With stores and malls reopening measuring foot traffic attribution is top of mind.

Gearing up for the holidays? Trying to understand the impact COVID-19 has had on in-store consumer shopping behavior? Wrapping your head around both? A key indicator of how the shopping economy is going to recover lies in traffic; and we’re not talking about visits to your website, lets dig into foot traffic.

Over the past 4 – 6 months, Google Analytics allowed marketers to have an almost-complete picture of how their consumers were behaving when shopping their brands: How many people were coming to the website? What pages were they visiting? How long until they were making purchases? This was all seamless, as brands’ websites were the only places consumers could visit for their purchasing needs. GA proved most critical for Marketsmith and our clients as we navigated through the COVID-19 environment.

But today’s world is slowly, but surely, shifting back to a new normal, where stores and malls are re-opening, consumers are venturing out once again into the brick-and-mortar world, and shopping behavior, as we know it, will fundamentally change once again. We, as marketers, are now challenged once again with understanding the consumers’ journeys, and how we measure foot traffic attribution as another touchpoint in those journeys.

How do we get there? By attributing and understanding foot traffic trends, leveraging device-level data and understanding incrementality through strategic test and control segmentation!

Let’s break it down step by step:

  1. Media campaigns are managed through our Demand Side Platform (DSP), search and social platforms of choice, like Google and Facebook. These platforms are gathering device IDs of all users we are serving ads to. These users are then mapped to what are called device graphs, or technology that links the user’s device ID to all the other device IDs that user owns. For example, if a user sees the digital ad on their desktop, that user’s desktop ID is matched back to their mobile device ID, which helps create the total snapshot of the consumer.
  2. At the start of the campaign, we are also creating holdout segments. These segments contain a statistically significant group of device IDs that we exclude from our media buys. These segments also must have already been to the destination that we’re trying to drive foot traffic to. We will use this holdout control group of existing customers to create a baseline of typical traffic/shopping behavior to these locations.
  3. We then leverage our location data provider partners, such as Factual, NinthDecimal or Cuebiq, to track our exposed segments and their traffic/shopping behavior through the Device IDs we are capturing through our media buys.
  4. Analyzing the data in real-time allows us to understand the difference between the exposed traffic patterns vs. the control baseline; in other words, our incremental foot traffic lift of media!
  5. Not only is the data telling us the story of what drives incremental traffic, but optimizations are also occurring in real-time to ensure that media dollars are allocated to top traffic-driving tactics.

This is just one way we’ve merged the digital world with the physical world and driven real-world results for our clients in real-time.  Download our foot traffic attribution quick guide to keep these steps top of mind!

It is critical for us, as marketers, to understand how media drives all consumer touchpoints, and foot traffic attribution is just another piece of the puzzle we are putting together. Let us help measure your user journey.