How to sell 10x more on Black Friday with AI ChatBot

Each year, Black Friday becomes an increasingly massive shopping event. Data shows that participation in Black Friday continues to grow year over year. During the 2023 event, 76.2 million consumers shopped in physical stores, while 90.6 million made purchases online. Online sales on Black Friday 2023 reached a record-breaking $9.8 billion, a 7.5% increase from 2022. Industry experts predict that in 2024, consumer spending could reach between $10 billion and $11 billion in the U.S. alone.

Black Friday is a peak traffic period for e-commerce. Increased website traffic naturally leads to more customer inquiries, and during this critical time, responding quickly and effectively to customer questions is crucial. Timely responses can have a significant impact on conversion rates.

With the rise of generative AI, AI-powered shopping assistants have become a secret weapon for e-commerce sites looking to gain a competitive edge and turn the holiday season into a revenue bonanza. These AI assistants, built on ChatGPT technology, act as virtual chatbots that provide seamless, end-to-end support throughout the entire online shopping journey.

AI shopping assistants are powerful tools for enhancing brand-customer interactions, offering personalized, always-available product recommendations and customer support. This leads to higher conversion rates and encourages website visitors to complete their purchases.

In this article, we’ll share case studies, insights, and data that demonstrate how using an AI shopping assistant like VanChat during Black Friday can significantly boost paid conversion rates and help you achieve a 10x increase in sales during this high-demand shopping period.

What is VanChat?

VanChat is an AI-powered shopping assistant designed specifically for Shopify stores, built on GPT technology. It automatically learns key data from your store, including product details, policies, discounts, and more. Leveraging advanced conversational marketing capabilities, VanChat significantly enhances the shopping experience and drives sales growth on your website.

Currently, VanChat serves over 1,000 Shopify stores worldwide and has become one of the most popular AI shopping assistants within the Shopify ecosystem. Data shows that users who install VanChat experience an impressive return on investment (ROI) of up to 1,000% in the first month. After three months of use, customer satisfaction increases by an average of 50.9%, and conversion rates improve by 18.5%.

Personalized Recommendations for Faster Purchases

Although most e-commerce websites offer product search functions, it’s surprising that 80% of users don’t rely on search to find products. Many shoppers leave a site simply because they can't find what they’re looking for within a short time. During Black Friday, when many stores offer huge discounts to attract shoppers, patience is further reduced. One study found that during BMCF, the average time it took for shoppers to place an order was 42.5% shorter than usual.

Personalized product recommendations can dramatically shorten shopping time. Our user research reveals that shoppers using the VanChat AI shopping assistant take an average of 5 minutes and 5 seconds to complete a purchase, compared to 10 minutes for those not using an AI assistant. VanChat reduces shopping time by 50%, significantly boosting conversion rates.

Recommending products that meet users’ preferences to increase the likelihood of completing a sale has always been a key goal for VanChat. To achieve this, VanChat offers a wide range of capabilities, including multi-dimensional product recommendations, new arrivals and best-sellers suggestions, and personalized recommendations based on user data.

Multi-Dimensional Product Recommendations

Shoppers often have a general idea of what they want to buy, such as summer clothes, but haven't decided on a specific item. Most customers gradually narrow down their choices while browsing the site. VanChat engages in multi-turn conversations with shoppers to analyze and identify their needs, quickly matching them with the most suitable products. VanChat uses four dimensions—category, brand, features, and context—to personalize product recommendations. This approach, called multi-dimensional product recommendation, helps guide users to the right products based on their specific preferences.

Best-Sellers & New Arrivals Recommendations

VanChat also offers targeted product recommendations. When shoppers ask questions like “What are the new arrivals?” or “What are the best-selling products?” VanChat can instantly suggest relevant items. This helps merchants increase product visibility and drive sales growth. As shown in the example below, on the Store & Products page under the Selection options, merchants can define which new arrivals or best-sellers they want VanChat to recommend. If no specific products are added, VanChat will automatically recommend best-sellers from the past three months and the most recently added items.

User Profile-Based Recommendations

VanChat leverages data from users' browsing history, purchase records, and chat interactions to gain insights into their brand preferences, shopping habits, and style. This allows merchants to build detailed user profiles. When shoppers inquire about products, VanChat automatically loads their profile and recommends items that align with their preferences and purchasing behavior, significantly increasing the likelihood of conversion. This feature is currently in development and will be available in the near future.

Scenarios

The following case demonstrates how VanChat helps users find the most suitable products, thereby driving purchases.

Helping Customers Find Anti-Inflammatories

In this scenario, a customer with a lump on their wrist turned to VanChat for assistance. After four rounds of conversation, they quickly found the right product and completed their purchase.

• Round 1: The customer described the issue: a painless lump on their wrist and asked for advice. VanChat recommended anti-inflammatory tablets or gels that could reduce pain and inflammation, and suggested relevant products.
• Round 2: The customer specifically asked VanChat for product recommendations. VanChat suggested several items, including Narcis brand rheumatoid patches, NO DOL active cream, and other products designed to alleviate pain and inflammation.
• Round 3: The customer mentioned that they had read online that the lump could be related to synovial fluid loss. VanChat quickly picked up on this key information and provided professional advice. VanChat explained, “Loss of synovial fluid can affect joint health and cause inflammation,” which made the customer trust VanChat as a knowledgeable AI consultant. VanChat then recommended NO DOL capsule supplements, explaining that they contained glucosamine and chondroitin, which support joint health and cartilage regeneration—exactly what the customer needed to address the inflammation and reduce the lump.
• Round 4: The customer, satisfied with the recommendation, confirmed their order and made the purchase. They thanked VanChat for its helpful assistance.

Throughout the process, VanChat acted like a highly trained pharmaceutical consultant—sharp, patient, and friendly. After helping the customer find the right product, VanChat earned the customer’s praise. It’s hard to believe that this entire experience was managed by an AI assistant.

Helping Customers Choose Gaming PCs

For tech products, especially electronics, the large number of complex specifications often leaves shoppers overwhelmed. They can spend a lot of time navigating through details, comparing models, and still not find the right fit. This leads many frustrated customers to abandon the site. This is where VanChat excels. Acting as a knowledgeable tech expert, VanChat quickly understands the specifications, performance, and features of various electronics, allowing it to easily recommend the best products for users. Additionally, it can compare different models, significantly reducing the time spent searching and enhancing the overall shopping experience.

One example describes a customer looking for a gaming monitor. With VanChat's help, they found the ideal product within just four rounds of conversation, taking only two minutes. In this brief exchange, VanChat provided personalized recommendations, explained product specifications, and compared different monitors. Once the customer was ready to make a purchase, VanChat also guided them through the checkout process. The customer quickly completed the purchase after finding the perfect product.

Throughout the interaction, VanChat behaves like a seasoned product expert—professional, patient, knowledgeable, and considerate. When the customer asked for a 27-inch monitor recommendation, VanChat provided a well-curated list of five models, offering convincing reasons for each suggestion. When the customer expressed interest in the MONITOR GAMER JANUS 27, VanChat patiently explained its specifications in six key areas, including resolution and refresh rate.

When the customer inquired about the difference between a 27-inch and 32-inch monitor, VanChat responded with wisdom. Rather than directly answering the question, VanChat explained the advantages and ideal use cases for each size. For example, a 27-inch monitor is perfect for fast-paced gaming, offering full HD resolution and high refresh rates, ideal for tight spaces. In contrast, the 32-inch monitor provides a more immersive experience, great for open-world games or movies, but requires more space.

Once the customer was ready to purchase, VanChat kindly provided step-by-step instructions for completing the order.

In just two minutes, VanChat successfully guided the customer through the selection process and converted them into a paying customer. This not only boosted sales for the store but also allowed the customer to find their desired product quickly, enhancing their overall shopping experience.

Helping Users Find the Perfect Wedding Dress

When shopping, many users often don’t know exactly what they want at first. As a result, their initial requests for product recommendations tend to be vague, such as “Please recommend some dresses” or “Suggest a few sofas.” In such cases, the AI needs to do more than just recommend products—it also needs to guide the user in clarifying their preferences and narrowing down what they actually need. By doing so, the AI can help users quickly identify the right products.

This case demonstrates how VanChat helped a lady find the perfect wedding dress. Initially, she only mentioned that she was looking for wedding-related items, but didn’t specify which kind of products. Based on her request, VanChat first suggested an elegant pearl and crystal headpiece suitable for a wedding. However, the lady’s description was too vague, making it challenging to find the right product. So, after providing the headpiece suggestion, VanChat proactively asked whether she was also interested in pearl earrings or a chic evening clutch.

VanChat continued to ask whether she was more interested in wedding accessories or attire. By presenting the user with three categories—accessories, perfumes, and clothing—VanChat allowed the customer to express a preference without directly asking for a specific product. This approach was smart, as the user might not have thought through exactly what they wanted. Directly asking might have resulted in an unclear response, or the conversation could have ended abruptly. Instead, by offering multiple options, VanChat encouraged the user to think and gave them time to clarify their needs. This subtle guidance ultimately helped the user realize she was actually looking for a wedding dress.

As a result, VanChat was able to accurately recommend five beautiful wedding dresses that suited her needs.

Through this clever, guiding question technique, VanChat helped the lady transition from the vague request for “wedding items” to the clear goal of finding “a dress for the wedding.” This type of thought-provoking guidance enables users to clarify their needs and find the perfect product more efficiently.

Case Study: CoolSport

CoolSport, a leading e-commerce platform for fitness equipment targeting the U.S. market, adopted VanChat to provide personalized product recommendations. The reason CoolSport chose VanChat was simple: they needed an AI shopping assistant capable of accurately recommending products tailored to individual customer needs.

CoolSport had identified through extensive customer research that fitness enthusiasts have varying requirements based on factors like gender, physical fitness, and fitness goals. With such diversity, offering personalized product recommendations based on each customer's unique characteristics significantly boosted conversion rates.

After integrating VanChat, CoolSport quickly saw impressive results. In the first month of using VanChat, the website received 23 additional orders, while Average Order Value (AOV) increased by 20%, and the Return on Investment (ROI) soared to an astounding 34,776%.

“VanChat is by far the best chatbot I’ve ever seen,” said the Director of E-commerce at CoolSport. “It has dramatically streamlined our customers’ shopping journeys, enabling them to find the right products in a fraction of the time. The chat experience is incredibly smooth and seamless."

VanChat’s ability to deliver personalized recommendations and improve the overall shopping experience has helped CoolSport enhance both sales performance and customer satisfaction.

Driving Quick Purchases with Discounts

Discounts are one of the most effective tools for encouraging shoppers to make quick purchases. While many retailers display promotional discounts prominently on their homepage, the reality is that shoppers typically spend less than 5 seconds on the homepage, meaning these offers are often overlooked.

VanChat addresses this issue by proactively mentioning discounts during conversations with users. Based on the products the user is interested in, VanChat provides specific discount details and even calculates how much money the user can save by using the offer. This personalized approach significantly boosts users' desire to buy.

By integrating discount promotions directly into the chat experience, VanChat amplifies the effect of these offers by up to 10 times compared to traditional static text on a webpage. This approach helps users make faster, more confident purchasing decisions, driving higher conversion rates.

Setting Up Product Discounts with VanChat

VanChat automatically learns and integrates the discount information set up in Shopify stores, including two main types of discounts: Discount Codes and Automatic Discounts.

1. Discount Codes: These are codes (such as "WELCOME10") that customers enter at checkout to receive a discount. This method is flexible and commonly used for promotional campaigns.
2. Automatic Discounts: These discounts are applied automatically at checkout, without the need for the customer to enter any code. For example, a discount may automatically be applied when a customer’s total reaches a certain threshold. Automatic discounts can include options like percentage-off, free shipping, or buy-one-get-one promotions.

In VanChat , merchants can view all learned discount information under the Store & Products section in Discounts.

• For Discount Codes, since they are tied to the store's specific discount strategies, they are disabled by default. This means VanChat will not share any discount code information with customers unless the merchant explicitly enables it in the settings. This precaution ensures security for the store’s promotional strategies.
• For Automatic Discounts, there is no need to enable them manually. VanChat will automatically apply these discounts when applicable during customer interactions.

With this setup, VanChat can effectively and securely help merchants promote discounts, improving the shopping experience for users while maintaining control over discount distribution.

Scenarios

Using Discounts to Drive Purchases

In this case, we see how VanChat used discounts to drive a customer's purchase of weight loss pills.

A shopper inquired about appetite-suppressing medications, and VanChat recommended two suitable weight loss products. The shopper then asked if there were any discounts available for these products. VanChat promptly responded with accurate information, informing the customer that both products were part of a tiered discount promotion: Buy two items for 20% off and three items for 30% off, with the discount applied automatically at checkout.

In addition, VanChat highlighted an additional offer: If the shopper subscribed to the email list, they could receive a 15% discount on their next purchase. This timely and personalized offer encouraged the shopper to move forward with their purchase. The customer thanked VanChat and proceeded to buy one of the weight loss products.

Through this seamless use of discounts, VanChat successfully motivated the shopper to complete their purchase while enhancing their shopping experience.

Offering Discounts to Fitness Shoppers

This case demonstrates how VanChat proactively offered a discount to a customer searching for fitness equipment, encouraging them to complete the purchase.

The shopper inquired whether the T1 Leg Press attachment was compatible with the M4 Smith Machine, to which VanChat provided a positive response. At this point, leveraging its intent recognition algorithm, VanChat detected that the customer was likely interested in purchasing the product. It then proactively asked if the shopper would like to receive a discount code for new customers.

Once the customer expressed interest, VanChat provided the relevant discount code. As a result, the shopper completed the purchase.

In this scenario, VanChat not only answered the customer’s query but, with its powerful intent understanding, identified the optimal moment to offer a targeted discount. This timely and personalized approach helped drive the shopper's decision to buy the product.

User Case: Patiowell

Founded in 2015, Patiowell is a leading American brand specializing in multi-functional storage solutions in a variety of sizes and materials, designed to meet different consumer needs for home organization. With Patiowell's storage products, users can easily organize and store backyard equipment, keep their homes tidy, and maximize space. The brand’s Sheds product line offers a wide range of options to cater to diverse needs and preferences.

One of the main challenges Patiowell’s customer service team faced was efficiently handling numerous inquiries related to product selection, installation, and returns for their Sheds products, which involve a variety of panels and components. Additionally, the growth team was looking for ways to enhance customer loyalty and increase website conversion rates.

To address these challenges, Patiowell sought an AI tool that could boost sales while reducing customer service costs. VanChat provided the perfect solution, quickly increasing website conversion rates and alleviating customer service pressure. In the first week of using VanChat, Patiowell received 18 orders, resulting in an ROI of 1568.1%.

Feedback from Patiowell Team:

"After a week of using VanChat, I’m blown away. It helped close 18 orders, resulting in an ROI of 15,687.1%—truly impressive! Plus, it collected leads from over 200 potential customers, significantly boosting our database. The proactive sales features actively engage and convert visitors, and we've noticed a clear reduction in our support workload and fewer incoming emails.

The dashboard is intuitive, making it easy to track user interactions and monitor their journey to purchase. VanChat is a true game-changer—a smart AI chatbot that drives sales and captures leads effectively. Highly recommended!"

Boosting Website Conversion Rates with Proactive Sales

User research shows that shoppers who interact with chatbots are 3.5 times more likely to complete a purchase compared to those who don't engage with a chatbot. Therefore, increasing shopper interaction with chatbots is crucial for improving website conversion rates.

Proactive sales involves monitoring shopper behavior and identifying key moments to engage with them. By using AI to interact in a more natural, personalized way, it can effectively nudge shoppers toward making a purchase. This approach significantly increases the likelihood of conversion by delivering timely, tailored assistance and product recommendations when shoppers are most receptive.

How Proactive Sales Works

VanChat monitors shoppers' behaviors on the website, such as page views, adding items to the cart, and recognizing cart abandonment. When these behaviors are detected, VanChat uses algorithms to identify key intervention moments, allowing it to proactively initiate conversations. By helping customers resolve doubts, suggesting product combinations, reminding of discounts, and promoting brand values, VanChat sparks more interest in the products and drives purchases. VanChat employs three dimensions for proactive sales:

• Key Event Intervention: In scenarios such as browsing the homepage, product pages, adding items to the cart, removing items, or abandoning the cart, VanChat proactively engages with shoppers in a personalized way to increase interaction.
• Personalized Greetings: Based on the user's chat history, shopping records, and the current page they are viewing, VanChat offers tailored greetings to increase user engagement.
• Automated Algorithm Recognition (coming soon): Using behavioral monitoring data, VanChat’s algorithm detects key moments, such as when a shopper shows strong interest in a product or is about to lose interest in browsing the site, and proactively starts a conversation, providing exactly what the user is looking for.

Key Event Interventions

In VanChat, you can find the currently supported key events under Proactive Sales: Homepage Visit, Add to Cart, Browse Collection Page, Browse Product Page, Remove from Cart, and Abandon Purchase.

• Coupon

The Coupon option allows you to offer shoppers discounts or free shipping vouchers proactively. Below is an example of how the Coupon configuration works in the Add to Cart scenario. Merchants can customize the interaction message, select the discount code to offer, and enable lead selection, triggers, and exit strategies.

For instance, with the following setup, when a shopper adds an item to the cart, VanChat will automatically display a pop-up after 3 seconds, informing the user about available coupons. If the user enters their email, they can claim the coupon. If the user is not interested in the coupon, the pop-up will automatically disappear after 60 seconds, and no further reminders will be shown to avoid disrupting the user.

• Product Recommendations

This option allows you to proactively recommend best-selling products or specific items to shoppers. For the displayed products, three types of recommendations are available: Best Sellers, New Arrivals, and Custom Recommendations. The first two options are based on system-generated data. For example, if best-selling products are configured, the system will display different best sellers based on daily sales performance.

If a merchant wants to recommend a specific product when a certain event occurs—such as showcasing a special offer when a shopper adds an item to their cart—this can be configured under Custom Recommendations.

To avoid disturbing the user, this option also lets merchants customize the timing of proactive sales pop-ups. Currently, the system allows pop-ups to be triggered based on two criteria: time and page scroll percentage. An upcoming feature, AI-triggered detection, will enable the system to analyze shopper behavior and trigger pop-ups at the most appropriate moment.

• Text Message

This option allows merchants to proactively deliver messages to shoppers via pop-ups, such as information about Black Friday promotions or other key details the merchant wants to communicate. This option also provides configurable trigger rules. Additionally, merchants can customize the color of the message card to match their branding or preferences.

Scenarios

Offering Discounts to New Users

This scenario demonstrates how merchants can use proactive sales to attract new users and encourage them to make a purchase. The merchant has configured a Coupon in the Proactive Sales homepage visit option. As shown in the image below, when a new user logs into the homepage, VanChat will automatically display a pop-up informing the user that they can claim a discount code.

The process is illustrated in the next image, where the customer claims the new user discount code and proceeds to checkout. After the user clicks Yes, VanChat will automatically provide the discount code for new users, along with instructions on how to use it. This pop-up, combined with the chat feature, significantly enhances new user engagement, increasing the likelihood of converting new visitors into paying customers.

Case study: Runge

Runge is a renowned Danish fashion brand known for its clean, comfortable, and bold avant-garde designs. The brand's products are not just clothes; they are expressions of personality and confidence. Runge specializes in streetwear for those who break the mold and pave their own way, and it has gained a loyal following across Europe.

As the popularity of the Runge brand grew, so did the pressure on customer support. The company was receiving a high volume of inquiries daily, through email, Instagram, and other channels. These questions were often repetitive and similar in nature. At the same time, with advertising costs rising, improving the conversion rate of its Shopify store became a pressing concern.

By implementing VanChat, Runge was able to provide customers with quick answers to both simple and more complex inquiries. "VanChat has significantly reduced the number of customer service requests," said Silas Runge, the brand’s founder. "On our website, rungecph.com, we installed VanChat and trained it with brand-specific information. This has had a remarkable impact on both increasing conversion rates and reducing the volume of support emails. Over this period, our conversion rate has increased by about 12%, and the number of support emails has also dropped significantly."