In the dynamic world of retail, regularly quantifying and characterizing traffic – online and offline – is key to tracking performance. While most retailers understand the importance of keeping close tabs on web and app traffic trends and changes, not everyone sees the value in applying the same level of scrutiny to foot traffic. But without visibility into offline data, brick-and-mortar retail stakeholders will never obtain a full picture of their brand’s reach and performance.
What Exactly Is Offline Traffic Data?
On the most basic level, offline traffic data (or foot traffic data) includes any data that quantifies specific aspects of offline visits and visitors. This can include overall visit numbers, shares of returning visitors, or demographic characteristics of visitor groups.
Retailers that scrutinize their online performance based on a long list of pointed KPIs will often use only a tiny set of metrics to evaluate their offline performance – and these metrics (same-store sales, sales/sq. ft., etc.) generally focus exclusively on the moment of sale and could never truly provide an in-depth understanding of their brick-and-mortar channels.
On an industry level, analyzing offline traffic can uncover large-scale changes in consumer behaviors, reveal the impact of new store concepts, and identify rising stars. When analyzed on a chain level, foot traffic data can show how a brand’s stores are performing relative to each other, to their competitors, and to their wider category. Offline traffic data can also provide insight into customer habits around specific properties to help the retailer identify potential synergies and competitive threats.
Expanding the Set of Offline Metrics
Ecommerce analysts understand that while at times a customer interaction will end with a sale, it often does not. So, to identify areas for optimization, analysts look at customers’ interactions with the brand at every level of the funnel, including points of entrance and exit. This gives retailers a high-resolution, multi-layered representation of the brand’s online impact.
For the offline world, the situation often looks radically different. The same retailers that scrutinize their online performance based on a long list of pointed KPIs will often use only a tiny set of metrics to evaluate their offline performance – and these metrics (same-store sales, sales/sq. ft., etc.) generally focus exclusively on the moment of sale and could never truly provide an in-depth understanding of their brick-and-mortar channels.
But sales-focused metrics cannot show all the ways in which physical stores create value for the brand by raising brand awareness, simplifying returns, and facilitating product discovery – and they cannot really help a brand understand who its customers are and what they want. Offline traffic data can answer questions such as – How often do customers return to the store within a quarter? What other brands does the customer like? How far do most of the customers travel? Are there differences between the types of customers the brand is reaching online and in-person? With the right information at hand, retailers can truly assess their brick-and-mortar performance and craft data-driven optimization strategies.
Using Offline Traffic Data to Optimize Performance
In extreme cases, offline optimization may require opening new stores or closing existing ones. But offline optimization is not confined to designing the perfect store fleet, just like online optimization does not end as soon as you set up the perfect website. Customers are people, and people change, so optimizing offline performance means constantly re-evaluating the latest offline data to keep a finger on the pulse.
Recent consumer trends in the grocery space offer a perfect example: In 2020, offline traffic showed that mission-driven shopping was on the rise – consumers were taking longer, less frequent trips to the grocery store. But the situation has now reversed, and the average grocery and superstore store visit is now shorter and more frequent than it was in 2019. Foot traffic data allows retailers to stay up to date on the shopping habits of their offline customers and plan their course accordingly.
Consistently Evaluating Performance is More Important Than Ever
Retail has always been characterized by shifting trends, but the rate of change has accelerated dramatically over the past two years; having a way to accurately and consistently quantify offline traffic is more important than ever. Amidst the rapid adoption of new retail technologies, companies have also recently stepped up their experimentation with different kinds of brick and mortar channels, from small-format stores to shop-in-shops. And retailers who truly want to understand how customers are responding to these innovations need to turn to offline data.
The data revolution has already moved the world of online retail light-years ahead of where it was just a few short years ago. It’s time for offline brick and mortar retail to catch up.
Note: Placer.ai is a Robin Report Innovator. Clink here to more insights and information, and visit the Placer.ai Innovators page.