Project Summary
The Client
A global restaurant that wanted to embed the customer throughout their digital experience.
The Challenge
The client wanted to optimize their mobile offers to ensure they were as compelling as possible for their target audience.
The Solution
The client used Upsiide to test approximately 100 different messages. With these findings to hand, our consulting team ran a TURF analysis to determine the route forwards.
The Impact
A refined list of messages for their mobile offering and a clear understanding of reach and incrementality.
The reason for the project
Over the past few years, one of the key strategies for this restaurant has been to embed digital capabilities through the customer experience. This has led to a wide range of efforts, one of which is the launch of a mobile app. Within the this app, multiple benefits exist for customers, including access to offers that are only available on the app.
As a way to improve customer engagement with this app, the client was looking to optimize their portfolio of mobile offers with a specific focus to: determine which mobile offers resonate best with customers, identify the optimal number of mobile offers to present at any given time, and discover the best combination of mobile offers across product categories that reach the widest audience and maximize revenue.
The solution
Spanning across multiple product categories (e.g., breakfast, lunch/dinner, beverages, fries, etc.), our client identified just over 100 mobile offers that were to be included within the research. We leveraged the Upsiide platform, where respondents went through multiple Idea Screen exercises, one for each of the product categories. Given how easy and intuitive the Idea Screen approach is, it allowed every respondent to assess all 100+ mobile offers quickly and comfortably.
Results from the Upsiide Idea Screen allowed us to determine the potential reach of each mobile offer. TURF analysis was used to determine the optimal portfolio of mobile offers. Knowing that multiple mobile offer portfolios could reach a similar sized audience, we supplemented the reach with two further points of data. The first determined the potential incrementality of each mobile offer – that is, the likelihood that a mobile offer is able to drive incremental visits to the restaurant. The second was the dollar value associated with each offer – this was secondary data provided to us by the client.
With these three pieces of data in hand, we built a custom Excel-based TURF simulator that allowed our client to build multiple mobile offer portfolios. It allowed the team to not only compare one portfolio to another on each of our three KPIs, but to also optimize any single portfolio of offers to ensure it was achieving a high level on reach, incrementality and dollars.
The outcome
With the ability to experiment with different offer combinations, our client gained valuable insights into the form and structure of the optimal portfolio of offers. The custom-built simulator allowed the team (both at the national and regional level) to plan out their mobile offer schedule for the upcoming year.
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