Corralling the Data Around Mobile Shopping

For some parts of mobile shopping, it’s all about the numbers.

Anyone tracking mobile shopping behavior is aware that the data coming from shopping activities is starting to look like a tidal wave.

A major report has taken a look at all of this data and points out that the retail analytics objective is to make better operating decisions and improve the shopping experience through the intelligent use of information.

One of the problems is that linking all of the relevant data is hardly an easy task, according to the report by the Platt Retail Institute commissioned by Tyco.

While every consumer digital interactions leaves a digital footprint, tying all those footprints together can be daunting. And that’s where data analytics comes in.

The report cites numerous customer-driven types of retail analytics, such as:

  • Segment, target and personalize offers
  • Identify customers with the likelihood to spend more and the categories for that spending
  • Identify customers likely to shop elsewhere and discover how to retain them
  • Understand which customers represent sales and margin increases (or potential losses)
  • Analyze buying patterns and preferences by segment
  • Analyze price and profitability
  • Gain insights into performance drivers
  • Analyze brand and sentiment
  • Recommend product offerings for particular customers
  • Understand social and other influences and how they impact customers
  • Make adjustments in assortments, pricing, service, marketing communications or other customer experience elements that can produce incremental revenue
  • Gather information about and analyze customer influencers and understand how they impact purchasing decisions.



All easier said than done.

And when adding customer location-tracking technology into the mix, in-store traffic can be included. The report notes that this is critical since 94% of all retail sales occur in a physical store.

The other critical factor is to make accurate inventory information available to mobile shoppers.

The number one experience most (73%) shoppers disliked when shopping was an item being out of stock.

There will continue to be even more numbers and data around mobile shopping as technology and behavior evolve. The challenge will be to identify and deal with all that data.

1 comment about "Corralling the Data Around Mobile Shopping".
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  1. Sarah Delevigne from No one, July 23, 2015 at 5:24 a.m.

    If you are looking for a great analytic tool for your stores, I recommend a french startup called What the Shop ( ). 

    It's a Wifi based solution which looks like Google Analytics but for real life ! And it's working without any app : the solution track all the devices, it's much more powerful than iBeacon in terms of reach rate... There's a lot fo data provided by the tool and they are also able to identify who is the costumer in order to link all those data to a profile.

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