

A few things to know before you connect Gorgias MCP:
Ask your helpdesk anything, and get a real answer from your actual data in seconds.
Gorgias MCP connects your Gorgias account directly to Claude, ChatGPT, Cursor, or any other MCP-compatible AI tool. No more exporting data or re-explaining context every time you need a different angle on your tickets. Ask a question, follow up, and execute, all in the same conversation.
This guide covers what Gorgias MCP is, how to connect it, and six specific workflows you can run in your first session.
The Model Context Protocol (MCP) enables AI systems to link directly with other tools.
The Gorgias MCP provides a first-party bridge, giving you a secure, direct connection between your chosen AI assistant and your Gorgias account.
Once connected, your LLM of choice can:
Setup takes about five minutes. Here is what you need and how to do it.
What you need:
Steps:
The exact steps vary slightly depending on which AI tool you use.
Read more: The Gorgias MCP setup guide specifically walks through Claude, ChatGPT, and Cursor.
Each workflow below includes the exact prompt to copy. Adjust the specifics to match your store, and run it in your first session.
CSAT dips are easy to spot in your dashboard. The cause is harder. Figuring it out usually means opening tickets one by one, building a custom filter, and reading through results one by one.
The prompt:
What you get: A grouped breakdown of the patterns behind your low scores, based on what customers wrote.
Follow-up prompts:
Handoff reports tell you how many tickets AI Agent escalated to your team. They rarely tell you why. Diagnosing the root cause and writing new guidance to fix it are usually two separate tasks that happen days apart, if at all.
With Gorgias MCP, you can do both in the same conversation.
The prompt:
Then, without starting a new chat:
What you get: A diagnosis of where AI Agent is struggling and a ready-to-review draft guidance to address the top gap. You apply it manually in Gorgias, but the thinking is done.
Follow-up prompts:
This is one of the most powerful early use cases customers have found. By connecting Gorgias MCP with the Shopify MCP, you can link what customers complain about in tickets to the product pages where that friction lives.
To use this workflow, connect both Gorgias MCP and Shopify MCP oto your AI tool first.
The prompt:
What you get: A prioritized list of friction points tied to specific content gaps on your product pages, ready to hand off to your product or merchandising team.
Follow-up prompts:
Gorgias's built-in reports cover the core metrics well. But when you need a specific cut, ticket volume by intent for a particular channel, or resolution time broken down by tag, getting there requires an export and a spreadsheet.
Ask for exactly what you need instead.
The prompt:
What you get: A custom breakdown you can copy directly into a slide or share with your team, built from a single question.
Follow-up prompts:
Every support inbox has repeat questions that agents are still answering manually. Some of those topics may already have a macro, but others show up again and again without consistent macro usage. This workflow helps surface the best candidates to standardize next.
The prompt:
What you get: A ranked list of frequent support topics that appear to be handled manually most of the time, helping your team prioritize where a new or better macro could save the most effort.
Follow-up prompts:
Tag libraries tend to grow organically. Over time, teams end up with overlapping labels like “return,” “returns,” and “return-request,” along with tags that are rarely used and naming patterns that make reporting harder to trust. This workflow helps identify cleanup opportunities based on how tags are actually used on tickets.
The prompt:
What you get: A list of likely tag issues grouped by type — duplicates, low-use tags, and inconsistent naming — based on actual ticket usage, with consolidation suggestions your team can act on.
Follow-up prompts:
Everything in the workflows above is already sitting in your Gorgias account. Gorgias MCP just makes it conversational.
Not sure where to start? Try workflow 1 (CSAT drop report) or workflow 6 (tag cleanup) first. Both deliver results quickly and work regardless of how your account is configured.
Gorgias MCP is currently in open beta and available to all paid plan customers.
TL;DR:
Getting more out of your Zendesk AI Agent comes down to better configuration. The problem is that auditing your own setup requires time you don't have.
Gaia for Zendesk is a free Chrome extension from Gorgias that clears that backlog in minutes. It connects to your Zendesk account, reads your tickets, and generates the components your AI Agent needs to resolve more conversations without escalation.
Below, you'll find everything you need to get started: how to install Gaia, what it can do, and the use cases teams are already putting it to work for.
Jump to:
Zendesk Suite admins and agents who want to set up or improve their Zendesk AI Agent (and, optionally, Zendesk Copilot).
Throughout this article, "AI Agent" refers to Zendesk's own AI Agent feature, not Gorgias's product. Gaia is the Gorgias-built Chrome extension that helps you configure it.
Gaia for Zendesk is a free Chrome extension built by Gorgias that connects to your Zendesk account and analyzes your real ticket history.
It autonomously transforms that data into the core components your Zendesk AI Agent needs to resolve more tickets without human intervention: guidances, instructions, voice-of-customer insights, and Copilot procedures.
Gaia opens automatically as a side panel on any .zendesk.com page. You choose a workflow, Gaia runs the analysis and generates structured drafts, and you review and approve what should be applied to your Zendesk workspace.
What Gaia can do:
Good to know: Gaia is autonomous in how it analyzes your data and generates recommendations, but nothing is applied without your approval.
How well your AI Agent performs comes down to how well it is configured. Clear instructions, well-defined intents, and up-to-date procedures are what separate an AI Agent that resolves tickets from one that escalates them — and building that foundation manually takes time most teams do not have.
Gaia removes that constraint by turning your existing support data into structured, ready-to-review outputs:
Tip: Teams that define five or more strong guidances typically see a meaningful lift in the share of tickets their AI Agent resolves without escalation. Gaia is designed to help you reach and expand beyond that baseline quickly.
Installation takes about five minutes. You'll need admin access to your Zendesk account to generate an API token.
Make sure you're using Google Chrome or another Chromium-based browser (such as Edge or Brave). Gaia is not available for Safari or Firefox at launch.
Follow these steps:
1. Install the Gaia for Zendesk extension. Go to the Chrome Web Store listing for Gaia for Zendesk by Gorgias and click Add to Chrome. Confirm the permissions to complete installation.
2. Generate a Zendesk API token. In Zendesk, navigate to Admin Center › Apps and integrations › Zendesk API. Enable Token access if needed, then click Add API token. Copy and store the token securely (it will not be visible again).
3. Open the Gaia extension and add your credentials. Click the Gaia icon in your Chrome toolbar, then open Settings. Enter:
4. Click Save. Gaia will validate the connection.
5. Open any Zendesk page. Navigate to any page in your Zendesk account. Gaia will appear as a side panel where you can select a workflow and begin.
Here are the four most common ways teams use Gaia for Zendesk.
Best for: Teams already using Zendesk AI Agent or Answer Bot but not reaching their automation goals
Select Improve my AI Agent. Gaia analyzes escalated tickets against your current guidances to identify missing intents, unclear instructions, and outdated logic, then proposes prioritized improvements.
Best for: Teams starting without an established AI configuration
Select Create my first instructions. Gaia generates a foundational set of 15 instructions covering common ecommerce scenarios (order status, refunds, cancellations, shipping, returns).
Best for: Support, CX, and operations teams planning improvements or reporting on performance
Select Analyze my tickets. Gaia summarizes ticket volume, top intents, and escalation drivers to highlight where automation or process improvements will have the greatest impact.
Best for: Teams using Zendesk Copilot who want consistent, scalable agent workflows
Requires the Copilot add-on in Zendesk. Select Create my first procedures. Gaia converts real agent behavior into structured WHEN/IF/THEN procedures that standardize how common scenarios are handled.
Gaia connects to your Zendesk account, reads your ticket history, and shows you exactly where your setup is falling short. Install the free Chrome extension and run your first analysis in under a minute.
The best in CX and ecommerce, right to your inbox

TL;DR:
Your ticket volume number is probably wrong. If customers are reaching you through email forwards, Slack DMs, or channels that bypass your helpdesk, those tickets aren't being counted, and your SLA reporting is built on incomplete data. This guide covers how to get an accurate count, break it down by channel and category, and use your vertical benchmark to figure out whether your volume is actually a problem or just normal for your industry.
Ticket volume is the total number of customer inquiries your support team receives across all channels — email, live chat, phone, social media, and contact forms — within a specific time period. It is the most direct measure of your team's workload.
Do not confuse it with contact rate. Contact rate = tickets ÷ orders (or customers). That normalized number is more useful for benchmarking and planning because it accounts for business growth. Raw ticket volume tells you how busy your team is. Contact rate tells you whether support demand is outpacing your business.
Start by looking at the last 30 days of customer conversations, no matter where they currently live.
Pull these four numbers:
Here’s how to pull that data depending on your setup:
Open your inbox or Sent folder and filter by the last 30 days. Count how many customer conversations came in during that period. You can also copy subject lines into ChatGPT or Claude to group conversations by topic.
Go to Inbox > Conversations and review your recent conversations. Count how many messages you received and look for repeated themes or questions.
Most helpdesks have ticket reporting or exports built in. Search “export tickets” or “ticket report” in your platform’s help center. From there, you can pull:
If a large portion of customer questions are still happening in untracked places like Slack DMs, personal inboxes, or Instagram comments, your reporting is incomplete. Before optimizing support operations, route customer conversations into one shared system so you can accurately measure volume, response times, and recurring issues.
A raw ticket count tells you how busy your team is. The breakdown tells you what to fix.
|
Category |
What high volume signals |
What to do |
|
"Where is my order?" |
No proactive shipping updates; poor tracking page |
Automate WISMO with AI Agent; add tracking link to order confirmation |
|
Returns and exchanges |
Confusing return policy; no self-serve portal |
Add a clear returns page; enable self-serve exchange flows |
|
Sizing and product questions |
Weak product page content |
Add size guides, FAQs, and fit notes directly on product pages |
|
Account and subscription issues |
Customers can't self-serve basic account changes |
Build or improve your Help Center; enable self-serve account management |
|
Payment and billing |
Checkout friction or unclear pricing |
Fix at the source — this is rarely a support problem |
Run this categorization for your last 30 days. Your top two or three categories are your highest-leverage targets.
Ticket volume only tells part of the story. Track it alongside:
Once you know what is driving your volume, address each category at the source. The goal is to eliminate unnecessary tickets.
Automate the highest-volume, lowest-complexity tickets first. WISMO inquiries, order status checks, and basic return initiations require no agent judgment. An AI Agent connected to your ecommerce platform can handle these end-to-end without a human stepping in. When a question is too complex, the AI escalates it with full context attached.
Build self-service content around your top categories. A Help Center that directly addresses your most common ticket types is the highest-leverage tool for sustained volume reduction. Start with your top five categories. Write one article per category. Surface those articles on relevant product pages, in checkout, and in post-purchase emails — before customers need to search.
Send proactive messages at the moments that generate the most tickets. Post-purchase is the single highest-value touchpoint: an order confirmation that includes a tracking link, estimated delivery window, and a clear link to your return policy eliminates a large share of inbound questions before they are ever submitted.
Measure deflection, not just volume. Deflection rate, the percentage of issues resolved through self-service or automation, is the metric that tells you whether your volume reduction efforts are actually working. Track it weekly alongside CSAT for automated interactions to make sure quality is holding.
The all-industry average is not your benchmark. Ticket volume per 100 orders varies 2.4x across verticals, so comparing yourself to a cross-industry number will either make you complacent or create false urgency.
According to Gorgias platform data from March 2026 across 14 verticals at the $10M GMV band, here is what tickets per 100 orders actually looks like by vertical:
|
Vertical |
Tickets per 100 orders |
|
Electronics |
46 |
|
Vehicles & Parts |
46 |
|
Hardware |
41 |
|
Luggage & Bags |
32 |
|
Home & Garden |
32 |
|
Sporting Goods |
32 |
|
Baby & Toddler |
24 |
|
Business & Industrial |
25 |
|
Animals & Pet Supplies |
25 |
|
Apparel & Accessories |
22 |
|
Health & Beauty |
21 |
|
Arts & Entertainment |
21 |
|
Food & Beverages |
20 |
|
Toys & Games |
19 |
Source: Gorgias Ecom Lab, March 2026
High ticket volume is not always a sign of poor CX — it often reflects product complexity. Electronics brands generate nearly one ticket per two orders because customers have more pre- and post-purchase questions about technical products. Food and Beverage brands generate about one in five. That gap is not a performance difference; it is a category difference.
The right question is not "are we below 10 tickets per 100 orders?" It is "are we above or below our vertical peers?" Find your row. That is your baseline. Then use the reduction tactics above to move below it.
If your ticketing tool uses usage-based pricing, where your bill scales with ticket volume rather than agent headcount, forecasting volume directly affects your budget.
The core formula is simple:
Projected tickets = projected orders × (tickets per 100 orders ÷ 100)
So if you expect 2,000 orders next month and your vertical median is 22 tickets per 100 orders, your forecast is approximately 440 tickets.
But a flat monthly estimate misses the real risk: peak seasons. A volume spike during BFCM that triples your order volume will also triple your ticket count — and your bill — unless you have guardrails in place.
To build a more accurate forecast:
Before signing any usage-based contract, ask two questions: What counts as a billable ticket? And is there a hard cap on monthly charges? Variable billing only works in your favor if you have clear definitions of what triggers a charge and a ceiling on how high costs can go during an unexpected spike.
If your platform bills per ticket resolved by a human agent (not AI), your deflection rate becomes a financial metric, not just an operational one. Every percentage point of additional deflection directly reduces your bill.
Begin by identifying your top ticket categories, then work backward to find the root cause of each one.
From there, layer in self-service content, automation, and proactive messaging to address those root causes directly. The result is a support operation that handles more customers and a team that spends its time on the work that actually requires human judgment.
Book a demo to see how Gorgias helps ecommerce brands reduce ticket volume and improve customer experience at the same time.
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TL;DR:
If you're wondering what it costs to add AI Agent to your Helpdesk, you're in the right place. This article walks through how pricing works, what counts as a billable interaction, and how to think about the investment before talking to anyone on our team.
The good news: there are no seat fees, no per-message charges, and no token-based billing. You pay for conversations your AI actually resolves. If you've looked into other AI tools for customer support and found the pricing models confusing or hard to predict, Gorgias AI Agent works differently.
A billable interaction is counted when the AI resolves a customer conversation entirely on its own. The customer asks something, the AI handles it, the conversation closes. That's one interaction.
If the AI can't fully resolve a conversation and hands it to a human agent, that ticket shifts over to your regular Helpdesk plan. It becomes a standard resolved ticket. You're not charged for both.
A few things that don't count as billable interactions:
This matters most for brands coming from seat-based tools. With Gorgias, your whole team can work in the platform. Agent seats are unlimited. Pricing scales with what your AI is actually doing, not with how many people have access.
Understand the difference between seat-based vs. usage-based pricing.
AI Agent is an add-on to your Gorgias Helpdesk plan. The two are priced separately but work together. Your Helpdesk plan covers all the conversations your human agents resolve. Your AI Agent plan covers the interactions the AI resolves on its own.
When you choose a plan, you select how many automated interactions you want included per month. Depending on your plan, that ranges from 90 to 2,500+ interactions, with custom interaction numbers available for enterprise. You can see the full breakdown on the Gorgias pricing page.
Each resolved conversation costs $0.90 on most plans. Starter plans begin at $1 per resolved conversation. You only pay for fully automated interactions, meaning conversations the AI handles from start to finish without a human stepping in.
The main input is your average monthly ticket volume. From there, you estimate how many of those conversations AI could realistically handle on its own.
Order status updates, return requests, and shipping questions tend to be the highest-volume ticket types AI resolves well. AI Agent actions shows the full range of what it can handle, which makes it easier to estimate your starting number.
Your actual automation rate, meaning the share of total tickets the AI ends up resolving, emerges from usage over time. Most brands start with their most repetitive ticket types and expand from there as they see results.
Related: Which Gorgias plan should you choose?
You're charged an overage fee for each additional automated interaction if you exceed your plan's baseline in a given month. The exact rate depends on your plan tier and whether you're on a monthly or annual subscription.
Generally, the higher your plan tier, the lower your overage rate. Annual plans also carry lower overage rates than monthly plans. So if you're regularly going over, upgrading to a higher tier or switching to annual often works out cheaper than paying overage fees month after month.
If you're on a Support + Shopping Assistant plan, the overage rate is $1.50 per interaction across all paid tiers. If you're on a Support-only plan, rates range from $1.00 to $2.00 per interaction on monthly plans, and $0.83 to $1.67 on annual plans, depending on your tier.
For seasonal businesses, forecasting your customer service volume before peak periods is the best way to choose the right plan size and avoid unexpected fees.
At $0.90 per resolved interaction on most plans, each AI resolution costs less than a human agent handling the same ticket. Once you know what a human-resolved ticket costs your business, the comparison becomes straightforward.
For brands building an internal case for the investment, how to pitch AI Agent to your boss covers the ROI framing in detail.
To see what results look like in practice, how 10 brands transformed customer support into revenue has real ecommerce examples.
AI Agent comes with everything you need to set it up, customize it, and improve it over time:
Learn more: Gorgias AI Agent guardrails: What they are and how to configure them
The best way to get a sense of what AI Agent will cost is to look at your own ticket volume and the types of questions your customers ask most. From there, the right plan becomes much clearer.
If you want to talk through the numbers with someone from our team, book a demo and we'll walk through it with you.
If you'd rather keep exploring first, here are a few good next reads:
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TL;DR:
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:
As ticket volume grows, even the best CX teams start running into roadblocks: limited integrations, repetitive manual work, clunky interfaces, and slower response times. You patch things together. You make it work... until you can’t.
Many growing ecommerce brands find themselves trapped in a system that demands constant workarounds just to function.
If your current customer service platform feels more like a burden than a backbone, you’re not alone—and you’re not stuck.
In this post, we’ll walk through:
There’s a tipping point most brands hit as they scale. The signs are subtle at first—maybe your agents are taking longer to respond, or the volume of customer support tickets quietly outpaces your team. Then it starts affecting revenue, customer satisfaction, and retention. Big yikes.
Left unchecked, small inefficiencies can snowball into bigger operational challenges.
Catch these warning signs before they start costing you growth:
Support teams that are always playing catch-up rarely have time to focus on higher-value work. If your inbox is constantly overflowing or first response times are creeping up, it’s likely a sign your tools aren’t scaling with your business.
That’s exactly what happened with apparel brand Psycho Bunny.
“As we grew and expanded, we needed a tool that was better suited for Shopify, easier to manage, and offered better support to help us get the most out of the tool,” said Jean-Aymeri de Magistris, VP IT, Data & Analytics, and PMO at Psycho Bunny.
If your agents are spending more time gathering context than solving problems, you’re losing time (and likely, patience) on both sides of the conversation. Fragmented tools can seriously undercut productivity.
Dr. Bronner’s experienced this firsthand, juggling Salesforce, spreadsheets, and disconnected systems.
“When I joined, we were logging calls and emails in Excel. It wasn’t scalable,” recalled Emily McEnany, Senior CX Manager at Dr. Bronner’s.
Some platforms require technical support even for small changes, such as custom workflows, new automations, or basic integrations. That may work at the start, but it becomes a bottleneck as your brand grows.
Disconnected systems strip away context, increasing the risk of mistakes. Whether it’s pulling up an order status or managing a return, agents need tools that work together, not against each other.
Every support team deals with repetitive inquiries. But without automation or self-service options, those tickets eat into your team’s time and keep you from focusing on higher-impact conversations.
Nude Project struggled to keep up with their ticket volume due to Zendesk’s lack of intuitive automation features. During Black Friday, the team received a record-high number of tickets—more than double their average volume.
“Connecting with customers through a screen is not always easy. With the high volume of messages, we need a tool that simplifies operational tasks while enabling effective communication and organization,” said Raquel J. Méndez, CX Manager at Nude Project.
Your platform should be easy for new hires to learn and for your team to evolve with. If ramping up agents takes weeks (or months), the platform might be getting in the way more than it’s helping.
Arcade Belts went through this process, trying one system, then switching back to one that better matched their needs.
“It just took a demo or two to realize what was actually going to support our team the way we needed,” their Ecommerce Coordinator, Grant, shared.
If any of these challenges sound familiar, you’re not alone.
The important part is recognizing when you’ve outgrown your current setup—and knowing that there are options out there to help you move faster.
Switching platforms isn’t just about solving today’s problems. It’s about creating space for your team to be efficient, serve customers better, and turn support from a cost center into a real growth engine.
Need to migrate to a new platform? Look for the following:
As your brand grows, support volume naturally increases.
Find a stable infrastructure that can handle that growth, has zero platform lag, and a robust engineering team that continuously makes the tool better for your needs.
To Psycho Bunny, Zendesk was a “legacy tool”—so they switched to Gorgias.
In just a few weeks, they migrated all historical conversations, tags, and Macros to Gorgias. Jean-Aymeri, their VP IT, credits Gorgias’s helpful onboarding specialists for making it effortless to integrate their apps and onboard their team onto a brand new tool.
Related: The engineering work that keeps Gorgias running smoothly
From “where’s my order” questions to return policies, prioritize AI tools that can automate repetitive inquiries.
Dr. Bronner’s implemented AI Agent to handle rising volumes of FAQs, allowing their team to focus on complex requests that require a human touch.
In just two months, they saw:
By systematizing the simple stuff, they freed up bandwidth to focus on what matters most—building relationships and solving more nuanced problems.

More brands are rethinking how support contributes to revenue. Look for a tool that combines support and sales. The most effective ones use AI to initiate upselling conversations, so your team can generate new revenue without needing to scale headcount at the same rate.
For jewelry brand Caitlyn Minimalist, which normally saw 30,000 tickets per month, AI Agent was the perfect fit. On top of answering FAQs, AI Agent also helped recommend products based on customer needs.
These conversations often begin as simple inquiries (“What should I get for my friend’s birthday?” or “What product suits me?”) and end in a purchase—handled entirely by AI. In fact, AI Agent’s conversion rates were 150% higher than the team average, proving that automation can support and sell.
The last thing scaling brands should have to worry about is relying on developers for basic changes. That includes being able to create macros and automations in-house and access key customer data without toggling across tools.
The platform should fit into your existing ecommerce stack—not fight against it.
That’s where Audien Hearing found themselves before switching to Gorgias.
“I’ve seen companies lose a lot of money because it’s not efficient,” said Zoe Kahn, former VP of CX. “You try to save money early on, but then you look at your helpdesk a year later and think, ‘Oh no, what’s happening?’”
Since switching from Richpanel, Audien Hearing’s CX team has been able to run CX on their own terms—without the bottlenecks.
They now resolve 9,000 tickets per month through self-service alone (including a customer knowledge base), cut first response times by 88%, and reduced return rates by 5%. With more time for one-on-one conversations, CSAT jumped from 80 to 86.
“But migration sounds hard.”
We get it. Moving your entire CX operation can feel intimidating. But with the right partner (and the right platform), it doesn’t have to be.
Here’s how Gorgias makes switching smooth and stress-free:
Most Gorgias customers are fully live within just a few days—ready to serve customers faster, smarter, and with less manual lift.
When fast-growing intimates brand Pepper outgrew their old CX platform, they knew they needed a system that could scale with them—without sacrificing speed or quality.
“Gladly didn’t offer any automation or inbox organization features. Our queue got really messy. We got 400 tickets a day during Black Friday, and we didn’t clear that backlog until the following Spring. We knew we couldn’t do that again,” explained Gabrielle McWhirter, CX Operations Lead at Pepper.
With Gorgias, Pepper was able to:

And the results spoke for themselves:
See how Pepper made the switch happen (and why they’re never looking back):
If you’re seeing the warning signs, here’s a quick gut check:
The right platform won’t just help your team work better. It’ll help you drive more revenue, boost customer retention, and actually make customers want to talk to you.
See what switching to Gorgias could do for your brand. Book a demo today.
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TL;DR:
Rising tariffs. Shipping delays. Unpredictable price hikes. For ecommerce, it's an understatement to say the pressure is rising. If you're on the CX team, you're already facing the fire head-on — all the customer frustration, confusion, and hesitation.
CX teams are on the frontlines of support and sales. You're shaping customer trust, buying decisions, and brand loyalty.
From pre-sales conversations to loyalty programs, it’s time to rethink the customer journey, so you can turn every interaction into an opportunity to grow your revenue.
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Customer service isn’t just about reacting to problems. It can be a proactive and strategic function that helps you stabilize and even grow your revenue.
Think about it this way: you have the power to turn everyday customer moments into wins.
At every stage of the customer journey, you can turn:
This isn’t about being pushy for sales. It's about anticipating needs and putting systems in place that protect customer relationships and revenue.
As you update your CX workflow, keep these two questions in mind:
Most pre-sales hesitation is rooted in uncertainty: What’s the return policy? How much is shipping? Will this fit? Will it arrive in time?
Reduce customer effort and build confidence with automation as your CX team’s first line of defense. Anything else more complicated, your agents can take care of.
Start by setting up automated answers for the questions your team responds to every day, especially the ones that delay conversions:
There are a few ways to automate these questions in Gorgias:

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

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

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

Once you’ve identified your at-risk customers, use win-back strategies, like:
When handled thoughtfully, a churn-risk customer can become one of your strongest advocates because you showed up when it mattered most.
Don’t forget, there are already customers who love you! These loyal customers don’t just come back to buy again — they bring friends, amplify your brand, and give your business stability when you need it most.
Use customer data to identify customers who purchase frequently, spend more, or have referred others. Tag them as VIPs in your helpdesk so that their requests are prioritized.
For example, in Gorgias, you can use Customer Fields (customer labels and properties) to group your customers under:
When you know who your top customers are, you can offer more personalized service and make sure every interaction strengthens their connection to your brand.
You don’t need to offer huge discounts to let customers know you appreciate them. Small, thoughtful gestures often make the biggest impact:
If you’re using macros and automations, you can even trigger some of these surprise-and-delight actions automatically, making it easier to scale while keeping the personal touch.
We know how overwhelming uncertain times can be. It’s easy to think you need to reinvent your entire strategy just to keep up.
But the truth is, you already have what you need. You have a team that knows your customers. You have conversations happening every day that can protect, nurture, and even grow your business.
By grounding yourself in what’s already working and creating proactive systems, you can turn uncertainty into strong and steady growth.
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TL;DR:
For many ecommerce teams, store policies are an afterthought, tucked away in the footer or buried deep in the FAQ. But they shouldn’t be.
Great customer experience (CX) starts before a customer reaches out. And with 55% of shoppers preferring self-service support, your store policies are often their first stop for answers.
In this guide, we break down the must-have policies for five key ecommerce verticals, based on real Gorgias ticket data. From shipping delays to subscription changes, you’ll learn how to prevent tickets before they happen.
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If you’re constantly fielding questions about returns, shipping times, or order changes, it’s a policy opportunity.
Well-crafted store policies are one of your CX team's most effective tools for setting expectations, building trust, and preventing support issues before they happen. When done right, they turn common friction points into effortless experiences.
When policies are vague or hard to find, customers turn to your inbox, driving up ticket volume and slowing down your support team.
Here are the most common blind spots we see:
When policies aren’t clear or easy to find, customers turn to your inbox. And that means more tickets, wait times, and pressure on your team.
Based on real data from Gorgias, these are the top 10 tickets customers send across channels like chat, contact forms, and email:
What do most of these have in common? You can address them with clear, accessible policies.
Customer expectations aren’t one-size-fits-all, and your store policies shouldn’t be either.
What shoppers expect from a fashion brand is very different from what they need from a wellness company or electronics provider.
We’ve broken down the top policy must-haves by vertical, using real-world examples from Gorgias customers and ticket data.
Use these examples as your plug-and-play guide to write better policies, reduce ticket volume, and create smoother support experiences — no matter what you sell.
When it comes to fashion, uncertainty drives tickets. “Will this fit?” “Can I return it?” “Where’s my order?” The most successful fashion brands like Princess Polly cut down on support volume by making these answers easy to find before customers ever reach out.


Consumer goods customers often want to know two things right away: “What’s it made of?” and “When will it get here?” These questions can quickly pile up in your inbox if your policies aren’t front and center.
Trove Brands, home to household favorites like BlenderBottle and Owala, solves this by proactively answering product and shipping questions across their site and emails.

At the end of each product page, BlenderBottle shares a support menu where shoppers can find information on order status and replacement parts.

Read more: What's the secret to reducing WISMO requests?
In electronics, clarity is everything. Customers want to know how to use the product, what to do if it doesn’t work, and how to get a replacement — without jumping through hoops.
Over-the-counter hearing aid company Audien Hearing nails this by creating crystal-clear support content around setup, shipping, and returns, so customers can troubleshoot confidently and independently.
Audien Hearing has clear visual policies that make it simple for shoppers to find the info they need quickly.

In the health and wellness space, trust and transparency are everything. Customers want to feel confident that the products they’re using are safe and that the support will be just as thoughtful as the product itself.
Brands like period underwear brand Saalt do this exceptionally well, pairing clear product education with empathetic policies that guide customers through everything from first use to subscription changes.
Saalt lets customers phrase questions themselves or choose from a dropdown menu.


Food and beverage customers tend to be both curious and cautious. They want to know what they’re putting in their bodies — and what to do if something goes wrong with the order.
Brands like Everyday Dose get ahead of these concerns by making their policies clear, accessible, and customer-first.
Everyday Dose lists frequently asked questions and makes it simple for customers to find important allergen and ingredient information.

Given that Everyday Dose is a mushroom supplement brand, many shoppers will likely have questions around allergens and exact ingredients. On each of their product pages, there is a clear “Read the Label” button.


Everyday Dose also has a chat which encourages customers to click through to the correct support link or to track their order.

Pro Tip: Use a conversational AI platform to handle common questions at scale. For example, Gorgias’s AI Agent can instantly respond to FAQs like “How much is shipping?” or “When will my order arrive?” — all in your brand’s voice. And when a request needs a human touch, it routes the ticket to the right agent automatically.
Even the most well-written policy won’t reduce tickets if it’s buried three clicks deep in your footer. To truly support your customers (and lighten your team’s workload), your policies need to show up in the right places, at the right moments.
Here’s how to get them in front of customers when they need them most:
Well-placed policies turn support into a self-service experience. They empower your customers to get what they need without ever opening a ticket — and that’s a win for everyone.
Clear, proactive policies do more than answer questions. They prevent tickets, build trust, and make your support team’s job easier. By tailoring your policies to your industry and placing them where customers actually need them, you turn potential friction points into smooth experiences.
Want to take it a step further? Book a demo to see Gorgias’s AI Agent handle common inquiries like shipping, returns, and product questions, across chat, email, and contact forms.
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If you're an ecommerce leader right now, you’re likely facing a new wave of uncertainty. Rising tariffs, disrupted imports, and sudden cost increases are putting pressure on your margins, and your customer relationships.
At Gorgias, we are working with thousands of brands that are grappling with tough calls: adjust prices, shift sourcing, or absorb costs to protect loyalty. And while the supply chain is where these issues start, the customer experience is where they play out.
Whether you’re a growing DTC or an enterprise brand, your customers deserve transparency. We know the pressure you're under, and we're here to help you navigate it. To help you not only manage the conversation, but lead it with clarity, empathy, and speed.
Ecommerce brands are in an impossible position right now, following the 24 hours news cycle, and waiting to see how tariffs will cut into profits and impact their business.
For customers? It can create confusion, frustration, and a flurry of angry tickets if brands aren’t proactive and transparent. But here's the truth: how your team talks about tariffs is just as important as what they say.
These moments of friction, and how you communicate these changes to your customers can be opportunities to build trust, reduce churn, and even demonstrate the real revenue power of your team. In a moment when clarity and trust are everything, the role of CX leaders is more important than ever.
Tariffs may seem like a back-end issue, but in reality, they shape front-end experiences—from product pricing and availability to fulfillment speed and satisfaction.
For ecommerce brands, especially those sourcing from China or shipping globally, these trade shifts hit close to home. Products get more expensive, shipping slows down, and some SKUs disappear altogether.
And CX teams are often the first to hear about it. The question isn’t if you should communicate tariff implications, but how.
Here’s the good news: customers don’t expect you to control global trade policy. But they do expect honesty.
What matters most right now is:
And even more specifically, your customers are likely looking for answers to three simple questions:
In times of change, trust becomes foundational. If you're not upfront about what’s happening and how it affects them, customers will fill in the blank, or worse, turn to competitors.
Tariffs are complex, but your messaging shouldn’t be. Strip out the policy jargon and explain the changes in human terms. Let customers know what’s changing, why it’s happening, and what steps you’re taking to protect their experience.
Instead of: “Due to regulatory changes impacting import duties…”
Say: “Because of new tariffs, some of our prices have gone up. Here’s why, and what we’re doing to keep costs down.”
From your Help Center to your agents to your email updates, your message should be consistent. Mismatched explanations create confusion and erode trust. Align your team on the key talking points and update scripts and automations across all customer touchpoints.
Speaking of your Help Center, now might be a great time to create an article specifically about tariffs and how you’re approaching them. The article can serve as a source of truth for your customers and your AI agents on the front lines answering questions.
Customers don’t just want the facts, they want to know you care. Acknowledge the frustration, and offer reassurance. Small gestures like a personalized note or a shipping perk can show you’re on their side.
Generic messages fall flat. Give customers details that they can rely on: Are the changes permanent? Are you absorbing part of the cost? Is a specific product impacted? When you’re upfront about the situation, and how you’re responding to it, you build credibility.
Times of uncertainty are times to cut costs, but it may also mean increased ticket volume. AI agents can help on the frontlines. But be sure to build your handovers to escalate to your team in the right moments to build trust.
Luggage brand, Beis, recently sent an email to customers that is a great example in customer-first communication. Rather than quietly raising prices or burying fees in checkout, they called it what it was: tariffs.

They explained the change clearly, why it was happening, and what customers could expect. And most importantly, they acknowledged the frustration. No spin, or vague language, just a clear message from a brand that respects its customers enough to be honest with them.
This kind of proactive messaging does more than prevent a flood of support tickets. It creates alignment between the brand and the customer. Beis didn’t make the rules but they’re navigating them with their customers, not in spite of them.
Too often, tariff policies get relegated to the FAQ page or terms and conditions. Customers typically only land there after they’re already confused or upset.
Instead, CX should treat tariffs as a key part of the customer journey and be equipped to speak about them empathetically and clearly.
Add a proactive message to your chat widget that addresses tariff-related questions before they even come up. A short note like, “You may notice some pricing changes – here’s why,” with a link to your FAQ or a specific article, helps to deflect confusion and prevents cart abandonment.
Surface timely information right where customers are most likely to look. Use your chat or search function to include a clear callout.
“Looking for information on recent pricing or shipping updates? Here’s what changed.”
This type of visibility empowers self-service, and reduces ticket volume.
Don’t leave your support team guessing. Create internal scripts with clear language on what to say (and what to avoid) when talking tariffs. Script empathy, not just compliance: Empower agents with language that acknowledges the inconvenience while reinforcing the brand's values.
Say:
Avoid:
If you’re using automation, make sure your AI Agent and autoresponders can explain tariff policies accurately and compassionately. Use macros to ensure fast, consistent replies, without sacrificing tone. Some key macro themes to create:
Each macro should strike a balance of clarity, empathy, and brand voice, offering both the what and the why.
Tariffs might be out of your control. But how you talk about them? That’s entirely in your hands.
This is your moment as a CX leader, not just to react but to lead. To turn friction into transparency, tension into trust, and confusion into connection. Because when policies change overnight and customer confidence is on the line, the brands that communicate with honesty, consistency, and care don’t just survive. They strengthen loyalty.
Your customers don’t expect perfection. They expect clarity. They expect empathy. And they expect you to show up.
At Gorgias, we’re here to make sure you can. With tools to automate answers, personalize conversations, and empower your team to deliver the kind of CX that builds long-term brand equity, even when times get tough.

TL;DR:
Chargebacks are more than a thorn in a merchant’s side — they’re a growing financial and operational threat. According to Ethoca, chargebacks are projected to more than double, from $7.2 billion in 2019 to $15.3 billion by 2026 in the U.S. alone. And while fraud plays a role, the primary reason customers file chargebacks is simpler: they feel ignored.

At Chargeflow, we recently published a comprehensive report analyzing why customers dispute chargebacks. The findings were eye-opening. While it’s true that fraud is a real concern, most chargebacks happen for a different reason: a lack of communication between merchants and customers.
Top stats from Chargeflow’s report:
When customers feel ignored or frustrated, they often turn to their bank for a solution instead of reaching out to the merchant first. Understanding these behaviors is key to preventing disputes before they escalate and cause chaos.
So, what actually drives customers to dispute charges? Here’s what the data says.
While chargebacks are often the cost of doing business, the truth is that many disputes are preventable — but only if merchants understand the root causes. We identified five key drivers behind chargebacks.
According to our research, most customers file a dispute right away after encountering an issue, leaving no opportunity to resolve the problem. Another 38% file within one to three days if they don’t receive a timely response.
Why? Customers assume the fastest way to get their money back is by filing a chargeback, especially if they receive no response from the merchant.
We found that 80% of customers never receive a follow-up after filing a chargeback. Additionally, 64% of customers state immediate communication is crucial, yet many businesses fail to reach out.
Why? Customers expect businesses to be proactive. When they don’t hear back quickly, they assume the merchant won’t help, making a chargeback seem like the best option.
98% of customers report a neutral to highly satisfactory experience when filing chargebacks, and only 12% are denied.

Why? Many customers believe chargebacks are faster and easier than dealing with merchants directly, especially if return policies are unclear.
The most common reason for filing a chargeback is “product not received” (35% of the cases). Other common reasons included:
Why? When customers don’t receive clear shipping updates or experience delivery delays, they assume their order won’t arrive and file a chargeback rather than waiting.
Friendly fraud occurs when a cardholder makes a legitimate purchase but later disputes the charge as fraudulent or unauthorized, leading their card issuer to reverse the payment.
Our research found that:

According to our State of Chargebacks report, 79% of chargebacks are actually friendly fraud, meaning they were filed for invalid reasons.
Why? Many customers mistakenly believe that a chargeback is just another way to request a refund, rather than a process intended for fraud or merchant failure.
📌 The takeaway: Most chargebacks aren’t actual fraud, but rather a result of customer confusion, impatience, or poor communication from merchants.
Merchants who want to stop chargebacks before they happen need a two-part strategy:
Chargebacks result from slow response times, poor communication, and unresolved issues, not fraud. Adopting AI-driven customer support and chargeback automation allows businesses to significantly reduce disputes and retain more revenue.
Many chargebacks happen because customers don’t receive a fast enough response. In fact, 52% say they will dispute a charge if the response time is too slow. AI-powered chatbots provide real-time support, resolving issues before they escalate.
Customers expect updates regarding orders and refunds, but often don’t receive them. 80% of customers report never hearing from a merchant after filing a chargeback.
Automated order updates, refund confirmations, and proactive notifications keep customers informed, reducing unnecessary disputes.
Customers expect round-the-clock support, but most businesses can’t provide live assistance. AI-powered ticketing and automation ensure every customer receives help, regardless of the time zone or urgency.
The result? Fewer chargebacks, faster resolutions, and increased customer satisfaction.
It’s impossible to please every customer. On average, chargebacks take 50 days to resolve successfully. Focus your energy on retaining high-value, long-term customers.
Lost inquiries take on average 15 days to resolve, and lost chargebacks take 38 days. Prioritize cases based on impact.
Advanced automated ticketing systems can route inquiries and prioritize urgent cases.
Ensure customer service teams have quick-response templates to speed their resolutions.
“Product not received” was the most cited reason for delivery-related chargebacks. Work closely with carriers and third-party suppliers to improve fulfillment and reduce disputes.
Use automated tools for real-time analytics, enhanced communication, and proactive alerts, which will reduce response times.
Successfully tackling chargebacks requires both proactive customer support and automated dispute management. That’s why Gorgias and Chargeflow work so well together to give merchants a comprehensive defense against disputes.
Post-purchase automation isn’t just about reducing customer support workload or quick replies. It's about finding the most effective ways to increase customer loyalty and prevent disputes.
Learn more about how AI-driven automation enhances post-purchase experiences here.
As you know, chargebacks are costly, frustrating, but most importantly, preventable. Our research shows that most chargebacks don’t stem from fraud, but from poor communication, slow response times, and customer uncertainty.
By prioritizing fast, AI-driven customer support and automated chargeback management, merchants can resolve issues before they escalate, improve customer experience, and protect their revenue.
With Gorgias handling proactive customer support and Chargeflow managing chargeback disputes, merchants get a powerful, end-to-end prevention system that ensures fewer chargebacks, higher dispute win rates, and, at the end of the day, happier customers.
Don’t let chargebacks drain your revenue. Take control today with faster, smarter automation.
Download Chargeflow’s full Psychology of Chargebacks Report to dive deeper into the data and start preventing disputes before they happen.

TL;DR:
When customer service teams are at their busiest, they need a helpdesk that keeps up. That’s exactly why our Site Reliability Engineering (SRE) team has been working behind the scenes to make the Gorgias platform faster than ever.
Over the past year, we've made remarkable improvements to our platform to eliminate bottlenecks, speed up data retrieval, and reduce incidents. For you, this means fewer disruptions, faster load times, and a more reliable helpdesk experience.
Here's how we did it.
Our platform relied on a single, shared database connection pool to manage all queries. Think of it as having just one pipe handling all the water flowing through your house — when too much water rushes in at once, the whole system backs up.
In practice, this meant a single surge in database requests could clog the entire system. When lower-priority background tasks got stuck, they could prevent high-priority operations (like loading tickets or running automations) from working properly. This would cause the entire helpdesk to slow down or, worse, become completely unresponsive.
Using PgBouncer, a tool that manages database connections and reduces the load on a server, we implemented multiple connection pools. Instead of relying on a single pipeline to stream all requests, we created separate "pipes" for different requests.

Like how road traffic picks up again after an exit, routing our database traffic into separate connection pools makes sure high-priority customer interactions don’t lag behind automated background tasks.
This solution is future-proof. In the event that a lower-priority task is delayed in one connection pool, other functionalities of the helpdesk will continue working because of the remaining connection pools.
The results speak for themselves:
We've eliminated incidents caused by connection pool issues in the helpdesk completely. This reduced major helpdesk outage incidents by around four per year and maintained an average uptime of over 99.99%.
As Gorgias grew to over 15,000 customers, so did the volume of data. We’re talking data from tickets, integrations, automations, and many more. The combination of more users and data meant slower searches within the helpdesk.
However, the amount of data was not the problem — it was how our data was organized.
Imagine this: An enormous storage room full of file cabinets containing every piece of data. Sure, those file cabinets kept data organized, but you would still need to spend time searching through the entire room, running up and down aisles of cabinets, to find your desired file. This method was cumbersome.
We needed a more efficient way to keep our data easy to find, especially as more customers used our platform.
The answer was database partitioning — breaking our large datasets into smaller, more manageable segments. Using Debezium, Kafka, and Kafka-connect JDBC, all managed by Terraform, we migrated over 40TB of data, including 3.5 billion tickets, without a moment of downtime for our merchants.
Instead of a giant room with thousands of file cabinets, we divided that giant room into 128 smaller rooms. So now, instead of looking for a file in one room, you know you just need to go into room number 102, which has a much smaller area to search.
This approach allows our system to quickly pinpoint the location of data, significantly reducing the time it takes to find and deliver information to users.
Additionally, database maintenance has become more efficient. Some of the partitions can probably sit without needing to be changed at all. We just have to maintain the partitions that are getting new files, which cuts down on maintenance time.
Better database partitioning provides several benefits:
When incidents occurred in the past, our response process was inconsistent, leading to delays in resolution. It was sometimes unclear who should take the lead, what immediate actions were required, and how to effectively communicate with affected customers.
Additionally, post-incident reviews varied in quality, making it difficult to prevent similar issues from happening again. We needed a standardized framework to address incidents in a timely fashion.
To streamline incident management, we introduced a replicable, automated process:
With our improved incident management process:
With more brands catching on to how essential a solid CX platform is, our team's got our work cut out for us. Here's what's on the way:
Gorgias will inevitably face new challenges in performance — no system is completely immune to downtime.
But we've built our architecture with the future in mind, and it’s more resilient than ever as more and more brands realize the power of conversational AI CX platforms.
The result? A platform you can count on to help you deliver exceptional customer service, without technical issues getting in the way.
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TL;DR:
Shoppers aren’t just open to AI — they’re starting to expect it.
According to IBM, 3 in 5 consumers want to use AI as they shop. And a McKinsey study found that 71% expect personalized experiences from the brands they buy from. When they don’t get that? Two-thirds say they’re frustrated.
But while most brands associate AI with support automation, its real power lies in something bigger: scaling personalization across the entire customer journey.
We’ll show you how to do that in this article.
Before AI can personalize emails, recommend products, or answer support tickets, it needs one thing: good data.
That’s why one of the best places to start using AI isn’t in sales or support — but in enriching your customer data. With a deeper understanding of who your customers are, what they want, and how they behave, AI becomes a personalization engine across your entire business.
Post-purchase surveys are gold mines for understanding customers — but digging through the data manually? Not so fun.
AI can help by analyzing survey responses at scale, identifying trends, and categorizing open-ended customer feedback into clear, actionable insights. Instead of skimming thousands of answers to spot what customers are saying about your shipping times, AI can surface those insights instantly — along with sentiment and behavior signals you might’ve missed.
Try this prompt when doing this: "Analyze 500 open-ended post-purchase survey responses. Identify the top 5 recurring themes, categorize customer sentiment (positive, neutral, negative), and surface any trends related to product quality, delivery experience, or customer support."
One of AI’s biggest strengths? Spotting intent.
By analyzing things like page views, cart activity, scroll behavior, and previous purchases, AI can identify which shoppers are ready to buy, which ones are likely to churn, and which just need a little nudge to move forward.
This doesn’t just apply to email and retargeting. It also works on live chat, in real time.
Take TUSHY, for example.
To eliminate friction in the buying journey, TUSHY introduced Shopping Assistant — a virtual assistant designed to guide shoppers toward the right product before they drop off.
Instead of letting potential customers bounce with unanswered questions, the AI Agent steps in to offer:

With a growing product catalog, TUSHY realized first-time buyers were overwhelmed with options — and needed help choosing what would work best for their home and hygiene preferences.
“What amazed us most is that the AI Agent doesn’t just help customers choose the perfect bidet for their booty — it also provides measurement and fit guidance, high-level installation support, and even recommends all the necessary spare parts for skirted toilet installations. It’s ushering in a new era of customer service — one that’s immediate, informative, and confidence-boosting as people rethink their bathroom habits.”
—Ren Fuller-Wasserman, Sr. Director of Customer Experience at TUSHY
AI also helps you see the road ahead.
Instead of looking at retention and loyalty metrics in isolation, AI can help you forecast what’s likely to happen next and where to focus your attention.
By segmenting customers based on behaviors like average order value, order frequency, and churn risk, AI can identify revenue opportunities and weak spots before they impact your bottom line.
All you need is the right prompt. Here’s an example you can run using your own data in any AI tool:
Prompt: “Analyze my customer data to forecast revenue by segment. Break customers into at least three groups based on behavior patterns like average order value, purchase frequency, and churn risk.
For each segment, provide:
Here’s what a result might look like:
Instead of flying blind, you’re making decisions with clarity — and backing them with data that scales.
When used strategically, AI becomes a proactive sales agent that can identify opportunities in real-time: recommending the right product to the right shopper at the right moment.
Here’s how ecommerce brands are using AI to drive revenue across every part of the funnel.
Your prices shouldn’t be static — especially when your competitors, inventory, and customer behavior are anything but.
AI-powered tools like Shopping Assistant help brands automatically adjust pricing based on shopper behavior. The goal is to make the right offer to the right customer.
For example:
With dynamic pricing, you can protect your margins and boost conversions — without relying on blanket sales.
AI-powered chat is no longer just a glorified FAQ. Today, it can act as a real-time shopping assistant — guiding customers, boosting conversions, and helping your team reclaim time.
That’s exactly what Pepper did with “Penelope,” their AI Agent built on Gorgias.
With a rapidly growing product catalog (22 new SKUs in 2024 alone), Pepper knew shoppers needed help discovering the right products. Customers often had questions about styles, materials, or sizing, and if they didn’t get answers right away, they’d abandon carts and move on.
Instead of hiring more agents to keep up, Pepper deployed Penelope to live chat and email.
Her job?
“With AI Agent, we’re not just putting information in our customer’s hands; we’re putting bras in their hands... We’re turning customer support from a cost center to a revenue generator.”
—Gabrielle McWhirter, CX Operations Lead at Pepper

Let’s look at how Penelope performs on the floor:
A shopper asked about the difference between two wire-free bras. Penelope broke down the styles, support level, and fabric in plain language — then followed up with personalized suggestions based on the shopper’s preferences.
Using Gorgias Convert chat campaigns, Pepper triggers targeted messages to shoppers based on behavior. If someone is browsing white bras? Penelope jumps in and offers assistance, often leading to faster decisions and fewer abandoned carts.
If a customer adds a swimsuit top to their cart, Penelope suggests matching bottoms. No full-screen popups, no awkward sales scripts — just thoughtful, helpful guidance.
Penelope also handles WISMO tickets and return inquiries. If a shopper is dealing with a sizing issue, Penelope walks them through the return process and links to Pepper’s Fit Guide to make sure the next purchase is spot on.

By implementing AI into chat, Pepper saw a 19% conversion rate from AI-assisted chats, an 18% uplift in AOV, and a 92.1% decrease in resolution time.
With Penelope handling repetitive and revenue-driving tasks, Pepper’s team now has more time to offer truly personalized touches — like virtual fit sessions that have turned refunds into exchanges and even upsells.
Bundling is a proven tactic for increasing AOV — but most brands still rely on subjective judgment calls or static reports to decide which products to group.
AI can take this a step further.
Instead of just looking at what’s bought together in the same cart, AI can analyze purchase sequences. For example, what people tend to buy as a follow-up 30 days after their first order. This gives you powerful clues into natural buying behavior and bundling opportunities you might’ve missed.
If you’re looking to explore this at scale, you can use anonymized sales data and feed it into AI tools to surface patterns in:
Try this prompt:
"Analyze this spreadsheet of order data and identify product bundle opportunities. Look for: (1) products frequently purchased together in the same order, (2) items commonly bought as a second purchase within 30 days of the first, and (3) patterns in high-value or high-frequency product pairings. Provide insights on the most promising bundles and why they might work well together."
Just make sure you’re keeping customer data anonymous — and always double-check the insights with your team.
Related: Ecommerce product categorization: How to organize your products
AI isn’t just here to deflect tickets. From quality assurance to proactive outreach, AI can elevate the entire support experience — on both sides of the conversation.
Manual QA is slow, selective, and often feels like it’s chasing the wrong tickets.
That’s where Auto QA comes in. Instead of reviewing just a handful of conversations each week, Auto QA evaluates 100% of private messages, whether they’re handled by a human or an AI agent.
Every message is scored on key metrics like:
It gives support leaders a full picture of how their team is performing, so they can coach with clarity, not just gut feeling.
Here’s what brands can do with automated QA:
Let’s walk through a real example.
Customer: “Hi, my device broke, and I bought it less than a month ago.”
Agent: “Hi Kelly, please send us a photo or a video so we can determine the issue with your device.”
Auto QA flags this interaction with:
Reactive support is table stakes. AI takes it a step further by anticipating issues before they happen — and proactively helping customers.
Let’s say login errors spike after a product update. AI detects the surge and automatically triggers an email to affected customers with a simple fix. No need for them to dig through help docs or wait on chat — support meets them right where they are.
Proactive AI can also be used for:
This saves the time of your agents because the AI will spot problems before they turn into tickets.
Your customers are telling you what they think. AI just helps you hear it more clearly.
By analyzing reviews, support tickets, post-purchase surveys, and social comments, AI can spot sentiment trends that might otherwise fly under the radar.
For example:
Related: 12 ways to upgrade your data and trend analysis with Ticket Fields
Whether you’re enriching customer data, making smarter product recommendations, triggering dynamic pricing, or proactively resolving support issues, AI gives your team the power to scale personalization without sacrificing quality.
With Gorgias, you can bring many of these use cases to life — from AI-powered chat that drives conversions to automated support that still feels human.
And with our app store, you can tap into additional AI tools for data enrichment, direct mail, bundling insights, and more.
Personalized ecommerce doesn’t have to mean more work. With the right AI tools in your corner, it means smarter work — and better results.
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TL;DR:
AI is no longer a futuristic concept associated with sci-fi movies and robots. It’s driving real change in ecommerce right now. Currently, 84% of ecommerce businesses list AI as their top priority. And it’s only getting bigger. By 2034, the ecommerce AI market is expected to hit $62.64 billion.
Brands that use AI to improve personalization, automate customer support, and refine pricing strategies will have a major competitive edge.
The good news? Most brands are still figuring it out, which means there’s huge potential for early adopters to stand out.
Let’s dive into the key AI trends shaping ecommerce in 2025, and how you can use them to future-proof your business.
Instead of searching for keywords, shoppers can upload a photo and instantly find similar or matching products. Visual search eliminates the guesswork of finding the right words to describe an item and reduces friction in the search process.
In 2025, improvements in computer vision and machine learning will make visual search faster. AI will better recognize patterns, colors, and textures, delivering more precise results in real-time.
For customers, visual search simplifies product discovery while brands benefit from increased average order values. Visual search creates more opportunities to surface related products that customers might miss during manual searches, ultimately boosting conversion and revenue.
Pinterest is already doing it. With Pinterest Lens, users can take a picture on the spot to find similar products or ideas to help them with easier purchases or creative projects.

Pro Tip: Optimize product images and metadata (like color, size, and material) so your products appear accurately in visual search results. Clean, high-quality images and detailed tagging will make your catalog easier for AI to process and match.
Conversational AI, like Gorgias AI Agent, already handles 60% of customer conversations. Brands that adopt it often see more than a 25% improvement in customer satisfaction, revenue, or cost reduction.
Soon, advanced natural language processing (NLP) will make it easier for customers to use text, voice, and images to find exactly what they’re looking for. These multimodal capabilities will elevate support conversations, resulting in fewer abandoned carts and support teams that can focus on more complex issues.
For example, Glamnetic uses AI Agent to manage customer inquiries across multiple channels, resolving 40% of requests automatically while maintaining a personalized touch. Their AI can automate responses to common questions, recommend products based on browsing history, and even track orders in real-time.

Pro Tip: Invest in AI chat tools that integrate with your customer support system and sync with real-time product and order data. Your responses will be accurate and timely, without losing the personal touch.
Read more: The Gorgias & Shopify integration: 8 features your support team will love
According to McKinsey, omnichannel personalization strategies, including tailored product recommendations, have a 10-15% uplift potential in revenue and retention. But with only 1 in 10 retailers fully implementing personalization across channels, there’s a massive opportunity for brands to innovate.
In 2025, AI-driven product recommendations will become even more precise by analyzing customer behavior, preferences, and purchase history in real-time. Predictive AI will adjust recommendations on the fly, showing customers the right products at the right moment.
Take Kreyol Essence as an example. They use Gorgias Convert to track customer behavior and recommend products based on past purchases and browsing patterns. When a customer buys a hair mask, AI suggests complementary products like scalp oil or leave-in conditioner — increasing average order value without feeling pushy.

Personalization boosts sales by helping customers discover products they actually want. Plus, it creates a more tailored shopping experience, which encourages customers to return.
Pro Tip: Test different recommendation strategies, like “frequently bought together” or “you may also like,” to see which ones drive the most conversions.
Learn more: Reduce Customer Effort with AI: A Smarter Approach Than Surprise and Delight
In 2025, more customers may use smart speakers and voice assistants like Alexa and Google Assistant to shop hands-free. AI will improve voice recognition and contextual understanding, so it’s easier for customers to find products they want.
Instead of fumbling with a keyboard, customers will be able to say, “Order more coffee pods,” and AI will not only recognize the request but also pull up the preferred brand and size based on past orders. Less friction will make the buying process more intuitive, especially for repeat purchases.
Voice commerce expands shopping accessibility and creates a more convenient experience for busy customers. It also opens the door for brands to surface product recommendations and upsell during the conversation.
Pro Tip: Optimize product descriptions and catalog structure for voice search. Clear, simple language and detailed product tags will help AI understand and surface the right products.
A recent McKinsey report suggests that investing in real-time customer analytics will continue to be key to adjusting pricing and more effectively targeting customers.
In 2025, machine learning will allow ecommerce brands to adjust product prices instantly based on demand, competitor pricing, and customer behavior. If a competitor drops their price on a popular item, AI can respond immediately, so you stay competitive without sacrificing margins.
Machine learning will also refine pricing models over time, finding the sweet spot between profitability and customer conversion.
For example, AI might detect that customers are more likely to buy a product when it’s priced at $29.99 rather than $30, and adjust accordingly. More competitive pricing means higher revenue and better margins, but it also increases customer trust when prices are consistent with market trends.
Pro Tip: Test different pricing strategies and monitor how they affect sales and customer behavior.
According to McKinsey, AI-driven personalization and customer insights can improve marketing efficiency by 10-30% and cut costs significantly.
In 2025, AI will analyze customer data like purchase history, browsing patterns, and feedback to generate smarter, more actionable next steps. Instead of guessing what customers want, brands will have the data to predict it.
For example, Shopping Assistant can identify a shopper’s interest level and purchase intent and then use it to adjust its conversational strategy. It analyzes shopper data like browsing behavior, cart activity, and purchase history.
Here’s how it would behave for different customers:

AI-driven personalization leads to a 5-10% higher customer satisfaction and engagement. Yet, only 15% have fully implemented it across all channels — leaving a huge gap to fill.
In 2025, AI-driven personalization will go beyond product recommendations. Brands will be able to adjust website layouts based on customer preferences, highlight products that align with their style, and even customize customer service interactions.
A higher level of personalization will boost conversion rates and customer satisfaction. When customers feel like a brand “gets” them, they’re more likely to make a purchase and come back for more.
For example, Shopping Assistant can adjust discounts and provide smart incentives to drive sales. When adjusting for discounts, AI Agent analyzes shopper behavior, including browsing activity, cart status, and conversation context, to offer a discount based on how engaged and ready the shopper is to buy.

Pro Tip: Use AI to test different personalization strategies and refine them based on performance data. Small adjustments, like changing product order or highlighting specific categories, can have a big impact on sales.
Keeping the right products in stock at the right time is about to get a whole lot easier. In 2025, AI will predict demand patterns and automate restocking decisions based on sales trends, seasonality, and customer behavior. Instead of manually tracking inventory, AI will handle it in real time to avoid stock issues.
For example, AI could notice a spike in orders for a specific product right before the holidays. It could then automatically increase stock levels to meet demand or scale back on items that aren’t moving as fast. Real-time tracking means fewer missed sales and less wasted inventory.
Efficient inventory management not only cuts costs but also improves the customer experience. When products are consistently available, customers are more likely to trust and stick with your brand.
Pro Tip: Implement AI-powered inventory management to sync data across all sales channels. This ensures accurate stock levels and seamless fulfillment, whether customers are shopping online or in-store.
AI makes it easier for brands to deliver a personalized and efficient shopping experience. From helping customers find products faster with visual search to automating support with conversational AI, there are plenty of opportunities for personalization.
The brands that adopt and refine these strategies now will be better positioned to meet customer expectations and stay ahead of the competition. Start by implementing conversational AI and later test some other AI trends like personalized suggestions.
Ready to see how AI can upgrade your brand? Book a demo to see AI Agent in action.
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