Data Analysis Helps Offset Holiday Shopping Volatility

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Black Friday retail sales online has topped $1 billion this year for the first time ever, with online spending trending way ahead of the retail industry’s predictions for the holiday season, according to data research firm ComScore Inc.

ComScore expects online retail spending to increase 17% through the whole holiday season, ahead of the retail industry’s expected 4.1% increase.

The growth is propelled in large part by shoppers using their smartphones while in physical stores to check deals and tablet computers to shop in the evening, ComScore notes.

This fact – as well as many stores opening on Thanksgiving Day – means an even more unpredictable holiday shopping season for retailers.

For example, CyberMonday has traditionally been a huge online shopping day for retailers. But Mia Shernoff, executive vice president for Chase Paymentech, a payment processing unit of J.P. Morgan Chase & Co, tells Reuters that this year’s sales will be lower than in past  years

“Faster broadband Internet connections in the office used to drive this,” she says. “But now many consumers have faster connections at home and smartphones and tablets – they don’t have to wait.”

In addition, she notes that while Black Friday online transactions have jumped almost 30%, the average ticket price is down more than 11%.

“It’s driving prices down,” Shernoff says. “Consumers are checking prices in stores and showing the retailer, and the retailer will succumb to the lowest price online so they don’t lose the consumer.”

According to IT research firm IDC, big data and predictive analytics can allow retailers to “earn customer loyalty, bring successful new products to market, collaborate through supply chains with business partners, enable associates, reduce risk, ensure compliance and promote their brand.”

However, to do this effectively, retailers need to capitalize on big data and predictive analytics.

Customer data sources, social data sources and other data sources create a huge data stream that retailers can mine, says Greg Girard, program director at IDC Retail Insights.

“The returns on investment in big data and analytics can be monetized through traditional levers of customer loyalty, revenue growth, cost reduction, and new business models,” he says. “Value creation requires aligning big data and analytics projects with three imperatives of omni-channel retail – insight, personalization, and personalized community engagement with the brand.”

Tapping big data – including data from mobile devices, indicators that customers or potential customers give about their preferences via blogs, on Facebook or in online forums – and combining it with traditional transactional and demographic data as well as data analysis and predictive analytics can allow companies to ease some of the volatility in today’s retail landscape by predicting future trends.

In fact, data analytics can effectively turn the traditional marketing 80/20 rule on its head, according to a recent ClickZ article. Marketers have long maintained that 80% of sales comes from repeat customers while 20% comes from new customers – and it costs 10 times more to gain a new customer than to get an order from an existing customer.

“Because of our ready access to customer history of sales and other behaviors and our ability to hitch those markers to other outside data points, we’re able to extend the experience of relevancy from actually relevant customers to potentially relevant pseudo customers,” the article notes. “Current customers can be romanced more cost effectively, leaving more budget and energy to apply to finding new customers.”

Here are fours ways to effectively flip the 80/20 rule:

  • Get social: Use social communities like Facebook and online forums to engage with your existing customers so that they can publicly share their connections to your brands and products.
  • Focus on customer experience: Because of the new buyer behavior such as rating products online and sharing thoughts about products with friends, it’s more important than ever to track customer experience and continually fine tune it based on feedback.
  • Span the channels: The options for customer touch points continue to expand, with consumers using smartphones, tablets, call centers and stores to interact with retailers. You must ensure that you can collect information about customer behavior and preferences no matter how they connect with you so that you can tailor the same offers and services to the customer regardless of the channel delivering them.
  • Listen and learn: “You don’t really need to communicate across all platforms if your customers tell you either explicitly or through data how they want to hear from you,” ClickZ notes. “You’ll also save money and avoid annoying customers if you have a measured and segmented communications approach that varies with the customer and season, among other variables. Using the appropriate level of testing and analytics for your business will enrich the customer picture dramatically.”