Shopper traffic data gathered from stores and shopping centres enables functions across the entire retail enterprise to perform more effectively. So who should be using this valuable source of business intelligence, and what can they hope to gain from it?
Analysing footfall data enables the store operations team to optimise staffing to create optimal customer experiences, known to increase conversions and sales. Traffic data can be used to manage labour scheduling effectively in line with known busy and quiet times in store, for instance weekly Power Hours or Bank Holidays. The data can also be used to reallocate available associates to achieve favourable STAR (Shopper-to-Associate Ratio).
Store managers, regional managers and operations managers can delve into traffic data to evaluate dwell time and conversion rate for each individual store, and make changes to staffing, training and store layout accordingly. Operational leaders also have the ability to make data-driven decisions based on KPI reporting at a store level to drive increased conversion rates, dwell time and average transaction values (ATV).
Property and Real Estate
Harnessing the power of people counting data can fuel data-driven decision-making for retail property and real estate professionals. Key uses include informing negotiations on lease contracts based on historical shopper foot patterns, resulting in increased profitability.
Footfall data can be used to identify high-performing shopping zones in malls and shopping centres, to support leasing negotiations with historic and current traffic count-per-square-foot, and to understand how external factors such as Bank Holidays influence shopper behaviour and footfall. Retailers can share their traffic data with shopping centre owners and leasing managers, to ensure joint traffic-driving initiatives are properly measured and improved over time.
Retail traffic analytics provide marketing departments with visibility into how marketing activity has influenced in-store footfall and the all-important rate of conversion. Tying campaign periods to footfall enables marketers to align draw rate and conversion metrics to promotional periods.
This makes it possible to build on successful campaigns that not only attracted traffic but also converted well, and thus to eliminate less successful in-store campaigns where ‘pass-by traffic’ is too high. Retail marketers can also understand how different types of campaigns influence in-store footfall and discover geographic nuancing of in-store shoppers.
The most successful retail brands tend to be those with meticulously-planned merchandising. Optimising product placements and properly allocating space are essential for increasing conversion rates, and this is where well-informed merchandisers can excel.
Traffic data analysis enables merchandisers to develop planograms based on traffic counts and shopper flow patterns. They can check the value of new product areas or innovative merchandising strategies, based on their ability to drive up dwell time and conversion rates. And most importantly they can plan for peak times, based on historic footfall, for instance showing which Mother’s Day or Christmas ranges and merchandising displays drove the most in-store traffic and conversions over a specific timeframe.
Retail professionals from the boardroom to the shop floor can improve their decision-making and store performance with footfall data and analytics.
To find out how to drive retail business performance using traffic data analytics, download our free eBook: