01Challenge
Helping Customers Find Suitable Products Across Large Assortments Is Difficult
On e-commerce websites with extensive product selections, customers may need to conduct multiple searches and comparisons before finding a suitable item.
In physical stores, employees cannot always understand every customer’s preferences and previous purchases well enough to recommend the most relevant products.
Displaying the same products to every customer may increase the amount of irrelevant information and make desired products more difficult to find.
02Solution
Combine Customer Interests with Product Information
With appropriate customer consent, AI can analyze purchase histories, browsing activity, favorites, and search behavior.
The system can combine these insights with product information such as category, price, size, color, material, and intended use to recommend products and related items.
For example, the following workflow can be established:
- 1Customer Behavior and Product Data Collection
- 2AI-Based Interest Analysis
- 3Product Candidate Selection
- 4E-Commerce, Application, or In-Store Display
- 5Purchase Result Analysis
- 6Recommendation Improvement
The purpose of personal-data use should be communicated clearly, with controls that allow customers to manage their settings and communication preferences.
03Use Cases
Potential Applications
- Recommending products based on purchase and browsing histories
- Displaying items related to products currently being viewed
- Suggesting coordinated or complementary products
- Sending repurchase recommendations at appropriate times
- Providing consistent recommendations across stores and e-commerce channels
- Filtering products according to customer requirements
- Recommending products based on season or intended use
- Analyzing the relationship between recommendations and completed purchases
04Expected Benefits
Reduce the Effort Required to Find Products and Improve the Shopping Experience
Presenting relevant products clearly can reduce the time and effort customers spend searching and comparing options.
Recommendations for related products and new alternatives can improve the customer experience while creating additional sales opportunities.
Robo Lab uses AI-powered recommendations and customer and product data integration to support personalized retail experiences.