Case Study: FlowerAura achieves real-time customer insights with Searce's AWS data lake and recommendation engine

FlowerAura Implements Data Lake Solution and Recommendations Engine for Actionable, Real-time Insights Into Customer's Behavior

Floweraura, an online florist delivering to over 220 cities, required a solution to manage the enormous data generated from its vast product catalog and over 250 million annual website visits. Their challenge was to implement a scalable data lake and a recommendation engine to gain better customer insights and enhance their BI capabilities cost-effectively. They chose the vendor Searce to leverage AWS for this transformation.

Searce implemented a data lake on AWS S3, using AWS Glue for ETL processes and Kinesis for real-time data streaming. They built a recommendation engine by training the data with Amazon SageMaker to provide personalized customer suggestions. The results included a centralized data store that reduced manual effort and licensing costs, faster and better predictions from the engine, and improved customer satisfaction leading to higher retention and lower advertising costs.

Floweraura