Signs That You Need a Data Warehouse
July 26, 2006

How do you know when you need a data warehouse, a data mart or at least an extracted set of files for marketing analysis? If the thought of pulling together any or all of the following analytics projects in the course of one day makes you want to throw up your hands in exasperation, then you’re a prime candidate: Task No. 1: Run a report of how many unique 12-month buyers you have. Try this in a leading enterprise resource planning (ERP) system, and you will arrive at a number. But do you have a way to check if each record is a unique account

Five Low-tech Data Mining Tips
June 28, 2006

In the data mining world, many would have you believe that refining the technical aspects of the analytic process is key for improving the performance of mining exercises and the insight gained from them. While there is some truth to this, the critical area for progress lies in the non-technical procedures that are so vital to a powerful outcome. Here are five low-tech ways to improve your data mining exercises, with a view to preventing all-too-common errors that can keep marketers from optimizing customer relationships. 1. Take time to prepare your data. We’ve all heard the “garbage in, garbage out” slogan that suggests the quality of the

CMP’s Al Rosato on Building a Better Database
June 21, 2006

When Al Rosato, director of database marketing for MediaLive International Inc.—now owned by CMP Media—came on board with the event marketer in October 2004, his goal was to complete the company’s database build. Changes to management and the business requirements at that time meant that much of the initial database structure had to be revamped. Nearly two years on, however, the database is firing on all cylinders. Having brought all legacy data into the system and established standardized data capture and feeds from all sources going into the database, Rosato’s goals for the database now have turned to bettering the company’s customer relationship management

Driving Performance
June 1, 2006

When shopping for a new car, the choices are infinite: Nissan or Honda? Accord or Civic? Atomic Blue or Galaxy Gray? And don’t forget about all those extended warranties and factory options. The number of unique combinations, not to mention the odds of marketing the ones that will resonate with individual consumers, are mind-boggling. But that didn’t stop AutoNation, America’s largest dealer of new and used vehicles, from leveraging analytics and digital print technologies to create a variable content direct marketing program that consistently delivers customized and relevant communications. As a result of its innovations, AutoNation has doubled response rates and generated a return on

Present Perfect
May 1, 2006

Some folks have a knack for gift giving. They just know the perfect gift for every special occasion, leaving you marveling at their great intuition and taste. However, while intuition may be good enough for some, Cleveland-based personalized gift retailer Things Remembered has taken gift giving closer to a science. What started as a key kiosk in a shopping mall parking lot has grown into a nationwide enterprise with approximately $300 million in sales, more than 650 retail locations and some 7 million active customers on file (another 8 million customers make up its customer archive). Specializing in personalized gifts for all occasions—everything from

Can You Integrate Your Channel Data In-house?
April 19, 2006

In general, marketers are good at managing their data systems in-house on a day-to-day basis, says Alan Weber, founder and CEO of Marketing Analytics Group, a database/direct marketing consultancy in Prairie Village, Kan. But the skill sets used to create day-to-day reports are different than those needed to assess the information in a database to make strategic decisions about what data stays, what gets deleted and what gets combined to create new data elements, he explains. The IT department’s desire to keep the database in-house is not a good enough reason to tackle data integration on your own. When considering any data integration project, especially

Taking Risks,
Increasing Response
March 9, 2006

Assurity Life Insurance Co. is a study in innovation, change and risk-taking—from its history to its direct mail program. Innovation: In 1890, Dr. E. O. Faulkner created Modern Woodmen Accident Association because he saw a need to make accident coverage available to working people—not just the wealthy. This Lincoln, Neb., company continued to expand and add products over the next century. Change: In 1954, three Woodmen companies were merged to create Woodmen Accident and Life Co., and in 1997, the Assurity Life Insurance Co. was formed as a subsidiary of Woodmen Accident and Life. Risk-taking: Assurity Direct, the direct marketing division of Assurity Life,

Seattle Times Segments and Scores
March 1, 2006

Challenge: Increase subscription and retention rates for daily newspaper Solution: Use predictive modeling to develop a comprehensive segmentation strategy Result: The Seattle Times Co. now is able to vary its prospecting and retention messages to different segments When The Seattle Times Co. (STC) set out to increase the subscriber base for its daily newspaper and get a clear picture of its retention rates, the multimedia publisher knew that good, solid data would be the backbone of such an initiative, so it got busy gathering a robust set of survey-based attitudinal data on both customers and nonsubscribers. But once it had that data, the challenge

What’s Your Value?
March 1, 2006

In today’s multichannel selling environment, there are a number of important analytical metrics that every direct marketer needs to know and constantly measure. Among them: • What is the value of your customer list—today and projected for the next three years? • What does it cost to recruit or acquire a new customer? and • What is your “payback” period—that is the time it takes for a new customer to become profitable? These are critical measurements of the financial health of a company. Let’s look at ways to value your customer list, and home in on the specific customer metric of

Customer Data Mining
February 1, 2006

Customer data mining is a complex process that involves highly trained professionals. Some companies handle data mining in house, while others farm it out, and still others follow a hybrid solution. Which option is right for you? Here are some factors to consider when you’re making this difficult decision. What Can You Afford? Most mid-size to large direct marketers have an in-house data mining department to handle at least some of the analytics work. They feel it’s important to have total control of this critical function, and for the data miners to be continuously steeped in the business. Also, the cost of an in-house staff can