Footfall along with the weather are the most often used and sometimes misunderstood words in the world of places/retail.
Often the data is incomplete, inaccurate or being disseminated for reasons beyond the actual meaning of the data.
Stats abound everywhere, every week from footfall being 9% down on high streets in the last 5 years to 3% down in shopping centres and 5% up in retail parks but what does this really mean and most importantly should we believe it?
Data be it big or small, should be transparent and clear.
Data be it big or small, should be transparent and clear, just as the number of transaction and sales from a shop are.
However, clarity of collection method, number of locations, what is being measured and the accuracy to the number of physical people at a point in time is something that no one, in my view, has been able to address.
Commercial organisations understandably want to convince a customer to part with money as a result of convincing them of the need to know. But is footfall still living in the land of the blind where the one eyed giant is king?
Is footfall still living in the land of the blind where the one eyed giant is king?
Consumer shopping habits, patterns and spend profiles are more complex, complicated and as a result more unpredictable than ever before.
You can no longer make assumptions about consumers in the way people did in the past.
The fact you live in a certain house, on a specific road in a type of town does not mean that you will buy a certain car, eat certain food, go on holiday to a specific place or have certain aspirations.
The recent two referendums in the UK and Scotland along with the last General Election prove this. So perhaps traditional footfall stats are going the way that election pollsters are.
Footfall is something which is important to everyone we work with, be it councils, retailers, leisure operators, landlords or investors.
With 13% of retail sales now online, does this make footfall more or less important?
My answer is: more important.
By having accurate, timely and shop specific data you can track the impact of campaigns, events, competition and the pitch of your physical channels.
If internet propensity (an index we have developed with Liverpool University) is higher in one area and lower in another:
- Should I expect more or less footfall?
- Should the footfall I see result in more or less sales?
- Does this profile and my surroundings mean that my store or restaurant will be more or less profitable as a result?
The real truth is no one knows!
At LDC we love these challenges and the partnerships we have with the UK’s leading universities enables us to take our customers issues, whether they know about them or not, and try to find out what really impacts their success.
Data creation, aggregation and analysis is the DNA of LDC and by making our data available to the leading brains in the country we are able to produce interesting insights which, we believe, will ‘make better places to be’, whatever your interest.
LDC data shows that in 2015, multiple retail and leisure occupiers closed a net total of 1,043 High Street stores.
In contrast, 593 independent retailers opened in High Street locations.
What does this mean?
- Is footfall really in decline or is it simply that the customer journey has changed?
- How is ‘pitch’ evolving across these towns and cities?
- Do high street coffee shop brands really increase footfall?
- How do vacant units impact footfall?
- Which high street types are suffering the most, or the least?
Footfall is our latest challenge.
To that end footfall is our latest challenge and we will research it in detail with the Consumer Data Research Centre (CDRC) and University College London (UCL) over the next three years.
It is called the SmartStreetSensor Project and it was officially launched yesterday at UCL to an audience of retailers, leisure operators, landlords and academics.
The SmartStreetSensor Project is to be the most comprehensive study of footfall patterns across Great Britain to date. Over 1,000 sensors will measure live footfall in 81 towns and cities across the UK. The locations have been chosen in order to offer a wide geographical spread, differing demographic profiles and a range of town centre profiles (based on health and occupancy).
LDC has spent 18 months developing and testing its SmartStreetSensor which has been developed and built in the UK.
LDC has partnered with UCL (University College London) and the CDRC to provide the technology and an dashboard for the analysis and interpretation of the live feed of footfall data. This specific project is focussed on High Streets and not Shopping Centres and Retail Parks, however, this is planned to follow in future studies.
Academic lead, Professor Paul Longley of UCL sums up the significance well;
“We think this project is an excellent example of how the world’s of academia and business can work together in the Big Data era. The same data that can tell a retailer how footfall translates into sales at the till can also contribute to a far better understanding of how people move around Britain’s towns and cities. This wider understanding is crucial to better comprehending the health of retail centres, as well as the still broader implications of transport and other planning policies.”
Approximately 50 sensors will be deployed in each week and every retail/leisure partner will have access to the data and wider research as it evolves.
I truly believe that this project enables retailers to get a real and micro level view of what really drives their store or restaurant performance.
Most importantly we will not be looking at footfall in isolation (we would not do the project if this was the case) but overlaying all of the unique LDC data on places and companies along with other publicly available datasets to to deliver the most comprehensive, robust and temporal view of what is really happening on our high streets.
By doing this we will create better places to live, work and play.
By creating independent, comprehensive and live data which all stakeholders can access I believe we can make for better landlord, tenant and council relationships which would enable all interested parties to not just survive but thrive and grow.
This post originally appeared on Matthew Hopkinson's blog here.