Segmenting for Catalog 2.0

In the Internet marketing world, Web 2.0 is about moving beyond the so-called nuts and bolts of technology and e-commerce and creating a more robust experience for users.

Perhaps it’s time that print mailers move beyond the “rules and best practices” of Catalog 1.0 to a smarter, more efficient catalog model — in other words, Catalog 2.0.

How should we define Catalog 2.0? It should be a set of practices in each of the core competencies — creative, merchandising and marketing — that would facilitate a more robust, more meaningful and more lucrative customer experience. For now, let’s focus on segmentation practices for the Catalog 2.0 environment.

RFM, or recency-frequency-monetary, is the fundamental segmentation methodology used by catalog and multichannel marketers around the world. RFM relies on the customer’s most recent transaction, total number of historical transactions and total or average monetary spend for either a lifetime or specified period to “predict” future purchase behavior.

The generally proven belief is that the more recently and often a customer buys, combined with the amount of money he or she either has spent or typically spends with a company, the more likely he or she is to buy again soon.

If Web 2.0 is about using technology and design to create a more collaborative network environment, why should Catalog 2.0 not employ technology to allow the multichannel marketer the ability to target and segment beyond basic strategies?

Increasing levels of selectivity to the database can yield big results, but you must take care to allow for meaningful results, too. Adding too many select criteria to a file can create small segments that are difficult to read after a campaign is complete.

Ideally, a segment will produce 100 orders or more for analytical purposes. If you anticipate a 2% response rate, you would want to mail segments of at least 5,000 names. If enhancing RFM with incremental variables is leading to meaningless segment sizes, you must choose which variables have the greatest impact in a given season.

For example, seasonality may play a critical role during an off-season. Perhaps the customer has a transaction in that time period in a previous campaign, but may not be a significant factor during peak periods. Know that one segmentation model may not be appropriate for all titles or all seasons.

That said, here are five enhancements to RFM that Catalog 2.0 has either ushered in or embraced. You should incorporate one or all of them into your catalog-marketing program to ease the pressures of rising costs and deliver a more relevant, meaningful and response-inducing customer experience.


Perhaps the most widely used “fourth variable” in segmentation is product. Enhancing RFM with product data allows you to target by product-level propensities.

In Catalog 2.0, product segmentation can be powerful in the event that you build targeted catalog and e-mail creative and multichannel contact strategies by product category. By targeting catalog and e-mail campaigns by product category, you can potentially shave page count and enhance click-throughs while maintaining sales levels and overall response. This also allows the Web to facilitate cross-sells and do the lion’s share of the selling work.

Many marketers already execute a form of product level segmentation. Banana Republic, for example, targets e-mail messages by gender at the most basic level: Men get menswear; women get women’s apparel. But that’s just the tip of the iceberg with the application of product segmentation.


Seasonality is another of the RFM enhancements that carries over from Catalog 1.0. Seasonality, or known purchase in a seasonal time period, can be effective for “fifth quarter” mailers — those companies that realize a significant portion of their annual sales revenues in the last eight weeks of the year.

Seasonality matters for these companies during the other 10 months of the year when customers aren’t necessarily buying for gifts. Likewise, business and institutional mailers can use seasonality to isolate “budget buyers” — those companies, schools and libraries that purchase when budgets come out or are about to expire — and routinized purchasers who buy on a set calendar.

Managing the segmentation to account for when the customer typically buys or when the customer has propensity to buy can stimulate significant savings and improve the customer’s experience with the company. Taken a step further, seasonality can be combined with product to segment certain product or category buyers by season.

If, for example, self-purchasers who buy widgets respond 60% better in the spring than the fall, it’s probably a good idea to market accordingly.


Understanding a customer’s purchase propensities by channel goes beyond just knowing that she buys online or over the phone. The fact is, many customers vacillate among channels — for instance, ordering online only after shopping the catalog.

Making the assumption that an online shopper doesn’t need a catalog without first testing the impact of fewer mailings is risky. But once you understand how channels interact with your customers, going beyond channel to channel-driver is the next step.

Driver refers to the stimulant for the transaction. Correlation analyses suggest that as much as 90% of the unallocated orders that come to the Web for the multichannel marketer are directly related to catalog mailings.

Moreover, tracking keys link traffic and sales to virtually all online efforts, including natural search, paid search, affiliate programs, e-mail and e-mail forward campaigns.

Catalog 2.0 requires you to understand and market to customers based not only on what channel they enjoy shopping from and buying in, but also by what got them to you. Where Catalog 1.0 dictated that you develop first-time buyer programs that were different from multibuyer programs, Catalog 2.0 says you must develop campaigns for affiliate-acquired customers that are different from paid-search acquired customers, and so on.


Research shows that targeting campaigns by attitudinal cohort group can increase response by more than 40%. Attitudinal or psychographic data available from data service bureaus can add depth to your marketing and brand messages and allow you to target your communication by major psychographic segments and attitudes.

By understanding the psychographic profile of customers, you are able to speak to them in ways that are more meaningful. Have a preponderance of younger on-the-move moms who look for the best deal in the shortest time? Maybe you should be focusing on sale items and expedited shipping offers in short e-mail messages.

If you have a lot of older customers who don’t easily part with their hard-earned cash, provide more details and reasons to buy without being too “salesy” or pushy in your catalog. Building a segmentation model allows you to target subtle copy changes, pagination, featured items and price points, and modified contact strategies that cater to the beliefs and desires of your target constituents. This can dramatically impact response and retention.

For catalog-centric multichannel marketers, it’s just too expensive to conduct business as usual. While enhancing your segmentation model may cost more in the short term, the goal should be to drive down costs long term while improving the customer experience and driving up overall retention and sales.

Success is targeting the right products and services to the right customers in the right channels with the right messages. It’s time for the catalog to evolve. It’s time to segment for Catalog 2.0.

Steve Trollinger is executive vice president of J. Schmid & Associates (, a catalog consultancy based in Mission, KS.

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