The client’s business model solely relies on online vouchers and purchases. In other words, the offline business model is left untouched and the “online-offline” loop has to be closed.
Our job is to understand all the possible variants of offline vouchers and the possible limitations of some 3rd party integrations.
In close collaboration with the client, we identified all the dependencies and resources needed to complete the given task. The proposed solution was additional support for “offline” vouchers which bring users closer to the actual shops, instead of their online equivalents.
Additional support was added for global and location-specific vouchers. The voucher providers could be either 3rd party or kept in-house.
The biggest issue is the resources (time, money) needed to satisfy the user’s searches in the location-specific vouchers.
Since the exact walking distance is needed for each of the locations from the user’s location or search query, integration with Google Maps API was also done. The integration meant time and money for each request, so we also had to optimize.
Using mathematical formulas we separated the locations into relevant and non-relevant and only relevant locations are sent to the Google Maps API for querying.
The second optimization was done by implementing caching policies for each of the queries. We used Redis, meaning that every following request which is present in the cache costs no money and takes minimum time to be served back to the user.
The solution is scalable and very intuitive for the user.
The optimizations rendered 5-7x less money spent.
Lastly, by using GA and GTM the client has insight into how their offline vouchers are running and enables them to do data-driven decisions on a daily basis.