Page Comparison

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🤝 Introduction

Through our Digital App, Tim Hortons (“TH”) gathers a significant amount of data on loyalty guests, including purchasing and traffic information. From a data analytics perspective, this data is predominantly utilized by the Digital Loyalty Analytics team. When examining the performance of new products following introduction to market, the Category Management team typically makes use of system-wide data and, using this, is able to analyze performance metrics based on these macro performance metrics. However, the lack of guest-level data prevents the wider organization, including Category Management, from gaining a deeper understanding of uptake of the new product, as guest level data is relatively inaccessible to these teams. For example, teams are unable to examine the critical measure of rates of repurchase of a product, as they are unable to track guest-level purchases. The availability of this data would allow Category to track guest level purchases, and importantly, repurchase behaviour.

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• The behaviour of guest cheque when purchasing the product [Product Category].

• The behaviour of guest cheque who purchased the product, and guest cheque who purchased the category (but not necessarily the provideproduct). Providing insights on whether guests are trading within category. This, in combination with other metrics, provides insights on product & category cannibalization.

• The behaviour of guest cheque when purchasing the product [Product Category] as compared to the overall guest base. This provides insights on whether the new product has an influence on guest cheque.

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