Finding What Users Shop and Where they Shop in a Retail Environment

Posted by Rahul Sethi on 1:10 PM

Analytics have resulted in the optimization of blogs, shopping sites, and other e- commerce sites alike. While the benefits of analytics have been enjoyed over the Internet, similar kinds of analytics have failed to really percolate into the real World.

True – there may be what one may call ‘retail scanners’ where cameras may be strategically placed, maybe even infrared counters coupled with observational researchers. They however, have very little scope in terms of scale and identifying mega trends in terms of the retail environment simultaneously.

Path Intelligence is a UK based company that could possibly provide some answers to this problem. The model hopes to monitor foot traffic in a rather indigenous way – through people’s mobile phones.

Our cell phones often work in a way where they ping the nearest tower and inform them about their location. So when I am in Worli, Mumbai – BPL Mobile has 2 towers. 1 in Worli Naka and one on Worli Sea Face. So depending on which corner of Worli I am in, one of the two towers will get pinged. Now in terms of identifying location of user – its not really accurate because the area each tower covers is quite huge so it does not really tell the data analyst anything. Path Intelligence has built receivers that detect these signals and triangulate the owner’s location with accuracy of up to a meter – and as a result has brought accuracy into the concept of tracking through mobile.

Each ping is identifiable with each single user. It’s almost like an IP address. IP addresses have their share of problems (think dynamic IP’s) – with mobiles the ping query will not change. So data trackers and analysts can effectively monitor movements in stores (or any other places for that matter – it depends on there the Path Intelligence Towers are put). They can get data such as time spent at locations, “bounce rate” for locations, roadmap for shopping (where do they go first – and subsequently what follows).

If Path Intelligence can somehow co relate the data of users across different retail outlets then they have a winner because they effectively percolate a person’s life. For example, if they can build systems where my data can be tracked in Big Bazaar, Wal Mart, Reliance Fresh, Shubhiksha, Pataloons, LifeStyle etc, and then all that can be combined – then imagine the data analysis potential.

The major disadvantage with this kind of a model is that one can track user movements but there is nothing that Path Intelligence can really know about the customer. Since everything is tracked through mobile phones, only mobile companies will know that.

In my post on the future of VAS I said that Mobile Distributors i.e. the service providers will hold the key to many forms of revenue. This again is one such example where the service providers can milk revenue.

I see an opportunity for cross media conglomerates such as Reliance where they can co relate such data tracking in their stores and super markets with their Infocomm divisions. The only problem is that Retail is being promoted by Mukesh Ambani and Infocomm by Anil Ambani.

Path Intelligence also plans to let users subscribe to services where they can tie their phones to their signal ID’s and receive contextual offers based on their location. The danger obviously is that of spamming.

The company is currently only launched in the U.K but has plans to expand into other countries if the research and business model are viable. If they don’t, expect other companies to develop similar products and monetize on them especially in countries like India where today, the possibilities of data collection through mobile are enormous.


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