Applying Big Data to 2011 Holiday Shopping Information

big data and 2011 holiday shopping 300x300 photo (advanced analytics)By most measures, 2011 holiday sales saw solid gains.

big data and 2011 holiday shopping 300x300 photo (advanced analytics)By most measures, 2011 holiday sales saw solid gains. Overall retail sales rose 4.1%, according to the National Retail Federation. And while 2011 holiday sales didn’t achieve the 5.2% gains made during the 2010 holiday season, they still outpaced the 2.6% growth over the past decade.

But a closer examination shows that not all categories fared well. For example, sales of “mature” consumer electronics devices dipped 5.9% during the Nov. 20 to Dec. 24 sales period, according to The NPD Group. Yet not all consumer electronics suffered. For example, 3DTV sales grew more than 100%, according to The NPD Group. 

Retailers, consumer packaged goods (CPGs) and other types of companies can glean valuable insights about consumers by using big data to examine holiday spending patterns and market basket analysis by customer segment. Business leaders can also use predictive analytics to help identify and provide more relevant upsell and cross-sell offers.

Retailers and consumer packaged goods companies can apply analytics to learn – and even prosper – from the multiple takeaways gathered during the 2011 holiday shopping season. For example, while overall holiday spending was up, department store retailers such as J.C. Penney and Kohl’s discovered that deep and extended discounting during the holidays may have eaten into profits.

Thanks to the use of analytics, retailers have become much more adept at identifying the degree to which they can discount products and still achieve certain profit margins. Analytics can also help retailers look more closely at correlations between discounting certain items and the cross-sell opportunities these might create (e.g. if we offer 30% off this set of children’s coats, what’s the likelihood that shoppers will also purchase hats, scarves, and/or gloves that are priced at X?).

Market basket analysis can also provide retailers and CPGs rich insights into potential upsell or cross-sell opportunities with customers. For instance, if a consumer buys a high-definition television set from Best Buy, the electronics giant typically follows up by email or through other channels to offer complementary products or services, such as HDMI cables, entertainment stands, or Geek Squad services to optimize the quality of the high-definition picture.

Even though the holiday shopping season has technically passed, Best Buy is still reaching out to consumers with relevant offers. Of course, the typical HDTV buyer has likely purchased all of the additional support equipment and services he needs. Nevertheless, Best Buy does an effective job of casting its net out to those stragglers who still need an additional item or two.

Retailers and CPGs can glean other insights from 2011 holiday shopping trends. For example, companies can gain a better understanding of the channels that shoppers tend to use to purchase certain items. From that information, companies can develop more targeted and relevant offers to consumers based on a better understanding of their needs, preferences, and current lifecycle status (e.g. young couple with two toddler-age children).

Some retailers and CPGs accrue up to 40% of their total annual revenue volume during the holiday shopping frenzy. But companies that mine this data effectively can arm themselves with valuable business intelligence that can extend well after the last of the holiday decorations has been stored away.

Next Steps:

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