Tuesday, October 25, 2005

Data Mining for Marketers

In the last few years there had been lot of importance given to satisfying customers, satisfying their changing needs and coming up with new products and services to satisfy those needs. But considering the diverse nature of customers, it becomes mandatory for marketers to have tools to segment the customers into homogeneous groups. Data Mining tools tremendously help the marketers to get all the above mentioned.

Data mining derives its name from the similarities between searching for valuable business information in a large database — for example, finding linked products in gigabytes of store scanner data — and mining a mountain for a vein of valuable ore. Both processes require either sifting through an immense amount of material, or intelligently probing it to find exactly where the value resides. Given databases of sufficient size and quality, data mining technology can generate new business opportunities by providing these capabilities:
1. Automated prediction of trends and behaviors
2. Automated discovery of previously unknown patterns

Artificial neural networks
Decision trees
Genetic algorithms
Nearest neighbor method
Rule induction


How exactly is data mining able to tell you important things that you didn't know or what is going to happen next? The technique that is used to perform these feats in data mining is called modeling. Modeling is simply the act of building a model in one situation where you know the answer and then applying it to another situation that you don't. This act of model building is thus something that people have been doing for a long time, certainly before the advent of computers or data mining technology. What happens on computers, however, is not much different than the way people build models. Computers are loaded up with lots of information about a variety of situations where an answer is known and then the data mining software on the computer must run through that data and distill the characteristics of the data that should go into the model. Once the model is built it can then be used in similar situations where you don't know the answer. For example, say that you are the director of marketing for a telecommunications company and you'd like to acquire some new long distance phone customers. You could just randomly go out and mail coupons to the general population. In this case would you achieve the results you desired and of course you have the opportunity to do much better than random - you could use your business experience stored in your database to build a model.


It is now a cliché that in the days of the corner market, shopkeepers had no trouble understanding their customers and responding quickly to their needs. The shopkeepers would simply keep track of all of their customers in their heads, and would know what to do when a customer walked into the store. But today's shopkeepers face a much more complex situation. More customers, more products, more competitors, and less time to react means that understanding your customers is now much harder to do. A number of forces are working together to increase the complexity of customer relationships:

  • Compressed marketing cycle times. The attention span of a customer has decreased dramatically and loyalty is a thing of the past. A successful company needs to reinforce the value it provides to its customers on a continuous basis. In addition, the time between a new desire and when you must meet that desire is also shrinking. If you don't react quickly enough, the customer will find someone who will.
  • Increased marketing costs. Everything costs more. Printing, postage, special offers (and if you don't provide the special offer, your competitors will).
  • Streams of new product offerings. Customers want things that meet their exact needs, not things that sort-of fit. This means that the number of products and the number of ways they are offered have risen significantly.
  • Niche competitors. Your best customers also look good to your competitors. They will focus on small, profitable segments of your market and try to keep the best for themselves.

Successful companies need to react to each and every one of these demands in a timely fashion. The market will not wait for your response, and customers that you have today could vanish tomorrow. Interacting with your customers is also not as simple as it has been in the past. Customers and prospective customers want to interact on their terms, meaning that you need to look at multiple criteria when evaluating how to proceed. You will need to automate:

The Right Offer
To the Right Person
At the Right Time
Through the Right Channel

Customer relationship management (CRM) is a process that manages the interactions between a company and its customers. The primary users of CRM software applications are database marketers who are looking to automate the process of interacting with customers.

Data and Marketers go hand in hand !!


Anonymous Anonymous said...

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January 31, 2007 5:05 AM  
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February 06, 2007 10:47 PM  
Blogger keerti mahajan said...

i am searching a topic for P.HD related to FMCG sector using data mining techniques. and here i am getting good information.

August 08, 2014 3:26 PM  

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