Case Study

A top e-grocer powers insight-led decisions with
a modern data framework

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Segment

Online Grocery

Objective

Build a reliable and scalable enterprise-wide data platform that supports key analytics and business requirements

Solution

AlgoLake – Modern Data Platform for Retail

Challenges

The client encountered several obstacles related to its data infrastructure that were hindering its business expansion, including

  • Limited ability to process high volume, variety and velocity of data to enable critical functions such as pricing, recommendations, personalization and more.
  • Overdependence on manual interventions to generate analytical reports as needed, and inability to extract valuable insights within a suitable time frame.
  • Increasing expenses linked to data storage and a decrease in business system dependability due to suboptimal data segregation.

In view of these aforementioned difficulties, the client endeavored to create a state-of-the-art data framework that would serve as a catalyst for their ongoing endeavors to spearhead the digital-first grocery landscape.

Solution

AlgoLake: Scalable, Agile and Insights-led Data Framework for Retail

Algonomy’s AlgoLake introduced a ready-to-use framework that empowered the Client to establish its modern data platform. This streamlined solution facilitated the platform’s implementation, allowing the Client to achieve the setup 40% quicker than traditional data lake implementation.

Key highlights of this solution include:

  • Aggregation of data from diverse sources, encompassing sales, procurement, social media, campaigns, clickstream, pricing, product catalog, customer and brand information, promotions, supplier details, and more, and seamlessly integrating it with downstream business systems.
  • Expanding data management capabilities to effectively handle extensive data loads across 700000+ SKUs, supporting up to 300,000 orders daily.
  • Automation of data synchronization and reporting to enable faster time-to-decisioning across business functions
  • Enhancing storage efficiency through intelligent segregation of active and archived data, resulting in reduced storage expenses and enhanced system dependability for the Client.

With the help of AlgoLake, the Client improved upon the following use cases:

  • Pricing Analysis
  • Brand intelligence
  • Category performance monitoring
  • Customer segmentation and personalization
  • Geospatial analysis

Results

  1. Achieved a 20% increase in data synchronization speed
  2. Elevated data responsiveness by 15%
  3. Achieved significant strides in data democratization across several dimensions, notably:
    1. Expedited time-to-insight
    2. Enhanced operational and cost efficiency
    3. Increased data utilization, adoption, and engagement
  4. Significant sales uplift with quicker and more efficient pricing analysis

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