FootFall is the solution to track and compare visits to your own and competitive locations. The weekly updates use permission-based and anonymized data collected from location-enabled mobile devices combined with EA’s proprietary geofence library. The data are weighted and projected to the total population. Most retail stores, businesses, business improvement areas and recreational locations across Canada are covered. FootFall can be used to track visits for individual locations, and overall retail banners. Reports are provided in an easy-to-use browser-based app. Data can be exported for use in your own reporting or analytical environment.
From competitive analysis to network planning and marketing, FootFall powers decision-making by providing simple, convenient, regularly updated KPIs on visit traffic for the locations that matter to you. For deeper consumer and trade area analysis, the traditional EA suite of products is there to help alongside FootFall, including MobileScapes, DemoStats, PRIZM and more. FootFall will become a critical part of the analytical toolkit used by businesses, not-for-profits and government organizations across Canada to gauge location performance.
Identify which locations have the most or least visits and how they are trending over time. Identify banner and category trends and seasonal impacts
Understand whether your share of total category visits is going up or down to assess competitive impacts
Quantify the impact of your marketing—or your competitors’—on visits using FootFall’s weekly data
• How do visits to my store compare to that of my competitor’s?
• What is the seasonal impact on visits to my store locations by city or region?
• How do my monthly changes compare to industry averages?
• What effect did a new neighbouring business have on visits to my location?
• Did a recent promotion or ad campaign increase traffic to my stores?
Enhance your data with our privacy-compliant, authoritative databases. Choose from over 45 databases including financial, demographic, segmentation and behavioural data.