

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:
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.
{{lead-magnet-1}}
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.
Want to try Gorgias for yourself? Start a free trial →
Prefer a walkthrough with an expert? Book a demo →

TL;DR:
Gladly pioneered identity-based support, where every customer interaction lives in one conversation thread. But for ecommerce brands, that innovation often comes with trade-offs. High per-agent pricing, limited automation, and weak ecommerce integrations push many brands to explore alternatives.
This guide compares 15 helpdesks that deliver what Gladly promises — unified customer support — while addressing its gaps in automation, pricing flexibility, and ecommerce-specific features. We'll cover the top platforms, key reasons to switch, and how to choose the right tool for your brand.
The best Gladly alternative depends on your specific needs, from budget and team size to automation requirements and Shopify integration depth. While Gladly offers a unified customer view, many alternatives provide more robust ecommerce integrations, flexible pricing, and powerful AI capabilities at a lower total cost.
Platform |
Starting Price |
Best For |
Key Strength |
Automation Level |
Ecommerce Integrations |
Gorgias |
$10/month |
Shopify brands |
Revenue generation & automation |
AI-powered |
100+ |
Kustomer |
$89/agent/month |
Enterprise brands |
CRM capabilities |
Advanced |
Limited |
Zendesk |
$55/agent/month |
All-purpose support |
Scalability & marketplace |
Advanced |
Moderate |
Intercom |
$39/seat/month |
Proactive engagement |
Conversational marketing |
AI-powered |
Moderate |
Re:amaze |
$29/staff/month |
Small ecommerce teams |
Multichannel support |
Basic |
Good |
Freshdesk |
$15/agent/month |
Cost-conscious teams |
Affordability |
Basic |
Limited |
Front |
$19/seat/month |
Collaborative teams |
Shared inbox |
Basic |
Limited |
Help Scout |
$20/user/month |
Simplicity-focused teams |
Ease of use |
Basic |
Limited |
Zoho Desk |
$14/agent/month |
Zoho ecosystem users |
Affordability |
Moderate |
Limited |
HubSpot Service Hub |
$18/month (2 users) |
HubSpot CRM users |
Marketing alignment |
Moderate |
Good |
Kayako |
$15/agent/month |
Journey mapping |
Customer insights |
Basic |
Limited |
LiveAgent |
$9/agent/month |
Real-time support |
Live chat & voice |
Basic |
Limited |
Choosing a helpdesk is a long-term commitment. Below is a detailed breakdown of the top Gladly alternatives, focusing on features, pricing, and ideal use cases for growing ecommerce brands.
Gorgias is a conversational commerce platform built specifically for ecommerce brands. It addresses Gladly's core weaknesses for online retailers by combining a powerful helpdesk with deep Shopify integration, revenue-driving tools, and advanced AI automation.
Unlike Gladly's per-agent model, Gorgias uses usage-based pricing that scales with your business, not your headcount. The platform unifies support and sales, allowing teams to manage orders, issue refunds, and recommend products directly within customer conversations.
Its AI Agent can automate up to 60% of common inquiries like "Where is my order?" returns, and product questions. This frees up agents to focus on complex issues and revenue-generating activities.
Main features:
Ideal for:
Pricing:
{{lead-magnet-1}}
Kustomer is an enterprise-focused CRM platform that provides a unified timeline view of each customer. It consolidates interactions from various channels into a single, chronological conversation. This makes it a strong choice for large businesses that need a comprehensive, 360-degree view of each customer.
However, its strength in CRM capabilities means less focus on ecommerce-specific workflows. While it integrates with platforms like Shopify, the functionality isn't as deep as purpose-built tools. Kustomer's pricing and minimum seat requirements place it firmly in the enterprise category.
Pricing:
Zendesk is one of the most well-known names in customer service software. It offers a scalable, all-purpose helpdesk with a vast app marketplace and the ability to support businesses of all sizes.
For ecommerce brands, Zendesk can be a solid choice, but it requires significant configuration and integration work to match the out-of-the-box functionality of an ecommerce-specific platform. Core ecommerce features like order management and revenue tracking often depend on third-party apps.
Pricing:
Intercom excels at proactive, conversational engagement. It's best known for its powerful chat widget and automation features designed to engage website visitors, qualify leads, and onboard new users.
While it has strong AI and automation capabilities, its focus is more on marketing and sales engagement than post-purchase ecommerce support. Brands looking for deep order management or returns handling within their helpdesk may find Intercom's ecommerce integrations less comprehensive.
Pricing:
Re:amaze is a helpdesk and live chat platform designed for small to medium-sized ecommerce businesses. It offers a good balance of multichannel support, including email, chat, social media, and SMS, in a single shared inbox.
Its native integrations with Shopify, BigCommerce, and WooCommerce are a key advantage. Compared to Gladly, Re:amaze is more affordable and more focused on the needs of online stores. However, its automation capabilities are more basic.
Pricing:
Freshdesk is a popular helpdesk known for its user-friendly interface and affordable pricing, including a free plan for small teams. It offers a comprehensive suite of tools for ticketing, reporting, and automation.
While Freshdesk is a capable general-purpose helpdesk, it lacks the deep ecommerce integrations found in specialized platforms. Ecommerce brands will need to rely on marketplace apps or custom development to bring customer order data into the agent workspace.
Pricing:
Front is a customer communication hub that centers around the shared inbox. It's designed to foster team collaboration by bringing emails, social media, and other channels into a single interface where teams can assign, comment on, and resolve conversations together.
Front is not a traditional helpdesk and lacks many core features ecommerce support teams rely on, such as deep Shopify integration, advanced reporting, and AI-powered automation. It's best for teams that prioritize internal communication over specialized support workflows.
Pricing:
Help Scout is a helpdesk platform that prioritizes simplicity and a human-centric approach to customer service. It offers a clean, uncluttered interface and focuses on features that facilitate personal, helpful conversations.
Like many general-purpose helpdesks, Help Scout's ecommerce capabilities are limited. While it has a Shopify integration, it doesn't allow for actions like editing orders or issuing refunds directly from the helpdesk.
Pricing:
Zoho Desk is the customer service module of the broader Zoho suite of business applications. Its biggest advantage is seamless integration with other Zoho products, like Zoho CRM. It's also one of the most affordable and feature-rich helpdesks on the market.
The platform's context-aware AI, Zia, can help agents with suggestions and automate simple tasks. However, its primary focus is serving the wider Zoho ecosystem, and its ecommerce-specific features aren't as developed as platforms built exclusively for online retail.
Pricing:
HubSpot Service Hub is customer service software that's fully integrated with HubSpot's CRM, Marketing Hub, and Sales Hub. This makes it an excellent choice for businesses already invested in the HubSpot ecosystem.
Service Hub provides a solid set of helpdesk tools, including a shared inbox, knowledge base, and reporting. However, its core strength is its connection to the HubSpot CRM, not its ecommerce-specific functionality.
Pricing:
Kayako is a helpdesk platform that focuses on providing a personal and context-rich customer experience. It offers a unified view of the customer journey by mapping out interactions across different channels.
Kayako is a general-purpose tool and lacks the deep integrations with ecommerce platforms that are critical for efficient online retail support. It's a good option for businesses that prioritize understanding the customer journey but don't require extensive ecommerce automation.
Pricing:
LiveAgent is a helpdesk solution that excels in real-time support channels like live chat and voice. It offers one of the most comprehensive live chat widgets on the market, along with a built-in call center.
The platform also includes gamification features to motivate support agents. While it provides a wide array of features at an affordable price, its focus is on real-time communication rather than the specific needs and workflows of ecommerce brands.
Pricing:
Gladly is a customer service platform built around identity-based support. Instead of treating each new email or chat as a separate ticket, Gladly consolidates all interactions from a single customer into one continuous conversation thread. This gives agents a complete history of every touchpoint, regardless of the channel.
This approach eliminates the need for ticket numbers and helps agents provide more personal and context-aware support. The platform is designed to be people-centric, not case-centric.
Key Gladly features:
Gladly pricing:
While Gladly's people-centric model is innovative, it's not the right fit for every business, especially in ecommerce. Brands often seek alternatives when they face challenges with pricing, automation, or lack of ecommerce-specific functionality.
High-growth ecommerce brands need pricing that scales with order volume, not just agent headcount. They also require deep integrations with platforms like Shopify to manage orders and track support's impact on revenue.
Cost-conscious teams find Gladly's high per-agent cost and annual contracts prohibitive. Teams looking for more flexible, usage-based pricing or lower monthly fees will find better value in alternatives.
Automation-first organizations want to automate a significant percentage of their support volume and need more advanced AI than Gladly offers. They require tools that can fully resolve tickets, not just route them.
Specialized support needs include businesses that rely on specific workflows for returns, subscriptions, or loyalty programs. These brands need a platform with a rich ecosystem of ecommerce integrations that Gladly lacks.
We evaluated dozens of helpdesks based on criteria that matter most to growing ecommerce brands. Our methodology focused on identifying platforms that not only match Gladly's core promise of a unified customer view but also solve its primary shortcomings for online retailers.
Core evaluation criteria:
When evaluating your options, focus on how each platform handles the core jobs of an ecommerce support team. Look beyond marketing claims and dig into specific functionality that will impact your team's daily workflow and your brand's bottom line.
Unified customer view capabilities:
Automation and AI features:
Ecommerce-specific functionality:
Pricing and scalability:
Start by auditing your current Gladly usage. Export your ticket data to identify common inquiry types and your cost per ticket. This gives you a baseline for evaluating alternatives.
Then, narrow your shortlist to two or three tools and test them using real scenarios. Focus on what impacts your team: automation rate, handle time, and access to order data.
If you're still deciding, these guides can help:
Want to test it with your own data? Start a free trial and see how Gorgias handles real support volume.

TL;DR:
Enterprise support platforms do more than manage tickets. They unify customer conversations across email, chat, social, SMS, and voice into a single workspace. The right platform connects your support data to your ecommerce stack, turning every interaction into an opportunity to resolve issues and drive revenue. This guide compares 12 platforms built for high-volume ecommerce operations.
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An enterprise support platform is a centralized system that manages high volumes of customer interactions across multiple channels. This means you can handle thousands of conversations from email, chat, social media, and phone calls in one place. Unlike basic help desks, these platforms integrate deeply with your business systems and offer advanced automation.
Platform |
Starting Price |
Key Strengths |
Best For |
Notable Limitations |
Gorgias |
$10/month |
Ecommerce-native, deep Shopify integration, AI Agent |
Shopify Plus brands focused on support-driven revenue |
Less suited for non-ecommerce businesses |
Zendesk |
$55/agent/month |
Mature feature set, broad industry use |
General enterprise use across industries |
Complex and costly to customize for ecommerce |
Salesforce |
$25/user/month |
Deep CRM integration, enterprise ecosystem |
Companies already using Salesforce |
High total cost, complex implementation |
Intercom |
$39/seat/month |
Strong conversational tools, proactive messaging |
SaaS and tech companies |
Expensive at scale, less post-purchase focus |
Freshdesk |
$15/agent/month |
Good value, broad feature set |
Mid-market all-in-one solution seekers |
Less advanced AI and automation |
Kustomer |
$89/user/month |
Customer timeline view, data aggregation |
B2C brands needing complete customer history |
Higher price, resource-intensive |
Front |
$59/seat/month |
Collaborative inbox, team communication |
Teams needing heavy email collaboration |
Not a traditional helpdesk, limited automation |
Zoho Desk |
$14/agent/month |
Zoho ecosystem integration, affordable |
Businesses using other Zoho products |
Dated interface, less retail specialization |
Help Scout |
$20/user/month |
Simplicity, clean UI, human-centric |
Small to mid-sized teams prioritizing ease |
Lacks advanced enterprise features |
Gladly |
$150/agent/month |
Radically personal, conversation-centric |
High-end brands focused on premium service |
Very expensive, not built for efficiency |
ServiceNow |
Custom |
Powerful ITSM, extreme scalability |
Large enterprises with complex needs |
Overkill for most ecommerce, very expensive |
Tidio |
$29/month |
Strong live chat, easy setup |
Small businesses focused on chat support |
Lacks enterprise omnichannel depth |
Choosing the right platform depends on your business model, primary sales channels, and growth goals. Here are the top solutions for enterprise ecommerce brands.
Gorgias is a conversational commerce platform built specifically for ecommerce brands. This means it combines customer support with sales capabilities in one system. Its key advantage is deep, native integration with Shopify, allowing your team to manage orders, issue refunds, and apply discounts directly from the helpdesk.
The platform unifies conversations from email, live chat, SMS, voice, and social media into a single view. You get customer data from over 100 ecommerce integrations automatically. The Gorgias AI Agent can automate up to 60% of common inquiries like "Where is my order?" It also acts as a shopping assistant, providing product recommendations and converting shoppers in real time.
Main features:
Ideal for:
Pricing:
Zendesk is one of the most established customer service software platforms. It offers comprehensive tools that work across many industries beyond ecommerce. The platform is known for flexibility, an extensive app marketplace, and mature features including ticketing, knowledge base, and robust reporting.
For enterprise teams, Zendesk provides advanced security, compliance, and customization options. However, its generalist approach means achieving deep ecommerce functionality often requires costly third-party apps and complex configuration.
Pricing:
Salesforce Service Cloud is powerful for enterprises already using the Salesforce ecosystem. Its greatest strength is seamless integration with Salesforce CRM, providing a complete view of each customer. It offers extensive capabilities for case management, automation, and omnichannel routing at massive scale.
This power comes with significant complexity and cost. Implementation often takes months and requires specialized expertise. For ecommerce brands not already using Salesforce, the platform can be overkill.
Pricing:
Intercom pioneered conversational support, focusing on proactive engagement through its messenger. It excels at engaging users on-site and in-app, making it popular with SaaS and technology companies. The platform includes live chat, chatbots, and targeted outbound messaging campaigns.
While Intercom's conversational tools are strong, its focus is more on user acquisition than the full post-purchase ecommerce experience. Managing high volumes of transactional support inquiries can be less efficient compared to platforms with traditional ticketing foundations.
Pricing:
Freshdesk offers a user-friendly and affordable helpdesk solution with broad features. It provides omnichannel ticketing, AI-powered automation, and self-service options. The straightforward interface makes it relatively easy for teams to get started.
For enterprise ecommerce, Freshdesk is a solid, cost-effective option. However, its AI and automation capabilities are generally less sophisticated than specialized platforms.
Pricing:
Kustomer uses a customer-centric data model, organizing all interactions into a single timeline view rather than separate tickets. This provides agents with rich, chronological context for every customer. The platform is designed for B2C brands and offers strong omnichannel and automation capabilities.
The main trade-off is Kustomer's higher price point and potential complexity of managing its data-heavy environment. It's best suited for brands that prioritize a deep, historical view of each customer over pure ticket-processing speed.
Pricing:
Front is a collaborative customer communication platform centered around a shared inbox. It brings emails, SMS, and social messages into a single space where teams can assign, comment on, and resolve conversations together. Its strength lies in facilitating internal collaboration around external communication.
Front is not a traditional helpdesk. It lacks robust ticketing structure, deep automation, and performance reporting that most enterprise support teams require.
Pricing:
Zoho Desk is an affordable helpdesk that's part of the broader Zoho suite of business applications. Its biggest advantage is tight integration with other Zoho products, like Zoho CRM. It offers solid omnichannel support, workflow automation, and AI-powered assistance.
For businesses not already using the Zoho ecosystem, it functions as a capable standalone helpdesk. However, its user interface can feel less modern than competitors.
Pricing:
Help Scout is known for simplicity, clean design, and focus on providing a human-centric support experience. It offers a shared inbox, knowledge base, and live chat in a straightforward package that's easy to learn and use.
This focus on simplicity means Help Scout lacks many advanced automation, reporting, and enterprise-grade security features required by large-scale operations.
Pricing:
Gladly offers a "radically personal" approach to customer service, eliminating tickets in favor of a lifelong conversation stream with each customer. The platform centers all communication around the individual shopper, regardless of channel.
This premium approach comes at a very high price point. Gladly is designed for luxury and high-end brands where the cost of providing exceptional, high-touch experience is justified.
Pricing:
ServiceNow dominates enterprise IT Service Management and extends those capabilities to external customers through its Customer Service Management product. It excels at automating complex, cross-departmental workflows and operates at immense scale.
For most ecommerce brands, ServiceNow is overly complex and expensive. Its foundation is in IT and internal processes, not the fast-paced, revenue-focused world of online retail.
Pricing:
Tidio started as a live chat and chatbot tool for small businesses and has expanded to serve larger teams. Its strengths are ease of use, strong chat automation capabilities, and affordable entry point.
While effective for chat, Tidio lacks true omnichannel depth and robust backend management features of a full enterprise support platform.
Pricing:
Enterprise features go beyond basic ticketing to enable scale, security, and strategic value. These capabilities separate a true enterprise platform from a standard help desk.
Omnichannel support means managing all customer conversations from a single, unified inbox. This includes email, live chat, social media DMs, SMS, and voice calls. The key is maintaining seamless conversation flow and full customer context as shoppers move between channels.
Your customers don't think in channels — they think in conversations. When someone starts a conversation on Instagram and continues it via email, your team needs to see the full history without switching tools.
At enterprise scale, automation is essential. This includes AI-powered ticket routing, intent detection, and automated responses for common questions. It also extends to customer-facing self-service tools.
Modern AI can handle complex scenarios beyond simple FAQ responses:
Enterprise platforms provide deep, customizable analytics. This goes beyond basic metrics like first response time. You get real-time dashboards, SLA tracking, agent performance scorecards, and custom reports that connect support activity to business outcomes.
The best platforms show you how support conversations drive revenue, not just how quickly you respond to them.
Large businesses have strict security requirements. Enterprise platforms offer SOC 2 compliance, single sign-on, multi-factor authentication, and role-based access controls to protect customer data. They also provide audit logs and options for data residency to meet global compliance standards.
Security isn't optional at enterprise scale — it's table stakes.
An enterprise platform must act as the central hub for customer data. This requires deep, bi-directional integrations with other systems like your ecommerce platform, ERP, and marketing tools. A flexible API and unified customer data model create a single source of truth.
When your support team can see order history, subscription details, and marketing engagement in one view, they can provide better service and drive more revenue.
For retail brands, the platform must support specific ecommerce workflows. This includes viewing and modifying orders, processing returns and exchanges, managing subscriptions, and tracking revenue generated from support interactions — all directly within the helpdesk interface.
Generic business software forces your team to jump between systems. Ecommerce-native platforms let them work where the conversation happens.
As your business grows, the tools that worked for a small team start to break. The differences between enterprise platforms and small-to-midsize business help desks reflect fundamental differences in scale, complexity, and strategic needs.
SMB help desks handle smaller teams and manageable ticket volumes. Enterprise platforms are engineered for hundreds of thousands of interactions across multiple brands, regions, and languages. They include advanced routing, multi-brand support from a single instance, and robust user permissions to manage large, distributed teams.
When you're processing thousands of tickets daily across multiple time zones, you need different tools than a five-person team handling dozens of emails.
SMB tools offer basic integrations. Enterprise platforms provide deep, two-way data synchronization with core business systems. They have extensive APIs, support custom integrations, and connect to data warehouses for advanced business intelligence.
This creates a unified data ecosystem rather than a collection of disconnected tools.
With SMB tools, support is often limited to email or chat. Enterprise platform vendors act more like strategic partners. They provide dedicated success managers, implementation support, guaranteed uptime SLAs, and ongoing strategic guidance.
You're not just buying software — you're buying a relationship that helps you scale.
Making the right choice requires clear evaluation of your business needs, technical stack, and long-term goals. Focus on these key areas to find the platform that best fits your operation.
Start by auditing where your customers actually contact you. Are they on Instagram, SMS, or still primarily using email? Ensure the platform you choose has native, robust support for the channels your customers prefer.
Don't choose based on what you think customers should use — choose based on what they actually use.
For ecommerce brands, deep integration with your store platform is non-negotiable. Look for bi-directional sync that allows agents to take action directly from the helpdesk. Verify that the platform also connects seamlessly with your other critical tools.
The best integrations feel invisible — your team shouldn't know they're using multiple systems.
Look beyond the per-seat license fee. Calculate total cost of ownership, which includes implementation, training, and necessary third-party apps. Measure this against potential return on investment from increased agent efficiency, higher ticket deflection rates, and support-driven revenue.
A more expensive platform that drives revenue can be cheaper than a "budget" option that doesn't.
Some platforms take months to implement and require a dedicated administrator. Others can be running in days. Be realistic about your team's resources and choose a platform with an implementation timeline and ongoing maintenance load you can support.
The fastest implementation isn't always the best, but the slowest is rarely worth it.
Work with your IT and legal teams to confirm the platform meets your company's security and compliance standards. This includes data encryption, access controls, and adherence to regulations like GDPR or CCPA.
Don't treat security as an afterthought — it's harder to fix later than to get right from the start.
The right enterprise support platform transforms customer conversations into competitive advantage. Whether you're scaling from SMB tools or evaluating alternatives to your current platform, focus on solutions that match your ecommerce operations and growth trajectory.
Book a demo to see how Gorgias delivers enterprise-grade support built specifically for ecommerce.
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TL;DR:
Picking a support platform is one decision. Figuring out whether you can actually forecast the bill is another. For ecommerce brands, the pricing model — how costs are calculated, what drives them up, and what happens during a volume spike — often creates more friction than the price itself.
This guide breaks down seat-based, usage-based, and hybrid pricing in ecommerce CX to help you answer the questions that matter most: Will this be easy to budget? What happens if usage spikes? Will you overpay during slow seasons? And how does AI complicate the cost?
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The wrong pricing model creates budget problems, internal friction, and surprise charges even if the platform itself is a strong fit. That's why the structure of how you're billed matters as much as the number on the invoice.
A seat-based model might look affordable until you're paying for 15 agents during a slow January when half the team is idle. A usage-based model might seem efficient until a Black Friday spike generates an overage nobody budgeted for. The model shapes how costs behave across seasons, headcount changes, and AI adoption. The wrong fit creates friction at renewal, during audits, and every time you have to explain a variable invoice to finance.
The real tradeoff isn't just predictability versus flexibility. It's whether your pricing structure matches how your team actually operates, and whether you can explain it clearly enough to get and keep internal buy-in.
|
Category |
Seat-Based |
Usage-Based |
|
What you pay for |
Number of agents |
Activity (tickets, AI, etc.) |
|
Cost |
Fixed per seat |
Varies with usage |
|
Predictability |
High |
Lower |
|
Flexibility |
Low |
High |
|
Main risk |
Paying for unused seats |
Cost spikes with high volume |
The core difference is simple: seat-based pricing ties your costs to team size, and usage-based pricing ties your costs to activity. Everything else flows from that distinction.
With seat-based pricing, you pay a flat fee per user regardless of how much your team actually uses the platform. Predictable, easy to budget, but you pay the same whether agents are handling 500 tickets a day or 50.
With usage-based pricing, you're billed for what you actually consume: tickets resolved, conversations handled, AI interactions completed. Costs can scale down during slow periods, but also up when volume spikes.
Most platforms today sit somewhere between the two, with a base fee for core access and usage charges on top for features like AI or automation. Understanding the billing units in play is key to forecasting what you'll actually pay.
Common billing units in CX tools:
Before evaluating pricing models, it helps to get clear on what you actually need from a billing structure. These are the questions worth answering before you start comparing plans.
Seat-based pricing means the bill is fixed, the math is simple, and finance knows exactly what to expect every month.
It works best for teams with stable headcount and consistent ticket volume year-round. If your support team size doesn't change much and your demand is predictable, seat-based pricing removes a lot of billing complexity without many cons.
The friction shows up when your usage doesn't match your headcount. During slow seasons, you're paying full price for seats that aren't generating much value. When AI starts resolving a large share of your tickets, the per-agent model starts to feel misaligned with where the work is actually happening. And when other teams want occasional platform access, such as marketing pulling customer insights or finance reviewing chargeback data, every additional user has a cost attached.
Seat-based pricing works well when:
It creates friction when:
Usage-based pricing is the more efficient model on paper. You pay for what you use, costs scale with demand, and you're not carrying unused capacity through slow seasons.
It works best for lean teams, highly automated operations, and brands with significant volume swings between peak and off-season. If AI is resolving the majority of your tickets, usage-based pricing reflects that reality better than paying per human agent.
The hesitation is legitimate, though. Variable billing is harder to forecast, harder to explain to finance, and carries real overage risk if usage spikes faster than expected. There's also a definitional problem: not every platform defines billable units the same way. A "conversation" on one platform may not equal a "conversation" on another, which makes apples-to-apples comparisons difficult.
Usage-based pricing works well when:
It creates friction when:
For seasonal ecommerce brands, the pricing model question is more urgent than it is for most SaaS buyers. A structure that works fine for a stable support team can create serious budget problems when your ticket volume in November is five times what it is in February.
Usage-based pricing looks like the natural fit. Costs go up during peaks and come back down in slow periods. But variable billing during your highest-revenue, highest-stress period of the year carries its own risk. An unexpected overage in November is a harder conversation to have than one in March.
The goal isn't just a model that scales up during peak season. It's one that scales back down reliably afterward, has a clear ceiling on costs, and doesn't lock you into commitments based on peak-period usage for the rest of the year. Before signing anything, make sure you understand exactly how the pricing behaves at both ends of your volume range, not just the high end.
Hybrid pricing is the most practical option for most ecommerce teams. It reduces the most common risks on both sides: the waste of paying for unused seats and the unpredictability of a fully variable bill.
A typical hybrid structure includes a base fee for core platform access and usage-based charges on top for features like AI, automation, or high-volume messaging. You get cost certainty for everyday operations and flexibility where your usage is harder to predict.
Common hybrid structures include:
The risk is complexity. When you're tracking multiple billing meters at once, forecasting gets harder, auditing gets harder, and explaining the bill to finance gets harder. A hybrid model is only better than a pure usage model if it's transparent enough to actually manage.
Regardless of which model you choose, the platforms that handle pricing best give you tools to stay in control of costs.
The most important controls to look for are usage caps that set a hard ceiling on monthly consumption, alert thresholds that notify you before you hit a limit, and transparent overage rules with published rates rather than ambiguous "contact us" language. Beyond those basics, look for clear definitions of what counts as a billable event, flexibility to upgrade or downgrade mid-cycle without penalties, and monthly commitment options that let you test a pricing model before locking into an annual contract.
If a vendor can't clearly answer what triggers a charge, what the ceiling is, and how you'll be notified before you hit it, that's a signal the pricing structure will be harder to manage than it needs to be.
AI introduces a second pricing layer that many buyers don't fully account for until after they've signed. Here's how it changes the pricing equation:
No single model works for every ecommerce brand, but most teams fit a recognizable pattern. Work through these steps to identify the right fit.
If your headcount and ticket volume are consistent year-round, seat-based pricing is likely the simpler, lower-risk choice. If either fluctuates significantly, move to step 2.
Identify the gap between your peak and off-peak support volume. The wider that gap, the more a fixed seat-based model will cost you in unused capacity during slow periods.
If AI or automation is already handling a significant share of your tickets, or you plan to scale it, evaluate AI pricing as a separate layer. A platform that looks affordable on seats may become expensive once AI usage is factored in.
Understand what your internal approval process requires. If finance needs a fixed annual number, that constraint should shape your model decision before you start comparing features.
The right pricing model matches how your team actually operates.
As your support volume grows and AI takes on more of the workload, reassess your pricing structure at least once a year. The model that made sense at 10 agents may work against you at 30.
Once you've identified the right model, the next step is finding the right plan.
See how Gorgias pricing is structured and which plan fits your team.


