There are several main things classical retailers could gain an insight about: dwell time is a base to make conclusions of personnel effectiveness and merchandise efficacy, capture rate (proportion between visitors and all people flow around the store) is the only unprejudiced measure of marketing campaigns effectiveness. Dynamics of the people flow outside the store gives a possibility to adjust local marketing campaigns and to make them more effective than before, adjust store opening hours, and many other options. Since system remembers MAC addresses of once visited the store, WiFi-analytics can even work as a “virtual loyalty” program, indicating a portion of loyal, returning visitors at any period of time, making RF-analysis, cohort analytics and many more.
Analytical abilities are really endless: for any brand or a store chain, it is possible to tell which shopping malls in the city have more of the relevant audience; it is possible to see if there is an audience cannibalization between closely located stores, etc.
Knowing the footfall around the store makes it an excellent argument while talking to landlords in shopping malls about rental prices; overall, the traffic around the store is a totally new metric that allows making a lot of exciting conclusions to be used by different stakeholders.
RetailInstruments could offer various metrics that are specific to stores working in the ‘isles’ format inside shopping malls, providing with valuable information.
System is widely used by marketing, business development, rental, retail, HR, and some other players inside retailer’s organization.
Actual system implementation takes minutes and hours, and not months and years – it is very close to a simple plug-n-play: after the sensor is installed and calibrated in each store, the full analytics is available next morning via any browser.