- On the demand generation side, they needed a way to pull together data from multiple ad platforms, in-app behavior, and order processing so that they could optimize ad spend, forecast demand, and minimize churn.
- On the supply chain side, Grofers' microservices architecture meant that data was being written to multiple isolated databases. This made it impossible to accurately analyze and interpret the data across every node of the supply chain or cut down on time and resources necessary for data integration while empowering analysts with decision- ready data in the format they need. Because of this, decision-makers lacked the rich insight they needed to proactively allocate warehouse resources, plan inventory, or understand how orders were moving from their warehouses to the customer's doorstep.
TRANSFORMING DATA AT SCALE IN A HIGH-GROWTH COMPANY
Before Integrate.io, analysts across Grofers' teams did their best to support stakeholders with reports that tried to bridge the knowledge gap between silos. But they lacked the engineering know-how to transfer data between sources for timely, accurate analysis.
This put enormous strain on the company's limited data engineering resources as they tried to build and maintain pipelines while responding to a skyrocketing number of analyst requests.
The need for an ETL solution became clear.
But it was critical that any solution Grofers implemented would help them both solve their immediate needs and scale up as their teams and shipment volumes grew.
To solve these challenges, Grofers turned to Integrate.io.
GROFERS SCALES UP, STREAMLINES ANALYSIS, AND SLASHES DATA ENGINEERING TIME
Grofers used Integrate.io's data integration platform to pull together data from microservices, including databases stored in RDS instances.
They leveraged Integrate.io's built-in REST API connector to pull data from multiple vendors and integrate with their existing systems, shortening the implementation period and simplifying data collection.
With Integrate.io's data transformation layer and intuitive GUI, analysts have direct access to the data they need, in the format they need, on a platform that anyone can learn.
And because data from across the entire customer journey and supply chain is merged and transformed, analysts and decision-makers finally have access to big-picture insight without relying on data engineering.
THIS DRAMATICALLY REDUCED DATA ENGINEERING TIME BY AT LEAST 480 HOURS PER MONTH
Grofers estimates that without Integrate.io in their stack they would need to hire four more data engineers to build and maintain pipelines full-time.
Overall, the 360-degree visibility Grofers has with Integrate.io helped the company execute on data-driven decisions more quickly, without having to hire a massive centralized BI team or data engineers for every internal team.
Integrate.io is a great tool for any data team that needs to be agile and produce results quickly. It saves us a huge amount of development time every month and enables your analytics team to start doing valuable analysis, almost from day one.
