AI Shopping Assistant Enhances User Experience and Revenue for Heureka

User rating 4.2 points out of 5

Achieved an average user rating 4.2 out of 5 points.

Increased revenue by 4%

By increasing conversion rate on desktop devices by 2.6%.

User engagement up to 26%

Per session without any targeted campaigns.

About the Client

Heureka Group is the largest price comparison website and online shopping advisor in Europe. Present in 9 countries in Central and Eastern Europe with over 23 million visitors per month and a network of over 55,000 online stores.

The Challenge

In the competitive world of online retail, choice paralysis has become a significant issue for consumers. Customers are often overwhelmed by the vast selection of products, making it difficult to make confident purchasing decisions. This issue is particularly acute in categories with numerous options and complex specifications, such as strollers, washing machines, and bicycles. The client's vision is to become a trusted shopping advisor, helping users find the best-fitting products while minimizing decision fatigue and improving the overall shopping experience. The AI Shopping Assistant thus perfectly fits into this vision.

The Solution

Datasentics developed an AI Shopping Assistant built on a state-of-the-art generative AI model to address this challenge. The AI Shopping Assistant focuses on understanding customer needs rather than relying solely on technical parameters. It leverages blog posts and parameter descriptions to create intuitive questions, translating complex numerical data into easily understandable formats.

The assistant automatically generates content for various product categories, ensuring that recommendations are always up-to-date and relevant. This solution was initially implemented and tested in categories such as washing machines, bicycles, and mobile phones.

The Benefits

Reduced Choice Paralysis: By guiding customers through personalized questions and recommendations, the AI Shopping Assistant significantly reduces the overwhelm caused by a vast array of product options.
Improved Customer Satisfaction: The initial implementation received an average customer satisfaction rating of 4.24 out of 5, demonstrating the assistant's effectiveness in enhancing the shopping experience.
Increased Engagement and Revenue: The solution helped increase the number of clicks to partner websites on desktop devices by 2.6%, boosting the revenue per session metric by 4%. This engagement indicates that users found the recommendations helpful and relevant, leading to higher conversion rates.
Scalability: The AI Shopping Assistant automatically generates content for various product categories using advanced AI techniques. Initially developed for one category, we successfully scaled it to two more, demonstrating its ability to maintain recommendations across thousands of categories efficiently.
Automated and Up-to-Date Content: With the ability to automatically generate content as soon as data is available, the assistant ensures that all recommendations are current and based on the latest product information.
Time and Expert Resource Efficiency: Through automation, we save time on the manual creation of such a solution, especially considering the multitude of product categories, totalling around 30,000 parameters.
Hypothesized Traffic Increase: There is a strong hypothesis that the AI Shopping Assistant can increase overall site traffic by enhancing user engagement and satisfaction. Users who find the assistant helpful are likely to share their positive experiences with friends and family, referring them to the website. This word-of-mouth referral can drive more traffic to the site, further boosting engagement and potential sales.