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Big Data Acts as Octane to Acquire, Grow, Retain Customers

October 21, 2013

At the start of this year, I had discussed in my blog post “Is Customer the King? In Retail, Analytics Say ‘Yes’,” about how the retail industry can leverage big data insights to optimize and personalize customer interactions, improve customer lifetime value, improve customer retention and satisfaction, improve accuracy and response to marketing campaigns.

An article in The Wall Street Journal last year said that big data refers to the idea that companies can extract value from collecting, processing and analyzing vast quantities of data about their customer experience. Businesses that can get a better handle on these data will be more likely to outperform their competitors who do not. Kimberly Collins, Gartner Research vice-president stated that big data will be the next major “disruptive technology” to affect the way businesses interact with customers.

In this new era of big data, companies need to create a team of customer relationship management experts that can understand the psychology and buying behavior of their customers apply their strong analytical skills to internal and external data and provide a personalized and individualized experience to their customers. In addition, companies will also need to apply futuristic insights using predictive and prescriptive models that will help steer innovation in the industry. Steve Jobs and his company created a need. Nobody knew they needed an iPhone or iPad when they first came out, but today it’s a need for millions of users. Companies need to reorient themselves to 21st century thinking, which unequivocally involves applying big data analytics to their customers (clients, employees and other stakeholders).

Today, companies have access to data unlike they have ever had before from internal systems and external media. This includes all structured and unstructured data. And now companies have access to advanced modeling and visualization tools that can provide the insight to understand customers and even more powerfully, predict and prescribe behaviors.

Ironically – although the retail industry is under tremendous pressure to stay competitive – the industry as a whole lags behind other industries in its use of big data analytics. A report from Ventana Research suggests that only 34% of retail companies are satisfied with the processes they use to create analytics. According to a recent infographic from marketing optimization company Monetate, 32% of retailers don’t know how much data their company stores. And more than 75% don’t know how much of their data are unstructured data like call center notes, online forum comments and other information-rich customer data that can’t be analyzed in a traditional database.

In one of the recent industry case studies, the CMO of a retail company convened a group of marketing and product development experts to analyze their leading competitor’s practices, and what they had found was the competitor had made massive investments in its ability to collect, integrate and analyze data from each store and every sales unit. The competitor had used this ability to run myriad real-world experiments, testing their hypothesis before implementing them in the real world. At the same time, it had linked this information to suppliers’ databases, making it possible to adjust prices in real time, to reorder hot-selling items automatically, and to shift items from store to store easily. By constantly testing, bundling, synthesizing and making information instantly available across the organization—from the store floor to the CFO’s office—the rival company had become a different, far nimbler type of business. What this CMO had witnessed was the fierce market competition with effects of big data.

Retailers that are taking advantage of big data’s potential are reaping the rewards. They’re able to use data to effectively reach consumers through the correct channels and with messages that resonate to a highly targeted audience. Smart retailers are using advanced revenue attribution and customer-level response modeling to optimize their marketing spends Although there are obvious benefits, many retailers are surprisingly still failing to act on these trends. This delay is largely due to a dependence on siloed information, lack of executive involvement and a general trend among marketers to fail to understand analytics. Without advancing internal structures, gaining executive support or educating internally, jumping on these big data trends is nearly impossible.

The new IBM/Kantar Retail Global CPG Study of over 350 top CPG executives revealed that 74 percent of leading CPGs use data analytics to improve decision making in sales, compared to just 37 percent of lower-performing CPGs. By the same token, the new IBM study of 325 senior retail merchandising executives, conducted by the IBM Center for Applied Insights in conjunction with Planet Retail, reports that 65 percent of leading retail merchandisers feel big data analytics is critical to their business compared to just 38 percent of other retail companies.

The two independently developed studies found interesting trends:

  • 63 percent of top retail merchandisers have the data they need to conduct meaningful analytics, while 33 percent of other retailers do not.
  • 37 percent of leading CPG companies make decisions predominately on data and sophisticated analytics versus just 9 percent in lower-performing CPG companies.
  • 83 percent of leading retail merchandisers are focusing more on the consumer, compared to just 47 percent of lower performing retailers.
  • 43 percent of leading CPG companies’ sales organizations are highly focused on the consumer versus 28 percent of others.
  • 69 percent of the marketing departments of top retail merchandisers are highly collaborative versus 39 percent of other retailers.
  • 44 percent of leading CPG companies report a “robust partnership” between marketing, sales and IT versus only 20 percent of their competitors.

For retailers like Macys, the big data revolution is seen as a key competitive advantage that can bolster razor-thin margins, streamline operations and move more goods off shelves. Kroger CEO David Dillon has called big data analytics his “secret weapon” in fending off other grocery competitors. Retailers are moving quickly into big data, according to Jeff Kelly, lead big data analyst at Wikibon. Big retail chains such as Sears and Target have already invested heavily in reacting to market demand in real time, he said. That means goods can be priced dynamically as they become hot, or not. Similar products can be cross-sold within seconds to a customer paying at the cash register. Data analysis also allows for tighter control of inventory so items aren’t overstocked.

To stay competitive, retailers must understand not only current consumer behavior, but must also be able to predict future consumer behavior. Accurate prediction and an understanding of customer behavior can help retailers keep customers, improve sales, and extend the relationship with their customers. In addition to standard business analytics, retailers need to perform churn analysis to estimate the number of customers in danger of being lost, market analysis to show how customers are distributed between high and low value segments, and market basket analysis to determine those products that customers are more likely to buy together.

Retail banks have gathered electronic data on customers for decades, but it is only in the past few years that they have learned how to put all that information to work. Wells Fargo, JPMorgan Chase, Bank of America, Citigroup and Capital One are now taking advantage of the big data opportunity. Big banks are embracing data analysis as a means to pinpoint customer preferences and, as a result, also uncover incremental sources of revenue in a period of stalled revenue growth.

Smarter banks will increasingly invest in customer analytics to gain new customer insights and effectively segment their clients. This will help them determine pricing, new products and services, the right customer approaches and marketing methods, which channels customers are most likely to use, and how likely customers are to change providers or have more than one provider.

Industries leading big data investments in 2013 are media and communications, banking and services. This is a change from last year’s leaders — education, healthcare and transportation. Planned investments over the next two years are highest for transportation, healthcare and insurance. However, every vertical industry again shows big data investment and planned investment.

 

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Clearly, a range of business problems are being addressed using big. In both of Gartner’s 2012 and 2013 studies, business cases that improve process efficiency (“operational excellence”) and business cases around customer experience dominate big data wish lists.

 

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Creating new products and business models is a game changer for many. For the services industry, creating new products and business models using big data is their No. 1 priority. Banks, retailers and CPG companies that are applying big data analytics to better understand consumers and adjust to their needs are outperforming their competitors who don’t, according to a pair of studies released by IBM. Advanced big data analytical applications leverage a range of techniques to enable deeper dives into customer data, as well as layering this customer data with sales and product information to help retailers segment and market to customers in the ways they find most compelling and relevant.

Historically, retailers have only scratched the surface when it comes to making use of the piles of customer data they already possess. Add social media sentiment to the mix, and they can access a virtual treasure trove of insights into customer behaviors and intentions. The timing couldn’t be better, because these days’ consumers award their tightly held dollars to retailers that best cater to their need for customized offers and better value. The ability to offer just what customers want, when they want it, in the way they want to buy it requires robust customer analytics.

A recent Gartner survey of over 720 leading companies revealed that big data investments in 2013 continue to rise, with 64 percent of organizations investing or planning to invest in big data technology compared with 58 percent in 2012. The opportunity is now: It’s critical that retailers step up their customer analytics capabilities as they transition to an all-channel approach to business.