Search our articles
Search

Featured articles

How to Pitch Gorgias Shopping Assistant to Leadership

Want to show leadership how AI can boost revenue and cut support costs? Learn how to pitch Gorgias Shopping Assistant with data that makes the case.
By Alexa Hertel
0 min read . By Alexa Hertel

TL;DR:

  • Position Shopping Assistant as a revenue-driving tool. It boosts AOV, GMV, and chat conversion rates, with some brands seeing up to 97% higher AOV and 13x ROI.
  • Highlight its role as a proactive sales agent, not just a support bot. It recommends products, applies discounts, and guides shoppers to checkout in real time.
  • Use cross-industry case studies to make your case. Show leadership success stories from brands like Arc’teryx, bareMinerals, and TUSHY to prove impact.
  • Focus on the KPIs it improves. Track AOV, GMV, chat conversion, CSAT, and resolution rate to demonstrate clear ROI.

Rising customer expectations, shoppers willing to pay a premium for convenience, and a growing lack of trust in social media channels to make purchase decisions are making it more challenging to turn a profit.  

In this emerging era, AI’s role is becoming not only more pronounced, but a necessity for brands who want to stay ahead. Tools like Gorgias Shopping Assistant can help drive measurable revenue while reducing support costs. 

For example, a brand that specializes in premium outdoor apparel implemented Shopping Assistant and saw a 2.25% uplift in GMV and 29% uplift in average order volume (AOV).

But how, among competing priorities and expenses, do you convince leadership to implement it? We’ll show you.

Why conversational AI matters for modern ecommerce

1) Meet high consumer expectations

Shoppers want on-demand help in real time that’s personalized across devices. 

Shopping Assistant recalls a shopper’s browsing history, like what they have clicked, viewed, and added to their cart. This allows it to make more relevant suggestions that feel personal to each customer. 

2) Keep up with market momentum

The AI ecommerce tools market was valued at $7.25 billion in 2024 and is expected to reach $21.55 billion by 2030

Your competitors are using conversational AI to support, sell, and retain. Shopping Assistant satisfies that need, providing upsells and recommendations rooted in real shopper behavior. 

3) Raise AOV and GMV

Conversational AI has real revenue implications, impacting customer retention, average order value (AOV), conversion rates, and gross market value (GMV). 

For example, a leading nutrition brand saw a GMV uplift of over 1%, an increase in AOV of over 16%, and a chat conversion rate of over 15% after implementing Shopping Assistant.

Overall, Shopping Assistant drives higher engagement and more revenue per visitor, sometimes surpassing 50% and 20%, respectively.

AI Agent chat offering 8% discount on Haabitual Shimmer Layer with adjustable strategy slider.
Shopping Assistant can send discounts based on shopper behavior in real time.

How to show the business impact & ROI of Shopping Assistant

1) Pitch its core capabilities

Shopping Assistant engages, personalizes, recommends, and converts. It provides proactive recommendations, smart upsells, dynamic discounts, and is highly personalized, all helping to guide shoppers to checkout

Success spotlight

After implementing Shopping Assistant, leading ecommerce brands saw real results:

Industry

Primary Use Case

GMV Uplift (%)

AOV Uplift (%)

Chat CVR (%)

Home & interior decor 🖼️

Help shoppers coordinate furniture with existing pieces and color schemes.

+1.17

+97.15

10.30

Outdoor apparel 🎿

In-depth explanations of technical features and confidence when purchasing premium, performance-driven products.

+2.25

+29.41

6.88

Nutrition 🍎

Personalized guidance on supplement selection based on age, goals, and optimal timing.

+1.09

+16.40

15.15

Health & wellness 💊

Comparing similar products and understanding functional differences to choose the best option.

+1.08

+11.27

8.55

Home furnishings 🛋️

Help choose furniture sizes and styles appropriate for children and safety needs.

+12.26

+10.19

1.12

Stuffed toys 🧸

Clear care instructions and support finding replacements after accidental product damage.

+4.43

+9.87

3.62

Face & body care 💆‍♀️

Assistance finding the correct shade online, especially when previously purchased products are no longer available.

+6.55

+1.02

5.29

2) Position it as a revenue driver

Shopping Assistant drives uplift in chat conversion rate and makes successful upsell recommendations.  

Success spotlight

“It’s been awesome to see Shopping Assistant guide customers through our technical product range without any human input. It’s a much smoother journey for the shopper,” says Nathan Larner, Customer Experience Advisor for Arc’teryx. 

For Arc’teryx, that smoother customer journey translated into sales. The brand saw a 75% increase in conversion rate (from 4% to 7%) and 3.7% of overall revenue influenced by Shopping Assistant. 

Arc'teryx Rho Zip Neck Women's product page showing black base layer and live chat box.
Arc’teryx saw a 75% increase in conversion rate after implementing Shopping Assistant. Arc’teryx 

3) Show its efficiency and cost savings

Because it follows shoppers’ live journey during each session on your website, Shopping Assistant catches shoppers in the moment. It answers questions or concerns that might normally halt a purchase, gets strategic with discounting (based on rules you set), and upsells. 

The overall ROI can be significant. For example, bareMinerals saw an 8.83x return on investment.  

Success spotlight

"The real-time Shopify integration was essential as we needed to ensure that product recommendations were relevant and displayed accurate inventory,” says Katia Komar, Sr. Manager of Ecommerce and Customer Service Operations, UK at bareMinerals. 

“Avoiding customer frustration from out-of-stock recommendations was non-negotiable, especially in beauty, where shade availability is crucial to customer trust and satisfaction. This approach has led to increased CSAT on AI converted tickets."

AI Agent chat recommending foundation shades and closing ticket with 5-star review.

4) Present the metrics it can impact

Shopping Assistant can impact CSAT scores, response times, resolution rates, AOV, and GMV.  

Success spotlight

For Caitlyn Minimalist, those metrics were an 11.3% uplift in AOV, an 18% click through rate for product recommendations, and a 50% sales lift versus human-only chats. 

"Shopping Assistant has become an intuitive extension of our team, offering product guidance that feels personal and intentional,” says Anthony Ponce, its Head of Customer Experience.

 

AI Agent chat assisting customer about 18K gold earrings, allergies, and shipping details.
Caitlyn Minimalist leverages Shopping Assistant to help guide customers to purchase. Caitlyn Minimalist 

5) Highlight its helpfulness as a sales agent 

Support agents have limited time to assist customers as it is, so taking advantage of sales opportunities can be difficult. Shopping Assistant takes over that role, removing obstacles for purchase or clearing up the right choice among a stacked product catalog.

Success spotlight

With a product that’s not yet mainstream in the US, TUSHY leverages Shopping Assistant for product education and clarification. 

"Shopping Assistant has been a game-changer for our team, especially with the launch of our latest bidet models,” says Ren Fuller-Wasserman, Sr. Director of Customer Experience at TUSHY. 

“Expanding our product catalog has given customers more choices than ever, which can overwhelm first-time buyers. Now, they’re increasingly looking to us for guidance on finding the right fit for their home and personal hygiene needs.”

The bidet brand saw 13x return on investment after implementation, a 15% increase in chat conversion rate, and a 2x higher conversion rate for AI conversations versus human ones. 

AI Agent chat helping customer check toilet compatibility and measurements for TUSHY bidet.
AI Agent chat helping customer check toilet compatibility and measurements for TUSHY bidet.

6) Provide the KPIs you’ll track 

Customer support metrics include: 

  • Resolution rate 
  • CSAT score 

Revenue metrics to track include: 

  • Average order value (AOV) 
  • Gross market value (GMV) 
  • Chat conversion rate 

Shopping Assistant: AI that understands your brand 

Shopping Assistant connects to your ecommerce platform (like Shopify), and streamlines information between your helpdesk and order data. It’s also trained on your catalog and support history. 

Allow your agents to focus on support and sell more by tackling questions that are getting in the way of sales. 

{{lead-magnet-2}}

min read.
Shopping Assistant Use Cases

11 Real Ways Ecommerce Brands Use Gorgias Shopping Assistant to Drive Sales

Here are 11 ways to use Gorgias Shopping Assistant to make the shopping experience more valuable.
By Holly Stanley
0 min read . By Holly Stanley

TL;DR:

  • Shoppers often hesitate around sizing, shade matching, styling, and product comparisons, and those moments are key revenue opportunities for CX teams.
  • Guided shopping removes that friction by giving shoppers quick, personalized recommendations that build confidence in their choices.
  • Across 11 brands, guided shopping led to measurable lifts in AOV, conversion rate, and overall revenue.
  • Your biggest upsell opportunities likely sit in the same places your shoppers pause, so start by automating your most common pre-purchase questions.

Most shoppers arrive with questions. Is this the right size? Will this match my skin tone? What’s the difference between these models? The faster you can guide them, the faster they decide.

As CX teams take on a bigger role in driving revenue, these moments of hesitation are now some of the most important parts of the buying journey.

That’s why more brands are leaning on conversational AI to support these high-intent questions and remove the friction that slows shoppers down. The impact speaks for itself. Brands can expect higher AOV, stronger chat conversion rates, and smoother paths to purchase, all without adding extra work to your team.

Below, we’re sharing real use cases from 11 ecommerce brands across beauty, apparel, home, body care, and more, along with the exact results they saw after introducing guided shopping experiences.

1. Recommend similar shoes when an old classic disappears

When you’re shopping for shoes similar to an old but discontinued favorite, every detail counts, down to the color of the bottom of the shoe. But legacy brands with large catalogs can be overwhelming to browse.

For shoppers, it’s a double-edged sword: they want to feel confident that they checked your entire collection, but they also don’t want to spend time looking for it.

How Shopping Assistant helps:

Shopping Assistant accelerates the process, turning hazy details into clear, friendly guidance.

It describes shoe details, from colorways to logo placement, compares products side by side, and recommends the best option based on the shopper’s preferences and conditions.

The result is shoppers who feel satisfied and more connected with your brand.

Results:

  • AOV uplift: +6.5%

2. Suggest complete outfits for special occasions

Big events call for great outfits, but putting one together online isn’t always easy. With thousands of options to scroll through, shoppers often want a bit of styling direction.

How Shopping Assistant helps:

Shoppers get to chat with a virtual stylist who recommends full outfits based on the occasion, suggests accessories to complete the look, and removes the guesswork of pairing pieces together. 

The result is a fun, confidence-building shopping experience that feels like getting advice from a stylist who actually understands their plans.

Results:

  • Chat CVR: 13.02%

3. Match shoppers to the right makeup shade when the formula changes

Shade matching is hard enough in-store, but doing it online can feel impossible. Plus, when a longtime favorite gets discontinued, shoppers are left guessing which new shade will come closest. That uncertainty often leads to hesitation, abandoned carts, or ordering multiple shades “just in case.”

How Shopping Assistant helps:

Shoppers find their perfect match without any of the guesswork. The assistant asks a few quick questions, recommends the closest shade or formula, and offers smart alternatives when a product is unavailable.

The experience feels like chatting with a knowledgeable beauty advisor — someone who makes the decision easy and leaves shoppers feeling confident in what they’re buying.

Katia Komar, Sr. Manager of Ecommerce and Customer Service Operations at bareMinerals UK says, “What impressed me the most is the AI’s ability to upsell with a conversational tone that feels genuinely helpful and doesn't sound too pushy or transactional. It sounds remarkably human, identifying correct follow-up questions to determine the correct product recommendation, resulting in improved AOV. It’s exactly how I train our human agents and BPO partners.”

Gorgias AI Agent recommends a powder that pairs well with the foundation a customer wears.
Gorgias Shopping Assistant recommends a powder that pairs well with the foundation a customer currently wears.

Results:

  • GMV uplift: +6.55%

4. Help find the perfect gift when shoppers don’t know what to buy

When shoppers are buying gifts, especially for someone else, they often know who they’re shopping for but not what to buy. A vague product name or a half-remembered scent can quickly make the experience feel overwhelming without someone to guide them.

How Shopping Assistant helps:

Thoughtful guidance goes a long way. By asking clarifying questions and recognizing likely mix-ups, Shopping Assistant helps shoppers figure out what the recipient was probably referring to, then recommends the right product along with complementary gift options that make the choice feel intentional.

It brings the reassurance of an in-store associate to the online experience, helping shoppers move forward with confidence.

Results:

  • Chat CVR: 8.39%

5. Remove the guesswork from bra sizing online

Finding the right bra size online is notoriously tricky. Shoppers often second-guess their band or cup size, and even small uncertainties can lead to returns — or abandoning the purchase altogether.

Many customers just want someone to walk them through what a proper fit should actually feel like.

How Shopping Assistant helps:

Searching for products is no longer a time-consuming process. Shopping Assistant detects a shopper’s search terms and sends relevant products in chat. Like an in-store associate, it uses context to deliver what shoppers are looking for, so they can skip the search and head right to checkout.

Results:

  • GMV uplift: +6.22%
  • Chat CVR: 16.78%

6. Guide shoppers through jewelry personalization step by step

For shoppers buying personalized jewelry, the details directly affect the final result. That’s why customization questions come up constantly, and why uncertainty can quickly stall the path to purchase.

How Shopping Assistant helps:

Shopping Assistant asks about the shopper’s style preferences and customization needs, then recommends the right product and options so they can feel confident the final piece is exactly their style. The experience feels quick, helpful, and designed to guide shoppers toward a high investment purchase.

Results:

  • GMV uplift: +22.59%

7. Recommend furniture that works well together

Decorating a home is personal, and shoppers often want reassurance that a new piece will blend with what they already own. Questions about color palettes, textures, and proportions come up constantly. And without guidance, it’s easy for shoppers to feel unsure about hitting “add to cart.”

How Shopping Assistant helps:

Giving shoppers personalized styling support helps them visualize how pieces will work in their home. 

Shoppers receive styling suggestions based on their existing space as well as recommendations on pieces that complement their color palette. 

It even guides them toward a 60-minute virtual styling consultation when they need deeper help. The experience feels thoughtful and high-touch, which is why shoppers often spend more once they feel confident in their choices.

Results:

  • AOV uplift: +97.15%
  • Chat CVR: 10.3%

8. Reassure shoppers about flavor before purchase

When shoppers discover a new drink mix, they’re bound to have questions before committing. How strong will it taste? How much should they use? Will it work with their preferred drink or routine? Uncertainty at this stage can stall the purchase or lead to disappointment later.

How Shopping Assistant helps:

Clear, friendly guidance in chat helps shoppers understand exactly how to use the product. Shopping Assistant answers questions about serving size, flavor strength, and pairing options, and suggests the best way to prepare the mix based on the shopper’s preferences.

Results:

  • Chat CVR: 12.75%

9. Match supplements to age, lifestyle, and health goals

Shopping for health supplements can feel confusing fast. Customers often have questions about which formulas fit their age, health goals, or daily routine. Without clear guidance, most will hesitate or pick the wrong product.

How Shopping Assistant helps:

Shopping Assistant detects hesitation when shoppers linger on a search results page. It proactively asks a few clarifying questions, narrows down product options, and points shoppers to the best product or bundle for their needs. 

The entire experience feels supportive and gives shoppers confidence they’ve picked the right option.

Results:

  • AOV uplift: +16.4%
  • Chat CVR: 15.15%

10. Align products with safety needs in kids’ rooms

Shopping for kids’ furniture comes with a lot of “Is this the right one?” moments. Parents want something safe, sturdy, and sized correctly for their child’s age. With so many options, it’s easy to feel unsure about what will actually work in their space.

How Shopping Assistant helps:

Shopping Assistant guides parents toward the best fit right away. It asks about their child’s age, room layout, and safety considerations, then recommends the most appropriate bed or furniture setup. The experience feels like chatting with a knowledgeable salesperson who understands what families actually need as kids grow.

Results:

  • GMV uplift: +12.26%
  • AOV uplift: +10.19%

11. Clarify technical specs that create hesitation

Even something as simple as choosing a toothbrush can feel complicated when multiple models come with different speeds, materials, and features. Shoppers want to understand what matters so they can pick the one that fits their routine and budget.

How Shopping Assistant helps:

Choosing between toothbrush models shouldn’t feel like decoding tech specs. When shoppers can see the key differences in plain language, including what’s unique, how each model works, and who it’s best for, they can make a decision with ease. 

Suddenly, the whole process feels simple instead of overwhelming.

Results:

  • AOV uplift: +11.27%
  • Chat CVR: 8.55%

What these results tell us

Across all 11 brands, one theme is clear. When shoppers get the guidance they need at the right moment, they convert more confidently and often spend more.

Here’s what stands out:

  • AOV jumps when products are technical or high in consideration. Home decor, supplements, and outdoor gear see the biggest lifts because shoppers feel more confident committing to higher-priced items once the details are explained.
  • CVR surges in categories with complex decisions. Lingerie, apparel, and personal styling all showed strong conversion rates because shoppers finally get clarity on fit, shade, or style.
  • GMV rises when AI removes friction from the buying journey. Furniture and beauty saw meaningful gains thanks to personalized recommendations that reduce uncertainty and push shoppers toward the right product faster.
  • The use cases reveal clear upsell opportunities. If your team sees recurring questions about sizing, shade matching, product differences, or how items work together, that’s a strong signal that guided selling can drive more revenue.

What this means for you:

Look closely at your most common pre-purchase questions. Anywhere shoppers hesitate from fit, shade, technical specs, styling, bundles is a place where Shopping Assistant can step in, boost confidence, and unlock more sales.

Want Shopping Assistant results like these?

If you notice the same patterns in your own store, such as shoppers hesitating over sizing, shade matching, product comparisons, or technical details, guided shopping can make an immediate impact. These moments are often your biggest opportunities to increase revenue and improve the buying experience.

Many of the brands in this post started by identifying their most common pre-purchase questions and letting AI handle them at scale. You can do the same.

If you want to boost conversions, lift AOV, and create a smoother path to purchase, now is a great time to explore guided shopping for your team.

Book a demo or activate Shopping Assistant to get started.

{{lead-magnet-2}}

min read.
Conversational Commerce Metrics

Your Support Team Drives More Revenue Than You Think: Conversational Commerce Metrics

Your chat might be closing more sales than your checkout page. Here’s how to measure it.
By Tina Donati
0 min read . By Tina Donati

TL;DR:

  • Support chats can now be directly tied to revenue. Brands are measuring conversations by conversion rate, average order value (AOV), and GMV influenced.
  • AI resolution rate is only valuable if the answers are accurate and helpful. A high resolution rate doesn’t matter if it leads to poor recommendations — the best AI both deflects volume and drives confident purchases.
  • Chat conversion rates often outperform traditional channels. Brands like Arc’teryx saw a 75% lift in conversions (from 4% to 7%) when AI handled high-intent product questions.
  • Shoppers who chat often spend more. Conversations lead to higher AOVs by helping customers understand products, explore upgrades, and discover add-ons — not just through upselling, but smarter guidance.

Conversational commerce finally has a scoreboard.

For years, CX leaders knew support conversations mattered, they just couldn’t prove how much. Conversations lived in that gray area of ecommerce where shoppers got answers, agents did their best, and everyone agreed the channel was “important”… 

But tying those interactions back to actual revenue? Nearly impossible.

Fast forward to today, and everything has changed.

Real-time conversations — whether handled by a human agent or powered by AI — now leave a measurable footprint across the entire customer journey. You can see how many conversations directly influenced a purchase. 

In other words, conversational commerce is finally something CX teams can measure, optimize, and scale with confidence.

Why measuring conversational commerce matters now

If you want to prove the value of your CX strategy to your CFO, your marketing team, or your CEO, you need data, not anecdotes.

Leadership isn’t swayed by “We think conversations help shoppers.” They want to see the receipts. They want to know exactly how interactions influence revenue, which conversations drive conversion, and where AI meaningfully reduces workload without sacrificing quality.

That’s why conversational commerce metrics matter now more than ever. This gives CX leaders a way to:

  • Quantify the revenue influence of conversations
  • Understand where AI improves efficiency — and where humans add the most value
  • Make informed decisions on staffing, automation, and channel investment
  • Turn CX into a profit center instead of a cost center

These metrics let you track impact with clarity and confidence.

And once you can measure it, you can build a stronger case for deeper investment in conversational tools and strategy.

The 4 metric categories that define conversational commerce success

So, what exactly should CX teams be measuring?

While conversational commerce touches every part of the customer journey, the most meaningful insights fall into four core categories: 

  1. Automation performance
  2. Conversion & revenue impact
  3. Engagement quality
  4. Discounting behavior

Let’s dive into each.

Automation performance metrics

If you want to understand how well your conversational commerce strategy is working, automation performance is the first place to look. These metrics reveal how effectively AI is resolving shopper needs, reducing ticket volume, and stepping into revenue-driving conversations at scale.

The two most foundational metrics?

1. Resolution rate: Are AI-led conversations actually helpful?

Resolution rate measures how many conversations your AI handles from start to finish without needing a human to take over. On paper, high resolution rates sound like a guaranteed win. It suggests your AI is handling product questions, sizing concerns, shade matching, order guidance, and more — all without adding to your team’s workload.

But a high resolution rate doesn’t automatically mean your AI is performing well.

Yes, the ticket was “resolved,” but was the customer actually helped? Was the answer accurate? Did the shopper leave satisfied or frustrated?

This is where quality assurance becomes essential. Your AI should be resolving tickets accurately and helpfully, not simply checking boxes.

At its best, a strong resolution rate signals that your AI is:

  • Confidently answering product questions
  • Guiding shoppers to the right SKU, variant, shade, size, or style
  • Reducing cart abandonment caused by confusion
  • Helping pre-sale shoppers convert faster

When resolution rate quality goes up, so does revenue influence.

You can see this clearly with beauty brands, where accuracy matters enormously. bareMinerals, for example, used to receive a flood of shade-matching questions. Everything from “Which concealer matches my undertone?” to “This foundation shade was discontinued; what’s the closest match?” 

Before AI, these questions required well-trained agents and often created inconsistencies depending on who answered.

Once they introduced Shopping Assistant, resolution rate suddenly became more meaningful. AI wasn’t just closing tickets; it was giving smarter, more confident recommendations than many agents could deliver at scale, especially after hours. 

BareMinerals' AI Agent recommends a customer a foundation that matches their skin tone

That accuracy paid off. 

AI-influenced purchases at bareMinerals had zero returns in the first 30 days because customers were finally getting the right shade the first time.

That’s the difference between “resolved” and resolved well.

2. Zero-touch tickets: How many tickets never reach a human?

The zero-touch ticket rate measures something slightly different: the percentage of conversations AI manages entirely on its own, without ever being escalated to an agent.

This metric is a direct lens into:

  • Workload reduction
  • Team efficiency
  • Cost savings
  • AI’s ability to own high-volume question types

More importantly, deflection widens the funnel for more revenue-driven conversations.

When AI deflects more inbound questions, your support team can focus on conversations that truly require human expertise, including returns exceptions, escalations, VIP shoppers, and emotionally sensitive interactions.

Brands with strong deflection rates typically see:

  • Shorter wait times
  • Higher CSAT
  • Lower support costs
  • More AI-influenced revenue

Conversion and revenue impact metrics

If automation metrics tell you how well your AI is working, conversion and revenue metrics tell you how well it’s selling.

This category is where conversational commerce really proves its value because it shows the direct financial impact of every human- or AI-led interaction.

1. Chat Conversion Rate (CVR): How often do conversations turn into purchases?

Chat conversion rate measures the percentage of conversations that end in a purchase, and it’s one of the clearest indicators of whether your conversational strategy is influencing shopper decisions.

A strong CVR tells you that conversations are:

  • Building confidence
  • Removing hesitation
  • Guiding shoppers toward the right product

You see this clearly with brands selling technical or performance-driven products. 

Outdoor apparel shoppers, for example, don’t just need “a jacket” — they need to know which jacket will hold up in specific temperatures, conditions, or terrains. A well-trained AI can step into that moment and convert uncertainty into action.

Arc’teryx saw this firsthand. 

Arc'teryx uses Shopping Assistant to enable purchases directly from chat

Once Shopping Assistant started handling their high-intent pre-purchase questions, their chat conversion rate jumped dramatically — from 4% to 7%. A 75% lift. 

That’s what happens when shoppers finally get the expert guidance they’ve been searching for.

2. GMV influenced: The revenue ripple effect of conversations

Not every shopper buys the moment they finish a chat. Some take a few hours. Some need a day or two. Some want to compare specs or read reviews before committing.

GMV influenced captures this “tail effect” by tracking revenue within 1–3 days of a conversation.

It’s especially powerful for:

  • High-consideration purchases (like outdoor gear, home furniture, equipment)
  • Products with many options, specs, or configurations
  • Shoppers who need reassurance before buying

In Arc’teryx’s case, shoppers often take time to confirm they’re choosing the right technical gear.

Yet even with that natural pause in behavior, Shopping Assistant still influenced 3.7% of all revenue, not by forcing instant decisions, but by providing the clarity people needed to make the right one.

3. AOV from conversational commerce: Do conversations lead to bigger carts?

This metric looks at the average order value of shoppers who engage in a conversation versus those who don’t. 

If the conversational AOV is higher, it means your AI or agents are educating customers in ways that naturally expand the cart.

Examples of AOV-lifting conversations include:

  • Recommending complementary gear, tools, or accessories
  • Suggesting upgraded options based on needs
  • Helping shoppers understand the difference between product tiers
  • Explaining why a specific product is worth the investment

When conversations are done well, AOV increases not because shoppers are being upsold, but because they’re being guided

4. ROI of AI-powered conversations: The metric your leadership cares most about

ROI compares the revenue generated by conversational AI to the cost of the tool itself — in short, this is the number that turns heads in boardrooms.

Strong ROI shows that your AI:

  • Does the work of multiple agents
  • Drives new revenue, not just ticket deflection
  • Provides accurate answers consistently, at any time
  • Delivers a high-quality experience without expanding headcount

When ROI looks like that, AI stops being a “tool” and starts being an undeniable growth lever.

Related: The hidden power and ROI of automated customer support

Engagement metrics that indicate purchase intent

Not every metric in conversational commerce is a final outcome. Some are early signals that show whether shoppers are interested, paying attention, and moving closer to a purchase.

These engagement metrics are especially valuable because they reveal why conversations convert, not just whether they do. When engagement goes up, conversion usually follows.

1. Click-Through Rate (CTR): Are shoppers acting on the products your AI recommends?

CTR measures the percentage of shoppers who click the product links shared during a conversation. It’s one of the cleanest leading indicators of buyer intent because it reflects a moment where curiosity turns into action.

If CTR is high, it’s a sign that:

  • Your recommendations are relevant
  • The conversation is persuasive
  • The shopper trusts the guidance they’re getting
  • The AI is surfacing the right product at the right time

In other words, CTR tells you which conversations are influencing shopping behavior.

And the connection between CTR and revenue is often tighter than teams expect.

Just look at what happened with Caitlyn Minimalist. When they began comparing the results of human-led conversations versus AI-assisted ones over a 90-day period, CTR became one of the clearest predictors of success. Their Shopping Assistant consistently drove meaningful engagement with its recommendations — an 18% click-through rate on the products it suggested.

That level of engagement translated directly into better outcomes:

  • AI-driven conversations converted at 20%, compared to just 8% for human agents
  • Many of those clicks led to multi-item purchases
  • Overall, the brand experienced a 50% lift in sales from AI-assisted chats compared to human-only ones

When shoppers click, they’re moving deeper into the buying cycle. Strong CTR makes it easier to forecast conversion and understand how well your conversational flows are guiding shoppers toward the right products.

AI Agent recommends a customer with jewelry safe for sensitive skin

Discounting behavior metrics

Discounting can be one of the fastest ways to nudge a shopper toward checkout, but it’s also one of the fastest ways to erode margins. 

That’s why discount-related metrics matter so much in conversational commerce. 

They show not just whether AI is using discounts, but how effectively those discounts are driving conversions.

1. Discounts offered: Are incentives being used strategically or too often?

This metric tracks how many discount codes or promotional offers your AI is sharing during conversations. 

Ideally, discounts should be purposeful — timed to moments when a shopper hesitates or needs an extra nudge — not rolled out as a one-size-fits-all script. When you monitor “discounts offered,” you can ensure that incentives are being used as conversion tools, not crutches.

This visibility becomes particularly important at high-intent touchpoints, such as exit intent or cart recovery interactions, where a small incentive can meaningfully increase conversion if used correctly.

2. Discounts applied: Are those discounts actually influencing the purchase?

Offering a discount is one thing. Seeing whether customers use it is another.

A high “discounts applied” rate suggests:

  • The offer was compelling
  • The timing was right
  • The shopper truly needed that incentive to convert

A low usage rate tells a different story: Your team (or your AI) is discounting unnecessarily.

This metric alone often surprises brands. More often than not, CX teams discover they can discount less without hurting conversion, or that a non-discount incentive (like a relevant product recommendation) performs just as well.

Understanding this relationship helps teams tighten their promotional strategy, protect margins, and use discounts only where they actually drive incremental revenue.

How CX teams use these metrics to make better decisions

Once you know which metrics matter, the next step is building a system that brings them together in one place.

Think of your conversational commerce scorecard as a decision-making engine — something that helps you understand performance at a glance, spot bottlenecks, optimize AI, and guide shoppers more effectively.

In Gorgias, you can customize your analytics dashboard to watch the metrics that matter most to your brand. This becomes the single source of truth for understanding how conversations influence revenue.

Here’s what a powerful dashboard unlocks:

1. You learn where AI performs best (and where humans outperform)

Some parts of the customer journey are perfect for AI: repetitive questions, product education, sizing guidance, shade matching, order status checks. 

Others still benefit from human support, like emotional conversations, complex troubleshooting, multi-item styling, or high-value VIP concerns.

Metrics like resolution rate, zero-touch ticket rate, and chat conversion rate show you exactly which is which.

When you track these consistently, you can:

  • Identify conversation types AI should fully own
  • Spot where AI needs more training
  • Allocate human agents to higher-value conversations
  • Decide when humans should step in to drive stronger outcomes

For example, if AI handles 80% of sizing questions successfully but struggles with multi-item styling advice, that tells you where to invest in improving AI, and where human expertise should remain the default.

2. You uncover what shoppers actually need to convert

Metrics like CTR, CVR, and conversational AOV reveal the inner workings of shopper decision-making. They show which recommendations resonate, which don’t, and which messaging actually moves someone to purchase.

With these insights, CX teams can:

  • Refine product recommendations
  • Improve conversation flows that stall out
  • Adjust the tone or structure of AI messaging
  • Draft stronger scripts for human agents
  • Identify recurring questions that indicate missing PDP information

For instance, if shoppers repeatedly ask clarifying questions about a product’s material or fit, that’s a signal for merchandising or product teams

If recommendations with social proof get high engagement, marketing can integrate that insight into on-site messaging. 

Conversations reveal what customers really care about — often before analytics do.

3. You prove that conversations directly drive revenue

This is the moment when the scorecard stops being a CX tool and becomes a business tool.

A clear set of metrics shows how conversations tie to:

  • GMV influenced
  • AOV lift
  • Revenue generated by AI
  • ROI of conversational commerce tools

When a CX leader walks into a meeting and says, “Our AI Assistant influenced 5% of last month’s revenue” or “Conversational shoppers have a 20% higher AOV,” the perception of CX changes instantly.

You’re no longer a support cost. You’re a revenue channel.

And once you have numbers like ROI or revenue influence in hand, it becomes nearly impossible for anyone to argue against further investment in CX automation.

4. You identify where shoppers are dropping off or hesitating

A scorecard doesn’t just show what’s working, it surfaces what’s not.

Metrics make friction obvious:

Metric Signal

What It Means

Low CTR

Recommendations may be irrelevant or poorly timed.

Low CVR

Conversations aren’t persuasive enough to drive a purchase.

High deflection but low revenue

AI is resolving tickets, but not effectively selling.

High discount usage

Shoppers rely on incentives to convert.

Low discount usage

You may be offering discounts unnecessarily and losing margin.

Once you identify these patterns, you can run targeted experiments:

  • Test new scripts or flows
  • Adjust product recommendations
  • Add social proof or benefit framing
  • Reassess discounting strategies
  • Rework messaging on key PDPs

Compounded over time, these moments create major lifts in conversion and revenue.

5. You create a feedback loop across marketing, merchandising, and product

One of the biggest hidden values of conversational data is how it strengthens cross-functional decision-making.

A clear analytics dashboard gives teams visibility into:

  • Unclear or missing product information (from repeated questions)
  • Merchandising opportunities (from your most popular products)
  • Landing page or PDP improvements (from drop-off points)
  • Messaging that resonates with real customers (from AI messages)

Suddenly, CX isn’t just answering questions — it’s informing strategy across the business.

CX drives revenue when you measure what matters

With the right metrics in place, CX leaders can finally quantify the impact of every interaction, and use that data to shape smarter, more profitable customer journeys.

If you're ready to measure — and scale — the impact of your conversations, tools like Gorgias AI Agent and Shopping Assistant give CX teams the visibility, accuracy, and performance needed to turn every interaction into revenue.

Want to see it in action? Book a demo and discover what conversational commerce can do for your bottom line.

{{lead-magnet-2}}

min read.
Create powerful self-service resources
Capture support-generated revenue
Automate repetitive tasks

Further reading

Should Brands Disclose AI in Customer Interactions? A Guide for CX Leaders

By Tina Donati
min read.
0 min read . By Tina Donati

TL;DR:

  • Check legal requirements. Some regions mandate AI disclosure—stay compliant.
  • Transparency impacts trust. Some customers appreciate honesty; others may disengage.
  • Frame AI as helpful. Position it as a support tool, not a human replacement.
  • Refine your approach over time. Monitor feedback and adjust AI disclosure as needed.
  • 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.

    The legal landscape: What are the disclosure requirements?

    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:

    • In email: Use your email signature to indicate that AI has assisted in generating the response.
    • In chat: Update your Privacy Policy to clarify when AI is involved 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

    How does disclosure impact trust and satisfaction?

    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:

    1. Clear disclosure: They want to know when AI is (and isn’t) used in customer interactions.
    2. Simple, non-technical language: AI disclosures shouldn’t feel like reading a terms-of-service agreement. Keep it digestible.
    3. Easy-to-find information: AI disclosures should be visible—not buried in fine print. A chatbot notification, a banner on your site, or a brief message before an AI-powered chat begins can make a big difference.

    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 business perspective: Risks and benefits of AI transparency

    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.

    Risks of disclosure

    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.

    Benefits of disclosure

    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.

    Example: How Arcade Belts used AI transparency without losing the human touch

    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.

    Arcade Belts' website uses Gorgias Chat to automate FAQs
    Arcade Belts uses Gorgias Automate to automatically answer common questions.

    Initially, automation helped manage routine questions, such as product recommendations and shipping policies. But when they integrated Gorgias 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.

    Decision-making framework: Should you disclose AI?

    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:

    Step 1: Assess legal requirements

    Before making any decisions, ensure your brand is compliant with AI transparency regulations.

    • Research regional laws governing AI disclosure, as requirements vary by jurisdiction.
    • Consult legal counsel to confirm whether your AI usage falls under any mandated disclosure policies.
    • Stay informed on evolving AI governance frameworks that could introduce new compliance obligations.

    Step 2: Review customer expectations and brand positioning

    AI transparency should align with your brand’s values and customer experience strategy.

    • Consider whether transparency supports your brand’s messaging—does your audience expect openness, or do they prioritize seamless interactions?
    • Analyze customer sentiment through surveys and engagement data to determine if they prefer knowing when they’re speaking with AI.
    • Review past AI interactions to identify patterns in customer reactions and adjust your approach accordingly.

    Step 3: Test both approaches and measure the impact on CSAT

    Rather than making assumptions, run controlled tests to see how AI disclosure affects customer satisfaction.

    • Conduct A/B tests comparing interactions with and without AI disclosure.
    • Track key support metrics like response time, CSAT scores, and AI resolution rates to measure effectiveness.
    • Experiment with different positioning strategies—does framing AI as a helpful assistant improve customer perception?

    Step 4: Adjust based on customer feedback and industry trends

    AI strategies shouldn’t be static. As customer preferences and AI capabilities evolve, brands should refine their approach accordingly.

    • Regularly collect customer feedback to understand how AI disclosure impacts their experience.
    • Monitor industry trends to see how competitors and market leaders are handling AI transparency.
    • Stay flexible—if sentiment shifts, be ready to adjust your disclosure strategy to maintain trust and efficiency.

    Best practices for AI disclosure (if you choose to disclose)

    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.

    First, make AI part of your brand voice

    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.

    AI Agent responding to good customer feedback with a discount
    AI Agent uses an outgoing, enthusiastic, and approachable tone.

    Read more: AI tone of voice: Tips for on-brand customer communication

    Clarify the AI’s role

    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.

    Blend human and AI seamlessly

    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."

    Frame AI messaging positively

    AI disclosure doesn’t have to feel like an apology. Instead of focusing on limitations, highlight the benefits AI brings to the experience:

    • Faster responses
    • 24/7 availability
    • Instant answers to common questions

    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.

    Monitor customer feedback and adjust messaging

    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… 

    When AI is done right: Jonas Paul’s success story

    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. 

    AI Agent responding to a customer asking about what eyeglass lenses to choose
    AI Agent helps a customer with the lens selection process.

    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 AI Agent with influenced revenue. You can dive in more here.

    Make AI transparency work for you with AI Agent

    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:

    • The Guidance, Articles, or Macros it referenced
    • The source of any account information it used
    • A prompt for your feedback to continually refine and improve responses

    Excited to see how AI Agent can transform your brand? Book a demo.

    {{lead-magnet-1}}

    Grow Your Business with Conversational AI: Insights from Glamnetic & Audien Hearing

    By Holly Stanley
    min read.
    0 min read . By Holly Stanley

    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."

    Glamnetic leverages AI Agent to support during important period of growth
    AI Agent helped Glamnetic’s support team decrease its ticket volume by 25%.

    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.
    Screenshot of AI Agent Bot replying to Barbara customer of Audien Hearing.

    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.

    {{lead-magnet-1}}

    Meet Auto QA: Quality Checks Are Here to Stay

    By Gorgias Team
    min read.
    0 min read . By Gorgias Team

    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.
    Access Auto QA right within the ticket view. Find it on the right-hand side of customer conversations.

    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?
    A text field for
    Improve Auto QA scoring by clicking the triangle to expand each category and entering feedback into the textbox. 

    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.
    Auto QA Report dashboard shows reviewed tickets, resolution completeness score, communication score, and individual agent performance
    Monitor the number of tickets Auto QA has reviewed, your average resolution completeness rate, and your communication score.

    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.

    {{lead-magnet-1}}

    5 CX Metrics To Track in 2025: A Guide for Managers

    By Alexa Hertel
    min read.
    0 min read . By Alexa Hertel

    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.

    {{lead-magnet-1}}

    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.

    A pink graphic with 70% next to stars and the text of CX teams use AI and automation to handle support inquiries during the holiday season.
    70% of CX teams use AI and automation to handle support inquiries during the holiday season. Gorgias

    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

    A peach bar graph that shows the different metrics CX leaders used to measure success for holiday 2024, with resolution time at the top.
    71% of CX teams used resolution time to measure success during the holiday season in 2024. Gorgias Customer Expectations Survey

    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: 

    An interaction between Gorgias's AI Agent and a Glamnetic customer in need of a shipping address change via email.
    AI Agent helped Glamnetic reduce first response time by tackling repetitive tickets like change of address requests. Gorgias 

    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. 

    An interaction between Gorgias's AI Agent and a Jonas Paul Eyewear customer who has a pre-sales question.
    Gorgias AI Agent supports pre-sales questions by offering detailed responses, like which glasses would work best for a customer’s 8 year old son. Gorgias 

    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

    A screenshot of the AI Agent Statistics view within Gorgias.
    Review AI Agent’s performance within the Statistics view. Gorgias If you’d like to change the metrics you see here, select “Edit Columns.” 
    A screenshot of how to change the metrics you track for AI Agent within the Statistics tab in Gorgias.
    Navigate to the ‘Performance’ section to switch out the metrics you track for AI Agent. Gorgias 

    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 →

    {{lead-magnet-2}}

    Say Hello to AI Agent on Chat: 24/7 Support for Online Stores

    By Christelle Agustin
    min read.
    0 min read . By Christelle Agustin

    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. 

    Four customer inquiries branching out from live chat which has an "AI Agent is thinking" chat message.
    AI Agent is context-aware and uses information from its knowledge sources to respond to customers in real time. 

    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.

    A graphic with a pink gradient background featuring the text "AI Agent is an extension of your CX team" on the left. On the right, a circular diagram highlights four key functions: "Onboard," "Automate," "Observe," and "Coach." The "Gorgias" logo is in the top left corner, and the phrase "AI-powered CX built for ecommerce" is in the top right.
    Onboard, Automate, Observe, and Coach AI Agent to flawlessly integrate it into your team.

    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.

    A GIF of a highlighted "AI Library" button with a purple sparkle icon. The button has a white background, rounded edges, and a blue underline that animates from left to right. The background shows part of a navigation bar.
    The AI Library recommends pre-written articles based on what your customers ask you.

    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.

    5 types of Guidance for AI Agent ranging from damaged items to returns, plus a customer guidance button.
    Access premade Guidance templates or make your own customer Guidance for AI Agent.

    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.

    Custom is selected under the Tone of Voice dropdown. There are instructions about being concise and using emojis for a personal touch.
    AI Agent’s tone of voice can be altered with preset voices or custom instructions.

    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.

    AI Agent greets the user to the AI Agent test area where they can test how AI Agent would respond to customer questions.
    Test AI Agent’s responses to ensure accurate answers.

    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.
    AI Agent’s answers improve as you provide feedback.

    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.

    {{lead-magnet-1}}

    The Gorgias & Shopify Integration: 8 Features Your Support Team Will Love

    By Holly Stanley
    min read.
    0 min read . By Holly Stanley

    TL;DR:

  • Gorgias centralizes Shopify support tasks in one platform. Agents can view and update order info without leaving the helpdesk.
  • Macros, Rules, and AI Agent automate personalized responses. Dynamic Shopify data combined with AI and automation features powers fast, on-brand support for growing brands.
  • Customers can self-serve routine order questions. Enable Order Management on Chat to deflect order-related tickets.
  • Support now drives sales, not just solves problems. Brands using Gorgias report higher revenue and faster resolution times thanks to integrated reporting and automation.
  • 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}}

    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

    Screenshot of Shopify order data within Gorgias ticket
    Customer order data, including their shipping address and product details, can be found directly in the ticket.

    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.

    Screenshot of duplicate order Shopify action in Gorgias ticket.
    Agents can perform Shopify Actions like duplicate an order directly from Gorgias.

    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. 

    Screenshot of templated response with Shopify data in Gorgias ticket.
    Shopify data lets agents create Macros, templated responses with personalized data.

    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.
    Rule setup for auto tagging VIP customers
    Rules let you identify VIP customers using Shopify variables.

    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.
    Screenshot of Revenue Statistics dashboard in Gorgias.
    Revenue Statistics highlight which support channels and agents are best at generating sales.

    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.
    Screenshot of AI Agent Actions.
    Using Gorgias’s AI Agent you can customize multiple Shopify actions with Gorgias.

    {{lead-magnet-2}}

    The Problem with Full-Screen Pop-Ups for Driving Conversions

    By Matilda Lee
    min read.
    0 min read . By Matilda Lee

    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.

    TUSHY's Convert Campaign
    TUSHY's promotional campaign creates urgency with a 50% off product offer.

    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.

    The campaign setup for a 10% off discount. 

    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.

    Soon, you can upsell 24/7 on chat with AI Agent for Sales.

    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.

    Glamnetic uses Gorgias Convert campaigns, even on mobile
    Glamnetic’s Convert campaign looks great on mobile, too.

    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.

    Edit discount offer dialog for Convert Campaigns
    Edit the discount offer featured on a Convert Campaign.

    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!

    Introducing Conversational AI: The Smartest Way to Handle Chat, Actions, QA, and Insights

    By Gorgias Team
    min read.
    0 min read . By Gorgias 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.

    AI Agent responding in chat and email
    AI Agent can autonomously respond to customers on email and chat.

    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.

    AI Agent actions are connected to ecommerce apps
    AI Agent can perform actions on ecommerce apps, right from the Gorgias platform.

    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.
    The Auto QA Score includes resolution, accuracy, efficiency, communication and text field for feedback
    Receive automatic QA checks on all customer conversations with Auto QA.

    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 performance displays metrics like automation rate and customer satisfaction
    Monitor AI Agent’s performance with a glimpse into metrics like automation rate, closed tickets, and customer satisfaction.

    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.

    AI Insights show automation metrics and top intents
    Find out which areas of your support workflow could benefit from automation with AI Insights.

    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.

    Coming soon: AI Agent for Sales
    AI Agent for Sales is coming to chat soon.

    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.

    {{lead-magnet-1}}

    Building delightful customer interactions starts in your inbox

    Registered! Get excited, some awesome content is on the way! 📨
    Oops! Something went wrong while submitting the form.
    A hand holds an envelope that has a webpage coming out of it next to stars and other webpages