COVID-19 - Traffic management with computer vision

May 05, 2020

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Aristotle argued that “locomotion is always for the sake of something”, in other words, movement is goal orientated. In this blog post, we begin to explore the ways retailers can use the concept of 'shopper goals', progress markers, and AI to increase compliance with new in-store traffic flow measures.

USING AI TO TRACK TRAFFIC FLOW COMPLIANCE

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Through our experience of tracking movement within stores, we have discovered that approximately 80% of a shopper’s time in the store is spent moving from place to place, making traffic management an important part of any store reopening program. The COVID-19 crisis and the 'Great Reopening' compels retailers to take a deeper look at how people move through their stores, ensuring that shoppers stay safe and stores stay open. Retailers' existing security cameras can be used to measure how effective their traffic management measures are and zero-in on the factors that significantly impact compliance with new measures.

ALIGN SHOPPER GOALS WITH TRAFFIC MANAGEMENT MEASURES

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The idea is that shopper compliance with in-store traffic management measures is largely governed by a shopper's goal for their shopping trip and the characteristics of the path leading them towards their goal. Path characteristics can alter a shopper's perceived progress towards reaching their shopping goal and therefore can affect their willingness to comply with new traffic flow measures. Put differently, cues along a path that signal progress toward a particular location will alter how people move to that location.

THE USE OF PROGRESS MARKERS IN-STORE

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In a supermarket environment, it is likely that new traffic management measures will focus on directing movement towards the end of aisles, product areas, the till area, etc. It is helpful to look at these locations as goals. A shopper's perceived proximity to these goals has important behavioral implications because the willingness to follow a prescribed path increases when the distance to the shopper's goal decreases.

One factor that influences the perceived proximity of a shopper to their goal is the number of “markers,” along a path to reaching the shopper's goal. For example, a route with fewer intersections is judged to be shorter than an equidistant route with more intersections. People might feel closer to their goal when fewer progress markers are placed along a path.

IT'S AN ITERATIVE PROCESS

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Given the multitude of factors that go into curating a customer experience, it is important to apply an iterative approach to creating an effective traffic management program. In this blog post, we looked at the impact that progress markers can have on directing traffic, but this is just one consideration. Finding the best ways to manage traffic in-store, during the COVID-19 crisis requires an iterative approach and solutions that allow you to track the performance of your new traffic management measures are essential.

What data are you using to make these types of decisions? Are you currently leveraging all the data available to you?

To learn more about how you can leverage occupancy data, get in touch with us a hello@auravision.ai.