Joining the multi-channel dots – using postcode data to attribute in-store sales to website activity

Working in a multichannel retail environment means a greater need for integrated reporting, an ability to evaluate different marketing activities, attribute sales accurately and ultimately measure how online/offline marketing impacts the bottom line.

We have been working with one of our clients to do just that. Their main website is non e-commerce functional i.e. it is used to drive enquiries for products that typically involve a long consideration period (reflected by the price point). In the digital sphere this means tracking the effectiveness of the website on the bottom line is more of a challenge than with fully e-commerce functional sites. In this instance, we wanted to help demonstrate the role the website plays in a complex sales journey. At Leapfrogg, we never shy away from a challenge so set about implementing a tracking project to attribute store sales back to website visits and enquiries.

The web can often be seen as the enemy of bricks and mortar with stores and the web often having separate revenue targets to hit. Joining the dots between website interactions which lead to in-store purchases is essential to bridging this gap and creative a cohesive multi-channel approach.

Using advanced software, we began tracking store finder searches through the collection of post code data on our client’s website. We began to build a picture of how many store searches were being carried out according to the online channel (e.g. paid search, natural search) driving the visitor to the website in the first place.

The different coloured pins in the screenshots below highlight the traffic source (blue = natural search, red = paid search). The larger the pin, the more store searches that took place in that location.

Overlaying the information captured via the online store search with in-store sales information, we are able to see any postcode searches which have resulted in an in-store quote and order, demonstrating cause and effect between the website activity, in-store visit and ultimately the revenue generated.

By combining this information with….

  • The channel the website visit was driven from e.g. paid search, natural search, email and so on
  • The first click search term
  • The last click search term
  • The order value

…we can further optimise our search strategy, both paid and natural, to support terms that drive in-store visits and purchases.

An interesting by-product of the tracking and analysis project, which hadn’t originally been set as an objective, was identifying potential areas for new store openings. Our client is looking to increase their number of physical stores over the next 18 months.

The postcode search mapping data has enabled them to identify possible areas for expansion based on demand rather than gut feel.

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