How Performance-Driven AI Boosts E-commerce Sales by 80%

According to data from Statista Digital Market Outlook, 63.8% of online consumers in Taiwan shop online weekly, and 34.7% purchase groceries and daily necessities online every week. These findings indicate a surge in online shopping frequency, making it a new norm for consumers. Consequently, the focus has shifted from the rational evaluation of product value to emphasis on the shopping and brand emotional experience. In this evolving landscape, the ability of brands to accurately understand and meet individual customer needs through personalized product recommendations has become crucial.

Google research data also shows that personalized products and services resonate more with consumers, increasing purchase intent by 80% compared to general product displays. This highlights that if brands can address consumer needs and offer precise, personalized product combinations, they can effectively reduce interruptions in the shopping process and achieve successful sales conversions.

To address this need, beBit TECH has leveraged its industry-leading product technology services to introduce the 'AI Product Recommendation' feature within its customer data platform, OmniSegment CDP. This new feature enables brands to utilize a performance-driven AI engine to automatically recommend products that are most likely to appeal to customers, across various sections of the website. This enhances the product browsing experience and increases the chances of purchase. Not only does this meet the growing demand for refined and personalized shopping experiences, but it also elevates brand value. Let's dive into the details of this exciting new feature!

Table of Contents - Click to Section👆 

• Personalized Product Recommendations: Two Major Challenges
• Performance-Driven AI: Instantly Activate Personalized Product Recommendations
• How Can Brands Implement AI Product Recommendations on Various Website Sections?

Personalized Product Recommendations: Two Major Challenges

When planning for ‘personalized product recommendations,' e-commerce brands often encounter two significant issues that diminish their effectiveness:

Challenge 1: Disproportionate Marketing Resource Investment

For e-commerce brands, creating personalized recommendations requires marketers to invest substantial time in gathering data, cross-referencing different products, and identifying trends for specific customer segments. However, due to limited marketing capacity and the lack of precision in predictive analysis, many brands were only able to deploy generic marketing messages, which not only takes up a lot of resources, but also fails to effectively stimulate consumer purchase intent. Such misalignment negatively impacts the actual return on a brand's marketing resource investment.

Challenge 2: The Inability to Provide Real-Time Recommendations Based on Customer Behavior

Many brands struggle to offer product recommendations on a timely manner by customer behavior (such as browsing products, adding items to cart, or adding products to favorites) during their initial interaction with the customer. As a result, they resort to featuring the month's bestsellers on the homepage. However, in the highly competitive retail landscape where customer experience is paramount, every interaction influences conversion success. If brands cannot provide thoughtful and personalized purchase options within limited touch points, it significantly reduces customer purchase intent and caused brands to miss potential sales opportunities. 

Given the numerous challenges in execution, many brands find their personalized marketing strategies falling short. To address these issues, beBit TECH has launched the ‘AI Product Recommendation' feature, an advanced application of the OmniSegment CDP powered by high-performance AI.

This feature aims to help e-commerce brands quickly implement personalized product recommendations. Performance-driven AI analyzes customer browsing behavior and automatically provides real-time recommendations for the most suitable products, enticing consumers to make purchases and addressing both brand and consumer pain points. Let's dive into the unexpected functionalities and application scenarios of the ‘AI Product Recommendation' feature, and explore how it can transform your e-commerce brand strategy! 

Performance-Driven AI: Activating Personalized Product Recommendations with Just One Click

The ‘Dr. Kao AI - Smart Product Recommender' feature built into OmniSegment CDP leverages device IDs to track and collect each customer's website browsing behavior. By analyzing behavioral events and interaction trajectories with various products, the system uses Bayesian Personalized Ranking (BPR) to calculate similarity indices and provide real-time recommendations. This ensures seamless interaction between the brand and consumers, delivering the most suitable product suggestions instantly to these customers.

For example, if Customer A browses vitamins, fish oil, and women's health products on a health e-commerce website, and spends nearly five minutes on the fish oil page, it indicates a strong interest in fish oil. However, Customer A has not yet made a purchase. As a diligent marketer, how can you guide the customer to complete the purchase?

This is where AI product recommendations become invaluable! How do we create a ‘personalized shopping journey' centered on the consumer? The system analyzes Customer A's past browsing behavior and interaction data to calculate and recommend the products they are most likely to purchase. Besides matching customer behavior data, the system also recommends similar products through product-to-product relationship calculations. Even if it's the customer's first visit, the system can recommend best-selling products based on overall site behavior data, quickly stimulating and increasing the consumer's purchase intent. 

Placement Options for AI Product Recommendations

How can brands use various website sections to ensure that customers felt understood, and that the consistently anticipates their needs, creating a strong sense of connection?

Placement 1: AI Pop-Up Windows

According to beBit TECH customer data, websites using AI pop-up windows have a sales conversion rate that is 327% higher than those without. This demonstrates that real-time communication centered on personalized needs can effectively stimulate consumer purchasing desire, significantly increasing sales conversion success. What features does the OmniSegment CDP's AI pop-up window offer? How can it help brands capture potential sales opportunities?

The ‘AI Product Recommendation' feature of OmniSegment CDP supports pop-up windows for both desktop and mobile versions, offering three layout configurations (top left, bottom right, center) for flexible adjustment based on website design.

For the desktop version, the pop-up window allows for display of up to four recommended products in the center. The system triggers personalized product recommendation pop-ups based on the customer's browsing behavior (URLs visited, time spent) and various product tags (e.g., purchased clothing but not shoes, active customers). It also includes A/B testing capabilities, allowing brands to continuously test and optimize the user experience for more accurate product recommendations.

For example, brand e-commerce sites can combine the NASLD customer activity model with AI product recommendations in pop-up windows to encourage first-time purchases from potential customers. If a customer spends more than five seconds on a best-selling product page, a related product recommendation pop-up window is immediately triggered, successfully guiding the customer to place an order!

▲ AI Pop up - Presentation on Desktop Web Pages

▲ AI Pop up - Presentation on Mobile Web Pages

Placement 2: AI Product Content Slot Recommendations

Beyond pop-up windows, another powerful application is the AI Product Content Slot, which can be utilized across various sections of a website, such as the homepage, product pages, and even the shopping cart page. With just a click, AI product recommendations can be activated to meet customer purchase intentions anytime, anywhere.

▲ Delivering Personalized Product Recommendations at Homepage

▲ Extending Product Recommendations at Product Page

▲ Personalized Product Recommendations at Checkout Page to Increase Average Order Value

In addition to making optimal product recommendations based on customer behavior, marketers can also manually set the source of recommended products to feature seasonal or promotional items (e.g., Top 3 Father's Day bestsellers) and link them to relevant promotional activities. This allows for real-time sales tracking, making AI an indispensable assistant.

According to beBit TECH customer research, customers who browse AI product content slots experience a 107% increase in conversion rates, and the average order value rises by 19%. This demonstrates that AI product content slots facilitate immediate, interactive engagement with customers, streamline the shopping process, and achieve an operational synergy where 1+1 > 2. This does not only enhance the quality and efficiency of marketing communication, but also helps brands capture potential sales opportunities in one go!

Conclusion

As personalized experiences become the key to success in the new retail market, e-commerce brands must focus on a human-centric approach, integrating thoughtful touches into product services to establish a two-way interactive relationship with customers in order to extend their lifetime value. beBit TECH has introduced the ‘AI Product Recommendation' feature, which helps brands activate personalized product recommendation services with just one click based on customers' shopping behaviors and specific conditions. This feature meets customers' immediate needs, enhances brand value, and establishes a differentiated competitive advantage.

• Continue Reading: Why Should Marketers Know About CDP: What is a CDP and Its Benefits