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Converting Shoppers To Paying Customers: The 7 Key Stages

Last year when presenting at a conference, the audience, composed predominantly of shopping centre managers and teams, were asked to raise their hands if they were using i-Beacon technology – a good 75% of hands went up. When asked how they were using the technology and what benefits to the business had been achieved, the same audience looked blank faced at one another. The truth is that many had jumped on the ‘new tech’ bandwagon and still needed to work out what they could do with it.

How do we utilise Wifi Analytics?

Mobile analytics have advanced a lot since then. At Ipsos Retail Performance we have certainly developed our thinking and capabilities in this area, and have settled upon Wi-Fi as our preferred technology. We have established what data and insights it can deliver to our clients and clarified what it can and cannot do. One thing that is clear is that mobile analytics are very useful in addition to customer counting sensors at doorways, not as a replacement for it, as some had believed. At best, Wi-Fi analytics gives us trend data on store footfall, but it cannot be used in calculating conversion rates – one of the fundamental KPIs at the heart of bricks and mortar footfall analytics. So where are we deriving value from the analytics provided by tracking and counting mobile devices if not in counting store footfall? The benefits all stem from being able to ‘recognise’ a device as it is detected by the AI (Artificial Intelligence).

What does WiFi Analytics tell us about customer behaviour?

Conventional counting provides a retailer with the core metrics of absolute store traffic numbers and conversion rate. Tracking mobile devices builds another layer of data and insights. We are able to add to a store’s anchor performance metrics, the time shoppers spend in the store and device, or shopper, patronage to the store and ‘peel off’ rate – the percentage of devices/people passing the store that ultimately enter it.

These three supplementary measures have now joined many of our clients’ performance KPIs. In most cases, their ambition is to extend the average dwell time, in the belief that the longer a shopper is in the store, the more engaged they are and the more likely they are to buy. More valuable to them still is being able to track their share of regular shoppers and overlay this with the number of regular spenders from loyalty card data. Adding ‘peel off’ rate enables us to contextualise changes in store footfall, for example, if the drop in store footfall was a consequence of fewer passers-by or if an increase in footfall was due to a specific marketing campaign.rnrnBeyond this, by incorporating mobile and counting data feeds, retailers can measure not only the percentage of passers-by that enter a store but also the volume, and with it a sense of pitch quality and the vitality of local retail demand, so valuable in reviewing estate footprints.

So as far as we are concerned, Wi-Fi is complementary to electronic in-store counters and not a replacement. The latter provides accurate counts of the absolute number of shoppers entering a retail store, and the former adds context in terms of the length of time shoppers stay, their frequency of visits and the ‘peel off’ rate into the store, based on sample data.rnrnWi-Fi alone can provide directional trends but not definitive numbers. As a supplement to counting, it adds another layer of detail – as a stand-alone technology it is far less useful.

At Ipsos Retail Performance, we have a clear understanding of mobile analytic technology and the commercial value it has to retailers. More importantly, we know how to properly implement, measure and consult, to the benefit of a business.