is a customer messaging platform that combines live chat, email, and automation for support and sales. It works well for SaaS companies, but ecommerce brands often run into friction fast.
The biggest issue is pricing. The jump from the Essential plan ($74 USD per month) to the Advanced plan ($395 per month) is steep, and many features — like custom bots and product tours — cost extra on top of that. For a growing brand managing hundreds of tickets a week, the total cost adds up quickly.
Beyond price, Intercom was not built with ecommerce in mind. There is no native Shopify integration, no order management inside conversations, and limited automation for common requests like "Where is my order?" That gap pushes many brands to look for tools designed around how online retail actually works.
Platform |
Starting price |
Free plan |
Best for |
Gorgias |
$10 USD/month |
Limited |
Shopify brands |
Zendesk |
$55/agent/month |
No |
Enterprise support |
Freshdesk |
$15/agent/month |
Yes |
Budget-conscious teams |
Help Scout |
$25/user/month |
No |
Email-first support |
Kustomer |
$89/user/month |
No |
CRM-focused brands |
Drift |
Custom |
No |
B2B sales teams |
Tidio |
$29/month |
Yes |
Small businesses |
Crisp |
$25/month |
Yes |
Startups |
Zoho Desk |
$14/agent/month |
No |
Zoho ecosystem users |
Front |
$19/seat/month |
No |
Collaborative inboxes |
Gladly |
$150/agent/month |
No |
Premium brands |
LiveAgent |
$9/agent/month |
No |
All-in-one on a budget |
HubSpot Service Hub |
$20/month |
No |
HubSpot users |
Salesforce Service Cloud |
$25/user/month |
No |
Large enterprises |
Groove |
$16/user/month |
No |
Small teams |
Gorgias is a customer experience (CX) platform built specifically for ecommerce brands. It connects your helpdesk directly to Shopify, so agents can view orders, issue refunds, and update subscriptions without leaving the conversation.
The AI Agent handles up to 60% of incoming tickets automatically — shipping questions, return requests, order status — across email, chat, and SMS. The Shopping Assistant goes further, proactively engaging shoppers on product pages to help them find the right item and complete their purchase.
Gorgias is the strongest Intercom alternative for Shopify brands that want support and sales in one place.
Key features:
Pricing:
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Zendesk is an enterprise helpdesk platform that handles high ticket volumes across email, chat, voice, and social. Its reporting tools are among the most advanced available, and its marketplace includes hundreds of integrations.
It is a strong fit for large teams with complex workflows. For smaller ecommerce brands, the setup time and per-agent pricing can be a barrier.
Pricing: Suite Team starts at $55/agent/month
Freshdesk is a helpdesk platform with a free tier for up to 10 agents, making it one of the most accessible Intercom alternatives for teams on a tight budget. It includes ticketing, automation, and a knowledge base across its plans.
Its ecommerce integrations are less deep than purpose-built tools, but it covers the basics well for brands managing moderate ticket volume.
Pricing: Free for up to 10 agents; paid plans from $15/agent/month
Help Scout is a shared inbox tool that makes email support feel personal and organized. Agents work in a clean interface that looks like a regular email client, which reduces the learning curve significantly.
When comparing Help Scout vs Intercom, Help Scout wins on simplicity. It suits brands that rely heavily on email and want a tool their team can use on day one.
Pricing: Standard plan starts at $25/user/month
Kustomer is a CRM-first platform that organizes every customer interaction into a single timeline. Agents see the full history of a shopper's orders, conversations, and behavior in one view.
It is best suited for enterprise brands that need deep personalization and are willing to invest in a more complex setup. Pricing reflects that positioning.
Pricing: Enterprise plan starts at $89/user/month
Drift is a conversational marketing platform built for B2B sales teams. Its chatbots qualify leads, book meetings, and route prospects to sales reps automatically.
When comparing Drift vs Intercom, both target sales use cases — but neither is built for ecommerce. Drift's pricing starts at $2,500/month, making it one of the most expensive options on this list.
Pricing: Premium starts at $2,500/month; advanced plans are custom
Tidio is a live chat and chatbot tool aimed at small ecommerce businesses. Its free plan covers up to 50 conversations per month, and its paid plans are affordable for brands just scaling up.
The chatbot builder is easy to use without technical knowledge. It lacks the deep integrations and automation power of more advanced platforms, but it is a solid starting point.
Pricing: Free up to 50 conversations; Starter from $29/month
Crisp is a multichannel messaging platform with a generous free plan that includes two seats. It brings together live chat, email, and social messaging in one shared inbox.
It is a practical, cheaper alternative to Intercom for startups and small teams. Paid plans unlock chatbots and more advanced automation.
Pricing: Free for two seats; Pro from $25/month
Zoho Desk is the support module within the Zoho software suite. Its biggest advantage is how tightly it connects with Zoho CRM, giving sales and support teams a shared view of every shopper.
If your brand already uses Zoho products, Desk is a natural fit. If you don't, the value of the integration is less compelling.
Pricing: Standard plan starts at $14/agent/month
Front is a collaborative inbox tool that brings email, SMS, and social channels into one shared workspace. Teams can assign conversations, leave internal comments, and track response times without switching tools.
Front is strong for collaboration but lighter on traditional helpdesk features like ticket routing and automation rules. It suits teams that manage a high volume of email and need better internal coordination.
Pricing: Starter plan starts at $19/seat/month
Gladly organizes all customer communication into a single, ongoing conversation thread — no ticket numbers, no channel silos. Agents always see the full picture, regardless of where the shopper reached out.
This model works well for premium brands that prioritize a personal, high-touch experience. The price point reflects that focus.
Pricing: Hero plan starts at $150/agent/month
LiveAgent is an all-in-one helpdesk that includes live chat, email, a call center, and a knowledge base in a single platform. It is one of the most affordable options with a broad feature set.
The interface feels dated compared to newer tools, but the functionality is solid for brands that want everything in one place without a high price tag.
Pricing: Small plan starts at $9/agent/month
HubSpot Service Hub is the customer service layer of the HubSpot platform. It connects directly to HubSpot CRM, giving support teams full visibility into a shopper's marketing and sales history.
For brands already running on HubSpot, it is a logical extension. For those who aren't, adopting the full suite just for support is a significant commitment.
Pricing: Starter from $20/month for two users
Salesforce Service Cloud is one of the most powerful and customizable support platforms available. It handles complex workflows, advanced automation, and deep reporting at enterprise scale.
The tradeoff is complexity. Implementation takes time, requires technical resources, and the cost scales quickly. It is best suited for large brands with dedicated operations teams.
Pricing: Starter from $25/user/month; Enterprise from $165/user/month
Groove is a simple helpdesk for small teams that have outgrown shared Gmail inboxes. It includes a shared inbox, knowledge base, and basic reporting without the overhead of a larger platform.
It is a practical, no-frills option for brands with low ticket volume and straightforward support needs.
Pricing: Standard plan starts at $16/user/month
The right platform depends on three things: your ecommerce stack, your ticket volume, and what you need the tool to do beyond answering questions.
Start with your platform. If you run on Shopify, you need a tool that connects natively — not through a workaround. Native integration means agents can see order details, edit shipments, and process returns without switching tabs.
Then think about scale. Per-agent pricing works well for small teams but gets expensive fast. Ticket-based pricing, like Gorgias uses, scales more predictably as your volume grows.
Finally, decide whether you need support only or support and sales. Some platforms on this list handle tickets well. Others — like Gorgias — are built to drive revenue through conversations, not just resolve them.
Key questions to ask any vendor:
Most platforms offer a free trial or starter plan. Use it. A week of real usage tells you more than any feature comparison chart.
For Shopify brands that need more than Intercom offers, Gorgias is worth a closer look. You get native order management, 60% automation coverage, and no per-agent pricing. Start a free trial to see it on your actual workflows.

TL;DR:
If you're wondering what it costs to add AI Agent to your Helpdesk, you're in the right place. This article walks through how pricing works, what counts as a billable interaction, and how to think about the investment before talking to anyone on our team.
The good news: there are no seat fees, no per-message charges, and no token-based billing. You pay for conversations your AI actually resolves. If you've looked into other AI tools for customer support and found the pricing models confusing or hard to predict, Gorgias AI Agent works differently.
A billable interaction is counted when the AI resolves a customer conversation entirely on its own. The customer asks something, the AI handles it, the conversation closes. That's one interaction.
If the AI can't fully resolve a conversation and hands it to a human agent, that ticket shifts over to your regular Helpdesk plan. It becomes a standard resolved ticket. You're not charged for both.
A few things that don't count as billable interactions:
This matters most for brands coming from seat-based tools. With Gorgias, your whole team can work in the platform. Agent seats are unlimited. Pricing scales with what your AI is actually doing, not with how many people have access.
Understand the difference between seat-based vs. usage-based pricing.
AI Agent is an add-on to your Gorgias Helpdesk plan. The two are priced separately but work together. Your Helpdesk plan covers all the conversations your human agents resolve. Your AI Agent plan covers the interactions the AI resolves on its own.
When you choose a plan, you select how many automated interactions you want included per month. Depending on your plan, that ranges from 90 to 2,500+ interactions, with custom interaction numbers available for enterprise. You can see the full breakdown on the Gorgias pricing page.
Each resolved conversation costs $0.90 on most plans. Starter plans begin at $1 per resolved conversation. You only pay for fully automated interactions, meaning conversations the AI handles from start to finish without a human stepping in.
The main input is your average monthly ticket volume. From there, you estimate how many of those conversations AI could realistically handle on its own.
Order status updates, return requests, and shipping questions tend to be the highest-volume ticket types AI resolves well. AI Agent actions shows the full range of what it can handle, which makes it easier to estimate your starting number.
Your actual automation rate, meaning the share of total tickets the AI ends up resolving, emerges from usage over time. Most brands start with their most repetitive ticket types and expand from there as they see results.
Related: Which Gorgias plan should you choose?
You're charged an overage fee for each additional automated interaction if you exceed your plan's baseline in a given month. The exact rate depends on your plan tier and whether you're on a monthly or annual subscription.
Generally, the higher your plan tier, the lower your overage rate. Annual plans also carry lower overage rates than monthly plans. So if you're regularly going over, upgrading to a higher tier or switching to annual often works out cheaper than paying overage fees month after month.
If you're on a Support + Shopping Assistant plan, the overage rate is $1.50 per interaction across all paid tiers. If you're on a Support-only plan, rates range from $1.00 to $2.00 per interaction on monthly plans, and $0.83 to $1.67 on annual plans, depending on your tier.
For seasonal businesses, forecasting your customer service volume before peak periods is the best way to choose the right plan size and avoid unexpected fees.
At $0.90 per resolved interaction on most plans, each AI resolution costs less than a human agent handling the same ticket. Once you know what a human-resolved ticket costs your business, the comparison becomes straightforward.
For brands building an internal case for the investment, how to pitch AI Agent to your boss covers the ROI framing in detail.
To see what results look like in practice, how 10 brands transformed customer support into revenue has real ecommerce examples.
AI Agent comes with everything you need to set it up, customize it, and improve it over time:
The best way to get a sense of what AI Agent will cost is to look at your own ticket volume and the types of questions your customers ask most. From there, the right plan becomes much clearer.
If you want to talk through the numbers with someone from our team, book a demo and we'll walk through it with you.
If you'd rather keep exploring first, here are a few good next reads:
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TL;DR:
You've already decided Richpanel isn't the answer. The question is what to replace it with.
If you're hitting Richpanel's ceiling, it usually looks like one of three things: your AI deflects tickets but can't resolve them, your agents view order data but still switch tabs to act on it, or your automation coverage stalls as ticket volume grows. The platform was built for self-service — not for teams that need to actually do things inside conversations at scale.
This guide compares seven alternatives built for ecommerce brands, with honest assessments of where each one wins, where it doesn't, and who it's actually right for.
One thing to flag before reading this table: "Shopify integration" means different things on different platforms. Viewing order data inside a ticket is not the same as editing an order, issuing a refund, or applying a discount code without leaving the helpdesk. The table distinguishes between the two.
Tool |
Starting Price |
Pricing Model |
Shopify Integration |
AI Capability |
Best For |
Gorgias |
$10/month |
Per-ticket |
Native; view + act |
Resolves tickets (60% automation) |
Scaling Shopify brands |
Zendesk |
$55/agent/month |
Per-agent |
App-based; view only |
Advanced, requires add-ons |
Enterprise, multi-industry |
Freshdesk |
$15/agent/month |
Per-agent |
App-based; view only |
Basic bots, add-ons required |
SMBs, multi-industry |
Help Scout |
$20/user/month |
Per-agent |
App-based; view only |
Basic AI assistance |
Teams prioritizing simplicity |
Kustomer |
~$89/agent/month |
Per-agent |
App-based; view only |
AI routing and suggestions |
CRM-focused teams |
Intercom |
$29/seat/month |
Per-agent |
App-based; view only |
AI chatbot, Fin AI agent |
Sales + support teams |
Tidio |
$29/month |
Flat-rate |
Basic; view only |
Lyro AI chatbot |
Micro-businesses, pre-sale chat |
Before you evaluate features, learn about pricing models because the model determines whether your costs stay predictable.
Per-agent pricing charges a monthly fee per user on your team. Zendesk, Freshdesk, and Help Scout use this model. It's predictable until your team grows, then adds up fast.
Per-ticket pricing charges based on how many tickets you resolve each month. It rewards teams that automate well: the more you automate, the lower your effective cost per ticket.
Flat-rate pricing charges a single monthly fee regardless of agents or volume. It works at a very small scale but typically comes with feature or usage caps that create problems as you grow.
The reason this matters before you look at any comparison table: a per-agent tool at $55/agent looks cheaper than a per-ticket tool at $360/month — until you have six agents and 2,000 tickets, and the math flips. Know your current ticket volume and team size before you read any pricing number in this article.
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Not all helpdesks understand ecommerce. Here are seven alternatives to Richpanel, each with distinct strengths for different types of brands.
Best for: Shopify and Shopify Plus brands processing hundreds of orders per day who want automation that resolves tickets, not just deflects them.
Gorgias is built specifically for ecommerce — not adapted for it. That distinction matters when you're evaluating what the platform can actually do inside a ticket versus what it can only display.
The core difference from Richpanel is in how automation works. Gorgias's AI Agent is designed for conversational commerce, meaning it doesn't run on pre-configured messages — it understands context and responds naturally. It can even execute actions, such as initiating a return, applying a discount code, and closing a ticket, without a human agent touching it. That's how it reaches 60% automation coverage for most ecommerce brands.
For support managers, the operational impact is straightforward: your team handles the conversations that actually require judgment, and the platform handles everything else.
Read more: Which Gorgias plan should you choose? (Pricing breakdown)
Where Richpanel's AI tells a customer how to start a return, Gorgias's AI Agent actually starts it. Key capabilities:
Native, not app-based — agents can edit orders, issue refunds, and create discount codes directly inside a ticket. Supports multiple Shopify stores from one dashboard, with automation rules triggered by Shopify data like order value, customer tags, and VIP status. For Shopify Plus brands, Gorgias includes multi-store management, custom automation at scale, and dedicated onboarding — most Plus merchants go live in under two weeks.
Read more: The Gorgias & Shopify integration: 8 features your support team will love
100+ native ecommerce integrations covering the tools Shopify brands actually use: Klaviyo, Attentive, Recharge, Loop, ShipStation, and Yotpo among them. Agents get full customer context — purchase history, active subscriptions, recent campaigns — without leaving the ticket.
Best for: Large, multi-channel retailers with dedicated support ops teams, complex escalation workflows, or multi-brand operations that need enterprise-grade configurability.
Zendesk is the default choice for enterprise support operations — and that's both its strength and its limitation for ecommerce brands. It can handle almost any support configuration at any scale, but that flexibility comes with complexity and cost that many Shopify teams don't need.
For support managers coming from Richpanel, the biggest adjustment is setup time. Zendesk is highly customizable, but out of the box it doesn't understand ecommerce workflows. Shopify integration requires a third-party app, and AI features are add-ons rather than native to the core product.
Read more: Zendesk pricing: Plans, add-ons, and if it’s worth it
Useful at higher tiers, but not included in base plans — expect to pay extra. What you get:
App-based via the Zendesk marketplace. Agents can view order data inside tickets but can't act on it — refunds, edits, and cancellations still require switching to Shopify admin. For high-volume teams, that tab-switching adds up. Zendesk can scale to Shopify Plus volume, but expect to involve a solutions partner — the configuration required to make it work well for ecommerce isn't something most teams can stand up on their own.
1,000+ integrations across CRM, ERP, marketing, and ecommerce. The caveat: "integration available" doesn't always mean seamless — many require configuration or a solutions partner to work properly.
Best for: SMBs and mid-market teams that need a broad feature set at a lower per-agent cost and aren't primarily Shopify-focused.
Freshdesk is one of the most widely used helpdesks in the market, and its appeal is straightforward: it covers a lot of ground at a price point that's hard to argue with. For teams coming from Richpanel, it's a credible step up in ticketing sophistication and reporting depth — without the enterprise price tag of Zendesk.
The trade-off is that Freshdesk is a general-purpose tool. It doesn't speak ecommerce natively, and its Shopify integration has the same limitation as Zendesk's: agents can see order data, but acting on it requires leaving the helpdesk.
Read more: Freshdesk pricing guide: What you actually pay
Freshdesk's AI features, branded as Freddy AI, are functional but uneven depending on which plan you're on. What you get:
App-based, with the same view-only limitation as Zendesk. Agents can pull up order details inside a ticket but can't take action without switching tabs. There's no native understanding of ecommerce workflows — things like return automations or order-triggered rules require custom configuration or third-party apps.
1,000+ integrations via the Freshworks marketplace. Ecommerce coverage exists but is slimmer than Zendesk's. Expect to do more legwork connecting the tools your Shopify stack relies on.
Best for: Small to mid-sized teams that prioritize a clean agent experience and handle lower ticket volumes without complex automation needs.
Help Scout occupies a specific niche: it's the helpdesk for teams that find tools like Zendesk and Freshdesk overwhelming and want something that feels closer to email. Setup is fast, the interface is clean, and agents can get productive quickly without a long onboarding process.
For support managers evaluating it as a Richpanel alternative, the honest assessment is this: Help Scout solves the inbox and collaboration problem well, but it won't solve the automation problem. If limited automation is what's pushing you off Richpanel, Help Scout isn't the answer.
Help Scout's AI features are the most recent addition to the platform and are still maturing. What's available:
App-based and view-only. Agents can see customer order history inside conversations, but order actions require going to Shopify directly. No native ecommerce automation triggers.
Lighter integration library than Zendesk or Freshdesk with around 50+ native integrations. Covers the basics but thins out quickly for teams with more complex Shopify tech stacks. A Zapier connection extends this, but adds another layer to maintain.
Read more: Help scout review: Pros, cons, and alternatives
Best for: Mid-market to enterprise brands that want a CRM-first approach to support, where full customer history matters more than the number of tickets resolved.
Kustomer's core idea is different from every other tool on this list. Instead of organizing support around tickets, it organizes it around customers. Every interaction, from purchases and conversations to returns and complaints, lives on a single customer timeline that agents see before they respond to anything.
For support managers coming from Richpanel, the appeal is depth of context. Where Richpanel shows you the ticket, Kustomer shows you the person. The trade-off is complexity and cost. This is not a platform you stand up in a week, and the pricing reflects that.
Read more: Kustomer pricing guide: What you’ll actually pay
Kustomer's AI is built around its CRM data model, which gives it more customer context to work with than most platforms. What you get:
App-based and view-only at the ticket level. Where Kustomer differentiates is in pulling Shopify purchase data into the customer timeline. Agents get a richer picture of buying behavior than they would in most helpdesks. Acting on orders still requires leaving the platform.
Solid coverage across CRM, marketing, and ecommerce tools. Klaviyo, Recharge, and Shopify are all supported. The integration depth varies — some connections are richer than others and may require development resources to configure properly.
Best for: Teams that run support and sales or marketing from the same platform — where proactive engagement and reactive support need to live together.
Intercom sits at the intersection of customer support and customer engagement. It's known for its messenger-first experience and its AI agent, Fin, which is one of the more capable AI support tools on the market. For brands where support is closely tied to conversion — think high-consideration products, subscription businesses, or brands with active sales chat — Intercom makes that connection explicit.
For support managers evaluating it as a Richpanel alternative, the key question is whether you need that sales and marketing layer. If you just need a better helpdesk, Intercom may be more than you need and priced accordingly. If your support team is also expected to drive revenue, it's worth a serious look.
Intercom's Fin AI agent is one of the strongest on this list for conversational resolution. What you get:
App-based and view-only for order data. Intercom's strength is in behavioral data rather than transactional data from Shopify. For brands where understanding browsing and purchase intent matters as much as order status, that's a meaningful difference. For teams that primarily need to act on orders, it's still a tab-switching situation.
Strong integration library with good coverage of ecommerce and marketing tools. Klaviyo, Stripe, Salesforce, and Shopify are all supported. The platform is built with product and growth teams in mind as much as support teams, so the integrations reflect that breadth.
Best for: Small ecommerce businesses or early-stage brands that want AI-powered chat for pre-sale engagement and basic support at a low entry price.
Tidio is the most limited tool on this list in terms of helpdesk depth, and it's worth being upfront about that. It's not trying to be a full support operations platform — it's a chatbot-first tool that happens to include a shared inbox. For teams coming from Richpanel with growing ticket volumes and complex post-purchase support needs, Tidio is likely a step sideways, not forward.
Where it does earn its place on this list: if your primary support challenge is pre-sale engagement and basic FAQ deflection, and your team is small enough that per-agent pricing on other tools becomes disproportionately expensive, Tidio's flat-rate model makes it genuinely cost-effective.
Tidio's AI product is Lyro, a conversational AI chatbot trained on your help content. What you get:
Basic. Tidio connects to Shopify to display order status information in chat, which is enough for simple WISMO queries. It doesn't support order editing, refunds, or any transactional actions from within the platform. For Shopify Plus brands, this integration depth will feel immediately insufficient.
Covers the basics — Shopify, Klaviyo, Mailchimp, and a handful of other common tools. The integration library is noticeably thinner than every other platform on this list, which becomes a constraint as your tech stack grows.
The honest answer is that most teams narrow this down to two or three tools quickly once they're clear on two things: how much of their ticket volume they want to automate, and how deeply they need to work inside Shopify without leaving the platform.
Here's how the shortlist typically looks by situation:
Gorgias is the obvious choice. The native Shopify integration and AI automation coverage are meaningfully ahead of everything else on this list for ecommerce-specific workflows. If your team is spending time on WISMO, returns, and order edits, those are exactly the tickets Gorgias automates.
Zendesk. The configurability, SLA management, and reporting depth justify the cost and setup investment at enterprise scale. Just factor in a solutions partner and don't expect it to work out of the box for ecommerce.
Intercom. If the line between support and revenue generation is blurry on your team — subscription brands, high-consideration products, anything with an active sales chat motion — Intercom's combination of Fin AI and proactive messaging tools is worth the premium.
Help Scout for inbox management, Freshdesk if you need more ticketing structure. Both are easier to set up than Zendesk and cheaper than Gorgias at low ticket volumes. Understand that you're trading automation capability for simplicity.
Tidio. It's not a full helpdesk, but if chatbot-driven lead capture and basic FAQ deflection is the actual problem, it's cost-effective and fast to set up.
Kustomer. If your support philosophy is built around knowing the customer rather than closing the ticket, the CRM-first data model is genuinely differentiated. Be prepared for the implementation investment.
If you're still in research mode, these might help:
If Gorgias is already at the top of your shortlist, start a free trial and see how it handles your actual workflows.

TL;DR:
Helpdesk 2.0 starts with the people who use it most: the agents.
We spent time understanding customer support from the agent's seat. What do they reach for constantly? What slows them down? What does a better workday look like?
Everything we found is in this brand-new update.
Conversational commerce is the new standard.
In customer support, this means customers expect context to remain intact wherever they reach out, whether a conversation starts on social, moves to email, or ends on a call.
This new approach to support has also changed the agent's role. Recurring tickets, like order status checks, shipping updates, and returns, are now handled by AI. What lands in the agent inbox are edge cases that require human judgment and troubleshooting, or tickets that require the full picture.
However, the original Helpdesk was built for a different era of support.
Context was separated across views rather than built into the conversation itself. It's something one in five Gorgias customers flagged, through support tickets, NPS surveys, and conversations with our team. So, we got to work.
Helpdesk 2.0 is the result.
Here's a look at everything that changed.
Conversations have a natural rhythm, one that’s already found in every messaging tool we use. We brought that same layout into the helpdesk.
Say goodbye to the 2000s email interface and hello to chat bubbles. This updated design changes how quickly you can orient yourself and resolve the ticket in one go.

Chats with customers now look like real conversations, using the speech bubble style you’re familiar with on popular messaging apps.
Checking a customer's history used to mean leaving the conversation, an extra step that interrupted what should have been a smooth workflow.
Now, past conversations open in a sidebar next to the active conversation. You can view a customer’s full history, search through their timeline, and open prior tickets without going to a new page.

Check past conversations, orders, and customer details in the brand-new Customer Timeline.
Order information is easier to reference than ever. Open a ticket, and you instantly see the customer's recent orders, marked with product images and invoice details at a glance. Need to dig deeper? Click on an order, and the expanded information appears in the same panel.
For teams using custom integrations, apps are fixed in a quick-access integration menu on the right.

See order details, product images, and totals at a glance on the right panel, without leaving the conversation.
You shouldn't have to dig through a thread to figure out what AI already tried. Now you don't have to.
When AI Agent escalates a conversation, it includes a concise handover summary that mentions the issue, what actions were taken, and why it was passed to your team.

Escalated tickets include a brief AI-generated handover summary, marked in yellow, for quick reference.
We restructured and simplified the navigation. The left sidebar organizes everything into clear categories: Inbox, AI Agent, Marketing, and Analytics, so anyone on your team knows exactly where to go.
To quickly update your knowledge base or adjust a workflow, both now live right in the sidebar. For teams managing multiple stores, switching between them is just as straightforward, accessible from the sidebar, so agents can move between inboxes without breaking their flow.

Agents can switch between stores and their corresponding inboxes directly from the left menu.
Support comes down to the person on the other end of the conversation. We built Helpdesk 2.0 is to make sure they have everything they need to show up for that moment.
The best way to see the difference is to work in it. Start a free trial today.

TL;DR:
Yuma AI works well for basic ticket deflection, but many ecommerce brands outgrow its limitations quickly. The per-resolution pricing becomes unpredictable as you scale, and the focus on simple deflection misses opportunities to drive revenue through conversations.
The best alternatives offer subscription pricing, deeper ecommerce integrations, and AI that can both resolve tickets and increase sales. We've tested the top options to help you find the tool for your brand's needs.
Yuma AI is an artificial intelligence tool that automatically responds to customer service emails for ecommerce brands. This means it reads incoming support tickets and tries to answer them without human help. The platform charges you each time it successfully resolves a customer inquiry, which they call per-resolution pricing.
The tool focuses on deflection rate, or the percentage of tickets handled entirely by AI. Yuma learns from your past customer conversations and help center articles to generate responses. When it can't handle a ticket, it passes the conversation to your human agents.
Brands start searching for alternatives when Yuma's limitations become clear. The biggest issues emerge as your business grows and your support needs become more complex.
Cost unpredictability: Per-resolution pricing sounds appealing until your ticket volume spikes. During Black Friday Cyber Monday or after a viral social media post, your support costs can double or triple overnight. You lose control over your monthly expenses.
Limited ecommerce actions: Yuma can answer basic questions but can't perform the actions your customers actually need. It can't cancel orders, process returns, or update shipping addresses. Your team still handles all the real work.
Channel gaps: Most customer conversations happen outside email. If your shoppers message you on Instagram, text you questions, or use live chat, Yuma can't help. You need separate solutions for each channel.
Setup complexity: Getting Yuma to understand your brand voice and policies takes weeks of training. You're paying for resolutions while the AI learns, often giving incorrect answers during the learning period.
Here's how the top alternatives compare to each other in terms of user, pricing, setup time, and Shopify compatibility.
Platform |
Best for |
Pricing model |
Setup time |
Shopify integration |
Gorgias |
Shopify brands wanting revenue + support |
Subscription |
Hours |
Native |
Zendesk AI |
Large enterprises with complex needs |
Per-agent + add-ons |
Weeks |
App-based |
Intercom Fin AI |
Proactive chat engagement |
Per-agent + usage |
Weeks |
App-based |
Ringly.io |
Email automation focus |
Per-resolution/subscription |
Days |
API |
Freshdesk |
Small businesses needing basics |
Per-agent + tiers |
Weeks |
App-based |
DigitalGenius |
Enterprise custom workflows |
Custom pricing |
Months |
API |
Alhena AI |
Simple ticket deflection |
Per-resolution |
Days |
API |
My AskAI |
Basic chatbot needs |
Subscription |
Hours |
Widget |
Each platform takes a different approach to AI customer service. Some focus purely on cost reduction, while others help you grow revenue through better conversations.
Gorgias is a customer service platform built specifically for ecommerce brands that sell on Shopify. This means every feature connects directly to your store data, orders, and customer information. The AI Agent doesn't just answer questions — it can take actions like processing returns, updating orders, and recommending products.
The platform treats customer service as a revenue driver, not just a cost center. Your AI can upsell customers, recover abandoned carts, and turn support conversations into sales opportunities. Everything happens in one unified inbox across email, chat, SMS, social media, and phone.
Gorgias integrates natively with Shopify, which means no complex API setup or data syncing issues. Your team can see order history, customer details, and take actions without switching between tools. The AI learns your brand voice quickly and starts resolving tickets within hours of setup.
Main features:
Ideal for:
Pricing:
Zendesk serves companies across all industries, from airlines to banks to ecommerce. The AI features are add-ons to their core helpdesk platform. Zendesk AI can suggest responses to agents, categorize tickets automatically, and power basic chatbots.
The platform works well for large enterprises with dedicated IT teams and complex support workflows. However, the ecommerce-specific features require custom development or third-party apps. You'll need separate tools to handle order management, returns processing, and product recommendations.
Pricing:
Intercom focuses on proactive customer engagement through live chat and messaging. Fin AI powers their chatbot, which can answer questions from your help center and knowledge base. The tool excels at starting conversations and qualifying leads before they reach your sales team.
Fin works well for pre-purchase questions and basic support, but lacks deep ecommerce functionality. You can't process orders, handle returns, or access detailed customer purchase history within the platform. Complex post-purchase issues require switching to other tools.
Pricing:
Ringly.io focuses specifically on automating email support for ecommerce brands. The AI learns from your historical tickets to automatically respond to common questions. It positions itself as a direct alternative to Yuma with similar per-resolution pricing options.
Since Ringly only handles email, you'll need other solutions for chat, social media, and phone support. The tool also lacks the order management capabilities that modern ecommerce brands need. Your team still manually processes returns, cancellations, and order updates.
Pricing:
Freshdesk targets small and medium businesses across industries. Freddy AI can automate ticket routing, suggest responses to agents, and power basic chatbots. The platform offers good value for teams just starting with AI automation.
Like other general-purpose helpdesks, Freshdesk requires additional setup for ecommerce-specific workflows. The Shopify integration exists but doesn't provide the deep, native functionality that specialized platforms offer. You'll spend more time configuring and maintaining integrations.
Pricing:
DigitalGenius targets large enterprises with highly complex support workflows. The platform integrates with existing CRM and helpdesk systems like Salesforce and Zendesk. It offers extensive customization options and can handle industry-specific requirements.
The complexity that makes DigitalGenius powerful also makes it overkill for most ecommerce brands. Implementation takes months and requires significant technical resources. The platform works better for companies with dedicated IT teams than for agile online stores.
Pricing:
Alhena AI offers ticket deflection similar to Yuma, focusing on reducing the number of inquiries that reach your human agents. The tool sits on top of your existing helpdesk to intercept and answer common questions automatically.
Alhena shares Yuma's limitations around ecommerce functionality and per-resolution pricing unpredictability. It can answer basic questions but can't take the actions customers need, like processing returns or updating orders. You're still paying for each resolution while handling the complex work manually.
Pricing:
My AskAI lets you create a simple chatbot based on your website content and help center articles. You can embed the widget on your site to answer basic questions automatically. The tool focuses on self-service rather than full support automation.
This works well for answering simple questions but can't handle complex ecommerce tasks. The chatbot can't access order data, process returns, or take any actions beyond providing information. It's a starting point for self-service, not a complete support solution.
Pricing:
We tested each platform from the perspective of a growing ecommerce brand. Our evaluation focused on practical impact rather than feature lists. We looked at how quickly you can get value, how well the tools integrate with your existing stack, and what the true costs look like at scale.
Key evaluation criteria:
It's easy for teams to underestimate what happens when migrating from one tool to another. The transition period can impact response quality, workflows, and even customer satisfaction if not planned carefully.
Tools like Yuma rely heavily on past conversations. When you switch, not all of that training carries over. Some platforms can start resolving tickets within hours, while others take weeks to reach acceptable accuracy.
It’s common to see a short-term drop in automation rate or response quality during the first few days. Teams that phase rollout — keeping humans in the loop while AI ramps — avoid most of this risk.
Macros, help center content, and policies don’t always transfer cleanly. Expect to rebuild or refine parts of your setup, especially if your workflows are complex.
If you’re moving from an email-only tool to a multi-channel platform, this is often the biggest unlock. It also requires rethinking how your team manages conversations across chat, social, and SMS.
The fastest transitions happen when the platform already understands ecommerce data like orders, returns, and customer history, not just conversation logs.
Related: When should you migrate helpdesks? 5 signs to watch out for
The right Yuma alternative depends on what your team needs and what kind of support experience you want to build. You don't have to compare every feature at once, just start with these four steps:
Some tools are built to answer simple questions. Others can fully resolve support requests or even help drive sales.
If your main goal is to reduce ticket volume, a basic automation tool may be enough. If you need AI to handle actions like returns, order updates, or product recommendations, look for a platform with deeper ecommerce functionality.
If most of your conversations happen over email, a narrower tool may work. But if your team also manages live chat, social media, and SMS, you’ll need a platform that supports those channels together.
The more your customer conversations are spread across channels, the more important it is to keep everything in one place.
Some tools require custom integrations and ongoing technical support. Others are easier to launch because they connect directly to platforms like Shopify.
If your team is lean, a tool with native ecommerce integrations will usually get you live faster and reduce maintenance over time.
Per-resolution pricing can work at lower volumes, but it becomes harder to predict as your ticket count grows.
If your support volume changes often during launches, promotions, or peak season, a subscription model usually gives you more control over costs.
The best choice is the one that fits your current operations without limiting what your team can do next.
If you’re moving away from Yuma, decide first whether you need a standalone AI tool or a full helpdesk with built-in AI. Most growing ecommerce brands benefit from a unified platform that can both automate and take action across channels.
Gorgias combines automation with revenue-driving features, built specifically for ecommerce brands.
Still comparing options? See how the best AI helpdesk tools stack up.
Want to test it yourself? Start a free trial.
Prefer a walkthrough? Book a demo.

TL;DR:
Most ecommerce support teams hit the same ceiling: ticket volume grows faster than the team can scale.
AI in customer service changes that equation. It automates repetitive requests, reduces response times, and turns support into a channel that can influence revenue, not just cost.
In this guide, we’ll walk through what AI actually does in customer service, the use cases that drive results, and how to implement it step by step.
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AI in customer service is technology that automates and enhances support operations using machine learning and natural language processing. This means your support team can provide instant, accurate answers to common questions and intelligently route complex issues without manual effort.
Natural language processing (NLP) is the technology that helps computers understand human language. This allows conversational AI to understand what your customers mean, even when they don't use specific keywords.
The core components work together to create a seamless experience:
Machine learning is what makes AI smarter over time. This means the system learns from every interaction and gets better at understanding your customers and resolving their issues.
For ecommerce brands, AI delivers measurable outcomes that directly impact your bottom line. You're not just adding technology — you're solving real business problems.
Instant response times mean your customers get answers immediately, even at 2 a.m. or during Black Friday rushes. No more waiting for your team to come online or catch up on tickets.
Cost reduction happens because AI handles repetitive inquiries automatically. You can scale support without scaling headcount, which means lower cost per contact and better margins.
Improved scalability lets you handle massive spikes in ticket volume during peak seasons. Your team stays focused on complex issues while AI manages the routine stuff.
Customer satisfaction improves when people get fast, consistent answers. AI doesn't have bad days or forget your return policy — it delivers the same quality response every time.
Your agents become more productive when they're not stuck answering "Where's my order?" for the hundredth time. They can focus on building relationships and solving complex problems that actually require human judgment.
Revenue generation happens when AI can recommend products, assist with checkout, and recover abandoned carts. Your support interactions become sales opportunities.
Explore real AI uses cases for ecommerce → 10 must-know AI Agent use cases for instant resolutions
The real value of AI shows up in specific, practical applications. For ecommerce, this means automating the high-volume tasks that consume the most time and have the biggest impact on customer experience.
"Where is my order?" (WISMO) is the most common question in ecommerce. AI connects directly to your shipping and order management systems to provide real-time tracking updates automatically.
The system can handle delivery exceptions and proactively notify customers of delays. This turns a potential negative experience into a positive one by keeping customers informed.
AI manages the entire returns process without agent intervention. It checks if an order is eligible for a return based on your policy, generates a return label, and provides instructions to the customer through automated actions.
When integrated with returns platforms, AI offers complete resolution without any human handoff. Your customers get what they need, and your team saves time.
Not all tickets are created equal. AI categorizes incoming tickets by intent, sentiment, and urgency, then automatically routes them to the right agent or team.
High-priority issues get handled first, and specialized teams get the tickets they're best equipped to resolve. This means faster resolution times and better customer experiences.
AI acts as a copilot for your human agents by providing real-time response suggestions and pulling relevant articles from your knowledge base. It also automatically summarizes long conversations.
This helps agents resolve issues faster and with greater accuracy. They spend less time searching for information and more time helping customers.
Understanding a customer's emotional state is critical for good service. AI analyzes the language and tone of messages to detect sentiment like frustration or anger.
The system automatically escalates sensitive conversations to senior agents or managers for immediate attention. This prevents small issues from becoming big problems.
AI powers interactive voice response (IVR) systems that intelligently route calls and provide answers to common questions. It can offer self-service options like sending a call to SMS.
Real-time call transcription and summaries help with quality assurance and training. Your team gets better insights into customer needs and agent performance.
AI powers your Help Center search and dynamically recommends relevant articles to customers in chat. It analyzes support conversations to identify gaps in your knowledge base.
This means customers find answers faster, and you know exactly what content to create next. Your self-service experience gets better over time.
AI can offer personalized discount codes to high-intent shoppers and re-engage customers who have abandoned their carts. It provides tailored product recommendations based on conversation context and browsing history.
Your support interactions become sales opportunities that drive revenue while solving customer problems.
Related: How to automate your WISMO tickets
A successful AI implementation is strategic, not just technical. You need a phased approach focused on clear goals and measurable results.
Start by identifying what you want to achieve. Are you trying to reduce first response time, lower cost per ticket, or increase your automation rate?
Set specific, measurable goals that align with your business objectives. At the same time, establish clear guardrails for what AI should and should not handle.
Sensitive or complex issues should always escalate to a human. This protects your brand and ensures customers get appropriate care when they need it most.
You don't need to automate everything at once. Analyze your support ticket data to identify the most common, repetitive inquiries.
For most ecommerce brands, this includes:
Start by automating these intents on channels where customers expect fast, simple answers, like live chat and SMS.
AI needs context to be effective. Connect it to your core ecommerce systems, including your order management system, inventory platform, and customer data platform.
This allows AI to perform real actions, like checking an order status or processing a return. Set up clear escalation rules and fallback options for when AI cannot resolve an issue.
Data integration is what makes AI powerful — without it, you're just running a fancy chatbot that can't actually help customers.
Launch your AI with a limited scope, such as handling one specific question type on a single channel. Closely monitor its performance using metrics like resolution rate and customer satisfaction.
Use this data to refine AI behavior, then gradually expand its responsibilities as you gain confidence in its performance. Always maintain a human-in-the-loop process for quality review.
Scaling too fast without proper oversight can damage customer relationships. Take your time and get it right.
Learn more: How to build an AI-driven support strategy
Scaling automation without sacrificing quality requires discipline and clear guidelines. These practices ensure your AI operates safely, accurately, and in line with your brand standards.
Data privacy and security must be your top priority. Ensure your AI platform handles customer data responsibly and complies with all relevant privacy regulations.
Preventing AI hallucinations means limiting your AI to verified information sources, such as your Help Center and integrated apps. This prevents it from providing incorrect or fabricated answers.
Clear escalation protocols ensure complex or sensitive issues get routed to human agents quickly. Design reliable handoff rules that protect your customers and your brand.
Continuous performance monitoring helps you track key metrics like accuracy, resolution rate, and customer satisfaction. You need to understand AI's impact and identify areas for improvement.
Regular optimization treats your AI like a team member that needs ongoing coaching. Use analytics and agent feedback to review and improve its performance regularly.
Transparency with customers builds trust and manages expectations. Be upfront when customers are interacting with AI, and make it easy for them to reach a human when needed.
Read more: Turning AI implementation into team alignment with Rhoback
AI capabilities in customer service are evolving rapidly. While today's tools focus on automating and assisting, the future points toward more autonomous and proactive systems.
Autonomous agents will handle increasingly complex, multi-step tasks from end to end without human intervention. Think complete order modifications, not just status updates.
Multimodal AI will seamlessly understand and respond across different formats, including text, voice, images, and video. Customers can send a photo of a damaged product and get an instant resolution.
Proactive support uses predictive analytics to identify potential customer issues before they happen. AI reaches out with solutions before customers even know there's a problem.
Real-time translation breaks down language barriers, allowing brands to offer high-quality support to a global customer base without hiring multilingual agents.
Deeper personalization leverages a complete view of the customer's history to deliver hyper-personalized support and shopping experiences. Every interaction feels tailored to that specific customer.
These advances will make AI even more valuable for ecommerce brands looking to scale without sacrificing quality.
AI in customer service works best when deployed with clear goals and proper guardrails. Start with high-volume, repetitive inquiries where automation delivers immediate value.
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