Saturday, October 27, 2018

#30 How Database Analysis Saved the Great Dane's Business

Issue #30 – Tuesday, October 30, 2018

Posted by Denny Hatch

How Database Analysis Saved the Great Dane’s Business

In the 1970’s I wrote two novels. Movie rights were sold and I got a small pot of money. (No film was ever made, alas.) But Peggy and I splurged and bought a top-of-the-line Bang & Olufsen stereo rig like the Danish beauty you see above—big bucks in those days.

It was glorious to listen to as well as to look at. This model was on exhibit at the Museum of Modern Art. Every time we put on an LP or listed to FM radio, it was thrilling.

At the time I was 42. I probably mailed in a warranty card back in 1977. It was a period well before sophisticated analysis and modeling. B&O no doubt stuck my registration card in a shoebox that was consigned to a warehouse, whereupon they forgot about me.

What's more, B&O had no idea who I was, who was buying their products or how to reach their market.

Who Were Bang & Olufsen’s Customers?
In the early 1990s, Bang & Olufsen began an aggressive campaign to expand its share of the audiophile market.

At that time the company had 17 retail stores across the country. All B&O management had to go on was a little list of 32,000 buyers.

When building a business, it's a good idea to:
• Know who your customers are.
• Go where the folks with those demographics are.

Bang & Olufsen was operating on the assumption that its typical buyer was a single professional male between the ages of 25 and 30 with an average income of $50,000.


The First Sad-Sack Survey
In 1994, Bang & Olufsen decided to survey its customers to find out more about them. An outside research firm designed the survey on single sheet of paper with a business reply envelope and mailed it to the list.

Thanks to the incentive of a free CD for completing the survey, it generated a 20-percent response. It was learned that the typical buyer earned more like $70,000 than $50,000.

Still very wrong.

Turning to Direct Marketers for Answers
In 1997, Bang & Olufsen decided to get serious about developing a customer profile. Chicago-based agency Lighton Colman brought the database wizards at Metromail together with Bang & Olufsen.

Lighton Colman's John Tomkiw recommended INSOURCE—a co-branded product created by Metromail and Experian (née TRW).

INSOURCE contained more than 300 individual data elements on 95 percent of the 100 million households in the U.S.

When the Bang & Olufsen wee housefile was bumped up against INSOURCE, the results astounded the corporate executives. (I was not astounded.)

It turned out the typical customer was:
• A married professional male.
• Average age: 50-55.
• Homeowner with grown children.
• Making an average salary of $150,000+.

“The data were full of surprises. Our previous suppositions were demolished. Through the INSOURCE enhancement, our data was amplified to such an extent that we really came up with a profile that's pretty unique—and that we can take action on. The differences are not subtle.” —Keith Lennartson, B&O Communications Director.

The Survey Revolutionized B&O’s Marketing
Now, instead of blazing away with a shotgun, Bang & Olufsen was armed with a sniper’s rifle. Among the immediate changes instituted as a result of the INSOURCE connection:

Radical Media Repositioning
For years, B&O was blowing advertising dollars on media with the wrong readers. The old schedule included: The Robb Report, Where, Departures.

The new schedule: Cigar Aficionado, Worth, Conde Nast Traveler, Wine Spectator, Audio Visual Interiors, The Advocate, Saveur.

New Retail Opportunities
By running the INSOURCE customer model against its database and doing a ZIP Code analysis, Bang & Olufsen uncovered potentially profitable new sites for retail stores that were previously below the radar screen. Among them: Washington, D.C., North Carolina and Minneapolis/St. Paul. The next step: use GIS mapping software to more finely target its retail store locations.

What's to Be Learned?
What Bang & Olufsen discovered is what direct marketers had known for years: database analysis can yield information so basic and low-tech that it can change the fundamental model of the business.

Database Analysis vs. Surveys
Bang & Olufsen's first survey garnered a respectable 20-percent response—but it was way off. You would think that based on those results, a fairly accurate customer profile could be assembled.

Why the Survey Was Probably Flawed
Consumers in the upper income brackets are too busy to fill out a survey. Very likely, only 25 percent of those making $150,000 a year bothered to fill out the survey while only maybe five percent of those making $250,000 responded. The result: a skew that could have been very dangerous to the health of their business had they not connected with INSOURCE. For example, Peggy and I weren't making anywhere near the average $150,000+ per year back in 1977 when I filled out that survey.

The Eye-Popping Changes in the 21st Century
Bang & Olufsen is now in the world of teeny geeky goodies for pocket, purse and studio apartment…

… On up to obscenely high-end audio extravaganzas to bedazzle friends, family, business associates and neighbors:

 A personal aside: Can you freakin' believe a tacky little 3-year guarantee on a $63,720.00 product? Oh, those sphincter-tight Danish bean counters!

And This!

Who buys this stuff? 
It ain’t Trumpy Country bumpkins who love beer, Big Macs and the hopeful resurgence of coal. Here’s B&O’s current footprint in the U.S.

13 B&O Dealerships Nationwide (plus Amazon, Best Buy, Crutchfield and others)

Here's B&O in the Rest of the World

316 Dedicated B&O Dealerships—Iceland, UK, Europe, Turkey, Saudi Arabia 

How’s B&O Doin’?
                              2018              2017              2016             2015   
  Sales/Revenue       $504.7           $452.4           $403.9          $359.2
    (In millions)
  Sales Growth                11.56%              12.02%               12.41%            8.63% 

It’s amazing what basic direct marketing data analysis can do to (and for) a business model!

Takeaways to Consider
• Concentrate on your own core competency (e.g., making and selling high-end electronics) and spend money on outside professionals for their core competencies (e.g., database enhancement and analysis).

• "Fish where the fish are." —Macrae Ross


Word count: 996


At age 15, Denny Hatch—as a lowly apprentice—wrote his first news release for a Connecticut summer theater. To his astonishment it ran verbatim in The Middletown Press. He was instantly hooked on writing. After a two-year stint in the U.S. Army (1958-60), Denny had nine jobs in his first 12 years in business. He was fired from five of them and went on to save two businesses and start three others. One of his businesses—WHO’S MAILING WHAT! newsletter and archive service founded in 1984—revolutionized the science of how to measure the success of competitors’ direct mail. In the past 55 years he has been a book club director, magazine publisher, advertising copywriter/designer, editor, journalist and marketing consultant. He is the author of four published novels and seven books on business and marketing.


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  1. Terrific piece Denny! Almost every client we have tells us they "HATE junk mail." That is until we show them the results of "junk mail" campaigns. We continuously have to remind our clients that they personally are not our target market, and ask them to set their personal feelings aside.

    Just like you said, we have to ask them to allow us to do what we do best while they do what they do best.

    Damaging admission: Not all "junk mail" campaigns work. But data substantially improves them.

    1. Will,
      Thanks for taking the time to Comment. One of my early bosses used to say: “When it doubt, do the obvious.”
      So damn few of the young practitioners have gone un-mentored that they don’t know the basics. Operate on hunch & gut à la our president.
      Do keep in touch.

  2. Brilliant. Let the data be your guide. I recall doing some work for a gigantic entertainment company that produced, among other things, lots of DVD's for kids. They were convinced that their sweet spot was middle income, larger families, etc.. the usual. Did a similar database mashup, and found that that was correct s far as it goes. However, we found an even sweeter spot, a group that bought (as I recall) 3x more often and spent 6x more annually. Grandparents!!!! Talk about a shift in marketing and ad placement. Big win!! They would have done OK but would have missed a golden opportunity if they relied on conventional wisdom, their gut, and not heeded the lessons of data.

    1. Ah, Richard,
      Good segue on your part: “Grandparents!!!” and “golden opportunity.”
      Never understood the 18-34 fetish of advertisers. Seniors have the discretionary dough.
      I don’t get it on for data. This lust on the part of marketers to scoop up every scintilla of data about every person on the planet is fatuous. They think the more data they have, the easier the sale to the point where if they have so much data, the sale will be automatic.
      This data-mania is what we used to call list research. Finding the logical prospect who buys long distance, has money to spend and pays his/her bills.
      That’s easy. Ed Mayer called the success formula: “40% lists, 40% offer and 20% everything else.” The 40% lists are the data. The other 60% interests me: offer, copy, headlines, fulfillment, renewals, referrals, etc. etc.
      Anyway, thanks for taking the time to Comment.
      Do stay in touch!

  3. Excellent story. I'm curious to learn how these methods can align with the very high-end luxury residences we build and market. The real estate development industry is steeped in historical data and past performances, and I have not identified a model or method that can give us a strong sense of future rents and prices. I wonder if somebody can model what happened with prices in similar markets over time to better predict pricing and target customers in new expanding real estate markets. There are a lot of subjective experts going on gut, but I have not yet found the data centric source. Thanks.

    1. Hey Matthew,
      Thank you for taking the time to comment.
      You have opened a positive Trumpian ;-) jar of Beluga caviar and (my favorite) Pol Roger Champagne (Churchill was addicted to it!)
      When you say, “curious to learn… with the very high-end luxury residences we build and market”
      Do you build in a specific locale, or like Trump do you build all over the country/world?
      As you know, I started and ran WHO’S MAILING WHAT! newsletter and archive service. Collected junk mail like crazy. You could see what worked over the years.
      In the real estate business, it seems to me you would need old ads for the sale and rents of high-end buildings at their birth and then current ads to see the price differential (if any).
      I think what you are suggesting is in those areas where newspapers are saved on microfilm/microfiche is a place to start. Say you are looking at the possibility of putting up a building on a vacant lot surrounded by lush residences that have been there a while. Could you determine the year when these prior buildings were finished and offered for sale and then go through the real estate sections of the paper to see what they were offered at.
      Then see what they are going for today to determine whether it’s a good prospect.
      I think it has to be info from print newspapers. Digital stuff comes and goes and probably can’t be found. (Or maybe it can if you know where to look.)
      Anyway, you’ve raised a fascinating challenge.
      What you propose ain’t easy—a bitch of a challenge!
      Thanks again for writing.
      Do keep in touch!