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November 27, 2013

4 Big Data Strategies for Black Friday

Alex Woodie

Americans’ annual year-ending shopping binge begins this Friday, when millions will head out to find the best deals on everything from TVs and books to handbags and scented candles. It’s also make-or-break time for retailers, who will be counting on the latest big data strategies to help lure shoppers to their stores and websites, and put them into the black for the year.

This Christmas, retailers will be rolling out the latest big data techniques to deliver personalized offers to prospects. The stakes are huge, as each American is expected to spend an average of $646 this holiday season, an 11 percent increase over last year. Here are four ways big data plays into retailers’ holiday selling strategies this year:

1.  Personalized Offers

Consumers are laser-focused on discounts this year. In fact, according to a recent Accenture survey, 62 percent of respondents said it will take a discount of 30 percent or more to persuade them to make a purchase, up 10 percent from last year.

Big data provides retailers with the tools to make intelligent offers to customers, and it all starts with the loyalty and shopping programs that major retailers use to entice consumers to give a little data in return for the promise of big discounts. Once a retailer has the pertinent personal info (name, address, phone number, email address) and the consumer agrees to the all-important opt-in, the retailer’s big data infrastructure (an enterprise data warehouse or maybe a Hadoop cluster) jumps into action.

The more data a retailer has about a consumer’s likes and dislikes, the more targeted they can make the promotions and offers to the consumer, and the more likely the consumer is to bite on those. A retailer whose finely tuned big data apparatus can detect that Jane Doe repeatedly searches the website for “high-end black leather Italian handbags” is more likely to close a deal with Ms. Doe for said product.

The data collected can extend to all sorts of things, such as consumer’s likelihood of searching from PCs to smartphones, her propensity to return items, or how often she calls the toll-free hotline. Retailers with incomplete pictures of their customers will often tap external data feeds from companies like Axciom and Experian, which have extensive profiles of consumers, or use the services of more targeted vendors, such as DigiWorks, which plays digital “matchmaker” between retailers and consumers.

2. Real Time Offers

Personalization goes beyond just the “what” of the product offer, and can also be extended to the “when” and the “where.” For example, a retailer that has generated a profile on Ms. Doe and her online searching and spending habits would like to know when she steps into a retail store to present her with an offer she is not likely to refuse.

There are several ways a retailer can detect physical location of consumers. For starters, the retailer can use the geo-tagging feature of Twitter and Facebook posts to detect when a customer is near. Some retailers have also started detecting consumer’s identities when they connect to an in-store Wi-Fi system. Mobile phone companies have also been known to help retailers by generating “heat maps” of their customer’s movements.

3. Social Media

Sites like Twitter are abuzz with talk of the start of the holiday shopping rush. Simply enter a search term, like #BlackFriday, and you can see some tabulated lists of the best deals. Twitter is also proving a popular place for users to post product reviews. So how can a retailer capitalize on piggyback on these trends? For starters, they can include the aforementioned hashtag in their promotions, which will help attract the highly coveted youth segment of the global pool of 554 million Twitter users.

Over on Facebook, which has 1.2 billion active users, tech-savvy kids (which is probably an oxymoron anymore) are foregoing the traditional Christmas wish list addressed to Santa Claus at the North Pole, and instead posting their wants and desires online for all the world to see–or at least for those 20 percent or so of Facebook users who have very public profiles. There’s a treasure trove of personal data available on Facebook, which is increasingly visible to “silent listeners,” like third-party apps from retailers, according to a recent study in the Journal of Privacy and Confidentiality.

Retailers with advanced big data strategies will gobble up these holiday wish lists and reviews, and correlate it with transactions and information from loyalty programs to devise highly targeted marketing campaigns with excellent success rates. This is where an advanced and well-configured data warehouse or Hadoop cluster will be worth its weight in gold for retailers this Christmas.

4.  Cross Channel

Having a flexible big data strategy will be key this holiday season, as consumers expect to be able to move back and forth seamlessly between the Web, mobile, and physical store fronts. According to the Accenture survey, 63 percent of shoppers are likely to participate in “showrooming” (or going into a physical store to see a product and then searching online for a better price), up from 56 percent last year.

“To be successful, retailers must be able to satisfy consumers who, more than ever, want to shop on their terms and expect every step in the journey to be a seamless one, whether they are online, shopping in a store or using their phones,” says Chris Donnelly, global managing director of Accenture’s Retail practice.

Related Items:

Report: Big Data Trickling Into Retail

Rethinking Loyalty Programs with a Big Data Brain

Retailers Explore WiFi Tracking to Gain an Edge

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