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Solving The Riddle Of Big Data

Ask Siri, the genderless iPhone personal assistant, what the weather is and it can tell you. If you a question like “are you married?” you’ll get an almost human response (it coyly dodges the question). But ask Siri what you’re likely to buy from your favorite retailer -- a deduction based in part on purchasing history and other behavior-based metrics -- and Siri will falter.

Siri fails for the same reason that many retailers fail when it comes to attracting, retaining and engaging customers. For all the talk of Big Data and its global impact, more than a quarter of North American retailers in 2012 -- 27% -- remain unaware of Big Data or are aware of its existence, but uncertain of its retail potential. The rest report partial awareness and knowledge.

For the more than 1 in 4 retailers that have yet to embrace the potential of Big Data, here’s a refresher. For them, the engagement riddle is that retailers have always been data-driven, but on paper and in siloed formats. It’s surprising, then, that so many have failed to grasp Big Data’s customer engagement and loyalty implications. Big Data concerns the accumulation and analysis of -- as well as action on -- the 2.5 quintillion bytes of data created every day, much of it freely available online or on mobile. In fact, 90% of all data that exists today was created in the last two years.

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Big Data and the customer relationship management software (CRM) managing today’s omnichannel environment -- POS, smartphones, tablets, kiosks, digital signage, etc. -- do one thing well and another increasingly well:

The recording of consumer habits: That includes items purchased, purchase location, purchase frequency, amount spent and, sometimes, purchaser gender.

The accumulation of psychographic metrics: Retailers can better predict customer feelings in real-time and use that information to tailor product offerings and loyalty rewards that address their immediate emotions.

Reverse engineering what’s already being done, this new approach to behavioral Big Data analysis helps retailers predict customer wants -- possibly even before those customers are even aware of wanting something.

Loyal to a more social data-driven experience

Retailers are gaining this more subtle but vital information through gamified loyalty programs and social media. Take Raley's Family of Fine Stores, a California-based grocery chain. The brand recently enhanced its Something Extra loyalty program with Try-It, an online loyalty feature only available to Something Extra members. Try-It members are invited to share their product experiences via blogs, social networks, site tools or offline communication. Consumers’ omnichannel interactions are scored by the brand based on their number of “likes,” comments and re-tweets, earning higher scores the greater their interaction. Higher scores also mean access to better deals and campaigns down the road.

Another example comes from David’s Bridal, a U.S. wedding gown and formalwear chain. In an effort to attract and retain customers by using social media to gather even more real-time customer information, David's launched the "My Event" section of its Web site. Brides-to-be use the site to organize and discuss the entirety of their wedding experience with select Facebook friends. The goal is for brides to help generate conversation beyond the dress. Party planning, shopping lists, tasks, even a wedding-related newsfeed are all encouraged. Perhaps the most interesting feature is the “mood board” where members describe how they envision their big day. While the above helps the bride and her family stay organized, the big win for David’s comes in the form of accumulated psychographic metrics and the possibility that more people -- the bride’s social network -- will consider David’s when it’s their turn to say “I do.”

Conversational-based data creating a more accurate customer behavioral picture is at the forefront of where Big Data is going. Considering the speed at which new information is generated and consumers’ increasing desire for timely and relevant offers, the more than 1 in 4 retailers who have yet to embrace Big Data are running out of time. This “retail riddle” shouldn’t be hard to crack.

If retail chains both large and small -- like David’s and Raley’s -- have figured it out, shouldn’t your brand as well? How has your brand embraced Big Data? If your brand has struggled with its incorporation or its analysis, how are you addressing the issue -- and what best practices for implementation can you suggest?

 

 

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