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Trends and Outliers

TIBCO Spotfire's Business Intelligence Blog


Using Data Discovery to Increase Holiday Sales

Up to half of a retailer’s annual profits and 20%-to-40% of a retailer’s annual revenues can be generated between the months of November and December, according to the National Retail Federation.

Sales Trends Using Data Discovery to Increase Holiday SalesMeanwhile, other service-related businesses such as restaurants, travel agencies, and caterers are also highly dependent upon sales that are generated during the holiday shopping period. The NRF also finds that 40% of shoppers start their holiday shopping before Halloween.

Add it up, and it’s critical for retailers to plan their holiday sales strategies early, especially if they don’t want to find themselves scrambling for customers at the end of the cycle by offering massive discounts that cut heavily into profits.

Discounting should be viewed for its addictive qualities much like a “potent drug,” notes Marco Bertini of the London Business School in a blog post for the Harvard Business Review.

“The initial effect of a price cut on sales is clear, immediate, and intoxicatingly strong,” writes Bertini. “But just as the company grows dependent on these concessions to meet its objectives, the market grows habituated and responds with less enthusiasm, fueling a downward spiral of deeper and more frequent price cuts.”

With so much customer and market data available for retailers to analyze, it makes sense for retailers of all sizes to closely examine the impact that discounts are expected to have on overall sales and profit volumes.

Data analysis, predictive analytics and data discovery tools and techniques have matured to the point where they can help a retailer identify a customer who’s in one of its stores using geo-location capabilities. The retailer can then analyze the information that’s available about that customer to predict whether it’s worth targeting that customer and, if so, to determine the type of offer that’s most likely to cause the customer to take action.

But there’s no need for retailers to panic about holiday sales volumes, at least not yet.

Four of the five busiest shopping days of the holiday season will come in the 10 days leading up to Christmas Day, according to ShopperTrak. And a frequently-cited report by McKinsey Global Institute indicates that a retailer that uses big data to its fullest extent has the potential to increase its operating margin by 60%.

Indeed, today retailers are able to gather a tremendous amount of information about customers that they can use for strategic planning. This includes the ability to examine the value of placing specific merchandise with specific prices in strategic locations in stores based on the data analysis of customer transactions and behaviors. It also includes using predictive analytics to predict with a fairly high statistical probability the volume of sales (and profitability) that the specific merchandise will generate.

Retailers, like companies in other industries, are looking to generate as much profit from each sale as possible. But merchants should also recognize that there should be some fairness between their uses of customer data for sales and marketing strategies and the markdowns they offer their customers.

“If people allow their data to be used in marketing, it seems right that they should get something in return,” such as special offers or loyalty points, notes Direct Marketing Association chairman Scott Logie in MarketingWeek.

Next Steps:

  • Subscribe to our blog to stay up to date on the latest insights and trends in data analysis, data discovery and predictive analytics.
  • Please join us on Tuesday, December 18th at 1 p.m. EST for our complimentary webcast, “TIBCO Spotfire Delivers Game-Changer – Brings The Power Of Discovery To Big Data,” presented by Lou Jordano, Director of Product Marketing, TIBCO Spotfire. In this webcast we will demonstrate the generally available version of Spotfire 5, the next generation of data discovery and business analytics, offering breakthrough capabilities to speed analysis of big data.

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