As a consumer, I’m sure that you have all received telemarketing calls. They usually arrive during dinner. “Hello, I’m calling from … I’d like to make you aware of our new program. By accepting our special offer, you can take advantage of all of the benefits … ” The script generally continues to point out the many rewards and conveniences that will follow if you take advantage of the special offer.
The problem is that you are not at all interested in or have no need for the product or the service that is being offered at the time. You were selected to receive the phone call because your name and your phone number appeared on a marketing list of potential customers. Very often, little else is known about you as a customer or your purchasing habits. Offers are made with the hope that marketing to the masses will generate a number of positive responses. This approach requires a large number of contacts to yield significant results.
If, on the other hand, the offer just happens to come at the right time and be for the right product or service – that is an entirely different scenario. You might actually take the time to listen to and consider the proposal. The key to presenting the appropriate offer – to the right person, at the right time – no longer needs to be an indiscriminate process.
New customer-intelligence technology can help. You may have heard it referred to as data mining: Sophisticated algorithms sifting through mountains of detailed customer transactional and demographic data to find concealed patterns, market segments and new customer insights. Powerful algorithms, such as neural networks, decision trees and memory-based reasoning are able to analyze enormous amounts of data to reveal undiscovered information.
The in-depth analysis provided by data mining reveals patterns and trends that might be missed through traditional methods of evaluating summarized data. This new customer insight offers a more detailed profile of the customer. A business able to identify particular attributes of their current customer base can customize offers to their current clients, and better focus marketing efforts to generate new business.
Some of the questions that data mining can answer are:
• Which customers are likely to respond to this offer?
• Which customers are likely to churn and why?
• What are the profiles of my “best” customers?
• What is the expected lifetime value (LTV) for each customer?
• What are my best retention and cross-sell opportunities?
• And, What offers should I display the next time a particular customer visits my web site?
Data mining is the key to unlocking customer intelligence. Businesses are already in possession of voluminous amounts of information about their customers. Data mining is a powerful method of uncovering meaningful patterns that will allow a more focused approach to marketing. Focusing on the right customer at the right time cuts time, saves money and enhances business. There should be no missed opportunities.
Analyzing “consumer relationship touchpoints” provides a wealth of knowledge. Cellular phone companies should be able to mine their data to find out exactly who will turn to a competitor with a better plan or newer product. They should be able to identify which customers might be interested in the “Family Plan” or the “Business Rate.”
Companies today need to go beyond simple customer transaction databases and start building customer data warehouses. Businesses need to gather all types of available data from the wide range of sources that are available. List and data companies can provide numerous fields of information on almost every consumer in the United States. Government census data can include information about a consumer’s family, home, education or neighborhood. Combined with the business’ own transactional databases and now the new e-business and “click-stream” data about web surfers’ paths and actions through your online store, a plethora of customer data is available to be exploited.
Most bricks-and-mortar companies have basic customer data on which they do some simple reporting. As companies evolve, they can combine all relevant e-business data about customers and store it in a customer data warehouse. As they move from bricks-and-mortar to a click-and-mortar e-business, they should start to build a “Webhouse” full of data about their customers. As companies evolve and begin to dig deeply into their data, they will find useful information that can be leveraged to make customer-specific offers. This repository of valuable customer information might be called an “intelligent” Webhouse.
If your company has not begun to collect and analyze customer data, now is the time to dig deeply into untapped corporate repositories to uncover the power of the information that is there.
