TL;DR:

• Customer experience (CX) encompasses every interaction a customer has with your brand, from first discovery through post-purchase support
• CX differs from customer service by including the entire journey, not just support touchpoints
• Great ecommerce experiences drive higher retention rates, increased lifetime value, and stronger word-of-mouth marketing
• Measuring CX requires tracking both quantitative metrics (CSAT, NPS) and qualitative feedback across all channels
• Modern CX relies on omnichannel tools, AI automation, and self-service options to meet customer expectations

Customer experience shapes how shoppers perceive your brand at every touchpoint. From the moment they discover your store through ads or social media to their post-purchase support interactions, each moment contributes to their overall impression. 

For ecommerce brands, this means coordinating everything from your website design to your shipping notifications to your return process. The brands that excel at CX turn one-time buyers into loyal customers who spend more and recommend your products to others.

What is customer experience?

Customer experience is the overall perception a shopper has of your brand based on every interaction they have with you. This means everything from seeing your Instagram account to unboxing their order and getting help from your support team shapes how they feel about your business.

CX includes three types of responses from your customers. Cognitive responses are what they think about your brand. Emotional responses are how your brand makes them feel. Behavioral responses are the actions they take, like making a purchase or leaving a review.

Your customer experience spans multiple touchpoints and stages:

• Discovery touchpoints: Social media ads, search results, influencer mentions, word-of-mouth recommendations
• Shopping touchpoints: Website browsing, product pages, checkout process, payment options
• Fulfillment touchpoints: Order confirmation emails, shipping notifications, delivery experience, packaging
• Support touchpoints: Live chat conversations, email responses, return processes, help center articles

Each touchpoint either builds trust or creates friction. When you nail the experience across all these moments, customers come back for more.

How is customer experience different from customer service?

Customer service is reactive support when problems arise. Customer experience is proactive engagement across your customer's entire journey with your brand.

Think of customer service as one piece of a much larger puzzle. Customer service focuses on solving problems after they happen, while customer experience shapes the entire journey that a customer goes through — from their welcome email, all the way to their conversation with an agent after purchase.

Why customer experience matters in ecommerce

Customer experience becomes your advantage when products and prices look similar across brands. A better experience makes shoppers choose you, come back again, and recommend you to others.

These are the main benefits of investing in customer experience as an ecommerce business.

Good first impression for new customers

A strong first experience builds confidence. When shoppers understand your product, know what to expect, and can get quick answers, buying feels easy instead of risky. Clear details remove second thoughts. Helpful support fills in any gaps. A checkout that “just works” keeps people moving forward rather than leaving you for a competitor.

Lower operating costs

When customers can find answers on their own, your team spends less time on repetitive questions. Good CX practices like communicating before issues pop up help your team avoid a wave of preventable tickets. And when your product info is accurate and helpful? You’ll notice fewer returns and disappointed reviews. All of this reduces workload and saves money as you grow.

Related: The hidden power and ROI of automated customer support

Stronger brand reputation

People love to talk about brands that make their lives easier, and that starts with the customer experience. A well-thought-out customer experience becomes strong enough to inspire positive word-of-mouth reviews, viral social shares, and a better reputation.

What makes a great customer experience in ecommerce

A great customer experience is the one shoppers barely notice because nothing gets in their way. The path from browsing to buying feels simple, and customers never have to wonder what to do next. When the experience feels this easy, it builds trust — and trust becomes the reason they come back.

Here are the core components that lead to that kind of experience.

Accuracy

As AI becomes essential to customer experience, accuracy is the new standard customers judge you by. Speed matters, but it's worthless if the answer is wrong. Shoppers want one-touch resolutions, not back-and-forth conversations or unnecessary escalations.

Related: AI Agent keeps getting smarter (here’s the data to prove it)

Speed

Speed still matters because most shoppers want to get in, get what they need, and get out. When they have a question about items already in their cart, a quick answer can be the difference between a completed order and an abandoned one. Slow support creates doubt, while fast responses and reliable shipping options keep momentum going and help customers finish their purchase with confidence.

Read more: Why faster isn’t always better: The pitfalls of fast-only customer support

Personalization

A 2024 survey found that about 80% of consumers expect personalized interactions from the brands they shop with personalization expectations. When recommendations feel relevant, customers feel understood and are more likely to come back.

Transparency

All your customers want is honesty. Showing accurate inventory, reliable shipping estimates, and clear return policies all build trust from the very start. Make your expectations clear, and you're less likely to face returns, complaints, and frustrated customers.

Accessibility

The best customer experiences feel intuitive. Give shoppers a clear path to the details they need, whether they’re checking sizing or reviewing return policies. Nothing should feel tucked away. Visible support options and intuitive navigation help customers move toward checkout without second-guessing the process.

How to measure customer experience (metrics and KPIs)

You need both numbers and stories to understand your customer experience performance. Quantitative metrics show you what's happening. Qualitative feedback explains why it's happening.

CSAT

Customer Satisfaction (CSAT) measures immediate happiness with specific interactions. Ask customers to rate their experience after support conversations or purchases. This gives you real-time feedback on individual touchpoints.

NPS

Net Promoter Score (NPS) measures overall loyalty by asking how likely customers are to recommend your brand. Scores range from zero to 10. Promoters (9-10) drive growth through referrals. Detractors (0-6) may damage your reputation through negative word-of-mouth.

Customer effort

Customer Effort Score (CES) measures how much work customers put in to get help. Lower effort scores predict higher loyalty. Customers remember when you make things easy for them.

Handle times

Average handle time (AHT) and first contact resolution (FCR) measure your support team's efficiency. While not direct customer experience metrics, they impact how customers perceive your responsiveness and competence.

Churn rate

Churn rate shows the percentage of customers who stop buying from you. High churn often signals experience problems that need attention. Track churn by customer segments to identify patterns.

Customer lifetime value

Customer lifetime value (CLV) predicts total revenue from each customer relationship. Improving experience is one of the most effective ways to increase CLV. Happy customers buy more often and spend more over time.

What you need to run your first customer experience function

A customer experience strategy is the plan for how your brand treats customers from the moment they discover you to the moment they buy again. The easiest way to think about it is in layers.

1. Customer-facing interactions

This is the top layer and the part customers notice first. Clear product pages, helpful support, fast shipping updates, and easy returns all belong here. These touchpoints affect how customers feel about buying from you. A strong strategy starts with deciding what “a great experience” looks like at each of these moments.

Quick Tip: Start small. Pick one or two touchpoints that cause the most friction, like a product page or the returns process, and improve them first. Early wins give you the confidence to keep expanding your CX foundation without getting overwhelmed.

2. Customer research

To deliver an unforgettable experience, you need to know what customers actually want. This layer focuses on gathering real feedback from reviews, surveys, and customer conversations. You don’t need a complex process for this — just a consistent way to spot patterns and record what customers love and don’t love.

Read more: How to use CX data to improve marketing, messaging & conversions

3. Journey planning

Once you understand your customers, map out their relationship with your brand from first click to repeat purchase. It can be a simple outline that shows the main steps customers take and where friction typically occurs. This layer helps you prioritize the improvements that will have the greatest impact.

4. Roles and responsibilities

It’s time to get in the weeds: decide who owns which part of the customer journey. Who will handle product info? Respond to support tickets? Oversee shipping and logistics? Clear ownership ensures a consistent experience even as the business grows.

Here are some guiding questions to help decide who should own what:

• Which parts of the customer journey should the CX team own right now? This might include support responses, FAQs, returns communication, and post-purchase messaging. It typically wouldn’t own inventory, shipping operations, or product page content.
• Which tasks take the most time or create the most friction for customers? These become your first areas to delegate or hire for.
• If you could hire one person next, what CX work would they take over immediately? This helps you prioritize whether you need a support specialist, a CX operations role, or someone focused on retention.

5. Tools and systems behind the scenes

This is the foundation layer that supports your entire CX function. You need tools that bring customer data together, help your team communicate with shoppers, automate repeat questions, and show how you’re performing. A good CX platform becomes the backbone of your operation.

We recommend using an ecommerce-specific helpdesk with the following features:

• Omnichannel: Your helpdesk should integrate all your support channels — from email and chat to SMS and social media — and funnel them into a single inbox for quick responding. 
• AI-powered chat features: Customers ask questions even when your team is offline. Ensure you can resolve their issues with an AI chat trained on your policies and can deliver accurate answers 24/7.
• In-depth analytics: Improvement is key to meeting customer expectations. It’s imperative that your tool comes with analytics on agent performance, automation opportunities, customer satisfaction, and product insights.

Read more: Best AI helpdesk tools: 10 platforms compared

Put your customer experience strategy into motion

You now have the building blocks of what makes a strong customer experience. The next step is to put those elements into practice by improving the touchpoints customers feel most strongly about and tightening the systems that support them.

AI-powered support helps you do this at scale by resolving repeat questions instantly and giving your team more time for work that moves the business forward.

Book a demo to explore how leading ecommerce brands use Gorgias to automate up to 60% of support inquiries.

{{lead-magnet-2}}

TL;DR:

• Conversational commerce uses real-time messaging to turn conversations into sales through chat, AI, and messaging apps
• Success comes from focusing on high-intent moments across the customer journey, from pre-purchase guidance to post-purchase automation
• The best tech stack for conversational commerce combines AI agents, helpdesks, and Shopify data for personalized experiences
• Future trends include agentic assistants, visual search, and stronger safeguards for customer trust

Online shopping has transformed from simple catalogs to live selling to conversational commerce — all in just a few years. The advent of conversational AI has turned shopping into a collaborative activity, with AI agents, or smart chatbots, assisting with searches, recommendations, and purchases.

As conversational commerce evolves, brands that embrace it now will be best positioned to nurture their customer base and unlock new revenue opportunities. 

In this post, we'll explore how AI is reshaping conversational commerce, where it drives the most ROI, and the technology you need to implement it successfully today and beyond.

{{lead-magnet-1}}

What is conversational commerce?

Conversational commerce is a sales and support strategy that uses real-time conversations to help customers shop, often via a conversational AI tool. This means you can sell products and solve problems through chat, messaging apps, and voice assistants. 

Think of it as bringing your store into the conversation. When a customer asks “Does this jacket run large?” through chat, they get an instant answer that helps them decide to buy. 

The core channels for conversational commerce include:

• Live chat widgets: Pop-up chat boxes on your website where customers can ask questions
• AI assistants: Smart chatbots that understand natural language and can complete tasks
• Messaging apps: WhatsApp, Facebook Messenger, and SMS where customers already spend time
• Voice assistants: Phone support powered by AI that can handle calls 24/7

This approach bridges the gap between shopping and support. Your support team becomes a revenue driver by helping shoppers feel confident and ready to buy.

How AI is changing conversational commerce for ecommerce brands

AI is the engine making conversational commerce work at scale. Modern AI can understand what customers mean, not just what they type, making conversations feel natural and helpful.

Round-the-clock conversations with generative AI

Generative AI and large language models have changed everything. These systems can understand context, detect emotions, and respond like a human would. This means your AI can handle complex questions about sizing, shipping, or product compatibility without sounding robotic.

You can train AI on your specific brand voice, policies, and product information. When a customer asks about your return policy, the AI responds using your exact guidelines and tone. This makes every automated conversation feel authentic and accurate.

Conversion uplift with proactive messaging

Modern AI doesn't just wait for customers to ask questions. It watches shopper behavior and jumps in at the right moment to help.

If someone spends three minutes on a product page without buying, AI can offer help with sizing or answer common questions. If a customer adds items to their cart but hesitates at checkout, the AI can address concerns about shipping costs or return policies.

This proactive approach catches customers before they leave your site. The result is fewer abandoned carts and more completed purchases.

Transparent escalations from AI to human, and vice versa

Customers want to know when they're talking to AI versus a human. Smart brands are transparent about their AI use and make it easy to escalate to human agents when needed.

The key is using AI to enhance the experience, not replace human connection entirely. Set clear boundaries for what your AI can handle and always provide an obvious path to human help for complex issues.

Where conversational commerce drives ROI across the customer journey

Conversational commerce impacts every touchpoint from discovery to retention. Here's where it delivers the biggest returns.

Pre-purchase guidance and conversion lift

When shoppers have questions about products, fast answers make the difference between a sale and a lost customer. Conversational tools provide instant responses about sizing, materials, compatibility, and shipping.

AI agents can also act as personal shoppers. They analyze browsing behavior and recommend products that match what the customer is looking for. This guidance removes friction and gives shoppers confidence to buy.

Key benefits include:

• Instant answers: No waiting for email responses or searching through FAQ pages
• Personalized recommendations: AI suggests products based on browsing history and preferences
• Confidence building: Customers feel supported in their purchase decisions

Cart recovery and reduced abandonment

Cart abandonment costs ecommerce brands billions in lost revenue. Conversational commerce offers a direct solution by engaging hesitant shoppers at checkout.

Instead of generic pop-ups, AI can start personalized conversations addressing specific concerns. Maybe the customer is worried about shipping costs or return policies. The AI can explain your policies or offer a small discount to encourage completion.

This personal touch turns potential lost sales into revenue. Customers appreciate the help and are more likely to complete their purchase.

Post-purchase automation and lower costs

The most common support tickets are post-purchase questions like, “Where is my order?” AI can handle these inquiries instantly, providing tracking updates, processing returns, or modifying orders without human intervention.

This automation dramatically reduces ticket volume for your support team. Your agents can focus on complex issues that require human judgment while AI handles the routine stuff. The result is lower support costs and faster resolution times.

Retention campaigns and higher lifetime value

Conversational channels like SMS and WhatsApp are perfect for staying connected with customers after purchase. You can send personalized offers, new product announcements, or win-back campaigns directly to their phones.

These messages feel more personal than email because they arrive in apps customers use daily. Higher engagement leads to more repeat purchases and stronger customer relationships.

Best practices to implement conversational commerce in 2025

You don't need to overhaul everything at once. Smart implementation starts small and scales based on results.

Start with high-intent touchpoints

Focus on pages where conversations will have the biggest impact. These are places where customers are actively making decisions or need help.

High-impact locations include:

• Product pages: Answer questions about features, sizing, and compatibility
• Checkout pages: Address last-minute concerns about shipping or returns
• Order tracking pages: Provide instant updates to reduce support tickets

Deploy chat on these pages first. Measure the impact before expanding to other areas of your site.

Integrate data and systems

Conversational commerce works best when connected to your other tools. Integration with Shopify, your customer relationship management system, and shipping software gives agents complete context.

When a customer starts a chat, your agent (human or AI) can see their order history, past conversations, and loyalty status. This eliminates the need for customers to repeat information and enables truly personalized service.

Measure conversation-to-conversion

Track metrics that matter for your business, not just support efficiency. While response time is important, the real goal is understanding how conversations impact revenue.

Key metrics to monitor:

• Conversion rate from chat: How many chat conversations lead to purchases
• Average order value: Whether chat customers spend more than average
• Cart recovery rate: How many abandoned carts get saved through conversation

Set up proper attribution to connect conversations to sales. This proves the value of your conversational commerce investment.

Keep human handoff obvious

AI is powerful but can't solve every problem. Make it easy for customers to reach human agents when needed.

Train your AI to recognize complex issues, frustrated language, or specific keywords that require human help. Display the “talk to a human” option prominently in your chat interface. This builds trust and ensures customers never feel trapped in automation.

The tech stack for conversational commerce on Shopify

Building effective conversational commerce requires the right tools working together. For Shopify brands, this means platforms that integrate deeply with your store data.

AI Agent for support and sales

A modern AI Agent does more than answer questions. It's trained on your brand voice and policies to handle both support tickets and sales conversations.

Your AI can resolve common inquiries like order tracking while also guiding shoppers with product recommendations. It can apply discount codes, answer pre-sale questions, and even upsell related products. This makes it a 24/7 revenue driver, not just a support tool.

Read more: How AI Agent works & gathers data

Ecommerce-centric helpdesk

Customers contact you through email, chat, social media, SMS, and phone. A helpdesk made for ecommerce brings all these conversations into one place.

This gives your team complete visibility into every customer interaction. They can see the full conversation history regardless of channel and provide consistent, informed responses. No more asking customers to repeat their issues or losing context when switching between platforms.

Voice and SMS for real-time engagement

Phone and text support shouldn't require separate systems. Integrated voice and SMS solutions work within your existing helpdesk.

Features like interactive voice response menus help customers self-serve common requests. SMS is perfect for order updates, shipping notifications, and marketing campaigns. The ability to seamlessly move conversations between channels gives customers ultimate flexibility.

What the future of conversational commerce looks like for DTC brands

Several trends will shape conversational commerce in the next few years. Preparing for these changes gives you competitive advantage.

Agentic assistants and guided selling

The next evolution is agentic AI that can complete multi-step tasks autonomously. Instead of just answering questions, these assistants will take action on behalf of customers.

Imagine a customer saying “I need to exchange this shirt for a larger size.” An agentic assistant could process the return, generate a shipping label, create a new order for the correct size, and send tracking information — all in one conversation.

This level of automation makes shopping truly effortless. Customers get what they need without jumping between systems or waiting for human agents.

Read more: Stop resolving these 7 tickets manually (Use AI Agent Actions instead)

Visual and voice search and faster discovery

How customers find products is changing rapidly. Soon, shoppers will upload photos of items they like and ask AI to find similar products in your store. Voice search will become more sophisticated, letting customers describe what they want in natural language.

To prepare, ensure your product catalog has rich descriptions and proper tagging. This helps AI understand and match products to these new search methods. Brands that optimize for visual and voice discovery will capture more traffic.

Security and safeguards in AI commerce

As more transactions happen through conversations, security becomes critical. Customers need to trust that their data is safe and their interactions are legitimate.

This means implementing strong fraud prevention, being transparent about AI use, and following privacy-by-design principles. Building customer trust requires balancing personalization with privacy protection. Brands that get this right will have lasting competitive advantage.

Turn conversations into revenue with Gorgias

Gorgias combines conversational AI, an omnichannel helpdesk, and deep Shopify integration to deliver true conversational commerce. Our AI automates up to 60% of common inquiries while increasing conversion rates through personalized shopping assistance.

Ready to see conversational commerce in action? Book a demo to learn how Gorgias can level up your customer experience. 

{{lead-magnet-2}}

TL;DR:

• Conversational commerce uses real-time messaging to turn support into sales opportunities
• Brands see higher conversion rates through instant answers to pre-purchase questions
• AI and automation handles repetitive inquiries while agents focus on complex issues
• Personalized recommendations and proactive messaging increase average order value
• Customer data from conversations powers smarter marketing and loyalty programs

Ecommerce and retail accounted for over 35% of conversational commerce spend in 2023, totaling $9 billion globally. This isn't surprising — conversational commerce delivers what customers demand nowadays: immediate, personalized responses wherever they shop. 

We’ll explain what conversational commerce is, its benefits for ecommerce brands, and how to implement it effectively.

What is conversational commerce?

Conversational commerce is the practice of using real-time, two-way conversations as your storefront, turning every customer interaction into an opportunity to sell, support, and build relationships through instant messaging.

The key difference from traditional ecommerce is the interactive element. You're not just displaying products and hoping customers buy. You're actively answering questions and guiding shoppers through their experience in real time.

These conversations happen across four main channels:

• Live chat: A chat widget on your site where shoppers get immediate answers from human agents or automation. One agent can manage multiple chats simultaneously, boosting efficiency while keeping things personal.
• AI assistants: Smart helpers that use Natural Language Processing (NLP) to understand customer intent. They guide shoppers through questions, offer product suggestions, handle FAQs, and can complete transactions or post-purchase support right in the chat.
• Messaging apps: WhatsApp, Facebook Messenger, and SMS. Instead of sending customers to your website, you bring the shopping to them in channels they already trust.
• Voice assistants: AI-powered voice support that delivers natural phone conversations without needing a call center. These agents answer questions, route calls, handle returns and exchanges, and personalize support based on customer behavior.

Read more: Conversational commerce: A complete beginner's guide

The benefits of conversational commerce for ecommerce brands

Conversational commerce delivers measurable results that impact both revenue and operational efficiency. Here are the seven key benefits you can expect.

1. Higher conversion rates from instant answers

When shoppers have questions, they want answers immediately. Making them wait for email replies often means losing the sale.

Conversational commerce removes this barrier by providing instant responses. Questions about sizing, product features, or shipping policies get answered in seconds. This is especially critical for mobile shoppers who have less patience for complex navigation.

Real-time answers work because they catch customers at the moment of highest intent. When someone is actively considering a purchase and asks a question, an immediate helpful response often provides the final push they need to buy.

2. Bigger average order value from personalized recommendations

Conversations create natural opportunities for upselling that are often hard to come by when a customer just wants to know where their order is. Based on what customers ask or what's in their cart, you can make relevant recommendations that feel helpful rather than pushy.

• Context-based suggestions: If someone buys a camera, suggest a compatible lens or carrying case
• Bundle recommendations: Offer complete outfits when customers buy individual clothing items
• Upgrade opportunities: Present premium versions when customers ask about basic products

These recommendations work because they're contextual and helpful. Customers see them as expert advice rather than sales pitches, leading to natural increases in average order value.

3. Lower cart abandonment with proactive messaging

Cart abandonment affects nearly every ecommerce store. Conversational commerce gives you powerful tools to combat this problem through proactive engagement.

You can set up triggers that automatically engage shoppers showing signs of abandonment. A simple message like "Questions about the items in your cart?" can re-engage hesitant buyers. You can also offer time-sensitive discounts or clarify shipping information that might be causing hesitation.

The key is timing. Catching customers at the right moment with the right message can recover significant revenue that would otherwise be lost.

Related: Why campaign timing matters: 4 ways to get it right

4. Faster resolutions with automation

Many support inquiries are repetitive and simple to resolve. Questions about order status, return policies, or shipping information can easily be handled by AI agents.

Automating these responses provides several benefits:

• Instant answers: Customers get help immediately, even outside business hours
• Agent efficiency: Human agents focus on complex issues that require personal attention
• Consistent quality: AI provides accurate, on-brand responses every time
• Scalability: Handle volume spikes without increasing headcount

This automation doesn't replace human agents. It frees them to do more work that drives actual business value.

5. Lower support costs with self-service

Self-service capabilities significantly reduce support ticket volume. AI-powered chatbots and well-structured help centers can deflect common questions before they reach your team.

This approach allows you to scale support operations without proportionally increasing costs. You can handle seasonal volume spikes like Black Friday Cyber Monday without overwhelming your team or sacrificing service quality.

The cost savings compound over time. Every automated resolution reduces the load on human agents, allowing smaller teams to support larger customer bases effectively.

6. Richer customer data for smarter campaigns

Every conversation generates valuable zero-party data — information customers willingly share with you. Through natural dialogue, you learn about preferences, pain points, and purchase motivations.

This data becomes a goldmine for marketing teams:

• Targeted segments: Create highly specific customer groups based on expressed interests
• Personalized content: Tailor website and email content to individual preferences
• Product development: Use customer feedback to inform future product decisions
• Campaign optimization: Understand what messaging resonates with different customer types

The more you understand your customers through conversations, the more effective all your marketing becomes.

7. Stronger loyalty through consistent, human-like support

Conversational commerce builds relationships through every interaction. When customers feel heard and valued, they become repeat buyers and brand advocates.

Fast, helpful, and personalized interactions create memorable experiences that build trust. By maintaining consistent brand voice across all channels and providing support that feels human, you foster emotional connections with customers.

These relationships are the foundation of long-term business success. Loyal customers have higher lifetime value, make more frequent purchases, and refer others to your brand.

High-impact use cases for DTC brands

DTC brands thrive by turning the online shopping experience into a competitive advantage. Maximizing each touchpoint with conversational commerce is how you do it. Focus on these use cases for quick, measurable impact.

Pre-purchase consultative selling for guidance

Products requiring education — like skincare, supplements, or technical apparel — hugely benefit from conversational selling. Chat acts as a virtual consultant, helping customers find the product made for them.

How to implement: Create guided flows that ask about customer needs and recommend perfect products. This consultative approach builds confidence and helps shoppers feel certain about their choices.

Order status and returns self-service for deflection

Order status and returns questions dominate most support queues. Automating these inquiries reduces the load of day-to-day tasks, benefiting long-term efficiency.

How to implement: Set up self-serve order management on your website. Guide customers through return initiation directly within chat and link to your returns portal. This deflects huge volumes of repetitive tickets.

Cart and discount recovery for saved revenue

Proactively engaging cart abandoners delivers some of the highest ROI in conversational commerce. When customers have items in cart but haven't checked out, trigger helpful messages.

How to implement: Offer to answer questions or provide time-sensitive discounts to create urgency. This simple intervention can recover significant otherwise-lost revenue.

Best practices to get started without overwhelming your team

Implementing conversational commerce doesn't require massive overhauls. Start small, prove value, and expand based on results.

Start with top intents like WISMO and returns

Don't automate everything immediately. Begin with your highest-volume, most repetitive inquiries — typically order status questions and return policy inquiries.

Build solid automation for these top intents first. Measure impact on ticket volume, resolution time, and customer satisfaction. This creates clear wins and builds momentum for future expansion.

Launch on one high-impact channel first

Choose one channel based on where your customers are most active. Analyze your data to understand whether that's website chat, Instagram DMs, or SMS.

Master that channel before expanding to others. This allows you to test, learn, and optimize in a controlled environment. Apply these learnings as you scale to ensure consistent, high-quality experiences everywhere.

The future of conversational commerce for ecommerce teams

Generative AI is making support conversations more natural than ever.

The future focuses on proactive and predictive engagement, where brands anticipate customer needs before they're expressed. As privacy concerns grow, owned channels and first-party data from conversations become increasingly valuable for building direct customer relationships.

Ready to see how leading ecommerce brands turn every customer conversation into growth opportunities? Book a demo to see Gorgias in action and learn how you can transform your customer experience.

{{lead-magnet-2}}

TL;DR:

• Most food & beverage support tickets during BFCM are predictable. Subscription cancellations, WISMO, and product questions make up the bulk—so prep answers ahead of time.
• Proactive CX site updates can drastically cut down repetitive tickets. Add ingredient lists, cooking instructions, and clear refund policies to product pages and FAQs.
• FAQ pages should go deep, not just broad. Answer hyper-specific questions like “Will this break my fast?” to help customers self-serve without hesitation.‍
• Transparency about stock reduces confusion and cart abandonment. Show inventory levels, set up waitlists, and clearly state cancellation windows.

In 2024, Shopify merchants drove $11.5 billion in sales over Black Friday Cyber Monday. Now, BFCM is quickly approaching, with some brands and major retailers already hosting sales.

If you’re feeling late to prepare for the season or want to maximize the number of sales you’ll make, we’ll cover how food and beverage CX teams can serve up better self-serve resources for this year’s BFCM. 

Learn how to answer and deflect customers’ top questions before they’re escalated to your support team.

💡 Your guide to everything peak season → The Gorgias BFCM Hub

Handling BFCM as a food & beverage brand

During busy seasons like BFCM and beyond, staying on top of routine customer asks can be an extreme challenge. 

“Every founder thinks BFCM is the highest peak feeling of nervousness,” says Ron Shah, CEO and Co-founder of supplement brand Obvi. 

“It’s a tough week. So anything that makes our team’s life easier instantly means we can focus more on things that need the time,” he continues. 

Anticipating contact reasons and preparing methods (like automated responses, macros, and enabling an AI Agent) is something that can help. Below, find the top contact reasons for food and beverage companies in 2025. 

Top contact reasons in the food & beverage industry 

According to Gorgias proprietary data, the top reason customers reach out to brands in the food and beverage industry is to cancel a subscription (13%) followed by order status questions (9.1%).

7 ways to improve your self-serve resources before BFCM

1. Add informative blurbs on product pages 
2. Craft additional help center and FAQ articles 
3. Automate responses with AI or Macros 
4. Get specific about product availability
5. Provide order cancellation and refund policies upfront
6. Add how-to information
7. Build resources to help with buying decisions 

1) Add informative blurbs on product pages

Because product detail queries represent 5.7% of contact reasons for the food and beverage industry, the more information you provide on your product pages, the better. 

Include things like calorie content, nutritional information, and all ingredients.  

For example, ready-to-heat meal company The Dinner Ladies includes a dropdown menu on each product page for further reading. Categories include serving instructions, a full ingredient list, allergens, nutritional information, and even a handy “size guide” that shows how many people the meal serves. 

2) Craft additional Help Center and FAQ articles

FAQ pages make up the information hub of your website. They exist to provide customers with a way to get their questions answered without reaching out to you.   

This includes information like how food should be stored, how long its shelf life is, delivery range, and serving instructions. FAQs can even direct customers toward finding out where their order is and what its status is. 

In the context of BFCM, FAQs are all about deflecting repetitive questions away from your team and assisting shoppers in finding what they need faster. 

That’s the strategy for German supplement brand mybacs. 

“Our focus is to improve automations to make it easier for customers to self-handle their requests. This goes hand in hand with making our FAQs more comprehensive to give customers all the information they need,” says Alexander Grassmann, its Co-Founder & COO.

As you contemplate what to add to your FAQ page, remember that more information is usually better. That’s the approach Everyday Dose takes, answering even hyper-specific questions like, “Will it break my fast?” or “Do I have to use milk?”

While the FAQs you choose to add will be specific to your products, peruse the top-notch food and bev FAQ pages below. 

Time for some FAQ inspo:

• Juice Plus+ FAQ
• Everyday Dose FAQ
• Chamberlain Coffee FAQ
• Jurassic Fruit FAQ
• Rebel Cheese FAQ
• The Dinner Ladies FAQ

3) Automate responses with AI or macros

AI Agents and AI-powered Shopping Assistants are easy to set up and are extremely effective in handling customer interactions––especially during BFCM.  

“I told our team we were going to onboard Gorgias AI Agent for BFCM, so a good portion of tickets would be handled automatically,” says Ron Shah, CEO and Co-founder at Obvi. “There was a huge sigh of relief knowing that customers were going to be taken care of.” 

And, they’re getting smarter. AI Agent’s CSAT is just 0.6 points shy of human agents’ average CSAT score. 

Here are the specific responses and use cases we recommend automating: 

• WISMO (where is my order) inquiries 
• Product related questions 
• Returns 
• Order issues
• Cancellations 
• Discounts, including BFCM related 
• Customer feedback
• Account management
• Collaboration requests 
• Rerouting complex queries

Get your checklist here: How to prep for peak season: BFCM automation checklist

4) Get specific about product availability

With high price reductions often comes faster-than-usual sell out times. By offering transparency around item quantities, you can avoid frustrated or upset customers. 

For example, you could show how many items are left under a certain threshold (e.g. “Only 10 items left”), or, like Rebel Cheese does, mention whether items have sold out in the past.  

You could also set up presales, give people the option to add themselves to a waitlist, and provide early access to VIP shoppers. 

5) Provide order cancellation and refund policies upfront 

Give shoppers a heads up whether they’ll be able to cancel an order once placed, and what your refund policies are. 

For example, cookware brand Misen follows its order confirmation email with a “change or cancel within one hour” email that provides a handy link to do so. 

Your refund policies and order cancellations should live within an FAQ and in the footer of your website. 

6) Add how-to information 

Include how-to information on your website within your FAQs, on your blog, or as a standalone webpage. That might be sharing how to use a product, how to cook with it, or how to prepare it. This can prevent customers from asking questions like, “how do you use this?” or “how do I cook this?” or “what can I use this with?” etc. 

For example, Purity Coffee created a full brewing guide with illustrations:

Similarly, for its unique preseasoned carbon steel pan, Misen lists out care instructions: 

And for those who want to understand the level of prep and cooking time involved, The Dinner Ladies feature cooking instructions on each product page. 

7) Build resources to help with buying decisions 

Interactive quizzes, buying guides, and gift guides can help ensure shoppers choose the right items for them––without contacting you first. 

For example, Trade Coffee Co created a quiz to help first timers find their perfect coffee match: 

Set your team up for BFCM success with Gorgias 

The more information you can share with customers upfront, the better. That will leave your team time to tackle the heady stuff. 

If you’re looking for an AI-assist this season, check out Gorgias’s suite of products like AI Agent and Shopping Assistant. 

{{lead-magnet-2}}

TL;DR:

• Conversational AI combines natural language processing, machine learning, and generative AI to create human-like interactions
• For ecommerce, it automates customer service, drives sales through personalized recommendations, and scales support 24/7
• Key types include chatbots, voice assistants, and AI agents that handle both support and sales tasks
• Implementation requires defining clear goals, choosing an ecommerce-ready platform, and connecting your tech stack

Conversational AI changes how ecommerce brands interact with customers by enabling natural, human-like conversations at scale, helping reduce customer churn. 

Instead of forcing shoppers through rigid menus or making them wait for support, conversational AI understands questions, detects intent, and delivers instant, personalized responses. 

This technology powers everything from customer service chatbots to voice assistants, helping brands automate repetitive tasks while maintaining the personal touch customers expect. 

For ecommerce specifically, it means handling order inquiries, providing product recommendations, and recovering abandoned carts — all without adding headcount.

What is conversational AI?

Conversational AI is a type of artificial intelligence that allows computers to understand, process, and respond to human language through natural, two-way conversations. This means your customers can ask questions in their own words and get helpful answers that feel like they're talking to a real person.

Unlike basic chatbots that only recognize specific keywords, conversational AI actually understands what your customers mean. It can handle typos, slang, and complex questions that have multiple parts. The AI learns from every conversation, getting better at helping your customers over time.

Think of it as having a super-smart team member who never sleeps, never gets frustrated, and remembers every detail about your products and policies. This AI team member can chat with customers on your website, answer questions through social media, or even handle phone calls.

What are the key components of conversational AI?

Conversational AI works because several smart technologies team up to understand and respond to your customers. Each piece has a specific job in making conversations feel natural and helpful.

Natural Language Processing (NLP) is the foundation that breaks down human language into pieces a computer can understand. This means when a customer types "Where's my order?" the AI can identify the important words and grammar structure.

Natural Language Understanding (NLU) figures out what the customer actually wants. This is the smart part that realizes "Where's my order?" means the customer wants to track a shipment, even if they phrase it differently like "I need to check my package status."

Natural Language Generation (NLG) creates responses that sound human and helpful. Instead of robotic answers, it crafts replies that match your brand's voice and provide exactly what the customer needs to know.

The dialog manager keeps track of the entire conversation. This means if a customer asks a follow-up question, the AI remembers what you were just talking about and can give a relevant answer.

Your knowledge base stores all the information the AI needs to help customers. This includes your return policy, product details, shipping information, and any other facts your team would use to answer questions.

How does conversational AI work?

Conversational AI follows a simple three-step process that happens in seconds. Understanding this process helps you see why it's so much more powerful than old-school chatbots.

1) It processes input across voice and text with NLP

When a customer sends a message or asks a question, the AI first needs to understand what they're saying. For text messages from chat, email, or social media, the system breaks down the sentence into individual words and analyzes the grammar.

For voice interactions like phone calls, the AI uses speech recognition to turn spoken words into text first. Modern systems handle different accents, background noise, and natural speech patterns without missing a beat.

2) It detects intent and context with NLU

Once the AI has the customer's words, it needs to figure out what they actually want. The system looks for the customer's intent — their goal or what they're trying to accomplish.

For example, when someone asks "Can I return this sweater I bought last week?" the AI identifies the intent as wanting to make a return. It also pulls out important details like the product type and timeframe.

The AI also uses context from earlier in the conversation. If the customer mentioned their order number earlier, the AI remembers it and can use that information to help with the return request.

3) It generates responses with NLG

After understanding what the customer wants, the AI creates a helpful response. It might pull information from your knowledge base, personalize the answer with the customer's specific details, or generate a completely new response using generative AI.

The system also checks how confident it is in its answer. If the AI isn't sure about something or if the topic is too complex, it knows to hand the conversation over to one of your human agents.

What are the types of conversational AI?

Different types of conversational AI work better for different situations in your ecommerce business. Understanding these types helps you choose the right solution for your customers and team.

Chatbots handle scripted and AI-driven chat

Chatbots are the most common type you'll see on websites and messaging apps. Early chatbots followed strict scripts — if a customer's question didn't match the script exactly, the bot would get confused and give unhelpful answers.

Modern AI-powered chatbots understand natural language and can handle much more complex conversations. The best systems combine both approaches: using simple rules for straightforward questions and AI for everything else.

These chatbots work great for answering common questions about shipping, returns, and product details. They can also help customers find the right products or guide them through your checkout process.

Voice assistants manage speech-based requests

Voice assistants bring conversational AI to phone support and other voice channels. These aren't the old phone trees that made customers press numbers to navigate menus.

Instead, customers can speak naturally and get helpful answers right away. Voice assistants can look up order information, explain your return policy, or even process simple requests like address changes.

This works especially well for customers who prefer calling over typing, or when they need help while their hands are busy.

Read more: How Cornbread Hemp reached a 13.6% phone conversion rate with Gorgias Voice

AI agents and copilots assist teams and customers

AI agents are the most advanced type of conversational AI. Unlike chatbots that mainly provide information, AI agents can actually take action on behalf of customers.

These systems connect to your other business tools like Shopify, your shipping software, or your returns platform. This means they can do things like:

• Process returns: Start a return and send the customer a shipping label
• Update orders: Change a shipping address or add items to an existing order
• Handle refunds: Issue refunds for eligible orders automatically
• Manage subscriptions: Skip shipments or update subscription preferences

Copilots work alongside your human agents, suggesting responses and pulling up customer information to help resolve issues faster.

Read more: How AI Agent works & gathers data

What are the benefits of conversational AI for ecommerce?

Conversational AI delivers real business results for ecommerce brands. The benefits go beyond just making your support team more efficient — though that's certainly part of it.

24/7 availability means you never miss a sale or support opportunity. Customers can get help at 2 a.m. or during holidays when your team is offline. This is especially valuable for international customers in different time zones.

Instant responses prevent cart abandonment and customer frustration, improving first contact resolution. When someone has a question about sizing or shipping, they get an answer immediately instead of waiting hours or days for an email response.

Personalized interactions at scale drive higher average order values. The AI can recommend products based on what customers are browsing, their purchase history, and their preferences, just like your best salesperson would.

Cost efficiency comes from handling repetitive questions automatically. Your human agents can focus on complex issues, VIP customers, and revenue-generating activities instead of answering the same shipping questions over and over.

Multilingual support helps you serve global customers without hiring native speakers for every language. The AI can communicate in dozens of languages, opening up new markets for your business.

What are the most valuable conversational AI use cases for ecommerce?

Certain moments in the shopping experience create the biggest opportunities for conversational AI to drive results. Focus on these high-impact use cases first.

Pre-purchase questions are your biggest conversion opportunity. When someone is looking at a product but hasn't bought yet, quick answers about sizing, materials, or compatibility can close the sale. The AI can also suggest complementary products or highlight features the customer might have missed.

Order tracking makes up the largest volume of support tickets for most ecommerce brands. Customers want to know where their package is, when it will arrive, and what to do if there's a delay. AI handles these WISMO requests instantly by pulling real-time tracking information.

Returns and exchanges can be complex, but AI excels at the initial screening. It can check if an item is eligible for return, explain your policy, and start the return process. For straightforward returns, customers never need to wait for human help.

Cart recovery works best when it's immediate and personal. AI can detect when someone abandons their cart and reach out through chat or email with personalized messages, discount offers, or answers to common concerns that prevent purchases.

Post-purchase support keeps customers happy after they buy. The AI can send order confirmations, provide care instructions, suggest related products, and handle simple issues like address changes.

How do you implement conversational AI in an ecommerce tech stack?

Getting started with conversational AI doesn't require a complete overhaul of your systems. The key is starting with clear goals and building your capabilities over time.

Step 1: Define goals and KPIs for automation

The best automation opportunities are found in your tickets. Look for questions that come up repeatedly and have straightforward answers. Common examples include order status, return policies, and basic product information.

Set realistic goals for your first phase. You might aim to automate 30% of your tickets or reduce average response time by half. Track metrics like:

• Automation rate: Percentage of tickets resolved without human intervention
• Customer satisfaction: How happy customers are with AI interactions
• Revenue impact: Sales influenced by AI recommendations or cart recovery

Step 2: Choose an ecommerce-ready AI platform

Not all conversational AI platforms understand ecommerce needs. Look for a platform that integrates directly with Shopify and your other business tools. This connection is essential for pulling real-time order data, customer history, and product information.

Your platform should come with pre-built actions for common ecommerce tasks like order lookups, return processing, and subscription management. This saves months of custom development work.

Make sure you can control the AI's behavior through clear guidance and rules. You need to be able to set your brand voice, define when to escalate to humans, and update the AI's knowledge as your business changes.

Step 3: Connect Shopify and key tools, then iterate

Start your implementation by connecting your Shopify store to give the AI access to order and customer data. Don’t forget to integrate the rest of your tech stack like shipping software, returns platforms, and loyalty programs.

Launch with a few core use cases like order tracking and basic product questions. Monitor the AI's performance closely and gather feedback from both customers and your support team. Use this data to refine the AI's responses and gradually expand its capabilities. 

The best approach is iterative — start small, learn what works, and build from there.

What are the challenges and risks of conversational AI?

While conversational AI offers significant benefits, you need to be aware of potential challenges and plan for them from the start.

Accuracy concerns arise when AI systems provide incorrect information or "hallucinate" facts that aren't true. Prevent this by using platforms that ground responses in your verified knowledge base and product data rather than generating answers from scratch.

Brand voice consistency becomes critical when AI represents your brand to customers. Set clear guidelines for tone, style, and messaging. Test the AI's responses regularly to ensure they align with how your human team would handle similar situations.

Data privacy requires careful attention since conversational AI handles sensitive customer information. Choose platforms with strong security measures, data encryption, and compliance with regulations like GDPR. Look for features like automatic removal of personal information from conversation logs.

Over-automation can frustrate customers when complex issues require human empathy and problem-solving. Design clear escalation paths so customers can easily reach human agents when needed. Train your AI to recognize when a situation is beyond its capabilities.

Integration complexity can slow down implementation if your chosen platform doesn't work well with your existing tools. This is why choosing an ecommerce-focused platform with pre-built integrations is so important.

Turn conversations into revenue with conversational AI

The brands winning with conversational AI start with clear goals, choose the right platform, and iterate based on real performance data. They don't try to automate everything at once. They focus on high-impact use cases that deliver real results.

Ready to see how conversational AI can transform your ecommerce support and sales? Book a demo with Gorgias — built specifically for ecommerce brands.

{{lead-magnet-2}}

TL;DR:

• How AI for customer support works: machine learning and natural language processing to automate repetitive tickets and assist human agents
• AI for customer support benefits: Reduced response times, lower support costs, and increased conversion rates 
• Common AI uses: Automating WISMO inquiries, returns processing, and product recommendations
• How to implement: Pay attention to data privacy, brand voice consistency, and measuring ROI

The days of waiting for support to respond for hours or days are gone now that AI is here to stay. In the ecommerce world, AI has become an essential part of CX team’s toolkits, addressing common questions about orders, returns, and products without losing personalized service.

This technology combines natural language processing with your brand's specific knowledge to deliver accurate, on-brand responses across email, chat, and other channels. The result is faster support that drives sales while slashing operational costs.

{{lead-magnet-1}}

What is AI for customer support

AI for customer support is software that uses machine learning to understand and respond to customer questions automatically. This means your customers get instant answers to common questions without waiting for a human agent to respond.

Unlike basic automation that follows pre-defined rules, AI actively learns from every conversation. It gets smarter over time and can handle more complex questions as it processes more data from your support tickets.

The technology works through several key parts:

• Natural language processing: AI understands what customers mean, not just the exact words they type
• Intent classification: The system figures out what the customer actually wants to accomplish
• Knowledge base integration: AI pulls answers from your product information, policies, and past conversations
• Omnichannel deployment: The same AI works across email, chat, social media, and phone support

AI doesn't replace your human agents. Instead, it handles repetitive questions so your team can focus on problems that require a unique human touch.

Related: What is conversational AI? The ecommerce guide

What are the benefits of using AI for customer support

AI delivers immediate improvements to both your customer experience and your bottom line. Your customers get faster responses, and your business saves money while increasing sales.

The most important benefits include:

• Instant responses: Customers get answers in seconds instead of hours or days
• Lower costs: Each ticket costs less to resolve while maintaining high quality
• 24/7 availability: Support never stops, even when your team is offline
• Consistent quality: Every response follows your brand guidelines and policies
• Revenue growth: AI turns support conversations into sales opportunities

You'll see improvements in key metrics like customer satisfaction (CSAT) scores and first contact resolution rates. Your average handle time (AHT) drops because AI resolves simple questions instantly. During busy seasons like Black Friday, AI helps you meet service level agreements (SLAs) without hiring temporary staff.

Most importantly, AI creates revenue. By providing instant product recommendations and helping customers complete purchases, your support team becomes a sales channel.

How ecommerce brands use AI for customer support

Smart ecommerce brands use AI to handle their most common and time-consuming support requests. This frees up human agents to focus on building relationships and solving complex problems.

Resolve where-is-my-order requests

"Where is my order" questions make up the biggest chunk of ecommerce support tickets. AI completely automates these by connecting to your order management system and pulling real-time tracking information.

When a customer asks about their order, AI instantly checks the status and provides tracking details. If there's a delay, it explains what happened and gives an updated delivery estimate.

Automate returns and exchanges

AI guides customers through your entire returns process without human help. It checks if items qualify for returns based on your policy, generates return shipping labels, and processes exchanges.

For brands using returns platforms like Loop Returns, AI can automatically send customers to their returns portal with all their order information pre-filled.

Handle cancellations and order edits

Speed matters when customers want to cancel or change orders. AI checks if an order has shipped yet and processes cancellations automatically for orders still in your warehouse.

For shipped orders or complex changes like address updates, AI gathers all the necessary information and routes the ticket to the right human agent with full context.

Related: Why faster isn’t always better: The pitfalls of fast-only customer support

Answer product and sizing questions

Shoppers need answers before they buy. AI acts as a personal shopping assistant, using your product catalog and sizing guides to answer questions about fit, materials, and features.

When items are out of stock, AI suggests similar alternatives to save the sale instead of losing the customer.

Troubleshoot shipping and delivery issues

Delivery problems create frustrated customers who need immediate help. AI tracks packages in real-time, identifies issues like delays or failed deliveries, and provides resolution options.

For serious problems like lost or damaged packages, AI escalates to human agents with all the tracking details and customer information ready.

Manage discounts and promotions

AI handles all types of discount questions, from explaining promotion terms to troubleshooting codes that won't work. It can even apply forgotten discount codes retroactively if your policies allow it.

During busy sale periods, AI prevents your team from getting overwhelmed with promo code questions.

Recommend products and drive upsells

AI doesn't just solve problems — it creates sales opportunities. By analyzing what customers are browsing and their purchase history, AI suggests relevant products they might want.

This personalized approach increases your average order value (AOV) and turns routine support conversations into revenue-generating interactions.

Give callers fast answers

AI phone solutions keep your phone channel helpful, fast, and cost-efficient without sacrificing the personal feel callers prefer. It takes care of simple, high-volume requests, such as order status, subscription updates, address changes, so your team can focus on calls that move revenue or require empathy.

It picks up on tone and frustration, then routes customers to a person before the situation escalates. This matters most when:

• The purchase is high-value and shoppers want to hear a voice
• Your team is buried during peak season
• You need a reliable fallback when chat and email queues are full

How to use AI for customer support to improve speed and sales

Getting the most from AI requires a strategic approach that is both efficient and beneficial to your bottom line. Start by analyzing your support data to find the highest-volume, most repetitive questions, then build automated workflows to resolve them.

What to consider before implementing AI for customer support

Success with AI requires planning around several key areas that affect both performance and customer trust.

Protect customer data and privacy

AI systems process sensitive customer information, so security is critical. Choose platforms that comply with privacy regulations like GDPR and have strong security certifications.

Be transparent with customers about how you use their data. This builds trust and ensures you meet legal requirements in all the markets where you sell.

Read more: Should brands disclose AI in customer interactions? A guide for CX leaders

Maintain brand voice and accuracy

Your AI must sound like your brand in every interaction. Train the AI on your specific brand voice, style, and terminology so responses feel authentic to your customers.

Set up guardrails to prevent off-brand or incorrect responses. Create a process for monitoring conversations and making corrections when needed.

Measure time to value and ROI

Define success metrics before you start. Identify which numbers you want to improve, like response time or cost per ticket, and establish baseline measurements.

Track both cost savings and revenue generation to calculate your full return on investment (ROI). This helps justify the investment and guide future improvements.

Align people, process, and workflow

AI works best when it complements your human team, not replaces them. Plan for change management and train agents on working alongside AI.

Redesign your workflows to create smooth handoffs between AI and human agents. This ensures customers get consistent service regardless of who helps them.

How to get started with AI for customer support

If you’re ready to go all in with AI, you don’t need to complete overhaul your support operations. 

Follow this practical roadmap to see value quickly while building toward more advanced capabilities:

1. Analyze your ticket data to identify automation opportunities
2. Define success metrics and ROI targets
3. Choose an AI platform built for ecommerce
4. Run a pilot with one high-volume use case like order tracking
5. Expand based on pilot results and learnings

How to choose an AI platform for customer support

Not all AI platforms work well for ecommerce brands. Focus on solutions built specifically for online retail with deep integrations into your existing tech stack.

Look for platforms that connect natively to Shopify, your shipping providers, and other essential tools. Strong API capabilities let you build custom workflows for unique business needs.

Consider these essential features:

• Ecommerce integrations: Native connections to your order management, shipping, and customer data systems
• Brand customization: Ability to train AI on your specific voice, policies, and product information
• Performance tracking: Clear reporting on AI effectiveness, resolution rates, and revenue impact
• Scalability: Handles peak season traffic without performance degradation
• Vendor expertise: Deep understanding of ecommerce support challenges and best practices

Pay attention to total cost of ownership beyond subscription fees. Factor in implementation time, training requirements, and ongoing maintenance needs.

Support your support team with AI

The brands winning with AI start with clear goals, choose the right platform, and focus on delivering value to customers while improving operational efficiency.

Book a demo with Gorgias to see how AI can transform your support operations and drive more revenue from every conversation.

{{lead-magnet-2}}

TL;DR:

• Suggestion turns browsing into buying by gently guiding action instead of forcing it.
• Fewer, clearer choices reduce decision fatigue and help shoppers move forward with confidence.
• A well-timed prompt with a friendly tone can make automation feel like a real conversation.
• Good design earns trust by being subtle, approachable, and easy to engage with.
• Small, thoughtful cues create moments of connection that make shoppers feel understood.

Shopping today isn’t a linear funnel. It’s a fluid conversation. Browse → question → help → buy → return → repeat.

Every step is a dialogue between the shopper’s intent and the brand’s response. 

But what bridges the gap between “just looking” and “I’m buying” isn’t persuasion or urgency — it’s suggestion: the subtle design, timing, and language cues that guide action without forcing it.

When done well, suggestion becomes the architecture of trust. It’s also the best way to make AI-powered experiences feel human-first, not tech-first.

This article explores how the power of suggestion — rooted in behavioral psychology and UX design — shapes modern conversational commerce. 

{{lead-magnet-1}}

Why suggestion matters in the age of conversational commerce

The average ecommerce shopper faces thousands of micro-decisions from the moment they land on a site. Which product? Which variant? Which review to trust? Which shipping method? Each one adds cognitive weight.

Psychologist Barry Schwartz coined the term The Paradox of Choice to describe how abundance often leads to paralysis. In his research, participants faced with too many options were less likely to make a choice and less satisfied when they did.

In ecommerce, that means overload costs conversions. When shoppers must evaluate too many variables, they hesitate, second-guess, or abandon.

Shoppers today expect empathy and ease, not persuasion. When you suggest rather than push, you signal empathy and support.

This is especially important for conversational commerce. Suggestion humanizes automation by making AI interactions feel like conversations rather than transactions.

When you push and persuade, you create a memorable experience for customers — but it’s not the kind you want them to remember.

One Reddit thread perfectly captures the problem: a user tried to cancel their Thrive Market membership and had to ask nine times before the chatbot complied.

Each time, the AI assistant tried to talk them out of it (offering deals, guilt-tripping responses, or irrelevant messages) until the customer’s frustration boiled over.

The thread exploded not just because it was mildly infuriating, but because it illustrated what customers fear most about automation: a lack of empathy.

Suggestion is how you design for trust, ease, and interaction. And for ecommerce and CX professionals, suggestion bridges browsing and buying by prompting dialogue in a gentle, psychologically sound way.

5 ways to use suggestion with agentic AI

The magic of suggestion is that it works with human psychology, not against it. It bridges the space between what a shopper wants to do and what helps them do it.

That’s the foundation of the Fogg Behavior Model, developed by Stanford’s Dr. BJ Fogg. The model states that behavior happens when three things intersect:

1. Motivation — the user wants to do something.
2. Ability — they can do it easily.
3. Prompt — they’re nudged at the right moment.

When these three align, the likelihood of action skyrockets.

In conversational commerce, suggestion is the gentle push that turns intent into interaction.

Below are five ways to apply suggestion with agentic AI (think chat, assistants, and marketing tools) to drive trust, dialogue, and conversion.

1. Build trust with a friendly invitation

A first impression shapes the entire interaction.

A greeting like “Need help?” or “Looking for something special?” signals availability without applying pressure. It’s the digital equivalent of a store associate smiling and saying, “Let me know if you need anything.”

This works because of linguistic framing, which is a form of persuasive language that subtly shapes how people interpret intent.

• Sentences using personal pronouns (“you,” “we”) increase perceived warmth and empathy.
• Questions (vs. imperatives) activate a conversational schema in the brain, inviting a cooperative response.
• Short, low-stakes phrasing signals that engagement is voluntary.

In practice, this means:

• Replace “Start chat now” with “Need a hand finding the right fit?”
• Use punctuation and tone cues that convey friendliness.
• Let the chat invite linger rather than pop up suddenly — this gives users agency.

Take a look at Glamnetic. Its shopping assistant sits at the bottom-right corner of every page. While shoppers scroll on the homepage, a prompt appears: “Shop with AI.” It’s transparent about being an AI chat, but subtle enough to be there for shoppers when they’re ready to use it at their own leisure. 

Gorgias Shopping Assistant is an easy way to do this. At the right moment, Shopping Assistant appears with a greeting such as “Need help?” or “Chat with our AI!” It’s friendly, low-pressure, optional, more “Hey I’m here if you need” than “Buy now!”

2. Make decisions easier by offering fewer choices

If you’ve ever scrolled through 80 product filters and given up, you’ve experienced choice overload. This is the Paradox of Choice in action: 

More options = higher cognitive effort = lower satisfaction.

Suggestion works because it reduces mental effort. When an AI assistant limits quick-reply options to just a few (say, “Long sleeve,” “Short sleeve,” “Sleeveless”), it transforms chaos into clarity.

Each small tap provides forward momentum, a concept known as the goal-gradient effect: the closer we feel to completing a goal, the faster and more positively we act.

How can you apply this to agentic AI? 

• Keep quick replies between 3–5 choices — enough to feel personalized, not overwhelming.
• Present them as progressive steps, not isolated decisions (e.g., “Show me styles” → “Show me colors” → “Add to cart”).
• Always include a “Something else” or “Other” option to preserve user autonomy.
• Refresh options dynamically based on prior selections — a technique known as choice scaffolding.

Gorgias’s Shopping Assistant does this well, surfacing only the most relevant next steps. Instead of forcing open-ended typing, it guides shoppers through mini-decisions that build confidence. Here’s an example from Okanui, showing four clear options to reply to Shopping Assistant.

3. Encourage interaction with a user-friendly design 

Before a shopper reads a single word of text, their brain has already judged whether your interface feels safe to engage with.

That’s the Aesthetic–Usability Effect — when people perceive something as visually appealing, they assume it will be easier and more trustworthy to use.

Design psychologist Don Norman put it best: “Attractive things work better because they make people feel better.”

Here’s why visual subtlety matters:

• Rounded edges and soft shapes signal continuity and friendliness (the human brain associates curves with safety; sharp angles with danger).
• Muted palettes and neutral contrast lower visual stress, allowing the interface to fade into the background until needed.
• Micro-animations — like a gentle glow or slide-in — trigger attention without hijacking focus.
• Minimizable elements give users a sense of control, reducing resistance to engagement.

OSEA’s product description page is a beautiful example of unintrusive design in action. The buttons have rounded edges, the 10% offer isn’t covering other page elements, and the chat sits in the bottom-right corner, making it easily accessible if a shopper has questions about the product.

4. Match your timing to the customer’s pace

Timing is everything in suggestion-based design. Even the most thoughtful interaction will fail if it appears at the wrong moment.

That’s where the Fogg Behavior Model becomes tactical: Behavior = Motivation × Ability × Prompt

When shoppers are motivated (interested in a product) and able (engaging is easy), a well-timed prompt (chat bubble, message, or offer) turns potential into action.

But mistime it, and you risk the opposite. A chat that appears too early feels like spam. Too late, and the user’s interest window closes.

Here’s how to align the timing sweet spot:

• Use behavioral triggers: Fire prompts after meaningful engagement (e.g., 25–30 seconds on a product page, reaching 70% scroll depth, or idling for 15 seconds).
• Match prompt to context: Offer size guidance on apparel pages, warranty info near checkout, or live help on return pages.
• Respect frequency: One well-placed nudge beats five redundant ones.
• Localize timing: Adjust based on device and location. Mobile users often need faster cues due to shorter browsing sessions.

Gorgias Shopping Assistant does all of the above. Using context — such as the current page, conversational context, and cart behavior — helps the AI trigger prompts like “Need help choosing a size?” or “Have questions about shipping?”

5. Aim to educate, reassure, or inspire — not just sell

Every small suggestion — a phrase, a button shape, a pause, a tone — creates what behavioral economists call a moment of micro-trust.

Individually, these moments may feel insignificant. But together, they turn a static interface into a relationship.

When greeting, choices, design, and timing align, conversation becomes the natural outcome — not the goal. That’s what conversational commerce gets right: it reframes success from “did they convert?” to “did they connect?”

For CX teams, this shift requires designing for the emotional continuity of the experience:

• Did each prompt respect the shopper’s autonomy?
• Did the interaction feel like a two-way exchange?
• Did the system adapt to intent rather than dictate it?

We love this example from Perry Ellis to drive this tip home:

Designing for trust in an age of AI

As AI continues to shape how people shop, brands face a choice: Design for control, or design for trust.

Suggestion is the path to the latter.

The right cue, delivered at the right time, reminds people that even in automated spaces, there’s still room for empathy and understanding.

Gorgias was built on the belief that great commerce starts with conversation, not conversion.

{{lead-magnet-2}}

TL;DR:

• AI Agent is getting more accurate every month: It’s improved 14.9% this year thanks to better LLMs, constant updates, and user feedback.
• It writes more correctly than most humans: With a 4.77/5 language score, it’s nailing grammar, tone, and clarity better than human agents.
• It’s empathetic, too: AI Agent now shows more empathy and listens better than human agents.
• Brands are gaining confidence fast: Quality scores jumped from 57% to 85% in just a few months, and CX teams are noticing.
• Customers are almost as happy with AI as with humans: AI Agent’s CSAT is just 0.6 points shy of human agents’ average CSAT.

Handing trust over to AI can be intimidating. One off-brand reply and you undo the reputation and customer loyalty you’ve worked so hard to build. 

That’s why we’ve made accuracy our top priority with Gorgias AI Agent.

For the past year, the Gorgias team has been hard at work fulfilling the pressing  demand for accuracy and speed. AI Agent is getting smarter, faster, and more reliable, and merchants and their customers are happier with the output. 

Here’s the data.

{{lead-magnet-1}}

AI Agent delivers more accurate answers than ever

This year, AI Agent’s accuracy rose from 3.55 to 4.08 out of 5, a 14.9% improvement from January. This average score is based on CX agents' ratings of AI Agent responses in the product, on a scale of 1 to 5.

In the past year, we’ve improved knowledge retrieval, added new integrations, expanded reporting features, and asked for more feedback in-product.

We saw the steadiest leap in July, right after the release of GPT-5. AI Agent began reaching levels of consistency and accuracy that agents could trust.

AI Agent writes with more linguistic precision than humans

Clear, easy-to-understand language helps people trust what they’re reading. Website Planet found that 85% more visitors bounced from a page when typos were present. That’s why we’ve made it a priority for AI Agent to respond to customers with correct grammar, syntax, and tone of voice. 

The efforts have paid off: AI Agent scores a high 4.77 out of 5 in language proficiency compared to 4.4 for human agents. The result is error-free messages that are easy to read and consistent with your brand vocabulary.

AI Agent shows that empathy can be scaled

Accuracy isn’t just about saying the right thing; it’s also about how a message lands. For that reason, we track AI Agent’s communication quality. Did it reply with empathy? Did it exhibit active listening and respond with clear phrasing?

Recently, AI Agent is even scoring slightly above humans with 4.48 out of 5 in communication, compared to 4.27. This means AI Agent captures the nuance of every message by considering the background context and acknowledging customer frustration before it gives customers a solution. 

AI Agent resolves every part of a customer’s question

What happens when a ticket ends without a clear answer? Customers feel neglected and leave the chat still unsure. This can make your brand look out of touch, leaving customers with the lingering feeling that you don’t care.

But don’t worry, we built AI Agent to close that loop every time: AI Agent’s resolution completeness score sits at a perfect 1 out of 1, compared to 0.99 out of 1 for human agents. 

In practice, this means customers feel cared for and understood, while your team receives fewer follow-ups, giving them more time to focus on strategic, high-priority tasks.

Read more: A guide to resolution time: How to measure and lower it

Brand confidence is on the rise

Building a great product is a two-way conversation between our engineers and the people who use it. We listen, review feedback, ship changes, and measure what improves.

From January to November 2025, AI Agent quality rose from about 57% to 85%. August was the first big step up, and September kept climbing. Brands are seeing fewer low-quality or incorrect answers and more steady decisions.

This is proof that merchants and their shoppers are witnessing the improvements we’ve been making, for the better.

Related: The engineering work that keeps Gorgias running smoothly

Shoppers are rating AI support almost as high as human support

At the end of the day, what matters is how customers feel when they talk to support. Do they trust the answer? Do they find it helpful? Are they running into more friction with AI than without it?

Our data shows that customers are appreciating AI assistance more and more. Since the start of 2025, AI Agent on live chat has gotten a CSAT score 40% closer to the average CSAT of human agents. For email, the gap has narrowed by about 8%.

The goal is to eventually achieve a gap of zero. At this point, AI’s support quality is indistinguishable from that of humans. To get there, we’re focusing on practical improvements like accuracy, clear language, complete answers, and better handoff rules.

How we measure CSAT gap: The CSAT gap is calculated by subtracting AI CSAT from human CSAT. When the number is closer to zero, AI is catching up. When it’s negative, AI is still below human results.

Reliable AI interactions start with accuracy

Behind every accurate AI reply is a team that cares about the details. AI Agent doesn’t make up answers—it follows what you teach it. The more effort your team puts into maintaining an up-to-date Help Center and Guidance, the better the customer experience becomes.

As we look ahead to 2026, we’re focused on fine-tuning knowledge retrieval logic, refining Guidance rules, and continuously learning from feedback from you and your customers.

We’re proud of the strides AI Agent continues to make, and can’t wait for more brands to experience the accuracy for themselves.

Want to see how AI Agent delivers exceptional accuracy without sacrificing speed? Book a demo or start a trial today.

{{lead-magnet-2}}