Why Retailers Are Spending Their Money on Big Data Analytics

Do you know anybody who has a smartphone that they only use to make phone calls?  I know a few, and I can only shake my head.  I mean, making phone calls is, in theory, a smartphone’s primary function, but if that’s all you’re doing with it, you’re only scratching the surface of its functional firepower.  It’s kind of the same with big data analytics. 

Integrated analytics tools have been around for quite some time, and most companies use them for their primary function of collecting and organizing customer information.  Many of these companies, though, are just starting to understand the real potential of big data solutions.  A recent Computerworld study found that 43 percent of companies surveyed planned on increasing their IT budgets in 2015, and that 38 percent of executive respondents said they would be dedicating IT budgets toward analytical capabilities this year.  It seems that businesses, especially retail and merchant businesses, are beginning to understand the value that big data and back-end analytics can bring and are investing heavily in figuring out ways to turn the data they're collecting into strategic action.

Leveraging Customer Information as Actionable Insights

Integrated analytics solutions are commonly used to oversee collected customer information. They create customer reports in order to establish a customer profile overview, which allows businesses to segment customers based on buying habits and reach out to them with relevant messaging at the right time.

This has proven to be effective, and now that integrated analytics have matured, retailers are taking things a step further. A recent Capgemini (News - Alert) outlook shows that retail businesses are currently looking to optimize their analytics efforts and find ways to get ahead of the curve when it comes to getting to know their customers. There are currently major efforts in place for retailers to find new, creative ways to leverage advanced shopper analytics.

Not only are businesses looking to interact with customers earlier in the buying process, they’re also looking to change how they interact depending upon a variety of data-driven factors. “Localization will be a big focus for retailers as they look to improve margins by creating the right product assortments for the right stores according to local customer demand, store attributes and product preferences," Forbes reported, citing Ben Pivar, retail leader for North America at Capgemini.  On top of this, advanced analytics may also help retailers design, develop, and forecast demand for new products. 

Retail Partner Collaboration Platforms

Perhaps the most significant way that businesses are gaining a deeper understanding of their customers is through collaboration with partners -- especially those who also touch the same target consumers. Through collaboration, retailers can build a psychographic picture of their target consumer, understanding the “ecosystem” of products and services they interact with every day, giving greater insight into new products and services that they might want to deliver.

In the coming years, secure and easy-to-use analytics sharing platforms will be the newest form of customer insight analysis solutions. Since buying habits in one vertical may vary from one to another, retailers can dramatically improve insight through business collaboration, and a multifaceted retailer can share and borrow customer information with various vendors and suppliers, which will in turn create more well-rounded data of what buyers want and when.

It’s encouraging to see trends that value the utilization of tools for their full functionality.  The future of data and business is all about finding new ways of turning information into action, and forward-thinking businesses already know that integration is the key to unlocking this power.

Deepak Singh is the co-founder, president and CTO of Adeptia, a B2B integration software company that helps its customers achieve faster data on boarding.

Edited by Rory J. Thompson

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