Do we even need footfall data?

No, footfall data is not the most important data set in the portfolio of retailers and restaurateurs. Unfortunately, we have to disappoint you. From a retailer's point of view, the concept of reflecting sales performance in frequency data is outdated and hinders the adoption of appropriate measures to increase sales. It is simply technically wrong. Retailers, restaurateurs, and culture creators need to take a broader view of urban ecosystems. More traffic to their website doesn't automatically mean more sales, either. Let's try to define the value of foot traffic in a contemporary way!

What is footfall?

Foot traffic is always the reaction to the liveliness, attractiveness, and accessibility of an urban ecosystem. The retail, gastronomy, and cultural offerings shape urban ecosystems. A response always follows an action. That is footfall. Footfall does not initially cause liveliness! This is a misconception and must be erased from our minds. People create vitality, but people must first be activated or mobilized by the relevance of an urban ecosystem. The significant key figure is, therefore, relevance and not footfall.

How do I create relevance in a place?

A place becomes relevant to people when it satisfies their needs. These needs can vary greatly and change dynamically from time to time. The reasons for people to stay are as diverse as the people themselves. If we look at the last two years, we understand that the situation in a high street can change very quickly. Positively, with strengthened relevance of concepts, and negatively, with adjusted relevance for consumers. For example, due to fewer visits to the downtown office or a change in the volume of tourism. The focus shifts, and so does the target group.

So if we want to increase the relevance of a location, we have to understand people's needs. That creates attractiveness. Attractiveness mobilizes people. Footfall is created as a result of attractiveness.

One example of how it doesn't work is Friedrichstrasse in Berlin. We saw rising footfall before the pandemic, yet retailers recorded lower sales. More footfall does not necessarily mean more sales. If what's on offer in the location is not suitable and irrelevant to visitors, the purchasing power they bring fizzles out. The downward spiral inevitably begins if no early action is taken in such a situation. If the frequency drops sustainably and persistently, it is already too late. Four years later, the frequency in Friedrichstraße is far below 2019's level. The commercial part of the street may slowly recover, but it will probably take a very long time ... it simply needs new concepts that are relevant for people.

So why would you want to increase the frequency at all? Exactly! The increase in footfall at any price makes no sense at all. Instead, it would help if you increase your relevance. Ultimately, we don't want to measure footfall but positive sales trends. The more sales a store makes, the more relevance it has. There are enough concepts in neighborhood locations that produce significantly more sales outside high-street, center, or retail park locations than in these highly frequented locations. You remember: the city centers need the stores, but the stores no longer need the city centers. There are many reasons for this and, incidentally, many advantages. Lower rents and more space are attractive. You are right next to the customer - at the pulse of the times.

"But I do benefit from the footfall caused by anchor tenants!" No. You benefit from the fact that an anchor tenant appears to have a good offer that people accept. And your concept complements the anchor's offering so that you can siphon off customers from the anchor. Ergo, you don't benefit from footfall but from the fact that you can help satisfy some of the needs of the anchor's customers. This makes a huge difference when looking at it from a merchant's perspective and helps to get things right. #mindset

Is relevance measurable?

"Relevance" as a stand-alone metric is hard to define, if not nearly impossible. If it were, we would probably all be rich. Many variables can give relevance values. For example, the following measurement points can serve this purpose:

  1. The number of competitors / anchors
  2. Market saturationany insights generated from cash register receipts
  3. all trends from customer loyalty programs  
  4. Expansive or contrary competitive behavior
  5. Demographic changes at the site
  6. and much more.

Every company must find its formula for defining its relevance in the stationary sector. Depending on the strategy and orientation, the recipe can be very different. A cheeky coffee house chain that deliberately accepts cannibalization to drive others out of the market understands relevance quite differently than a large department store.

What was that again about omnichannel?

The online store of a well-known perfumery brand sometimes has goods shipped directly from the brick-and-mortar stores instead of from the central warehouse when the algorithm detects that a store has too much in stock. A Scandinavian bedding retailer has every online order forwarded to the store in the customer's region to maintain proximity to the customer. The stores even handle communication with online customers.

Such processes increase stationary sales without ever having claimed footfall. These are just two examples of how the digital world interacts seamlessly with the "offline world." So many parallels can be drawn with online retail to understand even better why frequency is insufficient as a stand-alone dataset.

Online stores invest vast sums in digital marketing campaigns not to attract more webpage visitors but to attract the right visitors. The decisive factor, therefore, is the quality of the website visitors. The same is true for the high street. Imagine location #01 has 1000 visitors daily. Of these, 50 people are part of your direct target group. Not a very good skim. But what if location #02 had 400 people out of 500 visitors as its direct target group? Would you agree that they would prefer location #02 with less footfall, wouldn't you? They would have to spend less money on advertising, have a higher conversion, and maybe you would even pay less rent because location #02 is designated as a B+ location and not an A+++.


The first step is always to centralize data and break down data silos. With our European customers, we also look at footfall, but from a different angle. We blend customer data with data that WHATALOCATION produces itself (e.g., an accessibility index or an attractiveness index) and with third premium data that we buy in. Our various software modules bring together the marketing, sales, portfolio, expansion, and finance teams. Any location analyses result in recommendations for action that our users can take away as "homework." In this way, they sustainably increase the knowledge about their customers and thus also their relevance in their urban ecosystems.