Ask any database practitioner why a data warehouse is important and the answer will approximate: It is important because data warehousing supports corporate strategic advantage. Among other things, data warehouses support understanding the 360-degree view of the customer. A 360-degree view of the customer enables you to cross-sell, sell into households, qualify customers and so forth. In short, you have a world of business opportunity open to you, all through the foundation that is the data warehouse.

However, the reality of achieving a 360-degree view of the customer has been much more difficult than theory would suggest. There are several pitfalls awaiting the practitioner trying to build the data warehouse utopia for customer management, such as:

  • It is difficult to integrate and merge internal corporate systems when those systems have never been designed to fit together.
  • Huge volumes of data wait for the database administrator. There are only so many cycles in the day, and the volumes of data that need to be processed far outweigh the available time.

It is difficult to mix external data with internal data because there is no such thing as a universal key. External data has its way of structuring data, and internal systems have their own way of structuring data. Trying to make the two compatible is like trying to mix AC and DC current – it just doesn't work out very well, even in the best of circumstances.
Data quality is an issue everywhere you turn. People simply have no idea how poor the content of data is until they start to use it.

However, once even a modicum of data can be collected, one may conduct market segmentation. Even with a small amount of customer data, it is reasonable to start to segment customers.

It is plausible to segment customers into groups based on many different criteria. For example, you can look at the gender, age, address, etc. Furthermore, you can use multiple criteria such as age and gender. Market segmentation is something that can be done with even scanty and basic information.

What the corporation typically finds is that once segmentation starts, patterns emerge. First, one viable market category appears, then another. The corporation finds that city dwellers between the ages of 18 and 25 are one market segment and that men between 45 and 55 who live anywhere form another well-represented market segment.

Market segmentation is an interesting exercise. It can help the corporation make informed decisions in many ways. Once the corporation knows to whom its products and services should be catered, then the corporation has a good idea of how to conduct itself. For this reason alone, market segmentation is a very important activity that can be done with data emanating from the data warehouse.

However, there is another step beyond market segmentation. That step is using data in the data warehouse for activity analysis. In activity analysis, the emphasis is on understanding activities, not customers. Whereas market segmentation focused on understanding the demographics of the customer, activity analysis focuses on understanding customers' activities.

The appealing aspect of activity analysis is that it is behavioral. Activity analysis addresses the way people act. This is cause for great excitement because if the marketing analyst can start to understand behavior, the marketing analyst can start to proactively affect sales.

For example, suppose that the marketing analyst notices that the traffic inside the store picks up on cloudy and cold days. Normally when traffic increases, so do sales. However, in this case, the store traffic picks up, but sales do not.

Traffic may have picked up because people merely wanted to get out of the cold, are seeking shelter while waiting for the bus or because they realize that they need new shoes and umbrellas on an inclement day. Noticing a pattern is the first step. Understanding the motivations behind the pattern is the next step.

Once the analyst notices the pattern of behavior, he/she can start to capitalize on that behavior. If people come into the store because it is near the bus stop, then putting low-cost items in the front of the store – especially consumable items such as doughnuts and coffee – may boost sales. If people enter the store because they need new shoes and umbrellas, adding raincoats and hats to the racks near shoes and umbrellas may boost cross-sales.

In short, whatever the motivation for behavior, once the behavior is understood, the store is in a position to capitalize.

What's the difference between activity analysis and market segmentation? Market segmentation is information about customers. In order to boost sales and revenue, the analyst must also be an expert in demographics. The analyst is called upon to make forecasts about the dislikes and likes of whole groups of people. That connection is spurious at best. However, looking at activities is another matter. The very essence of activities is action. Once action occurs, the challenge is to tie sales and other beneficial events to that action. Additionally, action is easier to identify than demographics.

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