TL;DR:

• Implement quickly and optimize continuously. Cornbread's rollout was three phases: audit knowledge base, launch, then refine. Stacy conducts biweekly audits and provides daily AI feedback to ensure responses are accurate and on-brand.
• Simplify your knowledge base language. Before BFCM, Stacy rephrased all guidance documentation to be concise and straightforward so Shopping Assistant could deliver information quickly without confusion.
• Use proactive suggested questions. Most of Cornbread's Shopping Assistant engagement comes from Suggested Product Questions that anticipate customer needs before they even ask.
• Treat AI as another team member. Make sure the tone and language AI uses match what human agents would say to maintain consistent customer relationships.
• Free up agents for high-value work. With AI handling straightforward inquiries, Cornbread's CX team expanded into social media support, launched a retail pop-up shop, and has more time for relationship-building phone calls.

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.

Top learnings from Cornbread's conversational commerce strategy

1. Customer education drives conversions in wellness

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.

2. Shopping Assistant provides education that never sleeps

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.

3. Implementation follows a clear three-phase approach

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:

1. Preparation. Before launching, Cornbread conducted a comprehensive audit of their knowledge base to ensure accuracy and completeness. This groundwork is critical because your AI is only as good as the information it has access to.
2. Launch and training. After going live, the team met weekly with their Gorgias representative for three to four weeks. They analyzed engagements, reviewed tickets, and provided extensive AI feedback to teach Shopping Assistant which responses were appropriate and how to pull from the knowledge base effectively.
3. Ongoing optimization. Now, Stacy conducts audits biweekly and continuously updates the knowledge base with new products, promotions, and internal changes. She also provides daily AI feedback, ensuring responses stay accurate and on-brand.

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

4. Simple, concise language converts better

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

5. Black Friday results proved the strategy works under pressure

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: 

• Shopping Assistant conversion rate jumped from a 20% baseline to 30% during BFCM
• First response time dropped from over two minutes in 2024 to just 21 seconds in 2025
• Attributed revenue grew by 75%
• Tickets doubled, but AI handled 400% more tickets compared to the previous year
• CSAT scores stayed exactly in line with the previous year, despite the massive volume increase

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.

6. Strategic work replaces reactive tasks

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.

7. Continuous optimization for January and beyond

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.

Build your conversational commerce strategy now

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:

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

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

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

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

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

Why conversational AI matters for modern ecommerce

1) Meet high consumer expectations

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

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

2) Keep up with market momentum

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

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

3) Raise AOV and GMV

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

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

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

How to show the business impact & ROI of Shopping Assistant

1) Pitch its core capabilities

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

Success spotlight

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

2) Position it as a revenue driver

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

Success spotlight

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

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

3) Show its efficiency and cost savings

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

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

Success spotlight

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

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

4) Present the metrics it can impact

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

Success spotlight

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

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

5) Highlight its helpfulness as a sales agent 

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

Success spotlight

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

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

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

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

6) Provide the KPIs you’ll track 

Customer support metrics include: 

• Resolution rate 
• CSAT score 

Revenue metrics to track include: 

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

Shopping Assistant: AI that understands your brand 

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

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

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TL;DR:

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

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

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

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

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

1. Recommend similar shoes when an old classic disappears

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

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

How Shopping Assistant helps:

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

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

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

Results:

• AOV uplift: +6.5%

2. Suggest complete outfits for special occasions

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

How Shopping Assistant helps:

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

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

Results:

• Chat CVR: 13.02%

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

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

How Shopping Assistant helps:

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

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

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

Results:

• GMV uplift: +6.55%

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

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

How Shopping Assistant helps:

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

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

Results:

• Chat CVR: 8.39%

5. Remove the guesswork from bra sizing online

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

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

How Shopping Assistant helps:

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

Results:

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

6. Guide shoppers through jewelry personalization step by step

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

How Shopping Assistant helps:

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

Results:

• GMV uplift: +22.59%

7. Recommend furniture that works well together

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

How Shopping Assistant helps:

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

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

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

Results:

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

8. Reassure shoppers about flavor before purchase

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

How Shopping Assistant helps:

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

Results:

• Chat CVR: 12.75%

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

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

How Shopping Assistant helps:

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

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

Results:

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

10. Align products with safety needs in kids’ rooms

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

How Shopping Assistant helps:

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

Results:

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

11. Clarify technical specs that create hesitation

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

How Shopping Assistant helps:

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

Suddenly, the whole process feels simple instead of overwhelming.

Results:

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

What these results tell us

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

Here’s what stands out:

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

What this means for you:

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

Want Shopping Assistant results like these?

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

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

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

Book a demo or activate Shopping Assistant to get started.

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