TL;DR:

• Glamnetic eliminated over 15,000 repetitive responses with AI, letting their team focus on complex customer needs and sales opportunities.
• Audien Hearing found their AI support was matching or beating human performance, with faster responses and better conversion rates.
• AI turned out to be more than just a time-saver—it became a serious revenue generator by engaging shoppers in real-time and driving sales.‍
• This is just the beginning for AI in customer experience. AI will transform everything from personalized recommendations to proactive sales and marketing.

The AI revolution in ecommerce customer support is already here. 77% of service teams are already using AI, and 92% say it improves time to resolution. 

Brands that embrace AI can improve efficiency, scale faster, and deliver better customer experiences.

But what does that look like in practice?

In a recent Grow Your Business in 2025 with Conversational AI webinar, Kevin Gould, co-founder of Glamnetic, and Zoe Kahn, owner of Inevitable Agency & former VP of Retention and CX at Audien Hearing, shared how their teams use Gorgias AI Agent to streamline support, reduce workloads, and convert more shoppers into customers.

For them, AI isn’t just hype, it’s delivering real results—and Kevin and Zoe have seen it firsthand.

Ahead, we’ll break down Kevin and Zoe’s firsthand experiences, covering:

• How AI helped Glamnetic reduce manual responses by 15,000–16,000 tickets
• How AI-powered responses helped Audien Hearing capture more revenue
• The biggest misconceptions about AI in customer support—and why they’re wrong
• What AI-driven CX will look like in 2025 and beyond

Watch the full webinar replay here:

How AI reduces 16,000 manual tickets and scales CX

As ecommerce brands grow, so does the demand for fast, high-quality customer support. But hiring and training more agents isn’t always scalable—especially when a significant portion of support tickets are repetitive, like “Where’s my order?” or “How long does shipping take?”

That’s where AI comes in. Instead of bogging down human agents with routine questions, AI-powered support can handle high ticket volumes instantly, freeing up CX teams to focus on complex issues, relationship-building, and revenue-generating conversations.

Both Glamnetic and Audien Hearing have seen firsthand how AI can transform CX. Glamnetic reduced manual responses by 15,000–16,000 tickets, while Audien Hearing saw AI outperform some human agents in both response speed and upselling.

Related reading: How to build an effective AI-driven customer support strategy

How Glamnetic uses AI to cut manual responses by 25% 

As Glamnetic scaled, so did its customer support workload. Managing tens of thousands of tickets while maintaining fast, high-quality support became a challenge. Many of the inquiries Glamnetic receives are repetitive––think order updates, shipping questions, and product details.

The brand needed a way to streamline responses without losing the personal touch.

Here’s what made the difference: Glamnetic used AI Agent to automate responses for thousands of tickets, allowing human agents to focus on higher-value interactions that drive customer loyalty and sales.

Kevin Gould, co-founder of Glamnetic, was excited about infusing AI across the entire business. “CX felt like the first natural extension. A big part of that was [Gorgias] pushing us into it pretty quickly. We saw early on that AI could be a force multiplier for the business."

The results speak for themselves:

• 15,000–16,000 fewer manual responses—freeing up agents for more complex cases.
• Faster response times, improving the overall customer experience.
• Smarter AI-driven sales, turning support inquiries into revenue opportunities.

Read more: How Glamnetic uses AI Agent to handle 40% of Support Volume with "mind-blowing" results 

"What’s really interesting is that AI handled 24% of tickets across the entire year…Now, we’ve gotten much smarter about how we deploy AI for revenue generation, and it’s been highly impactful. It’s well worth your time to deploy this across your company." —Kevin Gould, Co-founder, Glamnetic

How Audien Hearing scaled support without adding headcount

Scaling customer support while keeping costs in check is a challenge for any fast-growing ecommerce brand—especially one focused on retention and long-term customer relationships.

For Audien Hearing, this meant managing a team of over 80 support agents while ensuring that every interaction added value to the customer experience.

Rather than endlessly hiring more agents, Audien Hearing turned to AI to optimize. AI Agent helped them handle high ticket volumes faster, without sacrificing quality. With AI handling routine inquiries, their team was able to focus on higher-value conversations that drove long-term growth.

Zoe Kahn, former VP of Retention & CX, notes the importance of efficiency when managing large teams, “Once you reach that scale, you have to figure out how to be efficient and adapt to the right tools. AI helped us a lot. That said, it’s not a magic button. It takes training and adjustment. Adopting AI with Gorgias has allowed our team to focus on the tasks that truly need a human touch."

The impact was undeniable:

• AI became one of Audien Hearing’s fastest agents, reducing response times.
• Support scaled without adding headcount, optimizing costs.
• AI-driven interactions increased revenue by converting browsing customers in real-time.

Read more: How Audien Hearing increased efficiency for 75 agents and reduced product returns by 5% 

"[AI Agent] ended up being one of our fastest agents—answering the most tickets and driving the most revenue. A lot of that revenue was potentially missed revenue because these were customers sitting on the site, asking questions about the products, and wanting an answer now so they could purchase…Now, AI can answer those questions immediately and convert those customers." —Zoe Kahn, former VP of Retention & CX, Audien Hearing 

Initial AI skepticism and common concerns

AI in customer support still raises eyebrows. Some brands worry about losing the human touch, while others fear AI will replace agents rather than support them. 

Even Zoe Kahn was initially skeptical about AI’s role in customer experience:

"I wasn't fully convinced at first—I wanted humans talking to my customers. But as soon as I saw it working well, and just as great as some of my agents, if not even better because of faster responses, and we're having agents train it... it's much easier now with a bunch of wins.”

What changed? Seeing AI in action—handling repetitive, time-consuming tasks like order tracking and FAQs, while human agents focused on complex cases, upselling, and retention.

For Kevin Gould, AI wasn’t brought in to cut costs but to help the CX team work smarter, not harder:

“We try to think a lot about how to work smarter, not harder. On one end of the spectrum, there's a lot of tedious, repetitive emails that can be automated right off the jump. Then as you move up the stack, from servicing up to generating revenue, it starts to get really interesting. If our ultimate goal is to provide customers with the best experience possible, then why not free up our agents from tedious tasks and double down on the things that push us towards that goal?”

The key takeaway? AI isn’t automation just for the sake of automation. It’s for scaling smarter and freeing up CX teams to have the right conversations at the right time.

Related reading: How to automate half of your CX tasks 

What’s next for AI in ecommerce CX in 2025?

AI in ecommerce customer support started as a cost-saving tool and is now proving to be a revenue driver. Looking ahead to 2025, AI’s role in personalization, proactive selling, and marketing integration will only grow.

For Zoe Kahn, the future of AI involves building stronger customer relationships:

"Take time to create community with your customers. Have the ability to think not only about revenue driving but also customer retention. Every time you have an opportunity to talk to a customer, take it. If teams don't have that time that could be freed up from training an AI agent, we see them rushing through replies that could really ruin their relationships with customers."

This shift toward AI-powered personalization is something Kevin Gould is already seeing in action. He predicts AI will become a key player in conversational selling, guiding customers to the right products at the right time:

"Eventually, we'll get to a place where AI is going to become a great recommendation engine. If we sell press-on nails, and a consumer has bought a few different styles in the past, AI can quickly pivot into conversational selling."

Beyond support, Kevin also believes that AI is blurring the lines between CX and marketing. As brands gain deeper insights into customer behavior, AI-powered support will help fuel marketing campaigns, drive retention, and create highly personalized experiences:

"If I asked [my support agent] how she sees her job, she’d say it started four years ago as customer service, then evolved into customer experience. Over time, different layers of customer experience emerged to the point where it's now an integrated marketing role.

She's collaborating closely with marketing specialists—growth marketing, brand marketing, and more. At this point, this role is almost like an extension of the marketing team...It requires a balanced mindset that blends marketing expertise with a deep understanding of customer experience to be successful."

Related reading: 6 ways to increase conversions by 6%+ with onsite campaigns

Why 2025 is the year to embrace AI in CX

In 2025, AI will go beyond responding to customers. It will anticipate their needs, personalize their journey, and turn support into a revenue-generating powerhouse.

As Kevin Gould and Zoe Kahn shared, brands that embrace AI free up their teams to focus on high-impact conversations that build loyalty and boost sales.

From Glamnetic reducing 15,000+ manual responses to Audien Hearing’s AI-powered revenue wins, the results speak for themselves. AI helps brands personalize support, engage customers in real-time, and even drive conversational selling.

Ready to see how many routine tickets you could automate? Book a demo to see AI Agent in action.

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TL;DR:

• Manual QA is time-consuming—Auto QA does the heavy lifting. It frees up team leads by automatically reviewing conversations with accuracy and consistency, so they can focus on improving support.
• Auto QA scores 100% of private text conversations, whether handled by a human or Gorgias AI Agent. It evaluates support quality based on Resolution Completeness, Communication, and Language Proficiency.
• Auto QA supports multiple languages but provides feedback in English. It can assess tickets in any language supported by OpenAI’s GPT-4, ensuring global teams can benefit from automated QA.‍
• Start with individual meetings before a team-wide rollout of Auto QA. One-on-one conversations help address specific agent concerns and ensure a smooth transition.

Customer satisfaction scores (CSAT) have long been the go-to metric for measuring support quality, with 53% of customer experience leads relying on them. However, CSAT only tells you part of the story. 

When customers rate their experience 3 out of 5, what does it really mean? Did they rate the agent’s actions or the company’s policies? Was an agent helpful or inefficient? Did they take unnecessary steps to get to the answer?

Quality assurance checks can fill these gaps, but manual QA is a heavy lift. Team leads often struggle to review more than a small sample of conversations, leaving many issues unchecked.

Auto QA redefines quality assurance for today’s support teams. It transforms QA from a manual task into an automated feedback engine that helps your team deliver excellent support, every single time.

Let's dive into how Auto QA works, how accurate its scoring is, and how you can add it to your support workflow to start improving customer conversations today.

What is Auto QA?

Gorgias Auto QA upgrades the customer service QA process by automatically evaluating 100% of private text conversations, whether handled by a human or AI Agent. 

Each message is scored on metrics like Resolution Completeness, Brand Voice, and Accuracy, helping teams fix and address areas of improvement.

With an automated QA process, brands can:

• Save time: Automated quality checks help team leads focus on the most critical tickets.
• Ensure consistency: Both human agents and AI Agent are evaluated with a unified, comprehensive quality score.
• Boost performance: Agents can receive targeted coaching to provide more consistent customer experiences.
• Meet customer expectations: Customers benefit from higher-quality support with quicker resolutions and accurate responses.

How Auto QA works 

Let's explore a real-life scenario: A customer reaches out about a product issue, seeking troubleshooting help. Here’s how the interaction unfolds:

Customer: "Hi, my device broke, and I bought it less than a month ago. -Kelly"

Support Agent: "Hi Kelly, please send us a photo or a video so we can determine the issue with your device. -Michael"

The ticket is eventually closed, but the customer doesn't leave a CSAT score.

In this case, Auto QA would provide the following insights:

• Communication Score: 3/5. Reason: The agent's wording could benefit from more empathy.
• Resolution Score: "Complete". Reason: The agent effectively addressed the customer's concerns.

How accurate is Auto QA’s scoring?

Auto QA uses a comprehensive scoring system that evaluates conversations on communication proficiency and knowledge accuracy.

To ensure accuracy, Auto QA only scores interactions with at least 250 characters and messages from both agents and customers. It's also smart enough to filter out automated responses, spam, and bot messages.

Auto QA automatically scores three main aspects:

1. Resolution Completeness: Did the agent solve everything the customer asked about? This area is scored with a "Complete" or "Incomplete.” For instance, it correctly marks a ticket as "Complete" when a customer resolves their issue or when there's no clear question to address.
2. Communication Quality: How well did the agent listen and show empathy? Uses a 1-5 scale, looking at how well your agents acknowledged a customer’s concerns and communicated the solution.
3. Language Proficiency: Did the agent communicate properly? Uses a 1-5 scale to check spelling, grammar, and syntax.

For deeper feedback, certain criteria require manual scoring from team leads:

• Accuracy: How accurate was the information provided by the agent?
• Efficiency: How quickly did the agent handle the ticket? How well did they minimize the number of follow-ups?
• Internal Compliance: How closely did the agent follow your team’s internal processes and brand guidelines?
• Brand Voice: How well did the agent use brand vocabulary, greetings, sign-offs, and tone of voice?

How to integrate Auto QA into your workflow

Whether you're just starting with quality checks or transitioning from manual QA, Auto QA can seamlessly fit into your existing processes. Here's how to get started.

1. Set your standards

What does “good” look like for your team? Review Auto QA's scoring system and decide which metrics matter most for your brand, from Resolution Completeness to Brand Voice. This will help you set realistic targets for your team to work toward.

Tip: Start by prioritizing a couple of areas. This could look like prioritizing a 5/5 Resolution Completeness score while deprioritizing Brand Voice. As your team gets comfortable with Auto QA, you can ramp up to improving Brand Voice.

2. Agree on a scoring system

Since some criteria—Accuracy, Efficiency, Internal Compliance, and Brand Voice—require manual scoring, it’s best to agree on how your team will use the scoring scale.

For example, each score from 1 to 5 receives a distinct piece of feedback. Here’s what that would look for the Efficiency criteria:

• 1/5 stars: Excessive back-and-forth that could have been avoided
• 2/5 stars: Resolution took longer than necessary due to poor process
• 3/5 stars: Average handling time with some unnecessary steps
• 4/5 stars: Quick resolution with minimal back-and-forth
• 5/5 stars: One-touch resolution

3. Prepare your agents

Start rolling out Auto QA through individual meetings with agents rather than overwhelming your team with a general training session. One-on-one conversations allow you to better address each agent's specific questions and concerns. Make sure to cover the following:

• Explain that Auto QA is meant to help make conversations consistent, not police agents
• Explain the scoring criteria and what each score means
• Highlight which criteria agents should prioritize

If regular one-on-one meetings aren't part of your routine, consider introducing Auto QA during your weekly team meetings or through a dedicated training session. Just remember to leave plenty of time for questions and walk through multiple examples to ensure everyone is comfortable with the system.

4. Establish a review schedule

To solidify QA checks, create a simple routine for reviewing Auto QA insights with the Auto QA Report (navigate to Statistics > Auto QA). 

• Weekly: Do a quick check of automated scores.
• Monthly: Analyze trends and patterns across conversations. 
• Quarterly: Review and adjust quality benchmarks.

5. Act on insights

Once you’ve collected a substantial amount of Auto QA data, there are a few follow-up actions you can take to continue having high-quality conversations:

• Set the example by sharing high-scoring conversations in your team meetings.
• Coach agents individually by reviewing their tickets together. Celebrate high-scoring conversations and provide targeted feedback on areas for improvement. This immediate, personalized approach helps agents grow faster than general training sessions.
• Increase product and policy knowledge by refining internal guidelines on brand voice, escalation processes, and more.

Remember, Auto QA works alongside your existing processes—it doesn't replace them. Start small, focus on the metrics that matter most to your team, and scale up as you get comfortable with Auto QA.

Brands are excited about the power of Auto QA

We invited leading ecommerce brands to beta test Auto QA, and their feedback highlights how it's transforming quality assurance across support teams of all sizes.

amika's support team values the complete visibility beyond CSAT: "Auto QA dramatically widens the volume of tickets we can review," they share. "A 5-point scale only tells you so much, and relying on consumers providing feedback limits what you're able to learn from."

Peachybbies' CX team enjoys real-time improvement: "Being able to give real-time feedback is pivotal, especially during peak times," their team explains. "Auto QA catches pretty much everything I'd want a human QA agent to catch."

OSEA Malibu's managers discovered operational insights: "It helps managers understand when a macro or process is leading to incomplete conversations versus when an agent made a mistake," their support lead shares.

Bring quality into every conversation with Auto QA

By prioritizing QA, your team can identify potential problems early, reduce errors, and improve overall performance, leading to a smoother, more reliable experience for customers––and your CX team. 

In the long run, brands focusing on QA can gain a competitive edge. Book a demo now to see what Auto QA can do for you.

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There are tons of CX metrics you could be tracking. But where you spend your time is crucial as a customer experience leader. 

According to recent data, these are the top five CX metrics for you to prioritize and improve on in 2025.

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Why CX metrics are essential for success 

Not tracking CX metrics is like putting a loaf of bread in the oven but leaving baking time to chance. Without a set timer, you could end up with an underbaked bowl of dough or a burnt mess. Unless you have a sixth sense, it’s going to be really challenging to end up with something good. 

In the same vein, metrics provide clear parameters for success. Meet or exceed them and your team is doing well; fall short and you’ll be better equipped to identify pain points and solve them. 

Here are a few additional reasons why setting customer support metrics is key to success.

• Measure success and ROI. By tracking KPIs like resolution time, first response time, and CSAT, you can gauge the health of your customer support program and potentially justify investments in CX initiatives in the future.‍
• Identify customer and team pain points. Metrics help uncover areas where customers or your team is struggling. For example, high resolution times or low CSAT scores signal friction in the experience that you can address. ‍
• Create accountability within your team. When everyone on your team understands what success looks like, it aligns efforts and keeps everyone focused on shared goals.‍
• Prioritize resources. Metrics guide CX leaders on where to allocate resources—for example, leveraging AI and automation to tackle repetitive tickets when ticket volume adds up or resolution times are getting high.‍
• Get proactive. Metrics reveal trends in customer behavior which can help you predict customer needs and make proactive adjustments in your CX strategy. By monitoring customer sentiment and acting on feedback, CX leaders can create more personalized and positive experiences.

Tip : AI and automation can be valuable sidekicks as you look to optimize and improve on metrics. That’s especially true for busy periods: in 2024, 70% of CX leaders relied on AI and automation during peak seasons.

Resolution time should be your main focus for 2025

Customers are done with being patient. One study found that two thirds of respondents valued speed to reply just as much as product price. 

A recent survey we ran found the same thing. 

In our 2024 customer expectations survey, we asked CX leads and agents which metric they used to track success. Here’s what they said:

• Resolution Time (71%)
• First Response Time (59%)
• CSAT (53%)
• Revenue or Sales Impact (41%)
• Ticket Volume (41%)

Resolution time is going to be a key differentiator for your team this year. It should be your primary focus when it comes to optimizing different facets of your customer service strategy. 

Top 5 CX metrics for 2025 & how to improve them with AI 

1) Resolution time 

Resolution time is the average time it takes to resolve a customer request from start to finish.

How do you calculate resolution time?

To calculate resolution time, you’ll take the total resolution time within a set period and divide it by the total number of customer interactions your team tackled within that same time frame.

Average resolution time = Total resolution time in a defined period / Total number of customer interactions resolved in that period

How to use AI & automation to improve it

According to a 2023 study from Statista, 70% of support leaders noted that the customer support metrics that AI had the greatest positive effect on was resolution time.

You can use automation features to send Macros to answer common questions, or leverage AI to interact as an agent via email or chat. The instant nature of these tools means that customers won’t have to wait in a queue for your team to get to them.

For example, Wildride implemented Gorgias AI Agent to manage an influx of 1,000 tickets per week. After AI Agent took over 33% of email inquiries, the team saw a 24% decrease in resolution time. That allowed the team to focus on more complex issues, streamline their support process, and make their customers happier. 

2) First Response Time (FRT)

First response time is the length of time it takes for a customer service team to send the initial reply to a customer inquiry.

How do you calculate first response time? 

To calculate average first response time, take the total amount of time it took for your team to respond to initial customer requests and divide by the total number of tickets within a set time frame. 

How to use AI & automation to improve it

Your team is busy––when they’re not tackling repetitive questions, they’re helping customers with complicated or high-effort requests. All of that work is going to bog down your FRT, especially during more buzzy periods like sales, new releases, or over the holidays. 

By using AI to jump in to handle those more routine requests, you can significantly reduce your FRT and give your team time back to tackle more heavy-lift needs. 

For example, AI Agent helped Glamnetic achieve a 91% improvement in first response time during Black Friday Cyber Monday (BFCM) 2024. They got FRT down from their pre-AI Agent time of eight minutes to 40 seconds. 

Here’s what that looked like in practice: 

3) Customer Satisfaction Score (CSAT) 

CSAT scores show how satisfied customers are with a product, service, or interaction, typically gathered through surveys.

How is CSAT calculated? 

CSAT is calculated via a five-point rating scale survey sent to customers after a support interaction, where one is the worst experience and five is the best. While it can be calculated in different ways, at Gorgias the average of all survey responses is your CSAT score.

How to use AI & automation to improve it

When customers reach out for support, they’re expecting a fast response––regardless if they have an issue or are contemplating their next purchase. 

That’s why using automation or AI tools to provide that lightning quick response, even if it directs shoppers to a self-service resource, can be extremely effective in raising CSAT scores. These responses could be sent by an AI agent that responds like a human agent would or an automated Macro built to fire off pre-crafted templates to common questions. 

In luxury golf brand VESSEL’s case, customers felt that the AI responses were helpful and seemed on-par with the level of support they’d expect from a human agent. 

“Our customers expect almost immediate responses, and so being able to automate that, even if it's not necessarily the exact answer that they're looking for, but being able to send over information to give them the reassurance that we're looking into it or trying to find an answer, whatever it may be, that's been a huge help to our team,” says Lauren Reams, the Customer Experience Manager at VESSEL. 

4) Revenue or sales impact 

The direct or indirect effect of customer service or business activities on generating sales or revenue.

How do you calculate it?

There are different ways to calculate revenue generated and the sales impact of customer support, and quantifying the indirect impact can be difficult. But generally, the formula looks like this: 

ROI = [ (Money earned - Money spent) / Money spent ] x 100

Resource: How to measure & improve customer service ROI

How to use AI & automation to improve it

Leveraging AI and automation can provide significant cost savings because it acts as an additional agent who can tackle repetitive questions, translating to money saved on the time it would take for human agents to manually answer those questions. 

The results are tangible: by automating 48% of inquiries, Dr. Bronner's saved $5,248 in the first month, and $100K in the first year. 

Jonas Paul Eyewear saw revenue influenced by AI Agent as well: the team tracked $600 of sales revenue directly to the tool after it effectively answered pre-sales support questions from shoppers. 

5) Ticket volume 

Ticket volume is the total number of customer service inquiries that a team receives over a specific period of time.

How do you calculate it?

The customer support tool you use will be able to calculate ticket volume for you, as it’s the total number of tickets that have come in within a set amount of time. If you don’t use a CX platform yet and are still using something like Gmail or Excel, you’ll perform this count manually.

How to use AI & automation to improve it

Set rules to trigger automated responses to common questions, or ask an AI agent to completely take them off your team’s plate. 

Arcade Belts, for example, saw a 50% reduction in ticket volume by using Gorgias AI Agent. 

How to get buy in to improve your CX program

Tracking CX metrics is valuable for more than just gauging your program's effectiveness. The more you improve upon your CX metrics, the more you can leverage them to prove your support function’s value within your company.  

1. Tie CX to revenue. Show how improvements in customer satisfaction or repeat purchase rates directly impact revenue growth. 
2. Show industry benchmarks. Compare your team’s stats to competitors or industry averages to demonstrate how well your support strategy is working.  
3. Demonstrate your team’s impact on sales and retention. Use the metrics you’ve collected to show support’s impact on converting customers asking pre-sales questions and getting repeat customers. 
4. Ask to expand your team’s budget. Pitch acquiring additional buy in and resources by presenting revenue generated, costs saved through tools like AI and automation, and happy customers created. 

How to use metrics to evaluate AI performanceIf you want to transform customer experience for the long term, the AI tools you use should never be “set it and forget it” solutions. Just as you do with your human agents, you can use metrics to evaluate your AI agent to make sure it’s performing well. If you use Gorgias, you’ll find these metrics under the AI Agent dashboard. 

To review AI Agent’s performance: 

‍It’s also easy to retrain your AI's performance by adjusting settings like Guidance, refining the internal documents it draws from, setting up brand voice, or creating a Handover topic list to escalate certain types of tickets to human agents.

Start tracking top CX metrics 

Whether you’re new to being a CX leader or you’re a seasoned pro, tracking and improving on your CX metrics will help your team stand out among the rest. A key way to improve them is to leverage AI and Automation tools, and Gorgias is here to help you do it.

‍Get started with AI Agent →

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TL;DR:

• AI Agent on Chat automates up to 50% of chat conversations. It ensures customers get fast, context-aware answers, product recommendations, and seamless handovers to human agents when needed.
• AI Agent goes beyond automated features like Flows and article recommendations. On top of basic automation features, AI Agent can handle complex inquiries like modifying orders and providing personalized product recommendations.
• Setting up AI Agent on Chat is quick. Brands can activate AI Agent with a few clicks, improving efficiency during peak seasons and reducing the need for follow-ups.‍
• Updating AI Agent’s knowledge and behavior ensures the best customer experience. Businesses should refine their Help Center, set Guidance instructions, personalize AI Agent’s tone, and test responses before going live.

It’s clear that shoppers want answers fast—chat accounts for 20% of all customer support tickets.

The appeal is obvious: Chat is an easy-to-access customer service channel for quick questions and a convenient and subtle way to cross-sell complementary products.

But without the right chat tool, brands risk losing these valuable opportunities.

Introducing AI Agent on Chat, a conversational AI assistant that can automate up to 50% of chat conversations. This new feature upgrades chat by combining agent knowledge with superhuman efficiency and response times.

Now, customers can guarantee personalized interactions at any point of the shopping journey—whether they’re looking for a quick answer or a tailored recommendation.

With AI powering every interaction, one-to-one conversations become a seamless part of every customer experience.

Why Chat is better with AI Agent

Before AI Agent, customers reaching out through chat outside business hours had two options: following pre-set Flows (automated FAQ conversations) or browsing through suggested Help Center articles. 

These features are great for quick answers to basic questions, but AI Agent takes support to the next level by handling more complex needs like modifying orders or offering personalized product recommendations.

With AI Agent in Chat, customers enjoy dynamic, real-time conversations available on multiple channels. AI Agent generates personalized responses that match exactly what customers ask for, automating 50% of chat interactions so agents get time back to upsell, create stronger relationships, and craft better experiences.

Related: How to optimize your Help Center for AI Agent

The key features of AI Agent on Chat 

Upgrade your chat support from a basic Q&A tool into an intelligent assistant that handles customer inquiries 24/7. Here's how AI Agent makes that possible:

Real-time conversations

AI Agent responds within 15 seconds or less, offering fast responses that result in frictionless conversations. Unlike traditional chatbots, AI Agent also adapts to your brand’s unique tone of voice to enhance the customer experience and assure shoppers their questions will be taken care of. 

24/7 availability

Today’s shoppers expect instant responses regardless of time zone or business hours. AI Agent on Chat means customers get the help they need, when they need it. This availability leads to higher customer satisfaction and fewer abandoned carts.

Instant product recommendations

AI Agent understands context and customer intent. Whether a shopper needs help finding the right product size or changes their mind and wants to compare features, AI Agent customizes its recommendations for each person.

Intelligent handovers

Some conversations, like technical issues or complaints, need a human touch. AI Agent recognizes these situations and smoothly transfers them to the right agent. 

Using Handover topics, you can choose which types of inquiries should go straight to human agents. Then, if AI Agent lacks the confidence to provide an answer or can’t locate relevant knowledge in its database, it automatically escalates the conversation.

Read more: Handover rules

Why enable AI Agent in Chat now?

Based on Hiver’s 2024 study, 62% of customers prefer live chat to other support channels. With AI Agent in Chat, agents can cut down average response times while customers get the answers they need in one conversation with zero wait times or follow-ups.

Easy setup

AI Agent on Chat is ready to use in a few clicks. Simply connect your Shopify store and Chat widget to AI Agent, and you’re ready to resolve questions asked by visitors and loyal customers faster than you ever have.

Capture the growing demand for live support

Chat is often a customer’s first touchpoint with your brand, whether they’ve just discovered your brand or are on their third order. Meet customer expectations by being available with AI Agent on Chat. The faster you can ease their concerns, the faster they can head to checkout.

Maximize team efficiency

AI Agent makes scaling support effortless, especially during peak seasons like Black Friday. While it handles repetitive support tickets like order status and shipping questions, your team can focus on high-priority tasks like requests from VIP customers.

Eliminate the need for follow-ups

Drawing from knowledge sources like your Help Center and policy pages means AI Agent can often resolve inquiries within one conversation. No more unnecessary back-and-forths. Quick resolutions = happier and more loyal customers.

How to activate AI Agent on Chat

Ready to get started? Here’s how to activate AI Agent on Chat:

1. Click Automate in the top left menu.
2. Select your store from the sidebar, then click on AI Agent.
3. In the Settings tab, under Chat Settings, select one or more Chat from the dropdown menu.
4. Toggle Enable AI Agent on Chat on.
5. Select Save Changes at the bottom of the page.

Already use AI Agent for email? No need to set up Guidance and Handover topics all over again—AI Agent will behave the same way in Chat.

Best practices for setting up AI Agent on Chat

Get the most out of AI Agent on Chat by following these best practices. 

1. Prepare and optimize your knowledge base

The Help Center is AI Agent’s brain. This customer knowledge database is the key to AI Agent’s accurate and on-brand responses. To ensure your AI Agent is as trained as your human agents, include important topics in your Help Center like shipping, returns, cancellations, and account management.

No articles yet? No problem! Gorgias has 20+ article templates for you to use and modify. Or, even better, check out the AI Library for AI-generated articles based on your customer tickets.

2. Set restrictions with Guidance

AI tools perform best when you set limitations. A Guidance is the main way to control AI Agent’s behavior. It is a set of written instructions that outline how AI Agent should interact with customers, handle certain requests, and more.

We recommend publishing a Guidance on the top five questions you receive from customers.

Tip: AI Agent prioritizes Guidance above Help Center articles. Unlike Help Center articles, the content in your Guidance will not be customer-facing.

3. Personalize AI Agent's voice

The beauty of AI Agent is its ability to speak like one of your agents. Select from Friendly, Professional, or Sophisticated presets—or create a custom tone that aligns with your brand.

Need help finding your brand voice? Here are seven brand voice examples.

4. Test AI Agent’s responses before going live

Use test scenarios to see how AI Agent responds to common customer questions, such as order status, shipping questions, and return policies. To cover all your bases, test AI Agent as both a new and returning customer to make sure it delivers accurate responses no matter the customer's need.

5. Improve AI Agent’s behavior

AI Agent becomes smarter as it learns from you. Like a human agent, give your AI Agent feedback on its responses, from how it speaks, which topics it escalates, and what actions it takes in certain scenarios. 

There are multiple ways to give AI Agent feedback on a ticket:

• Mark AI Agent’s message or any of the resources it used as correct or incorrect.
• Suggest that AI Agent use a different resource if a better or more correct piece of knowledge exists.
• Report an issue to the Gorgias Product team.

Try AI Agent Actions on Chat

AI Agent can also perform actions like accessing Shopify order details and executing third-party app actions, such as updating shipping addresses and order cancellations, directly in Chat.

Excited to deliver an elevated chat experience? Book a demo now to experience the power of AI Agent on Chat.

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TL;DR:

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.

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1. View Shopify data in tickets

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. 

2. Perform Shopify Actions

What it does: Agents can update Shopify order and customer data with Shopify Actions right in Gorgias.

Key features:

• Create a new order: Add existing products or custom items, apply discounts, modify quantities, add notes and tags, and choose to charge taxes. Then set the order as Paid or Pending and email the invoice to the customer.
• Duplicate an order: Replicate an existing order and make adjustments as needed.
• Cancel/refund an order: Cancel or refund orders by setting quantities to refund, specifying shipping amounts to refund, providing reasons for cancellation, restocking items, and notifying the customer.
• Edit shipping address: Update the shipping address for an order.
• Insert product links: Add product links or product cards from tickets so customers can add the product to their cart quickly.
• Display the customer’s cart: View the exact items the customer has in their cart at the moment they reach out via Chat.

Use case: Agents can perform Shopify actions directly from Gorgias, such as adding products, applying discounts, updating quantities, or issuing refunds.

3. Embed customer-specific Shopify data in Macros

What it does: Create templated responses called Macros with dynamic Shopify variables to automatically incorporate customer-specific information. 

Key features:

• Dynamic variables: Macros can include variables that pull real-time data from Shopify, such as order status, tracking numbers, and customer details.
• Automated actions: Beyond inserting dynamic content, Macros can perform actions like tagging tickets, setting statuses, or assigning conversations to specific agents. The automation streamlines workflows and ensures consistent handling of similar inquiries.

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 can quickly generate personalized responses that includes 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. 

4. Provide product information with Macros

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:

• Dynamic Shopify variables in Macros: Agents can use dynamic variables to pull real-time product information.
• Pre-built responses for common questions: Macros can include templated responses tailored for pre-sale inquiries, such as providing direct links to products or applying discount codes.

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 [customer name Macro],
Great news! The product [Shopify product information Macro] 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:

• Eliminates manual search and typing for agents.
• Ensures accurate, real-time product information for customers.
• Improves the likelihood of converting inquiries into sales.

5. Enable self-serve order management in Chat 

What it does: Using Gorgias Chat, customers can track orders or manage their purchases on their own with no agent assistance needed.

Key feature:

• Order management automation: Customers can access real-time order information, including status updates and tracking details, through the chat interface. This automation reduces the volume of live chat inquiries by up to 30%.

Use case: A customer wants to check the status of their recent purchase. By accessing Chat 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:

• Automates routine inquiries and frees up your support team to handle more complex issues.
• Enhances customer satisfaction thanks to immediate responses.
• Reduces the need for multiple communication channels, consolidating support interactions in one place.

6. Use Shopify variables in Rules


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:

• Automated tagging: Rules can automatically tag tickets based on specific Shopify data. For instance, you can set up a Rule to tag tickets from customers with high order counts or significant total spending as "VIP."
• Prioritization of tickets: Rules can prioritize tickets that meet certain criteria, such as high-value orders or repeat customers.

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:

• Improves customer experience by prioritizing high-value customers.
• Maintains consistent service quality.

7. Track revenue with reporting

What it does: Gorgias offers comprehensive reporting that allows you to measure how your support interactions influence sales.

Key features:

• Tickets converted: Tracks the number of support tickets that led to a sale within five days of the ticket's creation.
• Conversion rate: Calculates the percentage of created tickets that resulted in sales, helping you assess the effectiveness of your support team's interactions.
• Total sales from support: Sums the revenue generated from orders associated with converted tickets, accounting for refunds and order adjustments to provide accurate figures.

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:

• Quantifies the revenue generated from support interactions.
• Faster team optimization with data-driven insights.
• Understanding the correlation between support interactions and sales can help refine customer service strategies.

8. AI Agent integration

What it does: AI Agent automates Shopify actions like canceling orders, editing order details, and reshipping items.

Key features:

• Cancel Shopify order: AI Agent can automatically cancel unfulfilled orders upon customer request, restocking the items and issuing a full refund. A confirmation email is sent to the customer once the cancellation is complete.
• Edit order shipping address: When a customer needs to update their shipping address, AI Agent verifies if the order is unfulfilled, confirms the new address with the customer, and updates it in Shopify accordingly.
• Replace order item: AI Agent facilitates item replacements in orders by confirming the item to be removed and the new item to be added, checking stock availability, adjusting payments if necessary, and sending an updated order confirmation to the customer.
• Reship order for free: In cases where an order is lost in transit or arrives damaged, AI Agent can duplicate and resend the order at no additional charge.
• Remove order item: If a customer decides to remove an item from their order, AI Agent can handle the removal, restock the item in Shopify, process the refund for the removed item, and notify the customer of the updated order details.

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:

• Automating routine order management tasks reduces the workload on human agents.
• Quick and accurate responses to order modification requests lead to a better customer experience.
• Automated processes ensure consistency and accuracy in handling order changes, reducing the likelihood of human error.

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TL;DR:

• Full-screen pop-ups disrupt the shopping experience. They frustrate visitors by interrupting their browsing and increase bounce rates, driving 72% of customers away.
• Gorgias Convert offers a non-intrusive alternative. With a chat-based widget, it engages customers naturally without interrupting their journey.
• Convert tailors messages to shopper behavior. Personalized campaigns detect browsing habits, cart details, and exit intent to deliver relevant offers at the right moment.
• Shopify brands see measurable results with Convert. Users report conversion boosts of 6-10%, improved customer satisfaction, and revenue growth, proving its effectiveness over traditional pop-ups.

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.

What’s wrong with full-screen pop-ups?

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.

Disruptive experience 

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.

High bounce rates

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.

Lack of personalization

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.

Can be blocked

Many users employ ad blockers that filter out pop-ups altogether, meaning your message never even reaches a portion of your audience.

Why Gorgias Convert is the better alternative: 7 benefits

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:

1. Non-intrusive 

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.

2. Caters to user behavior

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.

3. Customizable messaging

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.

4. Encourages conversations

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

5. Mobile-friendly

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.

6. Integrated with Shopify and Gorgias

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.

7. A/B testing made easy

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

Rave reviews from real Shopify brands

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.”

Goodbye full-screen pop-ups, hello Gorgias Convert

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.

Questions in Chat, resolved in seconds

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.

Let your AI Agent take action

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 built into every support ticket

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:

• Scale quality consistently and easily. Both human and AI agents follow the same quality standards, allowing for consistent, high-quality customer experiences.
• Coach smarter. Use real-time QA ratings in tickets to give agents targeted feedback.
• Track team performance. The dashboard highlights metrics by agent, showing what’s working and where to improve.

Gain clarity on your AI Agent’s impact

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:

• The percentage of tickets automated by AI Agent
• The number of tickets closed by AI Agent
• Success rates for one-touch resolutions
• How satisfied customers are with AI Agent’s responses

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.

Meet your new AI sales assistant

Soon, we’ll be expanding AI Agent's skills with the launch of Shopping Assistant, a tool designed to assist customers on their shopping journey.

Shopping Assistanthelps 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.

Looking ahead with conversational AI

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.

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TL;DR:

• Ticket Fields make it easy to organize ticket data. They let agents collect the right information by filling out specific fields before closing a ticket.
• Conditional Ticket Fields are smart fields that adapt based on the ticket type. These fields show up only when they’re needed, helping agents capture just the right details.
• Use Ticket Fields to spot trends and improve your CX. Track things like return reasons, product feedback, or refund patterns to make smarter decisions and keep customers happy.
• Get your team up to speed with quick, practical tools. Share a best practices deck, give them a handy cheat sheet, and run a quick demo to make Ticket Fields easy to understand and use.

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.

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What are Ticket Fields?

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:

• Return Reason (Dropdown): Track why customers are returning items, such as incorrect sizing, damaged goods, or dissatisfaction. This can help you spot product deficiencies or fulfillment errors.
• Product Feedback (Text): Collect feedback about products directly from customers. Share this data with your product team and make it easier for them to make improvements that customers ask for.
• Refund Amount (Number): Use this to identify trends, like high refund rates for a specific product, and modify your refund policies to minimize losses.
• First-Time Buyer (Yes/No): Flag whether a customer is making their first purchase. Use this to address pain points among new customers.

Why Ticket Fields are more powerful than Tags

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:

Mandatory fields for comprehensiveness

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.

Conditional fields for a streamlined experience and in-depth data

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.

Ease of migration

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:

• Sort tickets in different Views. Tags are helpful for organizing your tickets into different views to aid your workflow. For example, you can focus on all urgent tickets by creating a view that only displays tickets tagged as “Urgent.” 
• Used as temporary categories for exceptions. Tags can be used to add extra detail to an existing category. For instance, if you have a field named “Subscription Type” with “Premium Plan” selected as value in the ticket, you can add a “Gift Subscription” Tag temporarily. 

12 Ticket Fields every CX team should consider for better reporting

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.

1. Contact reason

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:

• Status inquiry
• Discount
• Refund
• Product question
• Feedback

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.

2. Resolution

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:

• Sent more information
• Replacement sent
• Discount given
• Refund
• Sent tracking order information
• No action taken

3. Feedback

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.

4. Product

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.

5. Defect

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:

6. Cancellation reason

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:

• Too expensive
• Bad product-customer fit
• Don’t need it
• Moving to a competitor
• Poor customer service

7. Shipping carrier

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.

8. Purchase origin

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.

9. Customer escalation

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.

10. Discount percentage

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.

11. First-time buyer

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.

12. Months in use

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.

Who benefits from Ticket Fields?

Ticket Fields provide value across the entire CX ecosystem, from agents to decision-makers.

• Support teams: Gain a deeper understanding of shopper behavior and where issues arise from.
• Operations teams: Identify and resolve operational inefficiencies in your support, fulfillment, and feedback workflows.
• Data and tech teams: Analyze Ticket Fields reports from the support team that provide detailed customer service and product data that can inform other departments like product.
• Executives: Get visibility into CX operations, including shipping, damaged items, cancellations, and team performance, to make data-backed decisions.

How to make Ticket Fields a core part of your support process

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.

1. Define your data and reporting goals

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.

2. Set up Ticket Fields

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

3. Train and onboard your team

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.

4. Implement changes based on insights

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:

• Update FAQs in your Chat Flows
• Edit automated responses
• Retrain your AI agent with new information
• Add relevant answers to your Help Center
• Optimize product pages with more details like usage instructions, ingredients, or sizing charts
• Modify product categorization on your website
• Adjust internal workflows
• Renegotiate contracts with underperforming shipping carriers
• Redesign or reformulate products

5. Review Ticket Field data in monthly meetings

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:

• What trends do the reports reveal?
• Are agents consistently filling out each field?
• Which fields are consistently filled out and provide actionable insights?
• Have our priorities changed, making some fields less useful?

Lastly, remember to document the insights and update your team regularly to keep everyone aligned.

Drive smarter decisions with Ticket Fields

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.

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