To spot important opportunities and potential problems, marketing managers rely on internal reports of orders, sales, prices, costs, inventory levels, receivables, and payables.
1. THE ORDER-TO-PAYMENT CYCLE
The heart of the internal records system is the order-to-payment cycle. Sales representatives, dealers, and customers send orders to the firm. The sales department prepares invoices, transmits copies to various departments, and back-orders out-of-stock items. Shipped items generate shipping and billing documents that go to various departments. Because customers favor firms that can promise timely delivery, companies need to perform these steps quickly and accurately.
2. SALES INFORMATION SYSTEMS
Marketing managers need timely and accurate reports on current sales. Walmart operates a sales and inventory data warehouse that captures data on every item for every customer, every store, every day and refreshes it every hour.
Companies that make good use of “cookies,” records of Web site usage stored on personal browsers, are smart users of targeted marketing. Many consumers are happy to cooperate: Not only do they not delete cookies, but they also expect customized marketing appeals and deals once they accept them.
Marketers must carefully interpret sales data, however, to avoid drawing wrong conclusions. Michael Dell illustrates: “If you have three yellow Mustangs sitting on a dealer’s lot and a customer wants a red one, the salesman may be really good at figuring out how to sell the yellow Mustang. So the yellow Mustang gets sold, and a signal gets sent back to the factory that, hey, people want yellow Mustangs.”5
3. DATABASES, DATA WAREHOUSING, AND DATA MINING
The explosion of data brought by the maturation of the Internet and mobile technology gives companies unprecedented opportunities to engage their customers. It also threatens to overwhelm decision makers. “Marketing Insight: Digging into Big Data” describes opportunities and challenges in managing massive data sets.6
4. MARKETING Insight Digging Into Big Data
Although unverified, one popular estimate says 90 percent of the data that has ever existed was created in the past two years. In one year, people stored enough data to fill 60,000 Libraries of Congress. YouTube receives 24 hours of video every minute. The world’s 4 billion mobile phone users provide a steady source of data. Manufacturers are putting sensors and chips into appliances and products, generating even more data.
The danger, of course, is information overload. More data are not better unless they can be correctly processed, analyzed, and interpreted. In one poll of North American senior business executives, more than 90 percent reported collecting more information—86 percent more on average—than in years past. Unfortunately, roughly as many said they were missing out on new revenue growth because they could not gather the appropriate insights from those data.
And therein lies the opportunity and challenge of Big Data. Although a universally agreed-upon definition does not exist, Big Data describes data sets that cannot be effectively managed with traditional database and business intelligence tools. One industry expert, James Kobielus, sees Big Data as distinctive because of: Volume (from hundreds of terabytes to petabytes and beyond); Velocity (up to and including real-time, sub-second delivery); Variety (encompassing structured, unstructured, and semi-structured formats: messages, images, GPS signals, readings from sensors); and Volatility (with hundreds of new data sources in apps, Web services, and social networks).
Some companies are harnessing Big Data. UK supermarket giant Tesco collects 1.5 billion pieces of data every month to set prices and promotions; U.S. kitchenware retailer Williams-Sonoma uses its customer knowledge to customize versions of its catalog. Amazon reports generating 30 percent of its sales through its recommendation engine (“You may also like”).
Many financial brands are putting more emphasis on Big Data. Bank of America is tracking spending and demographic data and tailoring promotions—for example, offering back-to-school deals to cardholders with children. JPMorgan Chase has improved communications to new cardholders to gain more engagement. On the production side, GE set up a team of developers in Silicon Valley to improve the efficiency of the jet engines, generators, locomotives, and CT scanners it sells. Even a 1 percent improvement in the operation of commercial aircraft would save $2 billion for GE’s customers in the airline industry.
Sources: Schumpter, “Building with Big Data,” The Economist, May 28, 2011; Jessica Twentyman, “Big Data Is the ‘Next Frontier’” Financial Times, November 14, 2011; Jacques Bughin, John Livingston, and Sam Marwaha, “Seizing the Potential of Big Data,” McKinsey Quarterly 4 (October 2011); “Mining the Big Data Goldmine,” Special Advertising Section, Fortune, 2012; “Financial Brands Tap Big Data,” www.warc.com, September 13, 2012; Thomas H. Davenport, Paul Barth, and Randy Bean, “How ‘Big Data’ Is Different,” MIT Sloan Management Review 54 (Fall 2012), pp. 43-46; Andrew McAfee and Erik Brynjolfsson, “Big Data: The Management Revolution,” Harvard Business Review, October 2012, pp. 60-68; Ashlee Vance, “GE Tries to Make Its Machines Cool and Connected,” Bloomberg Businessweek, December 10, 2012, pp. 44-46.
Source: Kotler Philip T., Keller Kevin Lane (2015), Marketing Management, Pearson; 15th Edition.