Life was simpler in 1979 when DM News and NCR’s Teradata division were born. Sears’ “Big Book” was a staple in the American home, and television viewers turned to one of the three major networks to get their nightly news. The main marketing channels were TV commercials, print and direct mail.
But even then, something was unfolding that would change marketing: 500,000 computers were in use in the United States. About this time, E.F. Codd created SQL (Structured Query Language), a business language that would make it easy to run queries about customers based on information collected in the corporate systems.
SQL is the ANSI standard query language for all database tools, and every company has an online customer database today. Technology lets marketers worldwide gather increasingly detailed knowledge about their customers and businesses.
Then and Now
In 1979, large companies such as American Express and State Farm Insurance ramped up their use of direct marketing through mass mailings generated from customer lists to increase customer retention and cross-sell ratios. Database marketing back then meant creating standard fixed reports and doing list pulls.
Mass mailings brought sales, but reaching the customer was no small or inexpensive feat. Computing was performed by mainframes and controlled by the IT department. For every mailing, the client list was loaded manually into the mainframe via punched cards. In addition, batch processes were used to update client information. Both were time-consuming processes. The result was that even as mass mailings were being created, some customer data changed before mail pieces reached the post office, and companies had no easy way to capture those changes.
Tracking the success of mass mailings or television DM campaigns in the 1980s and early ’90s was primitive by today’s standards. Companies could track cost per sale, cost per lead and other basic metrics, but people in the marketing department did not control the system and could not get customer and sales data when they needed it.
Database marketing matured in the 1990s with the advent of complex scoring models to predict customer behavior. Today, most companies add third-party-append demographic data to their customer databases and routinely develop tens to hundreds of scoring models that use from two to more than 1,000 data fields.
The ’90s also brought legal challenges about list use and consumer privacy. We have no-call and anti-spam legislation as well as numerous privacy organizations. Still, surveys show that the majority of consumers are willing to share personal information with companies if it means getting more personal service while shopping.
Looking Ahead
Is something new on the horizon, or will it still be about the “right stuff” – the right message about the right product to the right customer at the right time over the right channel? I predict three evolutions and one revolution that I call cocooning.
First, the idea of one to one, espoused by Don Peppers and Martha Rogers, will become more realistic. This will happen as companies focus on the customer experience and adopt technologies that lay out dialogues in ways that are consistent (independent of channel); personalized (taking into account the entire history of interactions); and, most importantly, relevant in content (the next five best offers). Marketers will grow obsessed with mapping “the customer experience” for their best customers and ensuring consistent, quality interactions that maximize customer satisfaction.
Second, the idea of applying measurement and process improvement techniques like Six Sigma to marketing functions will gain ground, partly motivated by dashboard technologies so chief marketing officers can “see” the effects of campaigns and use data to prove the marketing group’s effectiveness.
This way, marketing will grow more creative, and not just in terms of art and words. Practitioners will build knowledge bases of what messages work with which audiences and when. Competitive advantages will stem not from breadth, but from the depth of customer insights. This should again lead to provable precision marketing.
The third evolution will be a jump in sophistication around timing. Timing is the most interesting aspect, with potentially the highest payoff. Few companies focus on distinguishing early adopters from laggards and adjusting the timing of push marketing efforts accordingly, yet it is feasible to use detailed data to create timing elasticity curves. As companies adopt dialogues as a systematic approach to marketing, they will discover, through experimentation, how to interject right-time ad messages into a conversation that may be customer-initiated. By gathering and interpreting customer clues from every interaction, companies will create sophisticated database triggers, or “event detectives,” that are good predictors of a chance for relevant dialogue initiation.
The revolution I predict is a collapse of TV advertising. If you look at the crude broadcast-based splatter approach, coupled with the dropping impact rates and the chokehold Nielsen has on TV technologies that could provide direct feedback, there is no reason to expect things to stay the same.
Personalized ads at the household level, with direct feedback to the advertiser and consumer and control over their “cocoons” as well as the timing and amount of broadcast advertising, all contribute to a potential seismic shift in TV advertising.
