Large company/Customer Intelligence

Customer needs analysis platform

A large French group needed to understand the current and future needs of its customers by aggregating a massive volume of consumer data. After a POC of 8 weeks, we industrialized a complete platform deployed on all French entities and is now being extended at the group level.

Problem

The client had no consolidated vision of the needs of its consumers. The data existed in very large volumes, but was scattered between multiple providers and internal systems, without processing or predictive models to exploit them. Business teams made decisions based on fragmentary and retrospective analyses, without the ability to anticipate. The result: missed business opportunities, non-existent personalization, and an inability to detect weak signals of changing customer needs.

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Solution

What we built

We deployed a team of 2 Data Scientists, 1 Data Engineer, 1 Data Architect and 1 Full-Stack Developer to design and industrialize a platform for analyzing and predicting customer needs.

Step 1 — POC in 8 weeks. Validation of technical feasibility and business value in real conditions. Definition of the perimeter, first models, first visualizations. The POC convinced the customer to move to industrialization.

Step 2 — Architecture and data ingestion. Implementation of a complete infrastructure on AWS: automated ingestion of provider data, pre-cleaning, storage and orchestration of flows. Designed to absorb a massive volume of consumer data that is updated daily.

Step 3 — Analysis and prediction models. Development and integration of machine learning algorithms to analyze current behaviors and predict future needs, by segment and by entity.

Step 4 — Visualization application. Development of an interface in ReactJS and VueJS allowing business users to consult analyses and predictions on a daily basis, to filter by segment and to manage their commercial actions.

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