

TL;DR:
CSAT surveys are the fastest way to measure customer happiness after any interaction with your brand. Unlike lengthy feedback forms that customers abandon, a well-designed CSAT questionnaire captures satisfaction data in seconds while the experience is still fresh.
This guide covers the exact questions, templates, and distribution strategies that ecommerce brands use to collect actionable feedback and improve their customer experience. You'll learn how to create surveys that customers actually complete and turn those responses into real business improvements.
A CSAT survey questionnaire is a measurement tool that captures how satisfied customers are with a specific interaction, product, or service. This means you ask customers to rate their experience on a scale, usually from one to five, right after they interact with your brand.
The core of any CSAT survey is one simple rating question: "How satisfied were you with [specific interaction]?" Customers respond on a scale from Very Dissatisfied to Very Satisfied. This simplicity drives higher completion rates than complex surveys.
CSAT differs from other feedback tools in timing and focus. While relationship surveys measure long-term loyalty, CSAT captures immediate reactions to specific touchpoints like support conversations, deliveries, or product experiences. The questionnaire becomes a survey instrument when you add follow-up questions to understand the "why" behind ratings.
Different metrics serve different purposes in your customer experience strategy. Using the right tool for the job ensures you get clear, actionable data that helps you make better decisions.
CSAT excels at measuring satisfaction with specific interactions. Use it after support tickets, deliveries, or purchases when you need quick feedback on how well you performed. The 5-point scale makes it easy for customers to respond and for your team to track trends.
Key benefits of CSAT surveys:
Net Promoter Score (NPS) asks customers how likely they are to recommend your brand on a 0-10 scale. This metric predicts customer retention and word-of-mouth growth. Send NPS surveys quarterly or after customers have experienced your full product range.
Customer Effort Score (CES) measures how easy it was for customers to complete a task or resolve an issue. Low effort correlates with higher loyalty. Deploy CES after complex processes like returns, account setup, or multi-step support resolutions.
The format of your questions directly impacts response quality and completion rates. Match your question type to the data you need and make it as easy as possible for customers to respond.
Likert scales offer five to seven response options from one extreme to another, like Strongly Disagree to Strongly Agree. Use them for satisfaction ratings, agreement levels, and frequency measurements. They provide data that's easy to analyze while giving customers enough options to express their true feelings.
Yes/No or thumbs up/down questions work best for simple confirmations. Think: "Was your issue resolved?" or "Would you shop with us again?" Binary choices maximize response rates but sacrifice detail. Use them when you need high participation over deep insights.
Text responses explain the "why" behind ratings. Keep them optional and place them after rating questions with prompts like, "What's the primary reason for your score?" These insights guide improvement priorities, even with lower response rates.
These proven questions address the moments that matter most for online shoppers. Start with these templates and adapt them to your brand's specific touchpoints.
Post-purchase surveys capture satisfaction with the buying and delivery experience:
Support surveys measure how well your team resolved customer issues:
Product surveys help you understand satisfaction with your actual offerings:
Loyalty questions gauge future purchase intent and advocacy:
Building an effective CSAT survey requires strategic planning before you write a single question. Following a structured process ensures your survey delivers reliable, actionable data.
Start with the business decision your survey will influence. Are you measuring support quality to improve agent training? Tracking delivery satisfaction to evaluate shipping carriers? Clear objectives determine which questions to ask and how to analyze results.
Choose the right tool for your goal. Select CSAT for transactional feedback, NPS for relationship health, or CES for process improvement. Match your survey type to your objective: post-interaction surveys for operational metrics, periodic surveys for strategic insights.
Use simple language that customers understand immediately. Avoid leading questions like "How excellent was our service?" which bias results. Instead, use neutral phrasing like, "How would you rate our service?" Test questions internally to catch confusion before launch.
Keep surveys under two minutes. Place rating questions first, followed by optional open-ended questions. Since most customers respond on mobile, use large buttons, minimal scrolling, and responsive design. Preview on multiple devices before sending.
Pilot your survey with a small customer segment first. Monitor completion rates, response quality, and technical issues. After launch, review results weekly to identify question improvements and timing adjustments.
Timing and channel selection determine whether customers engage with your survey or ignore it. The right approach maximizes response rates and data quality.
Send transactional surveys within 24 hours of the interaction while details remain fresh. Post-purchase surveys perform best two to three days after delivery. Support surveys should trigger immediately after ticket resolution.
Avoid survey fatigue by limiting requests to once per customer per month. During peak seasons like Black Friday, increase post-purchase surveys but reduce follow-up questions to maintain completion rates.
Different channels work better for different types of feedback:
Collecting feedback without acting on it damages customer trust. Here's how to close the loop and turn scores into improvements.
Assign clear ownership for each feedback category. Support owns resolution feedback, fulfillment owns delivery ratings, product owns quality scores. Create weekly reviews where owners present trends and action plans to improve your CSAT scores.
Break down scores by customer segment, product line, and support channel. Compare new versus returning customers. Identify which segments drive low scores and prioritize improvements with highest impact.
Key segmentation approaches:
Follow up with dissatisfied customers within 48 hours. Thank satisfied customers and request reviews. Share improvements made based on feedback through email updates or Help Center articles. This shows customers their voice creates change.
Use root cause analysis on negative feedback patterns. Tag responses by theme to identify systemic issues. Create escalation workflows for scores below your threshold. Set service level agreements for follow-up based on score severity.
CSAT surveys give you the customer insights needed to improve your support, products, and overall experience. The templates and strategies in this guide provide your starting framework for collecting valuable feedback data.
Gorgias automates CSAT collection right within your helpdesk. Send surveys automatically after ticket resolution, track scores by agent and topic, and identify improvement areas through AI-powered insights. This turns feedback into a powerful tool for operational excellence and customer retention.
Book a demo to see how Gorgias turns feedback into better customer experiences.
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TL;DR:
The way shoppers buy online has shifted and customers are at the center.
They no longer want to scroll through product pages, dig through FAQs, or wait 24 hours for an email reply. They open a conversation, ask a specific question, and expect a useful answer in seconds. Brands that can’t deliver these experiences at scale are seeing customer hesitation turn into abandoned carts and lost revenue.
This shift has a name: conversational commerce. It's the practice of using real-time, two-way conversations as your primary sales channel, through chat, AI agents, messaging apps, and voice.
What started as an experiment for early adopters has become a key growth lever, with 84% of ecommerce brands treating conversational commerce as a strategic pillar this year vs. last year.

We surveyed 400 ecommerce decision-makers across North America, the U.K., and Europe to understand how conversational commerce and AI are reshaping the ecommerce landscape. These findings are complemented by aggregated and anonymized internal Gorgias platform data from 16,000+ ecommerce brands.
The State of Conversational Commerce in 2026 trends report breaks down all of the findings, including five key trends shaping the ecommerce landscape.
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A few years ago, adding an AI chatbot to your site that could provide tracking links and Help Center article recommendations was a differentiator. Today, it's table stakes. McKinsey found that 71% of shoppers expect personalized experiences, and 76% get frustrated when they don't get them.
Right now, most ecommerce professionals use AI, with 93% having used it for at least 1 year. Enthusiasm is accelerating quickly, with only 30% of ecommerce professionals rating their excitement for AI at 10/10 in April 2025. Similarly, while AI adoption rose steadily year over year, it reached a clear peak in 2026.

The use cases driving this adoption are practical and high-volume:

These are the tickets that flood brands’ inboxes every day. AI agents resolve them instantly, without pulling teams away from conversations that actually require human judgment.
Explore AI adoption and use case data in more depth in the full report.
The traditional ecommerce funnel, visit site, browse products, add to cart, check out, is losing ground. Shoppers now discover products on Instagram, ask questions via direct message, and complete purchases without ever visiting a website.

Conversational AI is actively increasing revenue, with 79% of brands reporting that AI-driven interactions have increased sales and conversion in their business.

The practical implication is that every channel is becoming a storefront. Creating personalized touchpoints with customers earlier in the journey, through proactive engagement, is impacting the bottom line.
Read the full report to explore how AI conversions have increased QoQ by industry.
Pre-purchase hesitation is one of the biggest conversion killers in ecommerce. A shopper lands on your product page, has a question about sizing or compatibility, can't find the answer quickly, and leaves. That's a lost sale that had nothing to do with your product.
Conversational AI changes that dynamic. When a shopper can ask a question and get an accurate, personalized answer in real time, the friction disappears.
Brands using Gorgias saw this play out at scale in 2025. When AI Agent recommended a product, 80% of the resulting purchases happened the same day, and 13% happened the next day.

Brands are further accelerating the buying cycle through proactive engagement. On-site features such as suggested product questions, recommendations triggered by search results, and “Ask Anything” input bars drove 50% of conversation-driven purchases during BFCM 2025.
Explore how AI is collapsing the purchase cycle in Trend 3 of the report.
There's a persistent narrative that AI is making CX teams redundant. The data tells a different story. 62% of ecommerce brands are planning to grow their teams, not cut them. But the scope of those teams is changing.

New roles are emerging around AI configuration and quality assurance. Teams are investing in technical members to write AI Guidance instructions, develop tone-of-voice instructions, and continuously QA results.
CX teams are also bridging the gap between support goals and revenue goals, as the two functions increasingly overlap.

The result is CX teams that are more technical than they were before. Agents who once spent their days answering repetitive tickets are now spending that time on higher-value work: complex escalations, VIP customer relationships, and improving the AI systems and knowledge bases that handle the volume.
Learn more about the evolution of CX roles in Trend #4.
Despite increasing AI adoption, data shows that ecommerce brands shouldn’t strive for 100% automation. Winning brands are building systems in which AI handles repetitive tier-1 tickets, and humans handle complex, sensitive cases.

AI handles speed and scale. It resolves order-tracking requests at 2 a.m., processes return-eligibility checks in seconds, and answers the same shipping question for the thousandth time without compromising quality.
Human agents handle conversations that require context, empathy, or decisions that fall outside the standard playbook. There are several topics where shoppers still prefer human support.

Successful hybrid systems require continuous iteration, meaning reviewing handover topics, Guidance, and reviewing AI tickets on a weekly basis.
Discover how leading brands are balancing human and AI systems in Trend #5.
The 2026 trends are about expansion and standardization. The 2030 predictions are about what comes next.

Voice-based purchasing is the biggest bet on the horizon. Only 7% of brands currently use voice assistants for commerce, but 89% expect it to be standard by 2030. The vision is a customer who can reorder a product, check their subscription status, or manage a return entirely over the phone.
Proactive AI is the other major shift. Rather than waiting for a customer to reach out, AI will anticipate needs based on browsing behavior, purchase history, and where someone is in their relationship with your brand. Think of it as the digital equivalent of a sales associate who remembers what you bought last time and knows what you're likely to need next.
Explore where ecommerce brands are allocating their AI budgets in the full report.
The brands winning in 2026 are creating smart, scalable systems where AIhandles volume and humans handle nuance. They’re treating every conversational channel as an opportunity to serve and sell.
The data is clear: AI adoption is accelerating, customer expectations are rising, and the revenue impact of getting this right is measurable.
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TL;DR:
A year ago, ecommerce brands were still debating whether AI was worth the investment. That debate is over. Today, nearly every ecommerce professional uses AI to do their job.
The shift isn't just about adoption. It's about what AI is used for and how brands measure its impact. Support automation was the entry point. Now, AI is embedded across the full operation, from product recommendations to inventory control to real-time shopping conversations.
In our 2026 State of Conversational Commerce Report, we break down trends on AI usage among 400 ecommerce decision-makers and 16,000+ ecommerce brands using Gorgias.
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If we rewind 12 months ago, the industry was still split on AI. Some ecommerce professionals were excited, but most were still hesitant. In 2024, 69% of ecommerce professionals used AI in their roles. By 2025, that number reached 77%. In 2026, it hit 96%.

The confidence numbers back it up. 71% of brands say they are confident using AI for ecommerce, and 73% are satisfied with its business impact.
In early 2025, only 30% of ecommerce professionals rated their excitement for AI at 10/10. Today, zero percent of respondents describe themselves as hesitant about AI.

Using AI in ecommerce is not new. In fact, it dates back to the 1980s with the invention of algorithms and expert systems. And if you’ve ever leveraged similar product recommendations or chatbots, you’ve already integrated AI into your ecommerce stack.
Modern AI is far more sophisticated.
With the rise of agentic commerce and conversational AI, brands began leveraging AI agents to automate the processing of repetitive support tickets. That’s still happening today, but the scope has expanded beyond the support queue.

Ecommerce brands are deploying AI across every layer of their operation:
When brands were asked which channels contribute most to their AI success, conversational channels dominated. Social media messaging led at 78%, followed by SMS at 70%, and website live chat at 51%. Shoppers want fast, personal conversations, and AI is the best way to deliver that at scale.
Learn more about AI adoption, perception, and use case trends in the full 2026 Conversational Commerce Report.
For decades, customer support success meant fast response times and high satisfaction scores. Those are still important indicators of success, but leading brands are adding revenue-focused metrics to their dashboards.
91% of brands still track CSAT as a measure of AI's impact. But 60% now include AOV as a top indicator, and higher-revenue brands earning $20M+ are focusing on metrics like total operating expenses, cost per resolution, incremental revenue, and one-touch ticket rate.

AI can now start a conversation, ease customer doubts, sell, upsell, and recover abandoned carts in a single conversation. When you’re only measuring CSAT, you’re ignoring the real ROI of conversational AI investment.
Virtual shopping assistants now proactively engage shoppers, adapt to their needs in real time, and offer contextual product recommendations and upsells. When the moment calls for it, they can close the deal with a targeted discount.
Gorgias brands using AI Agent's shopping assistant capabilities nearly doubled their purchase rates and converted 20–50% better than those using AI Agent for support only.
Orthofeet, the largest provider of orthopedic footwear in the US, is a concrete example of this in practice. Using Gorgias, they achieved:
The data tells a clear story: AI has evolved beyond a tool for handling tier 1 support tickets. It’s a core part of your revenue generation strategy.
57% of brands are already using AI for 26–50% of all customer interactions, and 37% expect that share to rise to 51–75% within the next two years. The brands building toward that range now are the ones who will have the operational advantage when it matters most.
The practical question isn't whether to invest in AI. It's where to focus first. Based on where brands are seeing the most impact, three priorities stand out:
Want to go deeper on the full 2026 conversational commerce trends? Read the complete report for data across every major AI use case in ecommerce.
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TL;DR:
Customer education has become a critical factor in converting browsers into buyers. For wellness brands like Cornbread Hemp, where customers need to understand ingredients, dosages, and benefits before making a purchase, education has a direct impact on sales. The challenge is scaling personalized education when support teams are stretched thin, especially during peak sales periods.
Katherine Goodman, Senior Director of Customer Experience, and Stacy Williams, Senior Customer Experience Manager, explain how implementing Gorgias's AI Shopping Assistant transformed their customer education strategy into a conversion powerhouse.
In our second AI in CX episode, we dive into how Cornbread achieved a 30% conversion rate during BFCM, saving their CX team over four days of manual work.
Before diving into tactics, understanding why education matters in the wellness space helps contextualize this approach.
Katherine, Senior Director of Customer Experience at Cornbread Hemp, explains:
"Wellness is a very saturated market right now. Getting to the nitty-gritty and getting to the bottom of what our product actually does for people, making sure they're educated on the differences between products to feel comfortable with what they're putting in their body."
The most common pre-purchase questions Cornbread receives center around three areas: ingredients, dosages, and specific benefits. Customers want to know which product will help with their particular symptoms. They need reassurance that they're making the right choice.
What makes this challenging: These questions require nuanced, personalized responses that consider the customer's specific needs and concerns. Traditionally, this meant every customer had to speak with a human agent, creating a bottleneck that slowed conversions and overwhelmed support teams during peak periods.
Stacy, Senior Customer Experience Manager at Cornbread, identified the game-changing impact of Shopping Assistant:
"It's had a major impact, especially during non-operating hours. Shopping Assistant is able to answer questions when our CX agents aren't available, so it continues the customer order process."
A customer lands on your site at 11 PM, has questions about dosage or ingredients, and instead of abandoning their cart or waiting until morning for a response, they get immediate, accurate answers that move them toward purchase.
The real impact happens in how the tool anticipates customer needs. Cornbread uses suggested product questions that pop up as customers browse product pages. Stacy notes:
"Most of our Shopping Assistant engagement comes from those suggested product features. It almost anticipates what the customer is asking or needing to know."
Actionable takeaway: Don't wait for customers to ask questions. Surface the most common concerns proactively. When you anticipate hesitation and address it immediately, you remove friction from the buying journey.
One of the biggest myths about AI is that implementation is complicated. Stacy explains how Cornbread’s rollout was a straightforward three-step process: audit your knowledge base, flip the switch, then optimize.
"It was literally the flip of a switch and just making sure that our data and information in Gorgias was up to date and accurate."
Here's Cornbread’s three-phase approach:
Actionable takeaway: Block out time for that initial knowledge base audit. Then commit to regular check-ins because your business evolves, and your AI should evolve with it.
Read more: AI in CX Webinar Recap: Turning AI Implementation into Team Alignment
Here's something most brands miss: the way you write your knowledge base articles directly impacts conversion rates.
Before BFCM, Stacy reviewed all of Cornbread's Guidance and rephrased the language to make it easier for AI Agent to understand.
"The language in the Guidance had to be simple, concise, very straightforward so that Shopping Assistant could deliver that information without being confused or getting too complicated," Stacy explains. When your AI can quickly parse and deliver information, customers get faster, more accurate answers. And faster answers mean more conversions.
Katherine adds another crucial element: tone consistency.
"We treat AI as another team member. Making sure that the tone and the language that AI used were very similar to the tone and the language that our human agents use was crucial in creating and maintaining a customer relationship."
As a result, customers often don't realize they're talking to AI. Some even leave reviews saying they loved chatting with "Ally" (Cornbread's AI agent name), not realizing Ally isn't human.
Actionable takeaway: Review your knowledge base with fresh eyes. Can you simplify without losing meaning? Does it sound like your brand? Would a customer be satisfied with this interaction? If not, time for a rewrite.
Read more: How to Write Guidance with the “When, If, Then” Framework
The real test of any CX strategy is how it performs under pressure. For Cornbread, Black Friday Cyber Monday 2025 proved that their conversational commerce strategy wasn't just working, it was thriving.
Over the peak season, Cornbread saw:
Katherine breaks down what made the difference:
"Shopping Assistant popping up, answering those questions with the correct promo information helps customers get from point A to point B before the deal ends."
During high-stakes sales events, customers are in a hurry. They're comparing options, checking out competitors, and making quick decisions. If you can't answer their questions immediately, they're gone. Shopping Assistant kept customers engaged and moving toward purchase, even when human agents were swamped.
Actionable takeaway: Peak periods require a fail-safe CX strategy. The brands that win are the ones that prepare their AI tools in advance.
One of the most transformative impacts of conversational commerce goes beyond conversion rates. What your team can do with their newfound bandwidth matters just as much.
With AI handling straightforward inquiries, Cornbread's CX team has evolved into a strategic problem-solving team. They've expanded into social media support, provided real-time service during a retail pop-up, and have time for the high-value interactions that actually build customer relationships.
Katherine describes phone calls as their highest value touchpoint, where agents can build genuine relationships with customers. “We have an older demographic, especially with CBD. We received a lot of customer calls requesting orders and asking questions. And sometimes we end up just yapping,” Katherine shares. “I was yapping with a customer last week, and we'd been on the call for about 15 minutes. This really helps build those long-term relationships that keep customers coming back."
That's the kind of experience that builds loyalty, and becomes possible only when your team isn't stuck answering repetitive tickets.
Stacy adds that agents now focus on "higher-level tickets or customer issues that they need to resolve. AI handles straightforward things, and our agents now really are more engaged in more complicated, higher-level resolutions."
Actionable takeaway: Stop thinking about AI only as a cost-cutting tool and start seeing it as an impact multiplier. The goal is to free your team to work on conversations that actually move the needle on customer lifetime value.
Cornbread isn't resting on their BFCM success. They're already optimizing for January, traditionally the biggest month for wellness brands as customers commit to New Year's resolutions.
Their focus areas include optimizing their product quiz to provide better data to both AI and human agents, educating customers on realistic expectations with CBD use, and using Shopping Assistant to spotlight new products launching in Q1.
The brands winning at conversational commerce aren't the ones with the biggest budgets or the largest teams. They're the ones who understand that customer education drives conversions, and they've built systems to deliver that education at scale.
Cornbread Hemp's success comes down to three core principles: investing time upfront to train AI properly, maintaining consistent optimization, and treating AI as a team member that deserves the same attention to tone and quality as human agents.
As Katherine puts it:
"The more time that you put into training and optimizing AI, the less time you're going to have to babysit it later. Then, it's actually going to give your customers that really amazing experience."
Watch the replay of the whole conversation with Katherine and Stacy to learn how Gorgias’s Shopping Assistant helps them turn browsers into buyers.
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TL;DR:
In 2025, chat’s growth outpaced email by 2.5x quarter over quarter. Chat has become our most powerful customer experience tool for how shoppers discover products, ask questions, and decide to buy.
We knew it needed an upgrade, so we reimagined the entire experience from the ground up.
The result is 36% more engagement with product recommendations, nearly 2.25x more shoppers add-to-cart, and 7.3% more customer engagement.
In this post, we'll walk you through our thinking, what’s new in Chat, and how brands are already seeing big gains.
Chat has outpaced email support. Today’s shoppers prefer the speed of quick chat conversations over email. And when shoppers make a new move, we watch, listen, and move with them.
This behavioral shift isn’t happening in isolation. It aligns with the rise of conversational commerce and proves a universal move toward real-time conversations in ecommerce.
In fact, the signals were already there. Two years of building AI Agent showed us just how much design shapes behavior. The interface is the experience, and we knew that pushing chat experiences to closely resemble human interactions would transform how shoppers engage.
Our new and updated chat brings that vision to life. We believe that shopping is moving from static pages to conversations. This new update is built for how people actually want to shop.
The new design turns live chat into an interactive shopping surface made for modern shoppers. We've brought together multiple ways for shoppers to jump into chat, added clickable replies instead of typing, browsable product cards right in the conversation, and quick cart access.
Let's walk through what's new.
Chat now comes in a softer color palette that adapts to your store’s branding. We removed message bubbles in favor of an airy design that brings in the familiarity of speaking to your favorite conversational AI assistant. Every interaction now has the breathing room for deeper conversation and personalization.

It’s now easier for shoppers to get an answer with quick reply buttons and suggested questions in Chat. This replaces the tree-based flows of the previous Chat, removing the need to follow a fixed path. Shoppers can find answers faster without typing text-heavy explanations.

Browsing and buying within Chat is now possible. Previously, it only supported product links that would open in a new page. With the upgrade, you can view item details without leaving the conversation. Shoppers can browse, compare products, and add to cart in one place.

We’re keeping the context by removing the external redirects. The new interface lets shoppers browse product recommendations right in chat. View key product details, images, descriptions, variants, and pricing without opening a new tab.

Chat adds clickable questions on product pages — like “Is this true to size?” or “What’s the difference between shades?” — designed to match what a shopper is likely wondering in the moment. These context-aware prompts help remove buying hesitation before shoppers even think to ask.

Chat adds instant access to shopper actions, like a cart button and an orders button for returning customers. Shoppers can jump straight to their cart or check on an existing order without waiting for an agent to give them a status update.

Every update in Chat drives performance. We didn’t simply give it a makeover, we also fine-tuned its underlying mechanics.
When product suggestions are easy to browse, shoppers interact with them more. The new product cards make shopping feel natural, allowing customers to explore items at their own pace. That convenience led to a 36% increase in engagement with recommended products.
Chat keeps the entire shopping journey inside the conversation, from browsing and asking questions, to adding to cart and checking out. This new layout removes the usual tab-switching between chat and the website. Less friction has led to more than double add-to-cart actions than before the redesign.
Chat's cleaner design and contextual entry points make it easier for shoppers to start a conversation. With suggested questions on product pages and quick reply buttons, more visitors are choosing to engage earlier in their journey. This has resulted in a 7.3% lift in chat engagement.
Conversational commerce has moved from concept to reality. Chat makes it part of the everyday shopping experience, letting shoppers browse, ask questions, compare products, and check out in one interaction. It brings the ease of the in-person shopping experience into the digital world.
We built Chat to redefine the shopping experience. We hope you see it reflected in your customers’ journeys.
Book a demo to see what's possible with the new experience.

TL;DR:
Shoppers aren’t always going to reach out and ask the questions they have, especially if they’re going to have to wait for a response from a CX team.
That means you’re losing sales to friction, indecision, or information gaps.
In 2025, the average cart abandonment rate is 70.19%. But if you can find an AI tool that doubles as a support and sales agent, it could make all the difference.
Gorgias’s Shopping Assistant, for example, has brought a 62% uplift in conversion rate for brands that implement it.
Ahead, learn where you can leverage an AI shopping assistant to increase conversions and craft better purchase experiences.
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An AI shopping assistant is a chat tool powered by AI to provide pre-sales support for shoppers. It can answer questions, make product recommendations, and help guide shoppers in the right direction if they’re stuck.
Gorgias's Shopping Assistant is a powerful, hyper-personalized AI tool built for Shopify brands. Unlike other AI tools, Shopping Assistant starts conversations with customers, not the other way around. It’s uniquely tailored for each customer by tracking browsing behavior during each session and remembering what shoppers say, keeping conversations natural and recommendations relevant.
It’ll also chat with shoppers in your own brand voice, as its responses are pulled right from the knowledge you feed it.
The stages of the customer journey where common drop-off points occur for brands that lack proactive support include:
There’s a big chance that shoppers—especially first-timers—have questions, but aren’t willing to wait for a human to get back to them. And when your CX team is off the clock? Customers will likely leave altogether.
An AI shopping assistant can help you engage customers right away, even outside your business hours.
Bra brand Pepper uses Gorgias Shopping Assistant to help shoppers find their perfect size. When it detects hesitation, Shopping Assistant points customers to the sizing guide.
This proactive approach creates an easy path for conversation and sets the precedent that any questions will be answered immediately, providing a better––and less confusing––experience.

“With Shopping Assistant, we’re not just putting information in our customers’ hands; we’re putting bras in their hands,” says Gabrielle McWhirter, CX Operations Lead at Pepper.

For shoppers in the Discovery stage, using a Shopping Assistant boosts clicks and time on site and reduces bounce rate. It does this by surfacing specific questions on relevant product pages. Pepper boosted their conversion rate by 19% with Gorgias Shopping Assistant.
Read more: How Pepper’s AI Agent automates 54% of support and converts 19% of conversations
In a retail environment, a salesperson can give shoppers recommendations by asking a few questions, especially if they’re unsure of what to buy.
AI shopping assistants have the ability to mirror those in-person shopping experiences by interacting with customers in real-time to help them find their perfect match.
Shoppers can give as much (e.g., “Help! What dress is suitable for a wedding reception?”) or as little information as they’d like, and the AI shopping assistant will do the rest.
It’s possible even for questions that are slightly vague, like a customer who types in “how to make up” without any other context:

For example, jewelry shop Caitlyn Minimalist uses Shopping Assistant to recommend products, engaging interested customers and bringing them closer to a purchase.

“As a result of Shopping Assistant, we've seen a measurable lift in AOV through more meaningful customer interactions,” says Anthony Ponce, Head of Customer Experience at Caitlyn Minimalist.
“Our clients are provided the right information at the right time, creating a seamless experience that builds trust and drives confident purchases."
According to data from Gorgias, email is the highest volume support channel, with ~25% of that tied to pre-sales. AI shopping assistants tackle these pre-sales asks and also upsell by recommending complementary products. This can lead to a boost in average order value (AOV) and conversion rate.
Read more: How Caitlyn Minimalist uses Shopping Assistant to turn single purchases into jewelry collections
The main reasons customers abandoned a cart in 2025 include:
An AI shopping assistant can mitigate or resolve these issues. They resolve crucial questions—like delivery time or return policies—that need in-the-moment answers. By alleviating pre-sale concerns, they give customers the confidence to make a purchase.
For example, bidet brand TUSHY leverages Shopping Assistant to answer questions about toilet compatibility that might flush a pending sale.

Aside from quelling customer concerns, Shopping Assistant can also send discount codes to close deals. Unlike general discount codes you find across the internet, these discounts are uniquely generated for each customer, keeping them engaged and on your site.
AI shopping assistants can reduce cart abandonment rate and increase conversion rate. Gorgias Shopping Assistant adjusts to your sales strategy by sending customers discount codes that can be the final nudge to checkout.
Most AI tools are built just for support. They deflect tickets and answer FAQs, but they’re not built to sell.
Shopping Assistant proves that support teams can also drive revenue by upselling, suggesting exchanges, and giving shoppers the confidence to try a brand for the first time (or to give it another shot).
Gorgias’s AI Shopping Assistant uses context-based decision making and looks for specific behavioral signals:
|
Feature |
Traditional Chatbot |
AI Shopping Assistant |
|---|---|---|
|
Deflect tickets |
✅ |
✅ |
|
Answer frequently asked questions |
✅ |
✅ |
|
Upselling |
❌ |
✅ |
|
Proactively reaching out to offer support |
❌ |
✅ |
|
Use context-based signals to guide shoppers to checkout |
❌ |
✅ |
Ultimately, the cost of not adopting AI can be higher than the investment of implementing it. 77.2% of ecommerce professionals use AI to improve their work. Why not extend those benefits to your customers?
AI Shopping Assistants help you create better customer experiences overall. These tools help reduce customer effort, increase average order value, save would-be-lost sales, and create more customer touchpoints.
Hire the always-on Shopping Assistant that never misses a sale.
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TL;DR:
What’s the common factor between shoppers debating between products and considering a splurge? Hesitation.
Today’s shoppers are overwhelmed with choices. They don’t want to be left to figure things out on their own. They want guidance.
But most brands are missing that crucial piece of the puzzle. They lack a strategy that accompanies shoppers on their journey. A tool that encourages shoppers to proceed to checkout. And, ultimately, a customer experience devoid of a sales approach.
That’s why we built Shopping Assistant, an AI Agent that proactively engages browsers, offers context-aware product recommendations, and turns hesitation into conversions in real time.
And it’s working. Brands using Shopping Assistant are seeing a 62% uplift in conversion, 10% higher average order value, and 5x ROI.
Here’s a closer look at what’s behind the magic.
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Most traditional chatbots passively wait for questions and deliver answers that aren’t personalized to each shopper's preferences.
Unlike these bots, Shopping Assistant reads real-time signals like pages viewed, cart contents, and conversation tone. This results in a solution that not only offers support but also offers personalized, proactive selling. This enables Shopping Assistant to continuously refine and adjust its playbook, evolving with each shopper as their journey matures.
Here’s how Shopping Assistant engages with customers across the shopping journey:
Take this example below. When a customer vaguely asks “how to make up,” Shopping Assistant interprets it as a sign of interest in makeup products and recommends a starter kit.

Where traditional bots reset with every message, Shopping Assistant does the opposite. It has built-in context-aware intelligence that remembers what shoppers have clicked, viewed, and added to their cart during a session.
This enables natural, relevant, and persuasive conversations that truly resonate with each shopper. It goes beyond reading messages and observes behavior to adapt its responses.
That means it knows if someone has:
With plenty of context to work with, Shopping Assistant is not only smarter but also more profitable than the average chatbot. It drives more conversions with product recommendations and lifts average order value with timely upsells based on what’s been added to the cart or viewed.
Here’s what it looks like in action: When a customer engages through a product page, Shopping Assistant recommends a matching outfit, suggesting it’s aware of alternate product variants and the customer's likely interest in that style.

Promotions are powerful, but they’re not one-size-fits-all.
With Shopping Assistant, merchants can define their discount strategy to align with their brand. These strategies can range from offering no deals to using aggressive promotions.
Once the strategy is set, Shopping Assistant waits for hesitation and customer intent to trigger a discount, firing it at the most conversion-worthy moment.
Shopping Assistant initiates conversations. It’s built to engage shoppers, spotting when they linger or show signs of confusion, stepping in with timely, personalized help.
Every second counts in ecommerce. If a shopper pauses on a product page or is left scrolling through an endless search results page, Shopping Assistant detects it in real-time and reaches out with a relevant prompt like:
Here’s how Shopping Assistant reduces drop-off, builds confidence, and drives faster decision-making in three different ways.
Shopping Assistant automatically triggers commonly asked questions depending on the product currently being viewed. In one click, shoppers can get the answer to the question they’re curious about. This combats hesitation caused by a lack of information, resulting in more confident conversions.
When shoppers land on the homepage, it’s easy to become overwhelmed and not know where to navigate. The Ask Anything Input provides an easy way to start a conversation with Shopping Assistant and get the guidance they need.
Shopping Assistant can refine its response to the customer based on the page context. For example, when the customer is on a product page, Shopping Assistant knows exactly what product is being asked about.
Shopping Assistant can step in to offer pinpointed help based on a shopper’s search query. Instead of scrolling through a results page, Shopping Assistant triggers a message based on what the shopper entered, offering an easier and faster way to find what they need.
Shopping Assistant’s suggestions are rooted in real context: what the shopper has viewed, added to cart, or asked about. Whether they’re exploring a specific product line or revisiting a category they’ve shown interest in, Shopping Assistant delivers relevant upsells and complementary items that make sense for the customer.
This personalized approach to upselling increases cart size without feeling forced—it’s smart, seamless, and sales-driven.
Shopping Assistant can even turn vague product questions into upsell opportunities. By asking questions, it learns more about an individual to come up with recommendations that best fit their preferences.
Shopping Assistant is transforming the way shoppers engage and helping ecommerce brands sell more effectively. Through smarter conversations and real-time personalization, it turns every interaction into an opportunity to convert, build trust, and drive revenue.
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TL;DR:
The most coachable team member on your support team might not be human.
Brands that want to keep up with rising customer expectations are turning to AI to help meet demand. But as SuitShop’s Director of Customer Experience, Katie Eriks, will tell you, great results don’t come from flipping a switch.
They come from coaching.
Since implementing Gorgias AI Agent, SuitShop has reached a 30% automation rate, all while maintaining a lean CX team and giving every customer the tailored experience they expect (literally and figuratively).
“I consider myself its boss,” said Katie, who runs the entire coaching process solo. With under an hour of weekly maintenance now, SuitShop’s AI Agent runs efficiently, accurately, and on-brand.
Katie spoke at Gorgias Connect 2025 to share exactly how she got there. You can watch her full session below:
When brands think about automation, they often imagine flipping a switch and watching repetitive tasks vanish. But in practice, it’s not that simple, at least not if you care about customer experience.
Gorgias encourages brands to treat their AI Agent like a junior teammate — someone you onboard, train, observe, and coach over time.
Brands that do this well are already seeing massive gains:
For SuitShop, automation was about creating space for their small team to focus on specialized service. Space to scale without scaling headcount. And space to do it all without losing their voice.

Katie and her team had been longtime Gorgias users, but when they turned on AI Agent in August 2023, the results were unremarkable. The responses weren’t inaccurate, but they weren’t helpful enough either.
What Katie learned was to “Be hands-on early. Use downtime to train. And never stop refining.”
So she got to work, not by replacing the tool, but by going deeper into it. Here are her coaching tips:
Katie made herself the sole point of contact for training and QA. That might sound like a lot, but over time, it became a light lift.
“At this point, it’s definitely less than one hour per week,” she said. “In the beginning, it was more time-consuming because I needed to create help center articles and Guidance regularly. Now I’ve got it down to a pretty quick thumbs-up, thumbs-down kind of process.”
Katie uses Monday mornings to review AI Agent tickets from over the weekend, when fewer human agents are available and AI takes the lead.
Read more: Why your strategy needs customer service quality assurance
Unlike many retail brands, SuitShop’s busiest time isn’t the holiday rush — it’s wedding season in the summer and fall. So when things quieted down in December, Katie used that time strategically.
She temporarily turned off the AI Agent to regroup.
“I decided to turn it off and really beef up our Help Center,” she explained. “I went back to the tickets I had to answer myself, checked what people were searching in the Help Center, and filled in the gaps.”
She built out content with a mix of blog knowledge, internal macros, and ChatGPT. Once she felt confident the content base was solid, she turned AI back on.
Read more: How to optimize your Help Center for AI Agent
Once SuitShop’s foundational content was in place, Katie didn’t just sit back and hope for the best. Instead, she built a repeatable feedback loop grounded in data — one that helped her spot opportunities for improvement before they became issues.
Rather than combing through tickets at random, Katie created custom views inside Gorgias to zero in on the most impactful coaching moments:
To keep all of this actionable, Katie logs insights in a shared spreadsheet that functions as a live to-do list. Every row includes:
These insights are also available in Gorgias’s dashboard, where you can identify the top issues customers had.

“Sometimes I do it all in the moment. Other times I’ll log it and come back later when I can take the time to do it right.”
By combining frontline feedback with structured ticket views, Katie turned scattered QA into a consistent coaching system — one that ensures SuitShop’s AI Agent keeps getting smarter every week.
One of Katie’s most effective strategies comes from her own team.
Like many CX leads, she noticed that some agents consistently resolved tickets in a single touch. That pattern, Katie realized, wasn’t just a win for customers, it was a roadmap for an AI-driven support strategy.
Her teammate Tacy quickly became her go-to signal for what the AI Agent needed to learn next.
“I pull her tickets often to see what she’s responded with. It helps AI learn from her directly.”
By reviewing Tacy’s ticket history, Katie identified standard replies that didn’t yet exist as macros or Guidance. If Tacy was writing the same sentence repeatedly or copy-pasting a reply manually, that meant it could (and should) be taught to the AI Agent.
She also tracked Tacy’s macro usage rate. If Tacy frequently used a macro for a certain issue, but other agents weren’t, it flagged an opportunity to standardize responses across the team and the AI.
The key insight? If it only takes one touch for a human to answer, the AI can be trained to do it too.
These small efficiency wins added up quickly, especially during peak season, when the ability to automate just a few extra conversations per day created meaningful breathing room for the rest of the team.
Related: How to automate half of your CX tasks
Automation without brand voice feels robotic. Katie made sure SuitShop’s AI Agent sounded like a natural extension of the team, and that started with a name: Max.
“We get replies like, ‘Thanks Max!’ from customers who think it’s a real person.”
Using AI Agent’s tone of voice settings, Katie went deep on personalization. She customized everything from sentence structure and greeting format to whether or not emojis and exclamation marks should be used (they shouldn’t, in SuitShop’s case).

Her AI Agent instructions include clear direction on:
Katie also made sure she instructed AI Agent to acknowledge customer emotions — especially frustration — and to offer reassurance when things went wrong.
And because AI responses are written at lightning speed, she regularly reviewed messages to ensure they didn’t come off as cold or abrupt, especially in sensitive situations like delayed wedding orders or size issues close to the event date.
In the workshop, Katie walked through two real support tickets where AI missed the mark and how she used those moments to improve.
In one case, a customer asked a common question: “The navy suit I’m looking at says ‘unfinished pant hem.’ Will the pants need to be hemmed?”
Despite having help articles and macros explaining this exact issue, AI Agent responded: “I don’t have the information to answer your question.”
That was a red flag.
Katie immediately stepped in to coach the agent by:
“I like to write a short internal note, so if I see that ticket again, I know exactly how I coached it.”
In another case, AI Agent was incorrectly handing off a sizing question about jacket sleeve length. Katie realized that a previous broad handover topic ("sizing and fit questions") was causing confusion by flagging issues that the AI should have been able to handle.
So she deleted the handover topic and replaced it with a clear guidance article — complete with example questions, macros, and links to sizing resources.

“Once I added specific questions in quotes, it made a huge difference.”
SuitShop didn’t automate 100% of CX — but that’s not the point. At 30% automation (and growing), Katie gives her team more time to specialize, connect, and handle urgent or emotional conversations with care.
Here’s what Gorgias offers to help as well:
Whether you’re just getting started or trying to move beyond basic automation, Katie’s approach proves that coached AI outperforms out-of-the-box tools every time.
Want to coach your AI Agent like SuitShop? Book a demo to see how Gorgias can help you scale smarter.
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TL;DR:
At Gorgias Connect LA 2025, CX leaders from Tommy John, TUSHY, Triple Whale, and Talent Pop shared how support teams solve problems and drive revenue.
This shift, known as the support sales flywheel, doesn’t involve massive overhauls or shiny new tools. Instead, it means doing the small things exceptionally well, like picking up the phone, empowering agents to make judgment calls, and adding a personal touch where others automate.
These brands have shown that when support teams focus on consistency, connection, and conversion, the results compound. Every thoughtful interaction spins the flywheel faster, boosting loyalty, LTV, and revenue.
Ahead, we’re breaking down the most actionable takeaways so your team can start building its own support-led growth engine.
Watch the full panel here:
From scrappy install calls to AI-powered training, these CX leaders aren’t only talking about driving revenue, they’re doing it. Here’s how they’re turning support into a sales flywheel, and the tactics your team can start testing today.
“Customer service done right is actually a great source of revenue.” That’s how Tamanna Bawa, Tech Partner Manager at Triple Whale, kicked off the conversation on how data can transform CX from reactive to revenue-driving.
She advises segmenting customers based on purchase history and behavior to deliver more personalized, higher-converting interactions.
In a market where margins are razor-thin and ad costs are high, Tamanna emphasized that “incremental gains from personalization are the difference between companies that are thriving and the ones that are just surviving.”
What do you do when your hero product needs a cultural shift as much as it needs installation instructions? If you’re TUSHY, you send in your “Poop Gurus.”
Ren Fuller-Wasserman, Senior Director of CX at TUSHY, shared how her team launched a scrappy, free CX-led service that has now become a legendary video install program to help customers set up their bidets.
The real value wasn’t just tech support. As Ren put it, “It wasn’t about the actual install process, it was the encouragement they needed to change culture.” These calls sparked deeply personal moments (yes, even with cats and toddlers wandering in) and created the kind of emotional connection customers never forget.
Today, that service has evolved into a $15 paid add-on at checkout, and the customers who use it have significantly boost LTV and retention. It’s a masterclass in turning support moments into revenue through genuine human connection.
Phone support is back, and it’s becoming one of the most effective ways to turn conversations into conversions.
Ren from TUSHY swears by it. Her team uses customer phone numbers from abandoned carts to reach out directly. “You can send a hundred emails,” she said, “but a voicemail from a real person cuts through the noise.” Even if customers don’t answer, the fact that a brand called is memorable, and often enough to drive them back to checkout.
Max Wallace, the Director of CX Tommy John echoed the value of voice. His team recently implemented Gorgias Voice, using it to track conversion rates by agent. That visibility helps them identify what top performers are doing differently and replicate it across the team. “By the end of a tough call, customers often apologize for how they started. You can’t get that kind of de-escalation over email.”
In a world where inboxes are crowded and chat fatigue is real, a real voice builds real trust and real revenue.
Pro Tip: Don’t rush into phone if your other channels aren’t dialed in. “Master email and chat first. Then, start with limited phone hours. Taste it before scaling it,” said Armani Taheri, the co-founder of TalentPop.
For Max at Tommy John, revenue-driving support starts with two things: deep product knowledge and the freedom to bend the rules.
“We have five different fabrics for men’s underwear alone,” Max shared. To help customers choose the right one, agents need firsthand experience. That’s why Tommy John sends new products directly to the support team, so they can offer real, personalized recommendations like “Try Second Skin instead of Cool Cotton.”
But product knowledge is only half the equation. The other half is empowering agents to make judgment calls. Tommy John’s “Best Pair Guarantee” allows customers to try a product and get a refund or replacement if it’s not the right fit.
Agents are trained to prioritize retention, offering replacements instead of refunds, recommending better-suited products, and using their own discretion to keep customers happy.
As Max put it, “We don’t have really strict policies… we want them to use their best judgment.” That confidence translates into smoother resolutions, more cross-sells, and customers who stick around.
How do you train outsourced agents to drive revenue, without sounding like a sales team? According to Armani Taheri of TalentPop, it starts with confidence and context.
“You have to tailor-fit the training approach to each brand,” he explained. That means grounding agents in product knowledge, tone of voice, and customer journey before they ever interact with a shopper.
One of the most effective tactics is roleplaying. Armani’s team uses both live roleplays and AI-powered chat simulations to prepare agents for real conversations, pre-sales, post-sales, and everything in between. Tools like Replit and Lovable help create lightweight, brand-specific training environments agents can practice in at their own pace.
The goal isn’t to turn CX reps into hard sellers. It’s to give them the confidence and consistency to recognize revenue opportunities, and act on them in a natural, helpful way.
Ready to turn your CX team into a revenue engine? Here are some of the tools mentioned by the panelists that help make it happen:
Whether you're scaling phone support or experimenting with post-purchase outreach, the right tools make the flywheel spin faster.
They’re on the front lines with your most engaged customers, answering questions, easing doubts, and uncovering what really drives purchases. With the right tools and training, they resolve tickets and help close the sale.
With tools like Gorgias Voice, it’s easier than ever to connect the dots between conversations and conversions.
Want to see how your CX team can help drive growth?
Book a demo to see how Gorgias Voice powers sales through support.
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TL;DR:
Your CX team talks to customers every day. They know what’s confusing, driving purchases, and causing returns, because they hear it firsthand.
But all too often, those insights stay siloed in support tickets and live chat transcripts instead of informing the campaigns that shape the customer journey.
This post is here to change that. We’re breaking down the most valuable questions marketing teams should be asking their CX counterparts. When marketing and CX work together, you get more relevant messaging, smarter product positioning, and campaigns that convert.
Whether you’re planning a big seasonal push or just want to improve product education, this is where to start.
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Your CX team knows what makes shoppers hesitate. They’re the ones fielding questions like: Does this come in a larger size? Is it final sale? Will it arrive in time?
Beyond being pre-sale inquiries, they’re signals. They reveal what your customers care about most, and where your messaging may be falling short. When marketing teams tune into this, they can proactively address objections in landing pages, product detail pages (PDPs), emails, and top-of-funnel content.

At luxury jewelry store Jaxxon, Director of Customer Experience Caela Castillo saw firsthand how important it is to address these questions early.
“Chat used to be a support tool for repetitive questions and problem-solving, but now AI Agent takes care of that for us,” she said. Once those friction points were handled upfront, the CX team could focus on more meaningful conversations, and conversions improved.
And when AI recommended the wrong products? Conversions dropped. It was a clear signal that relevance matters, especially before the sale.
Ask your CX team:
“What do customers most often need to know before they buy, and how can we answer that earlier in the journey?”
Your best-selling product isn’t always your hero product. Sometimes, it’s that under-the-radar item that customers can’t stop talking about. The one that shows up again and again in reviews, chats, and post-purchase surveys.
The insight is gold for marketers. The key is to find out why people love it. Is it the fit? The feel? The results?
At online fashion brand, Princess Polly, Alexandria shared that her team expected Gen Z shoppers to lean on AI for recs, but what really influenced them was customer feedback. Reviews, not bots, built trust. That’s why campaigns built around real customer language and experiences often outperform the most polished product copy.
Shopping Assistant can turn those rave reviews into real-time action. It highlights top products using your Shopify product catalog to make personalized recommendations, proactively assists shoppers by using behavior signals, and even offers tailored discounts when they’re ready to convert. That means less guesswork, greater relevance, and an easier path to purchase.

Ask your CX team:
“Which product do customers rave about most, and what exactly are they saying?”
When customers are frustrated, it’s easy to blame the product. But in many cases, the issue isn’t quality, it’s communication.
At Shinesty, a men’s underwear brand, Molly Kerrigan, Senior Director of Retention, observed that high return rates often stemmed from unmet customer expectations.
She noted the importance of maintaining clear and consistent communication as the company grows, “We get a lot of praise from our customers, and they talk highly of our CX team after 1:1 interactions. We can’t lose that as we scale.”
Molly notes that using Gorgias AI Agent enables Shinesty’s customers to receive quick answers, freeing her team's time for more complex or sensitive issues.
Similarly, Princess Polly saw that delivering a standout customer experience meant being fast, consistent, and helpful at every stage. After switching to Gorgias, their support performance improved dramatically:
Before changing the product, try updating the messaging. Use insights from CX to rewrite descriptions, add size guides, include user-generated content, or even build a quick-fit quiz. Small tweaks help set clearer expectations and reduce unnecessary returns.
Ask your CX team:
“Which products are driving the most complaints, and what do customers wish they knew before buying?”
Confusion is a conversion killer. If a customer isn’t sure about how something works, what’s included, or whether it’s right for them, they’re more likely to bounce.
That’s why it pays to ask your CX team where customers get stuck. Is it a product feature that needs more context? A vague store policy? A missing detail on a bundle?
The good news is that most confusion is fixable. Start with the following steps:
If you’re using Shopping Assistant, you can go even further. It can detect when shoppers are hesitant and provides real-time nudges. Like an assistant who knows all your needs, Shopping Assistant automatically surfaces the questions customers are likely to ask when evaluating a product, so they’re equipped with the clarity they need to proceed to checkout.

TUSHY, a modern bidet brand, faced similar challenges. As bidets aren't mainstream in North America, shoppers often had concerns about product compatibility and installation. They’d ask questions like:
Without immediate answers, many potential buyers would abandon their purchase. To address this, TUSHY implemented Shopping Assistant, providing instant support. Taking this approach resulted in an 81% higher chat conversion rate compared to human agents and a 13x return on investment.
“The Shopping Assistant has been a game-changer for our team, especially with the launch of our latest bidet models. 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,” said Ren Fuller-Wasserman, Sr. Director of Customer Experience at TUSHY.
Ask your CX team:
“Where do customers get confused most often—and how can we clear that up sooner?”
Your CX team picks up on patterns that analytics sometimes miss. They hear which items customers ask about in the same chat, which products get added to carts together, and which pairings people reorder time and time again.
That intel is a goldmine for bundling and upselling. It helps you build smarter campaigns that feel relevant and drive real value.
Zoe Kahn, owner of Inevitable Agency and former VP of Retention and CX at Audien Hearing, emphasizes the importance of using AI to enhance customer interactions.
“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.”
With Shopping Assistant, you can act on these insights in real time. It will surface personalized product pairings, bundle suggestions, or accessories based on customer behavior. All before they hit the checkout page.

Returns cut into your margins and chip away at trust. Most of the time, they’re not caused by poor-quality products. They happen because expectations weren’t met.
Your CX team already knows which items come back the most and why. Maybe the color doesn’t match the photos. Perhaps the fit runs small, or the product description left out a crucial detail.
Instead of pushing the product harder, reframe how you present it. Add real customer photos. Include fit notes or a sizing chart. Call out anything that might surprise the customer post-purchase. A little clarity upfront goes a long way in reducing returns and boosting retention.
At Pepper, an intimates brand specializing in bras for small-chested bodies, they recognized the importance of pre-sale education. When customers have sizing questions, their AI Agent, Penelope, can provide immediate assistance.
“Penelope takes the information we give her and responds better than a Macro. She tailors it so that it sounds like a natural conversation between two people,” said Gabrielle McWhirter, CX Operations Lead at Pepper.
By proactively providing instant support, Pepper improved customer satisfaction and saw an 18% uplift in average order value.
Ask your CX team:
“Which products get returned the most—and what could we do upfront to change that?”
Before you launch your next campaign, start with a quick sync with your CX lead. They already know what your customers need to hear. You just have to ask.
From fixing messaging gaps to surfacing the right products at the right time, these insights help you connect with customers in personal, timely, and relevant ways.
Tools like Shopping Assistant make it easier than ever to act on this data in real time. You can turn CX knowledge into dynamic recommendations, personalized nudges, and smarter discounts.
Ready to see how you can improve your online shopping experience? Book a demo to see how Gorgias Shopping Assistant engages customers in real-time.

TL;DR:
Today’s best marketing starts with your customers.
According to Forrester’s 2024 research, “Customer-obsessed organizations reported 41% faster revenue growth, 49% faster profit growth, and 51% better customer retention than those at non-customer-obsessed organizations.”
Support teams interact with hundreds or thousands of customers every week, collecting valuable insights in the process. This voice of the customer (VOC) data is a goldmine for marketers, but it too often stays siloed among CX teams.
Ahead, we’ll break down how ecommerce brands can tap into CX insights to drive better marketing.
CX can play a crucial role in driving growth, but many brands aren’t leveraging it for marketing insights yet.
When connected to marketing, CX becomes a proactive engine that fuels better segmentation, sharper messaging, smarter campaigns, and more personalized content.
Support functions collect objections, complaints, compliments, and pre-purchase questions. When you capture and apply those insights, your marketing can target the precise roadblocks—and key sales differentiators—customers care about.
Here’s how to turn CX insights into a high-impact marketing strategy, with real examples from brands using Gorgias.
When you want to sharpen your brand messaging, there’s no better place to look than your support inbox. Your support inbox is a rich resource full of information specific to your brand and your customers.
Tools like Gorgias Ticket Insights help surface recurring themes, top questions, and friction points across all conversations. By analyzing these patterns, marketers can identify the exact words customers use to describe problems, questions, or product feedback and then reflect that language across ads, landing pages, and emails.
Spikes in tickets around specific topics (sizing, shipping timelines, and materials, for example) are insights marketers can use to update and improve corresponding content.
This can increase confidence and conversion on key pages.
By incorporating the same terminology and phrasing customers use in support conversations, brands can also increase resonance across ads, emails, and social media. Messaging that mirrors the customer’s language builds trust and helps audiences feel understood.
Ask your CX team 💬 What product issues or themes have emerged this quarter?

For example, cordless heating cushion brand Stoov® used Ticket Fields in Gorgias to understand and resolve a ticket spike. By figuring out that some customers were dissatisfied with the battery life of its core product offering, the team was able to add an optional upsell. For €20, shoppers now have the option to purchase a larger battery.
The results were meaningful: the brand saw 50% of customers opt for this battery, resulting in a 10% increase in average order value (AOV). And while the team saw a significant increase in revenue, they saw no increase in support ticket volume.
Most marketers rely on transactional data—like past purchases or time since last order—to build audience segments. But support data reveals a whole new layer of context: behavior, concerns, sentiment, and urgency.
Tools like Gorgias’s Ticket Insights and Ticket Fields allow CX teams to customize different properties attached to tickets. Agents can fill these out to capture data more accurately.
Here’s how these types of tools work: tickets come with a mandatory field for return reasons, product feedback, contact reason, etc. Before the agent closes the ticket, they use a dropdown menu to fill out the ticket field.
Studying support interactions helps answer key questions around why customers are getting in touch. This data can provide marketing teams with a way to build smarter segments for campaigns or personalized journeys.
For example, if one product is getting a large amount of inquiries, marketing teams could segment customers interested in those products and launch pre-sales education campaigns.
Fashion brand Psycho Bunny switched from Zendesk to Gorgias to improve access to reporting tools that surfaced customer patterns and support trends.
“By cross-referencing our Gorgias data with insights around basket size, product performance, and store performance, we can inform broader business decisions. For example, we can see if a certain store location generated more tickets or how many incoming queries are about a certain product,” says Jean-Aymeri de Magistris, VP IT, Data & Analytics, and PMO at Psycho Bunny.
By integrating insights like these with marketing workflows, teams can build more relevant segments that improve retention and engagement.
Ask your CX team 💬 Which customer segments are most likely to churn or repurchase?
Chat campaigns are proactive messages that trigger based on real-time behavior and context. You can use CX trends to design campaigns that directly address common objections, answer FAQs, or deliver tailored offers.
Start by reviewing your most common pre-purchase questions with your CX team. Then, create chat prompts that address those concerns exactly where they arise. For example, a sizing guide prompt on product pages or a shipping FAQ in the cart.
Make sure your message feels helpful and not overly salesy. Conversational AI assistants like AI Agent can also tailor responses in real-time, helping customers get what they need without leaving the page.

Pepper, a size-inclusive bra brand, put this into practice by combining their AI Agent (named Penelope) with targeted chat campaigns to guide shoppers through one of their most common friction points: sizing. Thanks to insights from their support team, Pepper created messaging that helped customers find the right fit instantly. The result was an 18% uplift in average order value.
“With AI Agent, we’re not just putting information in our customers’ hands; we’re putting bras in their hands. With Penelope on board, we’re turning customer support from a cost center to a revenue generator,” says Gabrielle McWhirter, CX Operations Lead at Pepper.
Ask your CX team 💬 How are customers reacting to recent promotions or launches?
When shoppers hesitate at checkout, it’s often because they don’t have the information they need.
Tapping into support conversations allows CX teams to identify common objections. They can then share those insights with marketing to refine product messaging, improve product pages, ads, and marketing campaigns.
Use customer service data to identify the top three objections customers have before converting. These might be concerns about sizing, compatibility, delivery time, or product setup. Then, pair that knowledge with a proactive AI sales tool like Shopping Assistant to offer timely answers that move shoppers closer to purchase.
For example, TUSHY, a modern bidet company, found that many prospective customers were hesitant because they weren’t sure how difficult the installation would be. By using a real-time shopping assistant to address these concerns directly on-site, TUSHY was able to guide shoppers past uncertainty.

Ask your CX team 💬 What are the top three reasons customers contact us before they buy?
If you want to know what content your customers actually need, your Help Center holds the answers. Real customer questions are found right in Help Center search queries and article analytics.
By tracking which articles are most viewed, most searched, and most frequently updated, marketers can spot common knowledge gaps and fill them with high-value content.
Start by reviewing your Help Center Statistics to see which articles are performing well, which ones are underutilized, and what terms customers are searching for.
If an article about “returns policy” is getting a spike in views, that’s your cue to simplify the policy or preempt questions with a dedicated email campaign. Marketing teams could also use this insight to build FAQ-rich landing pages, preempt questions in email flows, or even turn top-performing help content into organic blog posts or performance ad copy.

You can also use Gorgias's Dashboard to spot emerging trends across all your channels. This custom reporting feature lets you choose from various charts that reveal high-level patterns—like the most common contact reasons or sudden spikes in ticket volume—giving marketers early insight into shifting customer sentiment and trending topics across social platforms.
Ask your CX team 💬 Which articles in our Help Center are most searched right now?
When support and marketing teams collaborate, you unlock a cycle of continuous improvement. CX teams surface the insights, marketing turns them into strategy, and both sides drive measurable results.
Here’s how to make it work:
We need to reframe CX as a proactive function that drives revenue.
Support teams already have the answers marketers are searching for. You just need the tools to tap into them. Gorgias makes that easy, with flexible reporting features, powerful AI, automated tagging, and integrations that bridge the gap between CX and marketing.
Want to connect your support data to better marketing?
Explore Gorgias’s analytics tools or book a demo to speak to a product expert about how to integrate your support strategy with marketing.
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TL;DR:
Automated responses don’t actually resolve anything. In reality, they increase customer wait time.
What a customer really wants is immediate resolution, whether they’re looking to cancel an order, change a shipping address, or pause a subscription.
So, how do you go beyond automated text responses? AI Agent Actions.
Below, we’ll go over the 7 most common customer service requests you can resolve with AI Agent Actions, so your team gets time back to strengthen customer relationships, increase revenue, and improve your CX strategy.
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AI Agent Actions are tasks AI Agent can complete for your customers, such as canceling an order or updating a shipping address.
Instead of handing it off to a human agent, AI Agent resolves the ticket by connecting to your ecommerce apps and performing the action on its own.
You get maximum control over when and how Actions are executed. Before performing the Action, AI Agent asks customers for confirmation, respecting your processes and maintaining a high level of customer service. Once an Action has been taken, you can even share feedback with your AI Agent to reinforce its behavior or finetune it further.

Pro Tip: Unlike Guidance, which tells AI Agent how to respond in a conversation, Actions determine what happens. It’s the difference between saying “I’ll refund your order” and doing it.
Related: How AI Agent works & gathers data
Ready to resolve requests in seconds? Activate these pre-built Actions in Gorgias to keep your team efficient and your customers happy.

Action to use: Update shipping address
Supported apps: Shopify, ShipMonk, ShipHero, ShipStation
Incorrect shipping addresses lead to costly re-shipments, delays, and even refunds. Catch errors early to keep customers satisfied and excited about their order.

Why do you need this Action?
The reality is your agents aren’t available 24/7. Unless you hire a team to cover night and weekend shifts (which is unlikely), requests will be missed. AI Agent fills in that gap, handling time-sensitive issues when your team is off the clock. Missing them isn’t just about poor customer experience—it can also lead to extra costs, like reshipping orders.
Action to use: Cancel order
Supported apps: Shopify, ShipMonk, ShipHero, ShipStation
Perhaps a customer ordered the wrong item, chose the wrong size, used the wrong card, or simply changed their mind. Allow them to quickly cancel their order and receive a refund in one go.

“Actions responds to tickets within about 30 seconds and is available 24/7. Regardless of when a customer places their order, the likelihood of quickly catching and canceling the order has increased by 70% since we started using Actions. It’s an exceptional result."
—Jon Clare, VP of Customer Service at Trove Brands
Actions to use:
Supported app: Shopify
It happens—shoppers order the wrong size or color and want to change their order immediately. Regardless of the reason, make their new decision easy to implement. Quick, accessible order updates prevent returns, lost revenue, and, most importantly, customer disappointment.
Here’s what the replace order item setup looks like in Gorgias:

Pro Tip: If you have unique workflows, you can create advanced, multi-step Actions and connect to your tools beyond our default integrations. This option requires some tech know-how (like custom HTTP requests), so feel free to bring in your developers for assistance.
Actions to use:
Supported apps: Stay AI, Recharge, Subscriptions by Loop, Skio, Seal Subscriptions
Subscriptions shouldn’t be all or nothing. Let customers skip a shipment or pause their subscription, so they can come back when they’re ready. Giving them full control lets them manage their subscription on their own terms, reducing churn rate in the process.
Here’s how AI Agent handles a skip shipment request:

Action to use: Reship order for free
Supported apps: Shopify, ShipMonk
No customer expects a lost or damaged order. Let customers know that you have their backs by reshipping a new order free of charge. Fast resolutions during unexpected events demonstrate your commitment to customer satisfaction.
“An instant response builds confidence. We live in a world with short attention spans, so customers appreciate how quickly we can respond to their inquiries. Customers aren’t worrying unnecessarily for longer than they have to for an address change or order cancellation.”
—Mia Chapa, Sr. Director of Customer Experience at Glamnetic
Action to use: Send return shipping status
Supported app: Loop
Customers want to know that their return package is on its way to you, so they can redeem their refund. Easily send them a shipment tracking link to give them that peace of mind.
Action to use: Get order info
Supported apps: Shopify, ShipHero, ShipMonk, ShipStation, ShipBob, Wonderment
Based on Gorgias data, order status ranks among customers' top 10 questions for support teams. Reassure your customers with quick updates on their orders, including product details, shipping progress, expected delivery date, and other helpful information.
Here are a few helpful setup tips to make sure Actions run without a hitch:
If you want…
AI Agent Actions can get you there.
You’ve now seen how Actions can resolve tickets in a snap—no unnecessary handoffs, canned responses, or long response times.
Book a demo to see AI Agent Actions work in real time and start automating what you shouldn’t be doing manually anymore.
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TL;DR:
AI Agent is built to deliver fast, accurate support at scale, but like any teammate, it performs best when given clear and specific instructions.
That’s where Guidance comes in. Writing structured prompts that tell your AI Agent exactly what to do in a given scenario helps reduce escalations, speed up resolutions, and create a more consistent customer experience.
One simple, repeatable way to do that is with the “When, If, Then” framework.
In this post, we’ll show you how it works, using examples from our Gorgias Academy course, Improve AI Agent with Better Guidance.
You’ll learn how to write Guidance that results in:
Let’s break it down.
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Guidance is how you tell your AI Agent what to do. It’s a set of instructions that outlines how your AI Agent should respond in specific situations.
When Guidance is available, your AI Agent follows it first, even before checking your Help Center or website content.
That means if your Guidance is missing, unclear, or incomplete, your AI Agent might escalate the ticket, or worse, give a confusing or unhelpful response. Here’s an example:
Let’s say a customer wants to return an item. A human agent would send them a link to the return portal and explain the steps. But without that instruction in Guidance, your AI Agent might skip straight to escalation, turning a simple request into unnecessary work for your team.
That’s why clear, step-by-step Guidance is key to help your AI Agent respond the way your best support agent would.

Learn more: Create Guidance to give AI Agent custom instructions
Sometimes it’s hard to know where to start when writing Guidance. The “When, If, Then” framework gives you a simple, repeatable structure to follow, so there’s no need to guess.
Taking this approach mirrors how AI Agent processes information behind the scenes. When you write clear Guidance, your AI Agent can follow it step by step, just like a support teammate would.
Let’s walk through the three parts of the framework.
Start by identifying the situation your Guidance applies to. This is the trigger or scenario. Use it as the title of your Guidance so it’s easy to find later.
Example:
Keep it simple and action-oriented. You’re setting the stage for what comes next.

Once you’ve defined the scenario, add any conditions that determine what should happen. “If” statements help your AI Agent understand what to do based on specific details, like timing, order history, or customer tags.
Example:
Use as many “if” conditions as needed to guide different outcomes. Just make sure you cover all the possibilities so your AI Agent doesn’t get stuck.
This is where you tell your AI Agent exactly what to do. Be specific and use bullet points or numbered steps to keep things clear.
Example:
The more clearly you outline the steps, the more consistently your AI Agent will perform.
The framework keeps your Guidance simple, structured, and easy to understand—for both your team and your AI Agent. When your AI Agent knows exactly what to do, it can deliver fast, accurate, and helpful responses that keep customers happy.
Say a shopper messages your store asking to return an item and you want AI Agent to send them to your return portal.
Here’s how this looks in a complete piece of Guidance:
WHEN a shopper asks to return an order:
IF the order was placed less than or equal to 15 days ago,
THEN
These nine scenarios come up constantly in ecommerce support, and they’re perfect candidates for automation. They follow predictable patterns and are quick to resolve when your AI Agent knows what to do.
Use the examples below to jumpstart your setup. Each one is written using the When, If, Then framework and can be copied directly into Gorgias.
WHEN a customer asks about their order status:
IF tracking information is available,
THEN
IF tracking information is unavailable,
THEN
WHEN a customer inquires about product sizing for [item name]:
IF the customer asks what size to get, or mentions they’re unsure about sizing,
THEN
WHEN a customer requests to change their shipping address:
IF the order has not been fulfilled,
THEN
IF the order has already been fulfilled,
THEN
WHEN a customer asks to cancel their order:
IF the order has not been fulfilled,
THEN
IF the order has already been fulfilled,
THEN
WHEN a customer asks about returning an item:
IF the return is within the allowed return window of [x] days after the order was received,
THEN
IF the return window has expired,
THEN
WHEN a customer inquires about discounts or promo codes:
IF there is an active promotion for [item name],
THEN
IF there are no active promotions for [item name],
THEN
WHEN a customer requests to pause their subscription:
IF the customer has an active subscription,
THEN
WHEN a customer asks about product restocking:
IF a restock date is available,
THEN
IF the restock date is unknown,
THEN
WHEN a customer inquires about international shipping:
IF international shipping is available,
THEN
IF international shipping is not available,
THEN
Pro Tip: Test out your Guidance by going to AI Agent > Test, and iterate as you go.
If your AI Agent isn’t following your Guidance, or it’s escalating tickets you thought it could handle, run through this quick checklist to spot the issue:
Don’t have time to write Guidance from scratch? The good news is AI can help with that, too.
AI-generated Guidance is available for all AI Agent subscribers. This feature analyzes your historical ticket data and uses it to generate ready-to-use, customizable prompts for your AI Agent.
Here’s what it does:

Clear, structured Guidance is the key to unlocking better performance from your AI Agent. With just one well-written “When, If, Then” prompt, you can reduce escalations, speed up resolutions, and give your shoppers a smoother experience.
Not sure where to start? Try writing Guidance for one common question today—like returns, order status, or promo codes. Or, if you want to go deeper, check out our free Gorgias Academy course.


