Personalization vs. Customization

Direct marketers are always looking for ways to improve targeting to make a bigger impact on their audience. One traditional approach is “market segmentation,” where people are grouped by some set of characteristics.

One of the ideas behind segmentation is that it allows us to describe product benefits in ways that impact a particular audience. Since the same features in a product provide different benefits to different groups of people, it makes sense to segment the audience into groups where each marketing message can be delivered more efficiently. But there is another benefit to market segmentation on the web–you can learn more about your audience.

Profiling individuals on the web allows us to not only select which message to deliver to each individual, but also helps us learn about the needs and interests of each person. This can be used to segment an audience in ways that traditional direct marketers have only dreamed of.

So what can we actually learn by segmenting our audience?

Perhaps the easiest thing to learn is which products are purchased by the same people. Web sites that use collaborative filtering are helping marketers and consumers answer this question. You’ve probably seen sites that say, “People who bought this product also purchased these other products.”

For instance, if a group of customers buys what appear to be unrelated products, try cross-promoting the two products and see if other customers buy that combination, too. By using market segmentation tools and techniques, unique groups of people can be identified and marketing programs created to take advantage of this opportunity.

Even without collaborative filtering, we can use standard database queries to identify a number of clusters and learn about our audience. By just using your customer data file it’s possible to segment your audience by geography, season, order size, frequency of purchase, and other data that you already collect.

For example, how does the geographic distribution of your customers compare to the country as a whole? California has 12 percent of the US population, so if less than 12 percent of your U.S. customers are from California, that segment might not respond to the same marketing messages as other regions. By targeting a different email message to that market segment, you might find results are higher than sending the same email newsletter to everyone.

Many traditional catalogers project the profitability of customer segments by just using the recency of the latest order, the frequency of ordering, and the monetary size of the order (RFM Analysis).

In addition to RFM analysis, web marketers have an additional source of data — web server log data that can be combined with purchase history data. We can learn a great deal about our customers by looking for patterns of web behavior that lead to greater revenue.

For those with a strong interest in analytical and statistical techniques, there are a number of data mining products on the market that can help the savvy marketer find the smallest of segments in a market. By linking your web traffic data to your customer database, you can answer more complex web-related questions that can’t be answered based on web browsing behavior alone such as:

  • Is the cumulative amount of time spent on the site during multiple sessions related to inquiry or sales activity?

  • Is the number of visits to the web site a predictor of e-commerce sales?
  • What is the click-through rate for each product page to the shopping cart page?
  • Which affiliates generate customers with the highest profit margins?
  • Are people who come to your web site from one search engine more likely to make a purchase than people using the same search phrase at a different search engine?

There are almost as many ways to segment a market as there are data that can be collected. Fortunately, there are tools available for web marketers to make sense of the massive amount of data.

As more companies integrate databases and e-commerce into their sites, web marketers will be able to use market segmentation to learn more about their customers and improve performance of each aspect of web marketing.

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