TL;DR
At Gorgias, we work with over 16,000 ecommerce brands and one common challenge emerges over and over:
Ecommerce tools are essential, but too many tools becomes a burden.
With different teams responsible for different functions, brands risk creating a disconnected tech stack that causes inefficiencies, reduces productivity, and ultimately impacts profitability.
Ecommerce teams are shuffling between tabs, copying and pasting order numbers, searching for customer data, and trying to piece it all together. It’s not only inefficient—it’s expensive, frustrating, and unsustainable as you scale.
So we dug into that data.
Our 2025 Ecommerce Trends Report surveyed ecommerce professionals across industries and job roles to understand what they really think about tech stacks and AI’s role in it.
{{lead-magnet-1}}
There is now an ecommerce app for every possible use case a brand could need. But as businesses adopt new technologies for each part of their customer journey, their teams end up working out of dozens of platforms.
The study found that 42.28% of ecommerce pros use at least six apps daily to perform their role. Regardless of the number of apps used, integration and compatibility are a must. When technologies don’t talk to each other, you spend time context-switching instead of focusing on customer experience.
For Audien Hearing, Gorgias’s open API allowed them to create an integration with its warehouse software to manage returns directly in Gorgias rather than a shared Google spreadsheet. This integration helped them reduce returns by 5%, protecting their margins and leading to higher customer satisfaction.
Read more: How Audien Hearing Increased Efficiency for 75 Agents and Reduced Product Returns by 5%
The most successful ecommerce brands aren’t necessarily using more tools—they’re using smarter tools. Leading businesses are opting for platforms that are deeply integrated, AI-compatible, and built specifically for ecommerce needs.
A growing tech stack also comes with a growing tech budget. Each new app has new costs, including subscriptions, set-up, management, and development fees. They quickly add up.
Nearly 40% of ecommerce professionals spend $5,000 to $50,000 annually on their tech stack.
We asked ecommerce professionals what they actually value in their tools. Unsurprisingly, the answer changed based on who we were talking to.
Top tool benefits included:
There’s a clear difference between what ecommerce leaders and agents value in a tool and considering both is key to success.
Despite the benefits of using fewer, well-integrated tools, there are a few things that hold brands back from consolidating their tech stacks.
We asked respondents:
What, if any, are the biggest deterrents to consolidating your tech stack?
Top concerns are:
AI is dominating the world of ecommerce. It impacts every aspect of the customer journey, from brand discovery to the post-purchase experience. AI is actively reshaping the way ecommerce professionals work, so we wanted to know how they feel about it.
Despite growing usage and excitement, teams still have their concerns with AI:
Read more: 8 AI Trends in Ecommerce: What’s Changing and How to Prepare
The most impactful use cases we’ve seen aren’t just about reducing support ticket volume. AI is now driving revenue, increasing conversion rates, and enabling 24/7 coverage without expanding headcount.
Gorgias’s AI Agent is now capable of virtual sales assistance through personalized product recommendations, dynamic discounts to reduce cart abandonment, and cross-sells and upsells.
Top brands are already leveraging these new capabilities and seeing results. For example:
We asked one final question to make ecommerce folks really reflect on how they work:
How many tabs do you currently have open?
The average ecommerce professional works with 22 open tabs. We’re not here to judge, but if you’re looking to close a few of those tabs, Gorgias might be what you’re missing.
Gorgias replaces all that complexity with a single workspace. From support to sales, order management to automation, it all happens inside one platform.
Ecommerce businesses can now leverage Gorgias’s Advanced AI for both support and sales. Within the same AI Agent, ecommerce brands can
This blog just skims the surface of what we uncover in our 2025 Ecommerce Trends report.
Want the full story?
Download the complete 2025 Ecommerce Trends: AI Adoption & Smarter Tech Stacks report to access:
{{lead-magnet-1}}
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.
{{lead-magnet-1}}
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’s 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, Gorgias’s AI Agent for Sales 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, AI Agent for Sales 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.
{{lead-magnet-1}}
The best in CX and ecommerce, right to your inbox
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:
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 AI Agent for Sales — 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 pricing tools like AI Agent for Sales 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.
{{lead-magnet-1}}
TL;DR:
AI is everywhere in customer service—powering live chats, drafting responses, and handling inquiries faster than ever.
But as AI takes on more of the customer experience, one question keeps coming up: Should brands tell customers when they’re talking to AI?
Legally, the answer depends on where you operate. Ethically? That’s where things get interesting. Some argue that transparency builds trust. Others worry it might undermine confidence in support interactions.
So, what’s the right move?
This guide breaks down the debate and gives CX leaders a framework to decide when (and how) to disclose AI—so you can strike the right balance between innovation and trust.
Depending on where your business operates, disclosure laws may be strict, vague, or nonexistent. Some laws, such as the California Bolstering Online Transparency Act, prohibit misleading consumers about the use of automated artificial identities.
For maximum legal protection, it’s best to proactively disclose AI use—even when not explicitly required.
A simple disclaimer can go a long way in avoiding legal headaches down the line. Here’s how to disclose AI use in customer interactions:
Truthfully, AI laws are evolving fast. That’s why we recommend consulting legal counsel to ensure your disclosure practices align with the latest requirements in your region.
But beyond avoiding legal trouble, transparency around AI usage can reinforce customer trust. If customers feel deceived, they may question the reliability of your brand, even if the AI delivers great service.
Related reading: How AI Agent works & gathers data
Research shows that 85% of consumers want companies to share AI assurance practices before bringing AI-driven products and experiences to market.
But what does “transparency” actually mean in this context? An article in Forbes broke it down, explaining that customers expect three key things:
How you disclose AI matters just as much as whether you disclose it. At the end of the day, AI isn’t inherently good or bad—it’s all about how it’s implemented and trained.
The way a brand approaches AI disclosure can impact trust, satisfaction, and even conversion rates—making it a decision that goes beyond simple legal requirements.
While some customers appreciate honesty, others may hesitate if they prefer human support. Brands must weigh the pros and cons to determine the best approach for their audience.
Let’s be honest: AI in customer service still carries baggage. While some consumers embrace AI-driven support, others hear "AI" and immediately picture frustrating, robotic chatbots that can’t understand their questions.
This is one of the biggest risks of transparency: customers who’ve had bad AI experiences in the past may assume the worst and disengage the moment they realize they’re not speaking to a human.
For brands that thrive on personal connection and high-touch service, openly stating that AI is involved could create skepticism or drop-off rates before customers even give it a chance.
Another challenge? The perception gap.
Even if AI is handling inquiries smoothly, some customers may assume it lacks the empathy, nuance, or problem-solving skills of a live agent. Certain industries may find that transparency about AI use leads to more escalations, not fewer, simply because customers expect a human touch.
Despite the risks, transparency about AI can actually be a trust-building strategy when handled correctly.
Customers who value openness and ethical business practices tend to appreciate brands that don’t try to disguise AI as a human.
Being upfront also manages expectations. If a customer knows they’re speaking to AI, they’re less likely to feel misled or frustrated if they encounter a limitation. Instead of feeling like they were "tricked" into thinking they were talking to a human, they enter the conversation with the right mindset—often leading to higher satisfaction rates.
And then there’s the long-term brand impact.
If customers eventually realize (through phrasing, tone, or inconsistencies) that they weren’t speaking with a human when they thought they were, it can erode trust.
Deception—whether intentional or not—can backfire. Proactively disclosing AI use prevents backlash and reinforces credibility, especially as AI becomes a bigger part of the customer experience.
Arcade Belts, known for its high-quality belts, wanted to improve efficiency without compromising customer experience. By implementing Gorgias Automate, they reduced their reliance on manual support, creating self-service flows to handle common inquiries.
Initially, automation helped manage routine questions, such as product recommendations and shipping policies. But when they integrated AI Agent, they cut their ticket volume in half.
The transition was so seamless that customers often couldn’t tell they were interacting with AI. “Getting tickets down to just a handful a day has been awesome,” shares Grant, Ecommerce Coordinator at Arcade Belts. ”A lot of times, I'll receive the response, ‘Wow, I didn't know that was AI.”
You can read more about how they’re using AI Agent here.
We mentioned it earlier, but deciding whether or not to disclose your use of AI in customer support depends on compliance, customer expectations, and business goals. That said, this four-part framework helps CX leaders evaluate the right approach for their brand:
Before making any decisions, ensure your brand is compliant with AI transparency regulations.
AI transparency should align with your brand’s values and customer experience strategy.
Rather than making assumptions, run controlled tests to see how AI disclosure affects customer satisfaction.
AI strategies shouldn’t be static. As customer preferences and AI capabilities evolve, brands should refine their approach accordingly.
If you decide to be transparent about AI in customer interactions, how you communicate it is just as important as the disclosure itself. Let’s talk about how to get it right and make AI work with your customer experience, not against it.
AI doesn’t have to sound like a corporate FAQ page. Giving it a personality that aligns with your brand makes interactions feel natural and engaging. Whether it’s playful, professional, or ultra-efficient, the way AI speaks should feel like a natural extension of your team, not an out-of-place add-on.
Instead of:
"I am an automated assistant. How may I assist you?"
Try something on-brand:
"Hey there! I’m your AI assistant, here to help—ask me anything!"
A small tweak in tone can make AI feel more human while still keeping transparency front and center.
Read more: AI tone of voice: Tips for on-brand customer communication
One of the biggest mistakes brands make? Leaving customers guessing whether they’re speaking to AI or a human. That uncertainty leads to frustration and distrust.
Instead, be clear about what AI can and can’t do. If it’s handling routine questions, product recommendations, or order tracking, say so. If complex issues will be escalated to a human agent, let customers know upfront.
Framing matters. Instead of making AI sound like a replacement, position it as a helpful extension of your support team—one that speeds up resolutions, but hands off conversations when needed.
Even the best AI has limits—and customers know it. Nothing is more frustrating than a bot endlessly looping through scripted responses when a customer just needs a real person to step in.
AI should be the first line of defense, but human agents should always be an option, especially for high-stakes or emotionally charged interactions.
A smooth handoff can sound like:
"Looks like this one needs a human touch! Connecting you with a support expert now."
AI disclosure doesn’t have to feel like an apology. Instead of focusing on limitations, highlight the benefits AI brings to the experience:
It’s the difference between:
"This is an AI agent. A human will follow up later."
vs.
"I’m your AI assistant! I can answer most questions instantly—but if you need extra help, I’ll connect you with a team member ASAP."
The right framing makes AI feel like an advantage, not a compromise.
AI perception isn’t static. Regularly analyzing sentiment data and customer feedback can help refine AI messaging over time—whether that means adjusting tone, improving explanations, or updating how AI is introduced.
When you follow these best practices, AI can be a real gamechanger for your customer support. Just take it from Jonas Paul…
Jonas Paul Eyewear, a direct-to-consumer brand specializing in kids' eyewear, needed a way to manage high volumes of tickets during the back-to-school season without overwhelming their customer care team.
To streamline these conversations, Jonas Paul implemented AI Agent to provide instant responses to FAQs. This allowed human agents to focus on more complex cases that required personalized attention.
“Being able to automate responses for things like prescription details and return policies has allowed us to focus more on the nuanced questions that require more time and care. It’s been a game changer for our team,” said Lynsay Schrader, Lab and Customer Service Senior Manager and Jonas Paul.
Jonas Paul saw a 96% decrease in First Response Time and a 2x ROI on Gorgias’s AI Agent with influenced revenue. You can dive in more here.
Whether or not your brand chooses to disclose AI in customer interactions, the key is to ensure AI enhances the customer experience without compromising transparency, accuracy, or brand identity.
So how can you get started? Gorgias AI Agent was built with both effectiveness and transparency in mind.
For every interaction, AI Agent provides an internal note detailing:
Excited to see how AI Agent can transform your brand? Book a demo.
{{lead-magnet-1}}
Managing customer support as a Shopify store owner can feel like juggling too many tools at once.
Constantly switching tabs to look up orders, update customer information, or track returns wastes valuable time. Plus, it prevents your team from focusing on what really matters––delivering quick, personalized customer service.
Gorgias’s Shopify integration solves this. It keeps all your Shopify data in one place, so your team spends less time toggling tabs and more time helping customers. The result? Faster responses, better service, and more revenue.
Below, we break down the eight key capabilities of this integration, each paired with practical use cases to showcase its real-world value.
{{lead-magnet-1}}
What it does: Shopify order data is displayed directly within support tickets, allowing agents to view essential details like order status, customer information, and transaction history without leaving the helpdesk.
Use case: An agent handling a “Where’s my order?” request can instantly check tracking information and update the customer.
The fashion retailer Princess Polly improved their customer experience team’s efficiency by using Gorgias's deep integration with Shopify. Agents can view and update customer and order data directly within Gorgias, eliminating the need to switch between multiple tabs.
Taking a streamlined approach led to a 40% increase in efficiency, an 80% decrease in resolution time, and a 95% decrease in first response time.
What it does: Agents can update Shopify order and customer data with Shopify Actions right in Gorgias.
Key features:
Use case: Agents can perform Shopify actions directly from Gorgias, such as adding products, applying discounts, updating quantities, or issuing refunds.
What it does: Create templated responses called Macros with dynamic Shopify variables to automatically incorporate customer-specific information.
Key features:
Use case: A customer inquires about their order. With one click, the agent uses a Macro that pulls in the order status and expected delivery date, creating a faster and more personalized response.
Take Try The World, a gourmet subscription service, needed a robust Shopify integration to handle an increasing volume of customer inquiries. By switching to Gorgias, they gained the ability to unify conversations and embed Shopify data directly into Macros. Now, agents could quickly generate personalized responses that included order details, tracking links, and customer-specific information.
Try the World’s support team’s efficiency skyrocketed, enabling them to handle 120 tickets per day, up from 80, and reduce response times to just one business day.
What it does: Macros with embedded Shopify data let agents quickly and accurately share pre-sale information like product links, stock availability, and discount codes, helping to convert prospective customers into buyers.
Key features:
Use case: A customer asks if a specific product is available in their size and color. The agent can apply a Macro that automatically pulls the product's inventory details and includes a discount code, sending a response like this:
“Hi {{ticket.customer.firstname}},
Great news! The product {{ticket.customer.integrations.shopify.products[0].title}} is currently in stock in the size and color you’re looking for. You can check it out here: [Product Link]. Use the code WELCOME10 at checkout for 10% off your first order! Let me know if you have any other questions!”
How it helps:
What it does: Using Gorgias’s chat widget, customers can track orders or manage their purchases on their own with no agent assistance needed.
Key feature:
Use case: A customer wants to check the status of their recent purchase. By accessing the Chat widget on your website, they can enter their email and order number and receive instant updates on their order's progress, including shipping and delivery information, without waiting for an agent's response.
How it helps:
What it does: Rules paired with Shopify variables can automate various support tasks, such as identifying specific customer segments or tagging tickets, to boost efficiency and consistency.
Key features:
Use case: A customer with a history of substantial purchases contacts support. A rule detects that the customer's total spending exceeds a predefined threshold and automatically tags the ticket as "VIP."
This tag can then trigger other workflows, such as assigning the ticket to a senior support agent or escalating its priority.
How it helps:
What it does: Gorgias offers comprehensive reporting that allows you to measure how your support interactions influence sales.
Key features:
These metrics are accessible under Statistics → Support Performance → Revenue in your Gorgias dashboard. You can filter the data by integration, ticket channel, tags, or specific time periods to gain detailed insights.
Use case: By analyzing Revenue Statistics, you can identify which support channels or agents are most effective in driving sales. For example, if live chat interactions have a higher conversion rate, you might allocate more resources to that channel.
Additionally, recognizing top-performing agents can inform training programs to elevate overall team performance.
For example, One Block Down, a Milan-based streetwear brand, struggled to manage a growing volume of customer inquiries across multiple platforms. By integrating Gorgias with Shopify, they centralized all customer interactions into a single platform, giving agents instant access to crucial information like order history and returns directly within tickets.
The setup allowed the team to measure the direct impact of their support efforts on revenue.
The result? An impressive 1,000% increase in support-generated revenue and a 1-hour average first response time. By connecting the dots between customer service and sales performance, One Block Down demonstrated how proactive, data-driven support can directly influence the bottom line.
How it helps:
What it does: AI Agent automates Shopify actions like canceling orders, editing order details, and reshipping items.
Key features:
Use case: A customer realizes they've entered an incorrect shipping address shortly after placing an order. They contact support, and AI Agent promptly verifies that the order is unfulfilled, confirms the correct address with the customer, updates the shipping information in Shopify, and sends a confirmation email—all without human intervention.
How it helps:
{{lead-magnet-2}}
TL;DR:
Looking to grow an email list to capture leads or offer welcome incentives? These days, the default solution is to plaster a full-screen pop-up on your homepage.
It seems effective on the surface, collecting emails right off the bat, but dig deeper, and these pop-ups disrupt the shopping experience and skyrocket bounce rates—with 72% of customers exiting a website.
But how else do you get your message across?
That’s where Gorgias Convert comes in—a smarter, more customer-centric tool to drive conversions without pushing your visitors away.
Below, we’ll explore why it’s time to move on from full-screen pop-ups and how Gorgias Convert offers a better alternative for Shopify brands looking to boost engagement and revenue.
Pop-ups can be an effective marketing tool, but their full-screen counterpart often creates more problems than they solve. These intrusive overlays pose several challenges that can harm both user experience and your bottom line.
Full-screen pop-ups demand attention, often at the worst possible moment—like when a customer is browsing products or is just about to check out. This experience can frustrate visitors and lead them to abandon your site entirely.
The BBC says every extra second a page takes to load can cost you 10% of your users—and pushy pop-ups don’t help. If your pop-ups are poorly timed or overly intrusive, visitors feel unwelcome, causing them to leave before exploring your offerings.
Traditional pop-ups are static and one-size-fits-all. They can’t adjust messaging based on where the customer is in their shopping journey or their behavior on your site.
Many users employ ad blockers that filter out pop-ups altogether, meaning your message never even reaches a portion of your audience.
Gorgias Convert flips the script by offering a subtle, customer-friendly way to capture leads and drive sales without the drawbacks of full-screen pop-ups. Here’s why your Shopify brand should make the switch:
Gorgias Convert integrates seamlessly into your store, using a chat-based widget that feels like a natural part of the browsing experience. Using chat to double as a supporting and converting tool is less disruptive, allowing customers to explore your store at their own pace.
Convert makes it easy to bring any type of campaign to life. Catch the attention of the exact shoppers you want by detecting their browsing behavior, customer profile, cart attributes, and more.
For example, the exit intent campaign is the top-performing Convert campaign—it detects when a user is about to leave and displays a discount code. It’s fully customizable, allowing you to tailor offers based on how much time they’ve spent on a page, the number of items in their cart, or if they’ve visited more than three times without making a purchase.
Unlike one-size-fits-all pop-ups, Convert lets you tailor your messaging based on customer behavior, order history, and engagement. For example, if a customer is browsing a specific product, Convert can offer a relevant discount or incentive tied directly to that item.
With Convert, you’re not just collecting an email address—you’re starting a conversation. The tool allows you to engage with customers in real-time through pre-set flows that guide them toward taking action, whether it’s signing up for your newsletter, redeeming an offer, or completing a purchase.
Related: 6 types of conversational customer service + how to implement them
In 2024, smartphones were responsible for generating 68 percent of online shopping orders. To meet shoppers where they are, Convert’s chat-style interactions are optimized for mobile users. Unlike traditional pop-ups that don’t display correctly on smaller screens, Convert maintains a seamless experience for shoppers who prefer to shop on the go.
Using Convert means you can combine immediate assistance with smart marketing through its native integration with Gorgias and Shopify. For example, if a customer hesitates to make a purchase, you can intervene with a live chat offer or product recommendation in real-time.
The Shopify integration also allows you to generate unique discount codes that expire within 48 hours—preventing them from being shared on unauthorized coupon sites. These codes are automatically created with customizable thresholds, such as discounts for specific collections or individual users, without manual setup.
Convert allows you to test different messages and incentives, giving valuable insights into what resonates most with your audience. This data-driven approach ensures your lead capture strategy evolves with shoppers over time.
Read more: How campaign messaging can increase conversions
Shopify brands using Gorgias Convert have led to a conversion rate boost of 6-10% more across their website, up to a 24% click-through rate and 43% click-to-order rate, and improved customer satisfaction. By prioritizing a frictionless shopping experience, these brands are turning casual visitors into loyal customers.
Here’s what some happy brands have to say about Convert:
Haircare brand, Kreyol Essence, influenced 13% of revenue with Convert campaigns: “With Convert, we’ve not only improved our conversion rates but also created a seamless, personalized shopping experience that our customers love. It’s like having a personal assistant for each shopper. Thanks to Convert, we can interact with our customers and surface key information at the right time, turning clicks into connections."
Brands using customer service management agency, TalentPop, love how easy it is to generate revenue with Convert: “Clients are constantly surprised and delighted by how effective Gorgias Convert is for revenue generation. They especially appreciate that Convert can be used to target a diverse range of customers across the entire purchasing journey.”
In five months, yoga brand Manduka, increased revenue by 284.15% after using Convert: “Gorgias Convert has helped us make the shopping experience more intuitive. We can give a nice prompt to remind people of promotions we’re running, highlight specific product features, or just remind them we're here to help and answer questions. The chat campaigns make it easy for customers because they lead them to us, as opposed to them having to search for how to contact us for assistance.”
Shoppers want personalized experiences that respect their time and preferences. Full-screen pop-ups belong to an era of intrusive marketing that shoppers would rather leave in the past.
Gorgias Convert for your Shopify brand means delivering impactful interactions, more conversions, and an easy path to long-term customer loyalty.
Ready to make the switch? Start your effortless shopping journey today with Gorgias Convert. Chat with our team!
Today, we’re announcing our deeper investment in conversational AI for ecommerce.
"Since day one, Gorgias has been dedicated to helping ecommerce brands deliver exceptional customer experiences. We started with a helpdesk to centralize support, then introduced AI Agent to instantly resolve support questions,” says Romain Lapeyre, CEO of Gorgias.
“Now, we're taking the next leap forward with an AI Agent that powers the entire customer journey—anticipating buyer needs, boosting sales, and automating high-quality support. Today, I'm happy to announce Gorgias as the Conversational AI platform for ecommerce.”
Gorgias’s Conversational AI platform will let teams provide fast, scalable, and cost-effective support while helping them drive revenue growth. From automatic order changes and refunds to product recommendations and cross-sells, brands will be able to flawlessly combine their support and sales efforts.
The end result is an AI-powered customer journey where every customer interaction feels complete, personal, and connected, both before and after purchase.
Last year, we introduced AI Agent for email.
Some brands call their AI Agent Lisa, some call it Wally, and most treat it like a real member of the team. But this reliable support sidekick was only available to answer customers on email—until now.
Get ready for instant responses that tackle support inquiries of all sizes. Now, your customers can enjoy fast responses that keep their shopping experience as smooth as possible.
On top of improving first response times, AI Agent can play an even more critical role in unblocking sales, suggesting products, and driving upsells and cross-sells.
With responses sent in 15 seconds or less, brands can delight customers with near-instant resolutions.
Actions let AI Agent perform customer requests on behalf of your support team. This includes changing shipping addresses, fetching fulfillment status, canceling orders, adding discounts, and more.
You can use a library of pre-configured Actions for popular apps like Shopify, Rebuy, Loop, and more. And you don’t need any technical skills to set them up.
With almost half of queries requiring some kind of update, Actions is your go-to for complete resolutions so you can get more accomplished.
Quality checks have traditionally been manual, time-consuming, and inconsistent. Our brand new Auto QA feature changes that by automatically scoring 100% of conversations on resolution completeness and communication quality—whether from a human or AI agent.
With Auto QA, team leads can:
Support teams should be in complete control of their AI. That’s why the AI Agent Report and AI Agent Insights were created—to help you know exactly how your AI Agent is performing and contributing to your customer service operations.
The AI Agent Report provides full visibility into AI Agent’s performance, covering metrics like First Response Time, CSAT, and one-touch ticket resolutions. Fully integrated into your Support Performance Statistics dashboard, the report includes:
AI Agent Insights takes it a step further. It analyzes AI Agent’s performance data and provides you with a dashboard of recommendations, including potential automation opportunities, popular ticket intents to optimize, and knowledge base improvements.
Soon, we’ll be expanding our AI capabilities with the launch of AI Agent for Sales, a tool designed to assist customers on their shopping journey.
AI Agent for Sales helps brands boost their sales capabilities through smart product recommendations, on-page checkout assistance, and personalized conversations. Now it's easier to reduce cart abandonment, suggest complementary products to boost average order value, and overcome pre-sale objections.
This new tool will bridge the gap between marketing and CX, ensuring brands can scale personalized interactions 24/7 without increasing headcount.
As we continue to innovate with conversational AI, our focus remains on helping you succeed.
By combining smarter tools with valuable insights, we’re creating opportunities for you to put your customers first and build deeper connections at every touchpoint.
Join us as we pave a new way for the future of ecommerce.
{{lead-magnet-1}}
TL;DR:
Your customer service conversations contain a goldmine of insight about your shoppers—like why they reached out, trends in shopper behavior, and how your products or services perform.
But how do you turn thousands of unstructured support tickets into accurate, digestible, and actionable takeaways?
Ticket Fields are the answer. They give support teams extra layers of data by labeling tickets in a much smarter way than traditional tags. With the right setup, Ticket Fields can help you uncover patterns, make smarter decisions, and highlight the value customer experience (CX) brings to your entire organization.
{{lead-magnet-1}}
Ticket Fields are customizable properties that allow CX teams to collect and organize information about tickets. Agents fill in ticket fields before closing the ticket, making it much easier to scale data collection.
Ticket Fields can be mandatory, requiring an agent to populate a field before closing the ticket. They can also be conditional, only appearing when relevant to the ticket.
There are four types of Ticket Fields: Dropdown, Number, Text, and Yes/No. Here are some ways to use each:
Unlike Tags, which are single-reason and non-conditional, Ticket Fields ensure key information, such as fulfillment details or cancellation reasons, is built into a ticket.
Think of Tags as stickers added to a ticket, while Ticket Fields are part of the ticket’s DNA itself, giving you much more control and insight.
Let’s take a closer look at why Ticket Fields are far superior at collecting data than Tags:
Agents manually apply Tags, which means it’s easy to forget to tag a ticket.
Ticket Fields, however, enforce structure by allowing CX managers to decide which fields are mandatory and which are optional. This flexibility ensures that all tickets contain the same basic details.
Ticket Fields can be conditional, meaning certain types of tickets automatically include fields that must be filled in.
How does it work? Take a look at this example:
If the Contact Reason field is Cancellation, conditional ticket fields like Cancel Reason, Did We Cancel Subscription, and Order Number must also be filled out.
Here’s how it looks in the Field Conditions settings:
No more missing context, gaps in the data, or typing N/A in a field. Support teams can capture the data they need from each ticket every time.
For CX teams transitioning from other helpdesks, being able to import historical ticket data with the field information intact is significant. This preserves workflows and existing data, helping teams get set up in no time without losing crucial information.
Tags, on the other hand, should be used to:
Ticket Fields are incredibly adaptable, allowing you to capture the exact data your team needs to meet your goals—whether it’s tracking product trends, choosing a shipping carrier, or increasing customer satisfaction.
Here are 12 examples of custom Ticket Fields to level up your data analysis.
Type of ticket field: Dropdown
What to do with the data: Identify common reasons customers contact you and take proactive steps to address them.
The Contact Reason ticket field is an easy way to figure out why customers reach out to your support team in the first place.
You can quickly identify trends, such as a sudden spike in return requests, and investigate whether it's a website, fulfillment, product, or service issue.
Some common contact reasons:
Note: Gorgias AI automatically suggests contact reasons, pre-filling the field with a prediction based on message content. Agents can accept or adjust the suggestion, helping the system become smarter over time as it learns from these interactions.
Type of ticket field: Dropdown
What to do with the data: Assess the effectiveness of resolutions and refine your service level agreement.
The Resolution ticket field tracks the action taken to resolve a ticket. Analyzing how your team handles tickets and identifying opportunities to improve resolutions is essential.
For example, you could analyze how often issues are resolved with replacements versus discounts. If you find replacements are overused for minor issues, you might implement a policy to provide discounts instead, helping to reduce costs without harming customer satisfaction.
Here are some values to add to the Resolution ticket field:
Type of ticket field: Dropdown
What to do with the data: Use both positive and negative feedback to update your policies, escalation process, customer-facing resources, product, and more.
The Feedback ticket field can capture general feedback about your brand or feedback specific to your products.
This field is an excellent way to carry out product research. For example, if you’re a food brand, you can create a dropdown that categorizes feedback by sentiment, such as “Too Sweet,” “Too Salty,” “General Dislike,” and “Artificial Taste.” Once you’ve received a decent amount of feedback, you can return to the test kitchen and perfect your recipe.
Type of ticket field: Dropdown
What to do with the data: Track product trends and prioritize improvements.
The Product field is valuable for tracking which items generate the most inquiries. If you have a large inventory, incorporating a Product ticket field can help flag which products are causing the most issues or trouble for shoppers.
If a product is the most used value, this could indicate frequent issues with the product, such as quality issues, defects, or missing information on its product page.
If a product is the least used value, it may not be generating much attention. If this is due to low sales, consider enhancing its visibility through marketing to attract more shoppers. However, being the least used value can also be good news, meaning your product performs well, and shoppers have no complaints.
Pro Tip: To understand which specific products are getting returned, add a conditional “Product” ticket field.
Type of ticket field: Dropdown + conditional field
What to do with the data: Identify recurring quality issues and fix root causes.
Track the most prominent defects reported by customers with a Defect ticket field. This can help you monitor product quality and adjust production, manufacturer, or supplier processes.
For deeper insights, add a conditional “Product” field to pinpoint which products experience specific defects. For example, if you’re a bag brand, you might find that a certain backpack is usually tied to a “Zipper” defect. This can be a valuable insight to pass on to your product team to alter the design or adjust your manufacturing process.
Here’s a look at the dropdown values for the Defect ticket field:
Type of ticket field: Dropdown
What to do with the data: Lower churn by addressing cancellation triggers.
If you’re a subscription-based business with a climbing cancellation rate, adding a Cancellation Reason ticket field can help you stop the churn. This field tracks why customers cancel orders or subscriptions. It’s a powerful way to identify patterns, such as price sensitivity or delivery delays, and to take steps to retain customers.
Cancellation reason examples:
Type of ticket field: Dropdown + conditional field
What to do with the data: Evaluate shipping carrier performance and improve logistics.
For any ecommerce brand, your shipping carrier is a big contributor to customer satisfaction. The faster a customer’s order gets to them, the better.
Use a Shipping Carrier ticket field to track the shipping carrier for tickets related to delivery issues. This will provide insights into which carriers perform poorly, enabling you to modify your logistics and order fulfillment processes.
Pair the Shipping Carrier field with a conditional “Shipping Issue” field to identify potential correlations. For example, if “Delayed” is a top shipping issue for a certain carrier, it may be time to change your logistics process.
Type of ticket field: Dropdown
What to do with the data: Learn how customers find your brand and see what types of customers and issues are tied to the purchase source.
The Purchase Origin field helps you see where customers are coming from. Are they buying directly from your website? Or from social media platforms like Instagram or TikTok?
Dig deeper, and you may also spot connections between purchase origin and common issues.
For your marketing team, this data will help improve strategies at all levels, from advertising and messaging to targeting the right platforms.
Type of ticket field: Yes/No
What to do with the data: Reduce escalations by revising escalation processes and retraining agents.
The Customer Escalation field tracks whether a ticket was escalated to a manager. It helps teams identify training needs and improve processes to reduce escalations.
As the use of AI agents increases in ecommerce customer service, having a clear view of which tickets are escalated can help pinpoint gaps in AI performance and identify scenarios that require human intervention.
Analyzing this data over time can guide updates to AI workflows and agent training, reducing the need for escalations altogether.
Type of ticket field: Number
What to do with the data: Understand how discounts impact customer satisfaction.
The Discount Percentage ticket field tracks the percentage of a discount applied to a customer's order, offering insights into how promotions affect customer behavior.
For example, if customers using a 20% discount frequently contact support about order confusion or dissatisfaction, it might indicate unclear promotion terms or product descriptions. This data helps brands refine promotional messaging and determine whether higher discounts lead to increased ticket volumes, customer satisfaction, or sales.
Type of ticket field: Yes/No + conditional field
What to do with the data: Improve the customer experience for brand new customers.
The First-Time Buyer field flags whether a customer is making their first purchase, making it easier to spot and support new shoppers. When a customer is marked as a first-time buyer, a conditional “Customer Sentiment” field can appear to capture how they feel about their experience.
First-time buyers often have questions about products or need recommendations to feel confident about their purchase. Pairing this ticket field with sentiment data helps to identify common pain points, preferences, and patterns among new customers so your team can finetune the customer experience and leave a lasting first impression.
Type of ticket field: Number
What to do with the data: Analyze product performance over time.
The Months in Use field tracks how long customers have been using a product. It’s perfect for spotting when items start breaking down, spoiling, or losing effectiveness.
This data helps brands figure out where durability, shelf life, or packaging could be improved to keep customers happy and products performing as expected.
Ticket Fields provide value across the entire CX ecosystem, from agents to decision-makers.
Ticket Fields are only as powerful as the processes that support them. Follow these five steps to help your team turn support tickets into valuable data for better reporting.
Decide what insights your team needs to improve workflows, product quality, or customer satisfaction. For example, if you want to track cancellations, set up fields like "Cancellation Reason" and "Refund Amount." Keep your Ticket Fields focused on data your team can use.
Use Gorgias to configure Ticket Fields in a structured and easy-to-use format. Keep dropdown options concise and specific to avoid confusion. Then, run a test ticket or two to confirm the setup works smoothly for agents.
Read more: Create and edit Ticket Fields
Create a presentation deck that clearly explains the purpose of every Ticket Field, the options agents can select for each field, and how the fields tie into the team’s data goals. For added visuals, include flowcharts to show when and how to use each field.
Pro Tip: Give agents a quick reference tool they can easily consult by providing a cheat sheet summarizing Ticket Field best practices.
Whether the data points to gaps in your workflows, product details, or customer education, acting on these patterns is how you drive meaningful change.
Here are some fixes, from low to high effort, that your team can implement:
Schedule a monthly meeting to review your Ticket Fields Statistics and evaluate their impact on your support workflows and customer satisfaction.
During the meeting, discuss:
Lastly, remember to document the insights and update your team regularly to keep everyone aligned.
Gorgias’s Ticket Fields turn ticket data into insights you can actually use. Spot trends, improve workflows, and make faster, smarter decisions.
Are you ready to see it in action? Book a demo, and let us show you how Ticket Fields can elevate your support.
{{lead-magnet-2}}
TL;DR:
Not sure which Gorgias plan is right for you? It all starts with understanding how many customer interactions you handle each month.
Whether you’re just starting out with 50 tickets or managing thousands across different channels, we’ve got you covered.
Our ticket-based pricing grows with your business, making it flexible and easy to scale.
This guide will help you figure out your ticket volume, explore the plan options, and find the perfect fit for your needs.
{{lead-magnet-1}}
Billing is based on a monthly or annual subscription, with plans determined by the number of billable helpdesk tickets, automated interactions, and overages.
A billable ticket is any ticket where an agent or Rule (an action that triggers based on certain conditions) responds to a customer's message. Each ticket you receive on your helpdesk is counted as one billable ticket, no matter how many messages are exchanged in the thread.
An automated interaction is a customer request resolved with Automate features, including Flows, Order Management, Article Recommendations, and AI Agent.
Important: A billable ticket can also be classified as an automated interaction depending on the timing of the responses. If an agent or Rule responds more than 72 hours after the automated interaction, it will be billed as both. If the response is within 72 hours, it will be billed as a single billable ticket.
Overages occur when your billable ticket/automated interaction volume exceeds the number included in your plan. Consider changing to a yearly plan if your volume fluctuates from month to month. We will also notify you when to upgrade to the next plan to save money.
This structure applies to all our products and add-ons, making it flexible and scalable to fit businesses of any size:
Gorgias uses a ticket-based pricing model, allowing you to grow headcount without worrying about increased costs. We believe in AI-powered CX, and as AI tools become universal, brands can rely on agents to handle tasks more effectively at accelerated speeds.
Take a look at the advantages of paying by ticket volume:
You may be coming from another helpdesk or currently trying out Gorgias. If you’re considering switching to Gorgias, it’s important to know your current monthly ticket volume.
Below, we show you how to find your monthly ticket volume whether you’re using Zendesk, Tidio, Shopify Inbox, Re:amaze, or the Gorgias trial.
Here’s how to find ticket volume on the helpdesk platforms Zendesk, Tidio, Shopify Inbox, and Re:amaze.
Here’s a four-step guide to accurately gauge your monthly ticket volume on the Gorgias trial.
Immediately after sign-up, connect all the channels you offer support on, such as email, social media, voice, SMS, etc. All messages from these channels will now be consolidated in the Helpdesk.
Use Gorgias to reply to all incoming messages for the entire 7 days. This is crucial because only replies sent from the helpdesk will count as billable tickets. This process ensures you select the right pricing plan after the trial ends.
Find your ticket volume in Statistics > Support Performance > Overview. There, you can view your ticket volume (created, closed, and open tickets) and support metrics like first response time and resolution time.
Go to Statistics > Account > Billing & usage > Usage & Plans. To get your estimated monthly ticket volume, multiply the number of tickets used by 4 (for four weeks). For average yearly ticket volume, multiply the resulting number by 12.
As a starting point, we recommend automating 10-20% of your annual ticket volume to increase repeat purchases, reduce response times, and increase overall customer satisfaction.
Multiply your yearly ticket volume by 0.2 to find the optimum number of automated interactions you need.
Once you’re ready to find the plan that works for you, input your anticipated number of tickets, automated interactions, and Voice and SMS tickets per month into the pricing calculator.
Our pricing calculator is designed to help you find the most cost-effective plan for your business needs in four simple steps.
Use the slider to set the number of tickets your store receives per month, ranging from 0 to 10,000.
Not sure how many tickets you receive per month? On average, brands receive one support ticket for every 15 orders.
You can choose from four plan options. The first is a base plan with the number of tickets you can use per month and the overage fee. The following plans are the base plan with the addition of automated tickets, ranging from 10%-30% automation.
Pro Tip: Based on 2023 data, brands that automated 20% of their tickets substantially reduced response times and resolution times and increased CSAT.
Expand your customer service channels by adding Voice and SMS tickets to your plan.
Lastly, finalize your selection by toggling the option to pay on a monthly or yearly basis. You’ll see your final plan summary along with the time and money you save. When you’re ready, click ‘Book a Demo’ to get started with Gorgias.
Choosing the right Gorgias plan depends on your estimated ticket volume. Here are our recommendations based on your monthly ticket volume.
Customer Interactions |
Who You Are |
Plan Recommendation |
What You Get |
---|---|---|---|
50 tickets per month |
First-time helpdesk user without a support team |
Starter + Automate |
Basic support tools, three users, essential integrations |
50-350 tickets per month |
Small business with 1 agent |
Basic + Automate |
Unlimited user seats, essential integrations, self onboarding |
350-2,500 tickets per month |
Medium business with a growing support team of 1-3 agents |
Pro + Automate |
Unlimited user seats, unlimited integrations, lite onboarding support |
2,500-6,000 tickets per month |
Large business with a support team of 2-4 agents |
Advanced + Automate |
Unlimited user seats, unlimited integrations, full onboarding support |
6,000+ tickets per month |
Enterprise businesses with a support team of 4-5 agents |
Enterprise + Automate |
Unlimited user seats, unlimited integrations, full onboarding support |
8,000+ tickets per month |
Enterprise businesses with a large support team |
Enterprise + Automate |
Unlimited user seats, unlimited integrations, full onboarding support, customized solutions |
Pro Tip: We include Automate in every recommendation because it can automatically resolve up to 60% of your customer inquiries, freeing you from repetitive work and allowing you to focus on more complex tasks.
{{lead-magnet-2}}
TL;DR:
According to Salesforce research, 77% of support staff have dealt with increased and complex workflows compared to the year prior. In addition, 56% of agents have experienced burnout due to support work.
As teams transition into the next era of CX –– one where almost every customer expects efficiency, convenience, and friendly and knowledgeable service –– they’ll need the support of more than just a stellar lead to avoid the stress that comes with the job.
AI and automation are valuable and impactful tools that can aid teams in providing these top-notch experiences while helping agents lower their own stress.
Here are seven ways to leverage AI and automation to increase agent productivity, meet customer expectations, and decrease burnout on CX teams.
{{lead-magnet-1}}
While there will always be reasons for human intervention, here are seven support challenges that AI and automation can solve for CX teams long term.
Every CX team receives repetitive questions like “where is my order” (WISMO), “can I change my shipping address,” or “what is your return policy” every single day. These questions add up over time, creating frustration and burnout for agents and longer response times for customers.
Instead, teams can leverage AI and automation to answer these questions and take time back for other essential tasks.
If you use Gorgias, there are a couple of ways to put automation to work.
"Gorgias's AI Agent has been a game-changer for us, allowing us to automate nearly half of our customer service inquiries. This efficiency means we don’t need to hire additional staff to manage routine tasks, which has saved us the equivalent of two full-time positions.
—Noémie Rousseau, Customer Service Manager at Pajar
Resource: How to Automate Half of Your CX Tasks
Many customers get frustrated due to delayed support responses, especially if (they believe) they’re asking a simple question. Not only can AI and automation support by offering responses to these questions, they allow human agents to respond faster to customers who have more complex questions.
AI Agent has been an effective tool for the team at luxe golf accessory shop VESSEL. “Now we’re able to get back to people so much faster than before,” says Lauren Reams, their Customer Experience Manager.
“We can quickly collect information – avoiding the back and forth questions like what is your name, email or shipping address. Using AI to eliminate the back and forth has been great, and getting back to customers much faster than before has been the biggest win for our team.”
If customers see an inconsistent tone of voice across responses, it’ll affect your brand credibility. It also causes confusion and may create issues maintaining repeat and loyal customers.
Manual quality assurance checks are time-consuming and often inconsistent. But they’re key to providing great support at scale while maintaining a high standard across thousands of interactions. Aside from catching any errors, a regular QA process also builds trust with customers, increases personalization, and helps agents improve over time.
Automated quality assurance can provide up to 90% accuracy, according to research by McKinsey. All you’ll need to do to get started is to choose and implement an automated QA tool.
When CX teams are bogged down with an overwhelming amount of tickets, there’s going to be a lack of time and opportunity to upsell in customer conversations. This is especially true when dealing with angry or upset customers, and during high-impact periods like BFCM.
Activate onsite marketing campaigns with Gorgias Convert to provide product recommendations and promote current discounts, sales, or campaigns.
For example, you can use AI to promote relevant items to shoppers to increase their cart value. You might highlight items that are frequently bought together, or show a bundle that would make a great gift for someone. Research shows that these types of personalized recommendations can increase average order value (AOV) by 15%.
Resource: 5 Holiday Onsite Campaigns to Maximize Year-End Sales
The National Retail Federation (NRF) projects that retail returns will total $890 billion in 2024. With so many brands losing money from returns, it’s essential that you find ways to mitigate them.
By switching to Gorgias, Audien Hearing saw nearly a 5% drop in return rates. And Rumpl saw $8,000 in recouped return fees by integrating Loop Returns with Gorgias.
Loop lets customers self-serve returns through a returns portal that encourages exchanges instead. It makes the entire process a breeze, and eliminates back and forth between customers and busy support teams.
Many times, issues that were completely avoidable are escalated, leaving support teams with more tickets and already frustrated customers. These issues are likely common points of confusion that you can easily solve before they ever reach your customers.
If you use Gorgias, here’s how you can leverage automation:
“I’ve been in this role for four years and this was probably our best back to school season yet. In past years, you knew you were going to come in and be bogged down – but this year was way more seamless and much less stressful and that’s thanks to AI Agent.”
—Danae Kaminski, Customer Care Team Lead at Jonas Paul Eyewear
At Gorgias, our goal is to create solutions to the real problems CX professionals face every day. Tools like Automate and AI Agent make it possible for teams to provide better customer experiences, reduce agent stress, and create more cohesive and positive working environments overall.
”Thanks to the time we've saved by automating many of our routine tasks, our team has had the chance to bond more,” says Noémie.
“We even had time for a team picnic and painted a picnic table outside! It’s been great to step away and spend time as a team occasionally, knowing that our customers are still being taken care of by the AI Agent. It’s really improved team morale.”
{{lead-magnet-2}}
TL;DR:
The start of a new year is the perfect time to give your help center the refresh it deserves. For many ecommerce brands, the help center is one of the most underused support tools—yet it's also one of the most powerful. 88% of customers already search your website for some kind of knowledge base or FAQ.
Customers expect fast answers, and a well-designed, updated help center can meet their needs while taking some weight off your support team. We’ll walk you through why refreshing matters and how to do it.
{{lead-magnet-1}}
90% of consumers worldwide consider issue resolution their top priority for customer service. A robust help center gives you the tools to meet this expectation, delivering fast and reliable solutions that simplify your customers’ lives.
A well-designed help center benefits both your customers and your team. For customers, it lets them solve problems quickly and independently. Instead of waiting for an email response or queuing for live chat, a help center empowers them to find answers on their own terms 24/7.
For your team, a refreshed help center is transformative, too. Here’s what a help center update can achieve:
In short, refreshing your help center will improve customer experience and boost efficiency across your entire customer service strategy. It’s a win-win for everyone.
Refreshing your help center doesn’t have to be overwhelming. By breaking the process into clear, actionable steps, you can transform your help center into a powerful self-service tool that delights customers and supports your team.
Here are four key steps to guide your refresh.
Before making any major changes, you need to understand where your help center currently stands. A thorough audit will help you identify areas for improvement and ensure you make targeted updates.
Here's how to start:
Dive into your help center metrics to spot underperforming content. Look at article views, time-on-page, and bounce rates. Low engagement might mean the content is unclear, irrelevant, or hard to find.
With a customer experience platform like Gorgias, you can view the performance of each article:
Customer feedback is invaluable. Use surveys or follow-up emails to ask customers what information they had trouble finding. Their responses can highlight blind spots in your help center.
At the end of each help center article, include a simple question like, "Was this content helpful?" Use the feedback to pinpoint which articles are effective and which may need improvement.
Put yourself in your customers’ shoes. Try searching for answers to common questions. Is the layout intuitive? Are the search results helpful? A smooth user experience is key to a successful help center.
Check if your articles are outdated or missing important updates, like new product features or policy changes.
Read more: How to create and optimize a customer knowledge base
Fresh, well-organized content is the backbone of a great help center. Customers rely on clear and accurate information, so investing in your content can transform your help center into a powerful self-service tool.
Here’s how to refresh your content and make it shine:
Regularly analyze support tickets to identify common and emerging questions. Integrate these into your knowledge base to address customer needs proactively and reduce incoming tickets.
Text alone isn’t always enough. Use images, GIFs, and videos to break down complex topics and make instructions easier to follow. For example, a quick explainer video can save customers time and eliminate confusion.
Princess Polly’s customer help center exemplifies what a great help center should look like. Its visually appealing design ensures that customers can quickly navigate to the information they need. Whether they’re looking for help with shipping, payments, returns, or any other issue, the intuitive layout makes the process simple and stress-free.
Gorgias lets you customize fonts, logos, and headers for your Help Center without any coding. If you want more customization, you can dip into HTML and CSS to tailor specific elements.
Ensure your content reflects your brand voice while staying approachable and customer-friendly. Consistency builds trust and reinforces your brand identity.
Need help finding your brand voice? Read AI Tone of Voice: Tips for On-Brand Customer Communication for guidance.
Review older content for inaccuracies or missing information, such as policy changes or new product details.
Use bullet points, short paragraphs, and clear headings to make articles easy to scan. Most customers skim for quick answers—design your content to match their behavior.
Even the most well-crafted help center is ineffective if customers can’t locate it. Ensuring visibility across all customer touchpoints is key to driving engagement and making self-service the first stop for support. Here’s how to do it:
Make your help center easily accessible by placing links in strategic locations, such as your website’s header, footer, and main navigation menu. Include links in transactional emails, like order confirmations, tracking updates, or shipping updates, where customers often have questions.
Optimize your help center articles with keywords your customers are likely to search for. Use clear, concise titles, meta descriptions, and headings to boost search engine visibility and help customers find answers directly from Google.
Use tools like automated chat and automated email responses to proactively surface relevant help center articles. For instance, when customers type a question in a chatbox, suggest related articles before escalating to a support agent.
Read more: Offer more self-serve options with Flows: 10 use cases & best practices
Don’t wait for customers to stumble upon your help center—promote it! Highlight it in onboarding emails, social media posts, and banners on your site.
Jonas Paul Eyewear ensures their help center is easy to access by prominently linking it in the website’s footer under the “Quick Links” section. The thoughtful placement ensures customers can quickly navigate to the help center from any page, making it a convenient resource for addressing their questions or concerns.
Read more: Boost your Help Center's visibility: Proven strategies to increase article views
Your help center isn’t just for customers—it will also level up your AI-driven support strategy. By structuring your knowledge base effectively, you enable AI tools to deliver accurate, reliable, and consistent answers to customer queries.
Here’s how to make it work:
Ensure your help center articles cover a wide range of customer questions in detail. This makes it easier for AI tools to pull relevant information and respond accurately.
Organize your content with clear headings, bullet points, and simple language. Well-structured articles are easier for AI to parse and interpret.
Use uniform terminology across articles to prevent confusion and ensure AI tools can quickly identify relevant data.
Keep your knowledge base fresh by adding new FAQs, updating outdated content, and incorporating customer feedback. Up-to-date information ensures AI tools provide answers that align with your latest products, policies, and services.
Periodically review how well your AI tools are using your help center content to address customer needs. Identify gaps in information and fine-tune articles as needed.
Dr. Bronner’s built their help center to power AI Agent, a conversational support assistant that answers both transactional and personalized customer inquiries in the same style as a human agent. Making this change helps the brand save $100,000 a year and decrease their resolution time by 74%.
💡Pro Tip: Transform your help center into an AI training powerhouse with Gorgias’s help center AI optimization guide. This guide offers actionable tips for making your knowledge base AI-ready.
By using your help center to power AI tools, you’ll improve customer self-service options and lighten the load on your support team. AI-enhanced support delivers faster resolutions, higher customer satisfaction, and a scalable approach to customer service.
Refreshing your help center isn’t just about improving customer experience—it’s a game-changer for your entire support strategy. With tools like Gorgias’s Help Center, you can empower customers to self-serve while equipping your team with the resources they need to excel.
In 2025, make your help center the cornerstone of your support operations—and watch the results speak for themselves.
{{lead-magnet-2}}
TL;DR:
This year, 71% of customer experience (CX) leaders are using AI and automation to handle the holiday shopping season. These tools, including AI agents and email autoresponders, speed up tasks like responding to customers and updating orders.
But answering tickets isn't enough. Responses must also be high-quality, whether from humans or AI. And while customer satisfaction (CSAT) is the standard measure of how successful these interactions are, they have major limits.
CSAT scores don’t tell the full story about whether agents were helpful or if they used on-brand language. These gray areas in quality lead to missed sales, higher return rates, and frustrated customers during peak periods.
AI quality assurance (QA) is changing that. In this article, we’ll see what QA looks like today, how AI can simplify the process, and how CX teams can use tools like Auto QA to improve quality across all conversations.
{{lead-magnet-1}}
Today, QA in customer support is a largely manual responsibility. Customer conversations are reviewed by CX team leads to ensure customer satisfaction and identify areas for agent coaching. Team leads evaluate agent responses against a checklist of best practices, including the proper use of language, product knowledge, consistency, and helpfulness.
However, reviewing tickets takes a long time.
QA is important, but it's hard to prioritize when customers are actively waiting for help with refunds, urgent order edits, or negative reviews. And when CX teams are under-resourced and short-staffed, it’s easy to put QA on the back burner.
What’s more, as AI plays a bigger role in responding to customers, quality assurance must evolve to ensure the quality of AI-generated responses, not just human responses.
Over time, the lack of QA in CX can hold back support teams for three reasons:
AI-powered quality assurance (QA) uses AI to automate the process of reviewing customer interactions for resolution completeness, communication, language proficiency, and more.
Instead of team leads spending hours manually sifting through tickets, AI takes over and evaluates how well tickets were resolved by agents.
Shifting this traditionally manual work to an automated process pulls teams out of the weeds and into more beneficial work like speaking to customers and upselling.
With AI QA, routine ticket reviews are not just an optional part of your customer service strategy, they become a permanent part of it. The road to greater customer trust, resolution times, and stronger product knowledge becomes easier.
Read more: Why your strategy needs customer service quality assurance
Manual QA is like trying to review a handful of tickets during a flood of new customer requests. Team leads can only focus on a small sample, leaving most interactions unchecked. Without complete visibility, creating a standard across all interactions is challenging.
Now, switch over to AI QA. You don’t have to choose between QA duty or answering tickets — QA checks are automatically done. You’ll still need to monitor AI’s performance, but now there’s more time to focus on creating strategies that improve the customer experience.
Here’s how AI QA and manual QA measure up to each other:
Feature |
AI QA |
Manual QA |
---|---|---|
Number of Tickets Reviewed |
All tickets are reviewed automatically. |
Only a small sample of tickets can be reviewed. |
Speed of Reviews |
Reviews are completed instantly after responses. |
Reviews are time-consuming and delayed. |
Consistency |
Feedback is consistent and unbiased across all tickets. |
Feedback varies depending on the reviewer. |
Scalability |
Scales, regardless of ticket volume. |
Struggles to keep up with high ticket volumes. |
Agent Feedback |
Provides instant, actionable feedback for every resolved ticket. |
Feedback is delayed and limited to a few cases. |
Leader Advantage |
Frees up leaders to train the team and improve workflows. |
Disadvantageous, as leaders spend most time manually reviewing tickets. |
AI quality assurance helps CX leaders move beyond manual reviews by offering fast, thorough insights into performance and customer needs. Here are seven key benefits it brings to your team.
AI QA reviews every ticket, giving CX leaders a complete view of agent performance and customer trends. Nothing slips through the cracks, so you can act on real data each and every single time.
What the team wins: Key areas to focus on to improve the customer experience.
What the customer wins: A consistent support experience where their concerns are fully addressed.
Only a third of customers highly trust businesses, and without QA checks in place, that trust only deteriorates.
AI QA feedback can highlight confusing policies or common product issues that lead to unhappy customers. With instant feedback, teams can quickly make changes and create better, consistent customer experiences.
What the team wins: Faster fixes for recurring issues.
What the customer wins: A smoother, frustration-free experience.
Agents can receive feedback that instantly highlights gaps in workflows or unclear escalation steps. This is an efficient way to resolve issues within the wider team before they become more significant problems.
What the team wins: Process issues are solved quickly.
What the customer wins: Faster resolutions with little to no delays.
AI QA evaluates both AI Agent and human agent interactions using the same criteria. This creates a level playing field and ensures all customer interactions meet the same quality standards.
What the team wins: Fair evaluations for both AI and human responses.
What the customer wins: High-quality support, no matter who handles the ticket.
With less time spent on manual reviews, leaders can dedicate more energy to team development. Training sessions guided by AI insights help agents improve quickly and ensure the team delivers support that aligns with protocols.
What the team wins: More focused skill-building based on data.
What the customer wins: Clearer and more accurate support.
AI QA is helpful for showing agents which areas they need more training on, whether it's being better about using brand voice or polishing up on product knowledge. This leads to better support processes and stronger product understanding across the team.
What the team wins: Better support tactics and product expertise.
What the customer wins: Faster resolutions due to knowledgeable agents.
Since all tickets are reviewed, teams can feel confident they’re delivering high-quality support on a regular basis. Customers get clear, helpful answers, while agents gain insights from every ticket with AI feedback.
What the team wins: Consistent support performance.
What the customer wins: Reliable support they can trust.
AI QA analyzes tickets using predefined categories to evaluate how complete and helpful agent responses are. Let’s take a closer look at how it maintains accurate ticket reviews with an AI QA tool like Gorgias’s Auto QA.
Auto QA evaluates tickets based on three key areas: Resolution Completeness, Communication, and Language Proficiency.
For Resolution Completeness, it checks if all customer concerns were fully addressed. For example, if an agent resolves only one of two issues raised, the ticket is marked incomplete. Tickets where customers resolve issues on their own or don’t respond to follow-ups can still be graded as complete if handled appropriately.
Communication quality is scored on a scale of 1 to 5, assessing clarity, professionalism, and tone. Agents earn higher scores when they provide clear solutions and remain positive throughout the interaction.
Finally, Language Proficiency evaluates whether an agent displayed high proficiency in the language of the conversation. The score considers how well spelling, grammar, and syntax were employed.
Auto QA isn’t set in stone. Team leads can expand on AI-generated feedback by adding their comments. For example, if a resolution is graded as ‘Incomplete,’ a team lead can explain why and provide additional context. This helps clarify the evaluation for the agent and also helps the AI model improve over time.
Ready to bring the benefits of AI QA to your team? Here’s how to get started with Auto QA:
AI QA isn’t just about automating ticket reviews — it empowers CX leaders to focus on what truly matters: training and improving processes.
Leave spot-checking and inconsistent application of policies and brand voice in the past. As a built-in feature of Gorgias Automate, Auto QA makes high-quality customer interactions your brand’s standard.
Book a demo now.
{{lead-magnet-2}}