Database Marketing

Despite rapid online gains, future still bright for print catalogs. Considering it’s now been at least a decade since debates first surfaced in this business about whether the print catalog would ultimately become obsolete in favor of online catalogs, you’d think you could make a stronger case for such a phenomenon in 2006. And today, with a rapidly growing number of catalogers reporting 50 percent-plus levels of orders placed online, the writing would seem to be on the wall. But while it’s nice to dream of the cost savings associated with alleviating paper catalogs altogether, reports of its death are greatly exaggerated, to quote Mark Twain.

Which data models are worthwhile? What are the best predictors? Which metrics work? A panel of catalogers and list pros provided simple tactics to help mailers improve the quality of their databases at the “Trick Out Your Data and Kick Up Your Revenue” session held during the List Vision conference earlier this month in New York. Following are their tips: * Look for predictors within your customer data. For instance, Don Austin, director of client strategy for May Development Services, the nonprofit arm of list firm Direct Media, discussed a women’s apparel catalog for whom merchandise was a good predictor of lifetime value. Customers whose

Certainly all mailers want to improve their new customer acquisition performance. And in a session during the DM Days New York conference last week, Caryn Gray, Experian’s senior business & strategy consultant, outlined 10 key factors for mailers to consider when working with consumer prospect databases: Specifically, a prospect database is a client-specific database comprising multi-sourced, agreed-use, non-proprietary consumer records, such as vertical response lists, that marketers use for planning, executing and tracking or measuring new customer acquisition efforts. In setting the stage for her presentation, Gray noted that the key drivers for improved prospect databases include list fatigue, a lack of new names on the

Businesses in the United States lose 7.3 percent of annual revenue due to poor management of customer data, according to a recent survey by QAS, an address management solutions provider. Other data revealed by the survey: * 79 percent of companies around the world have three individuals take ownership of data throughout the organization, meaning responsibility is fragmented. * 60 percent of companies have the head of information technology (IT) take ownership of customer data. * 50 percent of companies have an administrator take ownership of customer data. * 47 percent of companies have an IT manager take ownership of customer data. * 42

The Internet certainly has changed since 1993 when I posted my first businesses, which were catalog-based, on the Web. I sold industrial liners for corrosion and environmental protection, and I had a mail-order pond and landscape supply catalog. Each targeted a different clientele, and I learned that marketing strategies have to be directed specifically at target markets. You must determine the effectiveness of any promotional sales program, because it will add to your overhead allocations. Statistical analysis is one such powerful tool. And regression analysis in particular is at the top of my list. Any tool that allows you to determine if your catalogs are

Customers who cared enough about your company to actually notify you of their changes of address should be handled with extra special care, said Bill LaPierre, vice president of catalog brokerage at Millard Group, during his talk “What Were They Thinking?” held at the Catalog-on-the-Road Conference in Cambridge, Mass., on Feb. 1. “Don’t treat them like they’re new customers or like catalog requests,” LaPierre said, speaking from his own experience. He moved last year, and recorded how catalogers whom he had notified with his new address handled this new information. Some sent catalogs with messages welcoming him as a new customer, “even though I had been

How your operations and marketing efforts can benefit from statistical analysis and modeling. Forgive me if I generalize for a minute. There are two approaches to marketing analysis: the arithmetic and the statistical. The Arithmetic Approach Sometimes called “descriptive analytics,” this is relatively straightforward and inexpensive, depending on a spreadsheet and the sweat of your brow. Extracting a season’s sales from your transaction system to your spreadsheet, you can determine the following: - percent response, by dividing your number of orders by your mail quantity per segment; - average order value, by dividing your gross sales by your number of orders per segment; -

The challenge for today’s catalogers is to more effectively identify and target those prospects who have the capacity to buy and the propensity to purchase specific products. What’s the most effective way to get and maintain your share of wallet in a highly competitive multichannel market? Many of the measures catalogers use in their targeting efforts, such as household income, tangible assets (house, car), spending habits, and traditional recency, frequency and monetary (RFM) segmentation, have either been fully exploited or just aren’t reliable indicators of a person’s capacity to spend. Thus, they don’t allow you to truly distinguish your ideal customers. Effectively identifying and targeting potential

Smart marketers, sales teams and business owners recognize the opportunity to develop a direct mail piece that exclusively promotes a single product — an item with a strong margin and an identifiable target audience. Usually the item has a high price point and specific benefits for the buyer — as well as a surplus of information that necessitates more space than a catalog page realistically can accommodate. If identifying the opportunity is that easy, how quickly do you become a victim of either yours or a colleague’s best intentions? If you’re unsure, here are mistakes to avoid when implementing a single-product mailing.

Do you want to create a reporting system that quantifies your catalog company’s successful interaction between customers and employees? Start with the five R’s: Retention analysis. Review both employees and customers. Companies with long-term employees can offer better service to customers than those with high staff turnover rates. Losing employees due to low wages and/or high stress is counter-productive when you look at the costs associated with recruiting and training quality employees. If you have a challenge retaining quality people, reallocate funds to improve existing employees’ wages. Becoming an employer of choice will improve your retention rates significantly and will reduce costs. To retain