How Data Mining Can Help You Optimize Your Marketing
If you are the owner of a business, you should already be aware of the fact that there are multiple techniques you can use to market to your customers. There is the internet, direct mail, and telemarketing.
While using these techniques can help your business succeed, there is even more you can do to tip the odds in your favor. You will want to become familiar with a technique that is called marketing optimization. This is a technique that is intricately connected to data mining. With market optimization, you will take a group of offers and customers, and after reviewing the limits of the campaign, you will use data mining to decide which marketing offers should be made to specific customers.
Market optimization is a powerful tool that will take your marketing to the next level. Instead of mass marketing a product to a broad group of people that may not respond to it, you can take a group of marketing strategies and market them to different people based on patterns and relationships. The first step in marketing optimization is to create a group of marketing offers.
Each offer will be created separately from the others, and each one of them will have their own financial attributes. An example of this would be the cost required to run each campaign. Each offer will have a model connected to it that will make a prediction based on the customer information that is presented to it.
The prediction could come in the form of a score. The score could be defined by the probability of a customer purchasing a product. The models will be created by data mining tools. These models can be added to your marketing strategy. After you have set up your offers, you will next want to look at the purchasing habits of the customers you already have. Your goal is to analyze each offer you’re making and optimize it in a way that will allow you to bring in the largest profits. To illustrate market optimization with data mining, let me use an example.
Suppose you were the marketing director for a financial institution such as a bank. You have a number of products which you offer to your customers, and these are CDs, credit cards, gold credit cards, and a savings account. Despite the fact that your company offers these four products, it is your job to market checking accounts and savings accounts.
It is your goal to figure out which customers will be interested in savings accounts compared to checking accounts. After thinking about how you can successfully market your products to your customers, you can have come up with two possible strategies that you will present to your manager.
The first possible strategy is to market to customers who would like to save money for their children so they can attend college when they turn 18 years old. The second strategy is to market to students who are already attending college. Now that you have two offers you’re interested in marketing, you will next want to study the data you have obtained.
In this example, you work for a large company that has a data warehouse. You look at the customer data over the last few years to make a marketing decision. Your company uses a data mining tool that will predict the chances of people signing up for your products.
You will want to create certain mathematical models that will allow you to predict the possible responses. In this example, you are targeting young parents who may be looking to save money for their children, and you are targeting young people that are already in college.
Computer algorithms will be able to look at the history of customer transactions to determine the chances of success for your marketing campaign. In this example, the best way to find out if young parents and college students will be interested in your offer is by looking at the historical response rate. If the historical response rate is only 10%, it is likely that it will remain the same for your new marketing strategy. However, historical response rates are simply, and to be more precise, you will want to use complex data mining strategies.