How Footfall Analytics helps optimise Retail performance

How many people entered the store (A) during the peak summer month of May?

How did they behave?

What was the footfall to sales ratio for those 31 days?

What was the footfall per square feet during the period?

What does the effective sales per square feet tell about the store visitors?

Retailers who want to get ahead of the competition need to ask many such questions to analyse their store performance data. Such information is put together to understand visitor behaviour and demographics, identify trends and make suitable decisions.

Although organized retail represents only a 5 – 7 % of the total retail industry in India, it is increasingly adopting technology to drive sales. The “footfall” is one such tool used to estimate various consumer and sales metrics.

What is “footfall”?

As the word suggests, it literally means the number of people who have visited the store. Although conventionally, the number of footfalls was used by a retailer to translate into sales, it no longer holds true.


First, because a family of five is considered as ‘one’ footfall (one decision making entity) rather than five footfalls. Second, a visitor (a.k.a ‘footfall) may enter the store to check out what’s on display, but walk out without buying – because(i)  the rates did not suit him, or (ii) the collar designs on the shirts were not what he wanted, or simply because (iii) he had entered to kill time, as he was early for his date!

Store A footfall analytics application

Take the above scenario, where the manager of Store A is checking why sales during May were poor, whereas data and video footage show a high footfall rate. When he correlates data of footfalls, video footage, time stamp and effective sales – he can conduct a suitable footfall analysis and arrive at several conclusions.

a) Most footfalls that did not convert into sales were during the peak afternoon hours.

b) When the visitor behaviour and demographics is studied from videos installed in the store, it reveals that most footfalls were casual strollers – either groups of youth or ‘repeat’ mothers.

c) It is analysed that these visitors had come in for the A/C cooling rather than purchases, and the mothers were probably marking time before picking up their children from the neighbourhood school.

Clearly, the store manager is disappointed. For mere footfall was not the true measure of business done.

Now what he will do with this insight  depends upon supporting retail analytics, technology deployed and store policy. Using technology driven analytics, the store manager can convert a large part of the causal footfalls into sales and additionally focus on the serious shoppers by giving them more moving space and product visibility for higher purchases.

So what does the store manage do? He gathers cell phone data from people who enter the store and leverages this to send personalised, location-specific shopping alerts each time the cell phone user is in the vicinity.

This mobile-enabled foot traffic technology works by “tracking the movement of a customer’s phone” to gather data on how the owner moves around a particular location.

As this report from Software Advice elaborates, “Retailers use this technology to determine peak traffic behaviors, conversion rates and dwell times in the stores.”  The data can be used to plan and re-configure store layouts and merchandise displays in order to attract the casual strollers (‘zero sales’ footfalls) who are seen to hover around the entrance /central area, and translate these casual footfalls into ‘real sales’.

south city

The report details 4 Ways Retailers increase sales with mobile-enabled foot traffic analytics.

  • Identify the differences in sales volume between two of the Group’s retail stores A and B, and apply this information to use incentives – to spike purchases by shoppers in lower-performing stores – a typical customer engagement scenario applied by Euclid Analytics.
  • By installing a mobile foot traffic analytics software, connected to digital advertising displays and a WiFi network. Data collected from smartphone users can be used to produce insights on ‘dwell times’ and visitor traffic patterns. The manager is also equipped with information on the footfall cluster areas that do not translate into sales, and those aisles that have real shoppers.

How to use this insight for furthering sales and store performance?

  • By segmenting the store into discrete zones, mobile-enabled foot traffic solutions can be used “to track the movements of customers down to a few feet.” The store manager can  place particular displays like discounted items or items with high shelf time in store locations that attract causal footfalls. On the other hand, he can enhance the shopping experience of ‘real customers; with promotional signs and prominent displays of profitable brands in the store areas they are seen to spend time.
  • Some mobile-enabled foot-traffic technology also feature A/B testing as part of their dashboards. “This means that you can test two variations, such as displaying the same item in two different store aisles and measuring which location sells more.”

So if you seriously want to make your career in the fast-paced realm of retail analytics, what better way than to suggest your client to use innovative technology-driven analytics? Propose investments into such mobile-enabled foot traffic analytics to boost sales, enhance profits and earn that tap on your shoulder and bonus too?

Bottomline – Sales  is equal to  Footfall  x Conversion ratio x Average Transaction Value. But to drive Sales > F x C x ATV – an analytic professional needs to get into the shoes of the customer and apply his thoughts as a businessman would do – applying innovative applications in the cutting edge retail landscape.

Related Reads:

Spotlight –  Retail Analytics

How to gain business insight with CRM Analytics

How the Analytics Professional can help Retailer unleash the power of Retail Analytics

Role of Analytics in a cutting-edge Retail landscape

How Predictive Analytics drives competitive edge in Online Retailing

Recommended Reads:

How to increase retail sales with foot-traffic analysis

Euclid Analytics’ technology for retail

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