This is the second half of a two-part blog post. You can read part one here
The Changing Face of Customer Analytics
The most recent advancement in capturing information about consumer visits is the coolest of them all. It avoids issues plagued by older techniques, is non-intrusive, incredibly flexible and provides very accurate location data, as well as trip patterns. All you need is a geo-fence – pictured below – and the movement of smartphones that entered the geo-fence can be extracted. This innovation brings together two market leaders – UberMedia and Tango. The new offering has been revolutionary to say the least!
This partnership was announced just last year at ICSC RECon 2015, and already we have restaurants and retailers capturing customer data for their stores, competitor stores and potential new locations. Just imagine if you tried to survey customers in one of your competitor restaurants. The outcome would not be pretty. That obstacle has been overcome and because customers carry a smartphone, you can generate a wealth of location information for your stores and your competitors. This has drastically decreased the costs of data capture and opened the possibility of building accurate forecasting models to everyone.
Tango was the first to bring a solution like this to market and we were very deliberate in our actions. If you are evaluating data sources that are based on telematics such as GPS tracking of vehicles or cell tower data, these solutions are not suitable for retail analysis. Simply put, the location accuracy of telematics and cellular tower-based customer tracking data is flawed and does not approach the accuracy that can be achieved using the UberMedia data. Locational accuracy is one of the most important metrics you should be using to evaluate solutions. An accuracy of 250 meters – compared to the 3 meters offered by UberMedia – would include customers in the store next to yours or pick up traffic on the road beside your drive-thru. Telematics and cell tower data sources are for crowd sourcing and large scale transportation planning, but they are not suitable for detailed retail location analytics.
Tango recently launched a new service with UberMedia called SiteImpact℠ which enables retailers and restaurants to quickly and cost-effectively determine the sales cannibalization impact of proposed new locations on existing stores. This new offering avoids the issues discussed throughout this post and can help franchisors and franchisees alike avoid situations where excessive cannibalization has turned a profitable store into a problem store.
The process is simple: login to the website, enter your details, locate your existing store or restaurant and draw a polygon (geo-fence) around it. This will be the geo-fence within which smartphone data will be extracted. Next, draw on the map to locate the proposed new store and enter the last Trailing Twelve Months sales. SiteImpact℠ will extract UberMedia data, calculate the cannibalization estimate and enable you to download the final SiteImpact℠ Report. The report provides a cannibalization estimate – the distance between the existing and proposed store and a breakdown of sales across common activity generators, such as residential, work, shopping, hotel/motel, transient road and ‘other’, which includes institutional, airport, hospital and military, to name a few.
Along with the generator breakdown, the trade area demographic details and a map of the UberMedia data are provided. The easy to read SiteImpact℠ Report provides all the information needed to understand the cannibalization a new site will have on an existing store. The Dark Days of Surveying are finally over! Retailers and restaurants can now achieve fast and reliable cannibalization estimates with a few clicks.
Tango is committed to helping you at every step of the Store Lifecycle and understanding cannibalization accurately should be considered at the very start of the process. To learn more about how Tango helps you understand the impact of cannibalization, download the Tango Predictive Analytics datasheet.
