Marketing technology


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 [email protected].