Client:
Bright Retail Solutions
Industry:
Retail & eCommerce
Location:
Global Operations
Challenge:
Bright Retail Solutions, a leading retailer with a global presence, was facing challenges in engaging customers and driving sales across their online platform. Despite having a wide array of products, the client struggled with delivering personalized shopping experiences that could keep customers engaged and increase conversion rates.
Solution:
The solution utilized machine learning algorithms to analyze vast amounts of customer data, including browsing history, past purchases, and user interactions. This data was then used to generate personalized product suggestions in real-time, improving the relevance of the recommendations and enhancing the overall shopping experience.
Challenge:
25%
Increase in sales
Personalized suggestions boosted sales by 25%
15%
Higher Satisfaction
Improved shopping experiences boosted satisfaction scores by 15%
20%
Rise in Repeat Purchas
Customers returned more often, with repeat purchases up by 20%
30%
Lower Bounce Rate
Relevant recommendations reduced bounce rates by 30%
35%
Increase Order Value
Customers added more items to their carts, raising AOV by 35%
60%
Increased conversion
Mobile shopping conversions grew by 60%
Tech Stack
Result
The AI recommendation engine boosted Bright Retail Solutions' sales by 25% and increased customer satisfaction by 15% within six months.
Repeat purchases also rose by 20%, highlighting AI's impact on customer engagement and business growth.
The AI recommendation engine developed by aiNexa has truly transformed our customer experience. Our customers are more engaged, and we've seen a noticeable increase in sales. The level of personalization we can now offer is a game-changer
— Head of Digital Marketing, Bright Retail Solutions
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