Launching all their partner-facing analytics MVP only took a week
Partner reports are now updated in real-time, not just once a day, as it used to be
The DoubleCloud solution was 20% cheaper than the previous one
About Yango Tech:
Yango Tech is a global technology company that offers customized solutions to help traditional retailers and e-grocers navigate the rapidly evolving digital landscape. We are the E-Grocery and dark store tech provider with c.500 connected shops generating GMV ARR in excess of $900m.
The company develops a universal set of tools that helps traditional retailers and online marketplaces to transition from a brick-and-mortar business model to online commerce with significant improvements in delivery processes. The product includes technological solutions for order fulfillment, delivery, and analytics that set a standard for retailers in the timely and complete delivery of goods.
Yango Tech’s built-in analytics in their product addressed operational tasks for warehouse management but their working solution had several drawbacks:
- Data was updated with a time delay since the pipeline had been designed for batch processing once a day, whilst partners needed real-time updates. Replication of data in real-time was necessary for making quality operational decisions.
- Partners couldn’t analyze aggregated data across all their warehouses. They had to look at separate reports for each.
Yango Tech management had a need for transparency because ambitious goals were set before the team. To achieve this, it was necessary to create internal commercial reporting with operational metrics based on aggregated data from all partners.
The speed of launching analytics was a key factor as there were difficulties because the existing ETL process was lengthy with no possibility to quickly pull something new from the backend, taking a couple of weeks to start displaying it on the dashboard.
It was necessary to quickly assemble an MVP version of cloud analytics that visualized real-time data for all partner stores.The finished solution had to be fast and scalable in terms of adding new data sources, dashboards, and reports. They also took into account Victor Shvedov’s desire: the solution should allow reports and dashboards to be embedded in the partner and product portal interface.
Alexandra, Analytics Product Manager: “Alternative solution options included classic architectures DWH + BI-solutions from the Gartner quadrant. However, Yango Tech was deterred by the lengthy process of product licensing, dependence on the infrastructure team to deploy the technology stack and the complexity of agreeing on a solution architecture that wasn’t based on open-source tech.”
For Yango Tech, analytics is part of their partner’s basic needs, but it was also essential to have their own BI to track the launch of new partners, configure data pipelines from various sources without additional development and waiting. With the introduction of comprehensive analytics, Yango Tech gained a huge advantage for its e-grocery SaaS product amongst industry solutions.
When the final decision was made, the ClickHouse® cluster was set up on AWS S3, and accesses were configured.
The next step was to implement data transfer from the WMS and ERP back-end, as well as develop reports and dashboards in DoubleCloud Visualization, where partners and the team can get information about all their stores.
For internal analytics, reports were created with basic commercial and operational metrics based on which Yango Tech could adjust their business model and look for insights to improve efficiency, profitability, and optimization.
The current architectural solution looks like this:
In the future, Yango Tech plans to improve the data stack: for example, very soon they plan to organize data streaming in their partners' DWH so they can develop their business analytics.
The solution based on DoubleCloud turned out to be 20% cheaper than the previous one, although cost was not the deciding factor in starting the project to implement a new data platform for reports.
Alexandra, Analytics Product Manager: “For me and my team, the key selection criteria were simplicity, speed, and avoiding vendor lock-in.”
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