Introduction

IGA (Independent Grocers Alliance) is the largest group of independent grocers in Canada. In Quebec its presence dates to 1953, but it all started in 1873 with the opening of a fruit and vegetable store on Rue St-Paul in Montreal. For generations, the job of running major Quebec grocery stores has passed from father to son and mother to daughter. Today IGA is based in the Canadian and French speaking Quebec region, where the retailer operates 290 participating stores.

In 2016 IceMobile – subsidiary of BrandLoyalty – and IGA introduced the My IGA Stamps app. This was the first Bright Stamps implementation in Canada, but most importantly the first tool for 100% digital promotion. Fully digital provides all the convenience of digital stamps collection, simplicity and efficiency for both retailer and the end-consumer, with maximum fraud prevention.

In 2018 the IGA stamps app implemented the Resono SDK for measuring in store movement. With the use of the Resono platform, IGA was able to gain valuable insights from in store behaviour.

Goals

With the Resono Platform IGA took an important step to further understand customer behaviour in-store and create an improved customer experience. Examples of the behaviour and analytics which were measured are:

  • In-store movement
  • Dwell-time of unique customers
  • Dwell-time in different aisles or sections
  • Measuring the number of visits of a unique customer
  • Number of unique visitors

Method

Beacons were placed in 10 stores throughout Quebec Canada to measure customer behaviour and interactions. In some stores all aisles were covered with sensors to gain more insight in customer behaviour.

All stores were also covered with geofences to measure out of store movement and to better understand conversion. Besides the 10 IGA stores with beacons also with geofences measuring stores throughout Quebec and Canada.

Results

To show a good overview of in store movement we used Sankey flowcharts, to show the most used routes in the flagship store. With this tool we showed in a quick overview of the walking routes of visitors.

  • We registered most customers were recurring at least 1 time during the loyalty program
  • Reports were made on the busiest aisles and sections in each store
  • Some store showed significant differences in customer behaviour which was attributed to store set-up and/or design
  • Cross visits to other owned locations like gas stations were reported in order to further expand on customer loyalty
  • Dwell time in stores were compared and attributed

Each store also had a loyalty program display with all items for which a customer could collect stamps. All customer contacts close to the displays were recorded and attribution models were made of the relation of success of the loyalty display and program compared the the number of contacts and dwell-time.