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Case Study

Data science for consumer research analytics

Data engineering, analytics, and NLP to understand brand, consumer and market trends for pharma clients and more


Our client seeks to develop the next generation of consumer analytics within their market intelligence platform. They possess a consistent stream of valuable and proprietary data and need to understand potential analytics and data science driven product features they could offer based on large, everchanging, dynamic datasets. Our client needs to develop an improved data engineering infrastructure to support robust analytics and future growth, with automated data engineering pipelines and sophisticated data visualizations.


Our product design team created new data science visualizations and analytics within a modern and sophisticated user experience to reveal new insights from the client’s proprietary data sets.

Our data engineering team implemented clean data processing pipelines and revamped our client’s data infrastructure to ensure consistent transformation and storage of the client’s extensive datasets.

Our data science team then explored these text-based datasets and developed strategic, high-impact NLP pipelines to automate manual internal workflows and unlock new insights available to their customers, driving sales and renewals to their program offerings.

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