Foot traffic data: The authoritative guide for data buyers and sellers

Foot traffic data has emerged as a leading category within alternative data in recent years. It has a broad range of uses, from monitoring the performance of bricks-and-mortar retailers to understanding trends in tourism, real estate and even demographics.

The insights to be gleaned from foot traffic — also described as footfall or mobility data — are vital for a range of users from different parts of the investment world.

From professional investors like hedge funds and other alternative asset managers to traditional investors, consultancy firms and corporations, there are big research budgets waiting to be deployed.

Neudata’s platform features foot traffic data products from multiple vendors and helps institutional investors, corporations and leading global organisations access them.

Read on to learn about the different types of footfall data, how it is collected, investment use cases and rising compliance concerns surrounding geolocation data collection.

Key takeaways include:

• How do funds use foot traffic data?
• How do vendors collect this data?
• Are there any compliance concerns associated with using this data?
• How can Neudata help firms looking to buy or sell foot traffic data?

How funds use footfall data

Foot traffic data has been used to analyse a wide range of situations. Traction among investors varies, but vendors commonly claim their data produces the strongest signals for the real estate, retail and restaurant sectors.

For instance, Neudata highlighted an analysis of how Hurricane Harvey impacted foot traffic at Walmart in Houston compared to the rest of the US in January 2018.

Investment funds could draw insights from this research about how hurricanes are likely to impact Walmart and possibly other retailers in future, and feed this information into their trading decisions during hurricane season.

More recently, vendors have provided data showing the level of correlation between reported sales and footfall data at Bed Bath & Beyond, a US retailer making headlines on Wall Street this year.

A research report on one of these vendors was among the ten most-read on Neudata’s platform during January. In this case, the data can be used to draw conclusions about a specific company.

Foot traffic is a well-researched area of alternative data – there is even research dating back to the 1940s on the data’s use cases. But it is a rapidly-changing area, particularly given the pace of technological change in recent years.

As with much of the alternative data world, this area comes with jargon attached. Two important terms when it comes to foot traffic data are ‘Point of Interest’ — or POI — and geofencing.

Point of interest

A POI is what it sounds like — a place on a map of interest to the user. It could be a cafe, a hospital or even an ATM. (Importantly, they differ from linear features on a map, such as roads).

Users can purchase an off-the-shelf location data product complete with device counts for POIs. Neudata provides research on plenty of vendors that are selling data products that fit this criteria.

This type of product could be used independently or combined with separately sourced raw location data. Some users improve the purchased product using secondary sources, while some go even further and build their own in-house POI database.

Geofencing

POIs are very helpful — but often not enough. For instance, if funds want an insight into foot traffic within a particular cafe they need to use a virtual perimeter, to understand how many customers visited within a certain time period. Footfall within this perimeter can then feed into their investment decisions.

This is where geofencing comes in. All mainstream mobile operating systems now allow for the creation of geofences which can be any shape and any size, from meters to — in theory — the surface of the earth!

Beyond customer and sales numbers

As we have seen in the case of Bed Bath & Beyond, this data is used to show correlation between foot traffic and sales — probably the most common use case.

But footfall can be used to test other company KPIs, such as inventory turnover and total liabilities.

Neudata lists several alternative data providers relevant to users who want to use foot traffic data in situations other than sales correlation.

Use cases for foot traffic data have typically been associated with tracking short-term mobility patterns.

But after regulatory and media scrutiny, which we cover below, it is increasingly being used to facilitate an understanding of long-term human mobility and population dynamics.

It also has a significant role to play in understanding trends in tourism. Many location datasets are able to track a tourist’s city of origin, as well as activities and POIs visited at a holiday destination.

This in turn gives insight into the performance of tourist venues and other assets in the hospitality sector.

Users should have an open mind when it comes to footfall data, which has practical uses in a far wider range of situations than previously thought.

Investment funds, particularly hedge funds and other alternative trading firms, are often at the cutting edge of innovation and are likely to use foot traffic data in an increasing number of ways in the future.

How do vendors collect this data?

Foot traffic data is harvested using geolocation, the process of identifying or estimating the real-word location of an object, usually a smart device.

There are six main data collection types which provide footfall insights:

1. Cell tower/wireless carrier data. Comparing the relative signal strength from multiple cell towers can be used to identify a rough device location, to about 200 meters. However, the accuracy of data collected in this way is variable — for instance, it does not offer the required precision for measuring foot traffic in physical stores.
2. Satellite GPS. Global Positioning Technology offers considerably better accuracy than wireless carrier data, but can be affected by factors such as satellite availability and atmospheric conditions.
3. Crowdsourced Wifi networks. Location data sourced in this way is highly accurate and a good supplement to GPS data, particularly in environments where GPS signals are weaker.
4. Beacon data. The beacon approach relies on Bluetooth Low Energy technology, which can provide indoor insights, for instance to retailers tracking dwell time at certain aisles. But it depends on customers enabling Bluetooth on their device.
5. IP addresses. Web browsers can collect device location data via IP addresses, but is less accurate than other sources and can be manipulated through VPN usage.
6. Smart card purchase records. Automated fare collection (AFC) systems that rely on smart cards can provide insights into population movement trends.

Are there compliance concerns surrounding this data?

In a word, yes. Raw location data has been criticised in the media and drawn increased regulatory scrutiny due to the ability to re-identify users based on their activity.

2022 was a difficult year for the mobile location data ecosystem. The American Data Privacy and Protection Act, a new federal data bill in the US, was proposed last year. If passed, it could have an impact on the business models of some providers.

Against this backdrop of regulatory change, compliance teams at funds will now be even more laser-focused on possible issues surrounding raw location data.

Anonymised data is not generally subject to data protection laws in the US. That means that many vendors will aggregate/anonymise data to reduce the risk that funds will receive data with PII, or personal identifiable information.

Geolocation data has always been on compliance teams’ radars, but this category is increasing in riskiness, in terms of potential privacy violations and the survival of data providers as viable businesses.

Looking ahead

Despite the turbulence, location data retains the potential to add value for investors and new providers are launching with this type of data.

Neudata has information about at least three datasets expected to launch in 2023 which will be hoping to capture market share following last year’s market turbulence.

Though approaches vary, it seems like there is an increased focus on aggregated data sets after the regulatory issues described. Regulatory change in this area is dynamic and should be monitored closely by customers of this data.

How can Neudata help?

As of February 2023, Neudata has identified more than 80 foot traffic datasets from more than 50 unique vendors.

Neudata is an alternative data-focused research platform that specialises in the objective and neutral assessment of data vendors and datasets. We connect institutional investors, corporations and leading global organisations to the most relevant alternative data sources that are used in their internal data ingestion processes.

Our platform is the global authoritative source for unbiased, independent alternative data intelligence.

We don’t buy or sell data, or require data providers to pay us a revenue-share or commission in exchange for recommending their products to data buyers. That means you get unbiased intelligence that’s tailored to your specific research goals and strategies.

Neudata users leverage insights from our research experts based in London, New York and Shanghai. We can also advise on data scouting.

Since 2016, we have helped our clients understand the landscape of available datasets, increasing the efficiency of their data spending budgets. Neudata’s data buyer clients represent 60-70% of industry-wide spending on alternative data.

If you have foot traffic data and want advice on monetising it, or if you're looking to buy this type of data, please reach out to info@neudata.co to learn more about how Neudata can help.

Photo by Hunter So on Unsplash

‍