Let’s Talk Data

The more things change, the more they stay the same — or so they say.

Today I read about a “new” application of data by Simmons (acquired by Experian over a year ago). At first, I was intrigued. Once I dug a little deeper, I was more impressed that they got NBC Universal to buy it.

Basically, the announcement (link below) explains that NBC Universal agreed to license “Behavior Graphics” a product that was launched in 2002 (according to the web site.) The “innovation” is that Nielsen TV diary data is now linked to Simmons behavioral data for a more complete picture of the viewer. Methodology can be found on the Simmons web site.

It’s not that I dismiss this segmentation product, it’s just that its not really revolutionary.
Mediamark Research has been selling behavior based “single source” data since they started back in 1979. I put together countless presentations ranking magazine audiences (then cable, and tv, and now, ISPs like AOL) by propensity for lots of different targeted behaviors.

What is interesting is that some clever person decided to link two disparate databases through a common piece of information OTHER than demographics or neighborhood segmentation assignments.

What is good to take away from this is that just about any common field(s) on two databases could potentially be used to link the two together. Of course, this is called modeling 101. It’s not revolutionary, but it is clever.

from: NBC Universal Signs Agreement with Simmons Research as Network Moves towards Behavioral Targeting; NBC Can Now Identify Prospects Based on Consumer Viewing Habits.

source: Business Wire, February 7, 2006.

via: HighBeam™ Research

COPYRIGHT 2006 Business Wire

I’m spent.

It was more than I expected. I’m drained yet pumped.

As an alumna of SUNY Oswego, I offered to participate in their Education Based Experience program. I have a few ideas for Catosphere and while I’ve got a great network of professional consultants that I could engage, I wanted to try a new approach.

And what better place but on a pulsing, beating, living campus can you find some new ideas — some real fresh views, fresh blood? After thinking about the responsibility of being a dedicated guide to interns, I decided that I would try to tap into the college. I wanted to find passionate, eager, smart partners who could help me plan and execute an idea I’ve been mulling over for some time. (This is no “fetch my coffee” internship/project.) While I was hoping to get a few takers, I was honored that so many expressed interest in the business and the project.

I had the privilege of speaking with Dr. Ian Cuthills’s Market Research class in the Business School. “Speaking” is probably not the right word. I felt like I spewed incoherent tidbits of information that I have gathered over the last seventeen years. How does one describe what market research is in 55 minutes?

Yeah, you are collecting data to make a decision, but it’s so much more than that when it’s done with an eye on the big prize, the big picture.

Each industry has its own history, its own jargon. It takes awhile to feel at home in your own skin when you are introduced to something new. I loved the whole one to one communication you get with real radio — my first love. But slowly over time, I’ve been steeped in the world of data and now it practically oozes from my pores. Each technique I discuss is intricately linked to others in my brain. Primary research, geocoding, segmentation, pattern-recognition, file scoring, thematic mapping… there’s so much to learn.

And that’s not even the half of it. Privacy laws, balancing out the needs of a corporation against the rights of the consumer, benefits of certain methodologies over others, and the increasingly difficult time market researches have getting busy people to stop and give them the answers they seek…. there’s so much to cover.

How will I pass on this information without overloading them? More importantly, how to you awaken a passion in someone for something you feel compelled to do? How can I explain that once you learn the basics, you can make anything you want. You don’t have to stay between the lines?

One day at a time, I guess. It took me a long time to learn this stuff, and yet, sometimes, I am surprised as how excited I am about the prospect of learning something new — I feel like I’m 19, still, with my whole life ahead of me, and a whole world to explore.

New cool tool of the day: Clusty — this is organization (and segmentation) of the web at its best. I remember seeing this site ages ago, and somehow or another I lost the bookmark and forgot about it. But type in anything in the search, and watch how quickly and consistently it groups together like sites/pages and how much more meaningful research becomes when you are using it.

Yawn…. no more for me tonight.

I sat down this morning, and before my first cup of Java even got cold, I happened upon an article which essentially says that market segmentation is too inefficient to be an effective tool. The author goes on to explain how other methodologies can be employed to pinpoint “buckets” (instead of segments (?)) of customers by targeting individuals and their behavior.

My reaction? “Uh, yeah…”

As if this were some great revelation.

I’m not trying to disparage the author. He makes valid points. And frankly, this isn’t the first negative article I’ve seen about segmentation. However — think about this. What’s the number one marketing issue facing most businesses today? If you want to grow, you need to add new customers. First, you determine who your best customers and then and you have to find more just like them and sell to them in order to increase profits. That’s called prospecting.

I have discovered an incredible amount of well-educated, well-intentioned marketers dismissing broad based neighborhood segmentation systems. And you know what? For companies that maintain lots of transactional data on their databases and can afford to append household level demographics — they are 100% correct. If you are looking to optimize your current customer database — then it is most efficient, most effective, to use modeling techniques to score individual customers with propensities to purchase different products/services the company provides.

But even the most data-rich companies still have to prospect like the rest of us. And you know what? Modeling is based on having similar data on both the customer file and the list of prospects that you wish to score. Simply put, you can maintain gadzooks of data on your own database but no other source is going to be able to put that exact same data onto any other database because it doesn’t exist.

Take this example. John Smith, your customer, spent $500 last year. He called the support line 10 times, he pays with an American Express card and you know all the products he bought. Now you are going out to buy a list of prospects. Meet Mary Jones — she’s on the list you purchased from expiring, InfoUSA, Acxiom — what do you know about her? You’ll get her name, address, demographics (some individual, some neighborhood (block group or zip+4) based, and usually some summarized credit information. You don’t know how many times she’s called the support line or what credit cards she pays with — because she’s a prospect — not a customer! You have no customer data.

Repeat this with me. The only way to tie customers to prospects through modeling is to find characteristics that are on both files and use those characteristics to predict potential behavior.

So, when I read broad stroke articles like the one below, I shake my head. After 15+ years in this business (working for the leaders in the industry) I can tell you that the majority of small to medium sized businesses — and truthfully, some of the bigger ones too, HAVE VERY LITTLE TO NO TRANSACTIONAL DATA worth modeling. And, budgets are limited, time lines are short (”Help! We need to mail in 3 weeks!”) so we can’t append all kinds of household level demographic and behavioral data for prospecting purposes. What’s that saying? You can have it fast, you can have it perfect, and you can have it cheap, but not all three at the same time.

So, what’s the solution? Neighborhood segmentation — with a twist.

No matter what flavor you use — Community Tapestry, MOSAIC, Personix, PRIZM — you still need to tweak a bit to get the maximum lift if you plan to do direct marketing (mailing) by clusters. I think one of the best ways is to isolate the top clusters that have the greatest propensity, then take that small group, have household-level universally available data appended, and then further refine your target.

Imagine if you will, this scenario. You sell (relatively) pricey clothing and furniture for young children. If you just target neighborhoods with children you’ll likely get a small response. If you target to people with a certain income (and children), you’ll get a slightly better lift. However, if you use the segments that have lifestyles which are typically status-conscious (upscale suburbia and urban elite) along with presence of children and income — you’ll get the most bang for your buck without the expense and time needed to do advanced custom analysis.

If you simply accept those articles that dismiss practices that have been used successfully for years — without addressing the positive reasons why these tools can still be used — then you’re not getting the complete picture.

I maintain that prospecting is a completely different ball game — and segmentation tools can help businesses of all sizes further narrow their prospect lists.

from: Segmentation: thin edge of the marketing wedge.

source: B&T Weekly, October 14, 2005.

via: HighBeam™ Research

COPYRIGHT 2005 Reed Business Information Ltd. All Rights Reserved.