Marketing technology Featured

8:00pm EDT April 25, 2007
Marketing technology has made huge leaps in recent years. And companies that have not jumped on board have been left in the dust. “It’s all about predictive analytics and data mining,” says Dr. Joe F. Hair, professor of marketing at the Coles College of Business at Kennesaw State University in Kennesaw, Ga. “These practices can use the mountains of digital data being collected every day and give companies useful information that can improve their decisions, increase profits and provide added value to customers.”

Smart Business spoke with Hair about the value data mining can bring to companies that are looking to ramp up their marketing efforts and boost their bottom lines.

What is the number one marketing mistake companies make?

The number one mistake is probably not keeping up with changes in technology that impact marketing. Digital technology is pushing marketing into a new dimension. In the past 10 years, more than half of the human race has moved its work, shopping, playing and chatting online, creating mountains of digital data that once would have languished on scraps of paper or vanished as forgotten conversations. And until the last few years, a lot of information just disappeared. It either wasn’t collected or it was overlooked as a resource.

Much of it was potentially valuable for businesses and government. The information wasn’t collected or simply thrown away because it wasn’t economical to collect, store, analyze or interpret. Today, virtually all companies large or small can convert what once was a ‘waste byproduct’ into knowledge that improves its decisions, increases profits and provides added value to customers.

What sort of innovations in technology have made marketing more effective today?

Survival in a knowledge-based economy is derived from the ability to convert information to knowledge. To do so, managers increasingly rely on the field of predictive analytics, which uses confirmed relationships between decision variables to predict future outcomes. Data mining first searches for data patterns and identifies promising relationships. The relationships are based on searching data (numbers such as sales, cost, profits, etc.), text (words or phrases in both internal and external documents), Web movements (click-through and time-spent patterns), visual images and so on.

Predictive analytics then uses confirmed relationships to predict future trends, events and behavior patterns. By using predictive analytics, marketing and business researchers help companies solve problems, pursue opportunities and identify relationships as they currently exist or as they’re likely to exist in the future.

Increased data comes from many sources, including retail point-of-sale purchases, online transactions, medical, educational and governmental records, global positioning systems, RFID (radio frequency identification devices), wireless electronic data sensors and so on. In many instances, it costs little to collect data today since it’s a byproduct of information technology developments that are an integral part of modern organizations, including government agencies and most business types. Once data is collected, it costs little to store in data warehouses.

Another innovation in marketing technology is mobile phone advertising and, most recently, location-based advertising. Location-based advertising over mobile phones has been available for a couple of years, mostly in Asia. It gets ad messages out by installing special transmitters in prime locations for particular market segments, such as in airports, train stations, shopping malls and on billboards that send messages to anyone carrying mobile phones with Bluetooth technology.

What benefit can a company achieve through data analytics?

Mainly, companies can control costs and grow revenue. Many companies use the techniques to manage all phases of the customer life cycle, including acquiring new customers, increasing revenue from existing customers and retaining good customers. By determining good customers’ characteristics, companies can target prospects with similar characteristics. Profiling customers who have bought a particular product can focus attention on similar customers who haven’t bought a product or service (cross-selling). Identifying customers who have left enables a company to understand customers who are at risk for leaving (reducing churn or attrition), because it’s usually far less expensive to retain a customer than acquire a new one.

Predictive analytics is having the most impact on improving marketing research and changing advertising strategies. The result is that nontraditional media, such as the Internet, podcasting, blogs, product placement, video games and search ads, are now the fastest-growing media to communicate with customers and account for almost 20 percent of many companies’ annual ad budgets.

JOE F. HAIR, Ph.D., is a professor of marketing at the Coles College of Business at Kennesaw State University in Kennesaw, Ga. Reach him at jhair3@kennesaw.edu.