Mind the gap, what the London Underground can teach retail about using location data

Ed Armishaw

The last three years have been a complete whirlwind for Walkbase, and, indeed, for me with 100s, if not 1000s of conversations all focussing on the core challenge we’re trying to help retail solve “How do you shed light on the black hole of data which are actual real world stores?” 

When I started, I was an evangelist, preaching the good word of Walkbase to retailers who just didn’t know that this sort of data was out there, dealing mainly with e-commerce teams or digital teams as they were the guys who “got” data. Now I’m reading articles on Gizmodo (a popular tech blog if you’re unfamiliar) featuring an exciting project delivering customer flow analytics right on my very doorstep in my home city of London!

Here’s the article in all its glory which is, by the way, a great read put together, I believe, from a Public Information Request…indeed, the only thing I take umbrage with is the use of the “T” word in the title. I’ll give you a minute to read through but please make sure you click back here for my thoughts!

So, what did TFL do exactly?

The project:

Monitor (better than the “T” word) passenger traffic using Wi-Fi tech deployed just prior to the London Olympics in 2012 to anonymously measure traffic flows in 54 London Underground stations across a pilot period of about 6 weeks or so over Christmas 2016.

TFL’s stated aims (as per their blog site):

  •    Providing better customer information for journey planning and avoiding congestion

  •  Helping TFL better manage disruptions and events and ensure a safe environment for all

  •  Better planning of timetables, station designs and major station upgrades

  •  By understanding how customers move through and around stations, TfL also believes it may be able to increase revenue from companies who advertise on poster sites or rent retail units, and this revenue would be used to reinvest in improving services across London.

The results:

Whilst these haven’t been shared fully yet, it’s clear that TFL have uncovered a few hidden gems in analysing this data. The biggest and most obvious win will come in changes to staff planning to ensure demands are met in each station at peak times. 

What really caught my attention, though, was some of the routing data that they pulled together through this project, as it showed why Wi-Fi as a data source is invaluable, even compared to more traditional data sets (Oyster transactions). TFL already know when we start and finish our journey, what they have little view on is how we get there! By analysing this data, showing Wi-Fi impressions picked up at each station on a passenger’s journey, it’s not too much of a stretch to think that TFL could start to optimise tube schedules, and even tube routes in the future! 

What can retailers learn from the good old London Underground?

As the great William Ralph Inge once said, “originality is undetected plagiarism” – and yes I did just google that. With that in mind, it would be silly for us not to have a think about what retail can learn from this project.

Here are 6 ways that I think retail could take from this interesting tech trial by TFL:

1) Sweat your assets.

TFL haven’t invested in ANY additional technology to undertake this trial, quite the opposite, in fact, they have just used the kit which they deployed around the London Olympic Games in 2012. Indeed, these access points have been collecting customer data since they were deployed, they’ve just never interpreted it before.

2) Know your sample, and do WHATEVER you can to strengthen it.

TFL have reported that, based on the stats, 1 in 3 people had Wi-Fi turned on during their trial. They have validated this by comparing the Wi-Fi data with the entry & exit information provided by their ticket barriers. 

This is an identical approach to that which we take with our retail customers – by comparing Wi-Fi data from the store’s interior with footfall data from an entrance counting device we can provide a much better picture of the entire store’s performance. Many go one step further and add Point of Sale data (POS) into the mix to help understand conversion!

3) Tackle the privacy “question” head on

TFL made a big deal of telling their passengers they were undertaking this trial, and that is something I think UK retail can absolutely learn from. Whilst current rulings do not require UK venues to inform customers they are utilising this sort of technology in their stores, if handled in the right way, it can only be a good thing for their brand.

4) If you’re going to pilot, then PILOT

TFL have dived in with both feet on this one, undertaking this research across 54 of 270 London Tube stations. Something retailers can learn from, with so many retail customers in the last 3 years starting too small, and struggled to gleam the insight they expected. Think again about those 1-store pilots, or “store of the future” conversations, PLEASE!

5) Measure things that can be changed, and test test test

This project focussed on some clear deliverables, which should, if actioned correctly, show a direct return to TFL in happier customers and more efficient operations. 

If TFL can do this, then surely retail has a fighting chance. I’ve got countless stories of how retail has used the same data to make more £s, measure marketing attribution and run more efficient store operations. The trick is to drive at actionable insights, and not just data, and this is something we’ve got good at helping our clients out with over the past few years.

6) Turn this data into cold, hard (or warm soft!) cash

I am purely speculating here, but I would be incredibly surprised if TFL are not using some of the routing information, tied with other data sources to work with their advertising partner Exterion Media to create new commercial opportunities for advertisers. I’m going to leave any further comment on advertising for the time being, as my colleague Kate is currently authoring a blog on this exact area, be sure to check it out.

Happily, this is an area I’ve seen retailers really embrace, with Walkbase data used to measure everything from new concession effectiveness to fitting room and till conversion, all with the aim of creating more retail spend. With the high street “struggling”, it’s clear that any data which creates new revenue streams is only going to be a good thing.

Anyway, it’s about time to wrap things up, as I’ve got to jump on a tube …let’s hope TFL have optimised my route to my next meeting! I’d love to hear your thoughts, and comments and am happy to answer any questions. If you enjoyed this read please give it a like and/or a share.


Walkbase provides a retail analytics solution for improving the impact of marketing on physical stores and personalising in-store shopping experience.