Food and Drink
Case Study: Takeaway
Founded in 2000, Takeaway.com is the leading online food delivery marketplace in Continental Europe—with operations in the Netherlands, Germany, Belgium, Poland, Austria, Israel, Switzerland, Luxembourg, Portugal, Bulgaria, and Romania. The company is focused on connecting consumers and restaurants through its platform. With nearly 50,000 connected restaurants, it offers consumers a wide variety of food choices. Takeaway.com mainly collaborates with delivery restaurants. In addition, the company provides restaurant delivery services in 91 cities in ten countries for restaurants that do not deliver themselves.
As the company continues to expand its presence around the globe, the need to have consistent, reliable data sets became ever so prevalent. Working with Adjust, Takeaway.com streamlined its mobile measurement set up and leveraged raw data callbacks for deeper insight into its marketing spend and ROI. By working with Adjust, Takeaway.com was able to achieve a 35% uplift in conversion rates, and ultimately decrease their Cost-Per-Order by 37%.
Aligning Mobile Measurement Tracking Across Countries
Takeaway.com operates in 11 different countries and has 11 apps, each country with a different name tailored to a specific market. The Adjust SDK is integrated into every single one. All in-app events are tracked through the Adjust SDK and are sent to Takeaway.com’s internal database. To tell a story about a user’s transaction, Takeaway.com tracks a select set of unique events that reflect the order process flow and leverages Adjust’s unlimited event parameters to do necessary LTV calculations.
With the acquisition of food delivery platforms and the expansion into new countries, Takeaway.com was always presented with different mobile measurement setups. For example, the team was often confronted with different sets of KPIs, events tracked and naming convention for events, etc. This misaligned set up made it incredibly difficult to analyze results on a global scale. Not to mention the challenges for Takeaway.com’s internal business intelligence team to compile data for analytics and decision making. This lack of a complete view of their users made it difficult to create marketing campaigns that would drive conversions.
Adjust's raw data callbacks enable us to be a truly data driven company. In marketing, we work with several departments that rely on the data coming from Adjust to make decisions. We can append as many parameters as we want which means we can get really granular with our insights
Team Lead Performance Display, Takeaway
Setting the foundation for a data-driven company
In order to set the foundation for Takeaway.com to be a truly data-driven company on a global scale, measurement and activation between the high number of apps needed to be aligned. To create consistency, the company narrowed its focus down to only the most important steps in the user flow. Once those were defined, the team implemented them as events in the Adjust SDK. The naming convention for these events were aligned across all countries and platforms to provide consistency across all the tracked events. This way managers from all levels could quickly assess performance results across the board and the business intelligence department could easily group data.
Leveraging user level data for LTV calculations
By leveraging Adjust’s raw data callbacks, Takeaway.com set up its internal business intelligence team to ingest conversion data and receive user-level data for a more in-depth analysis. Together with the BI team, the marketing team clustered the incoming data into different groups based on recency, frequency, and monetary value. Data was divided into conversion type, which helped them to see the user's evolution from an install to an order. What’s more, they built dynamic user segments using Adjust user level raw data to predict LTV over time. The data coming from these segments then fueled the retargeting strategies which allowed them to focus on key messaging and imagery to increase conversions. The results of these efforts were significant, with some campaigns experiencing over a 35% uplift in conversion rates and a 37% decrease in Cost-per-Order.