WiFi Analytics - Friend or Foe?

27th Mar 2017

The answer to that question should, I think, always be ‘Friend’ but as with so many technologies today, navigating the maze of product offerings and filtering the enormous volumes of data available to get the solution you need as a business is a far from straightforward task. 

We live in a vastly connected world, with consumers carrying one or more mobile connectable devices with them all the time; the widespread deployment of wireless networks in businesses and homes, together with the increasing deployment of public/metro wireless networks, means that vast amounts of data on position, movement, activity, etc., is collectable, and potentially analysable, 24 x 7.

Leveraging big data analytics

One of the great difficulties though, is to actually get to, and take advantage of that, possibly small, subset of all that data to your benefit.

Many years ago when 10Gb optics were at the pinnacle of technology (I know, the ‘good old days’), the great claim was that whole libraries of information could be sent across the Atlantic in less than 5 minutes (say around 20 TByte).

So what!?

It’s a completely pointless exercise unless you can quickly and reliably extract the tiny proportion of this data that will individually be of benefit to the many readers who will have diverse and disparate requirements on what data they want and what they’re going to do with it…

The same applies to the world of WiFi analytics data. With all that information out there, how do you set about making the best use of it?


What do you want to know?

The critical first part is to actually figure out what it is you want to know.

The ‘simple’ route of saying “just give me all the data and I’ll decide what’s useful therein” is the road to ruin; all that happens is that you waste (yes, waste) days/weeks/whatever in crawling through the data and, most likely, discovering all sorts of interesting things.

While they might be interesting, whether or not they are actually useful to you is rather more debatable.

Not only does deciding what you want upfront guide you in the data you want to collect and analyse, it also lets you think about interactions with other systems you may already have in place.

Consider a couple of commonly stated key requirements in the retail arena; tracking customer paths around the store (location-based analytics) and looking at the dwell time in particular areas.

If the final path is towards a payment point then there’s a fair chance that they’re buying something, but if they’ve stopped for a while in several areas on the way then it’s tough to know exactly what they’re buying.

Combine that data with information from the tills (time of purchase, loyalty card data, RFID data, etc.) then the picture becomes clearer. These identified buying patterns then lead to opportunities for location or known habit based marketing to further drive customer purchases and drive the overall business benefits of the analytics process.

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Early adoption

Wi-Fi analytics has the potential to revolutionise brick-and-mortar retailing, and has the power to bridge-the-gap between the online and physical consumer experience, but understanding which metrics are the most insightful and actionable will be the key to successful implementation.

There are currently a number of vendors on the market offer varying degrees customer data through WiFi analytics:

Talk to Ensign’s Retail Wi-Fi experts, contact us today!

What Next?

If you are planning to deploy an enterprise-grade wireless network or are experiencing problems with a existing setup, please feel free to contact Ensign Communications for a chat with our technical team.