Analytical CRM: Definition & Applications

Instructor: Sudha Aravindan

Sudha has a Doctor of Education Degree and is currently working as a Information Technology Specialist.

This lesson explains what analytical CRM (customer relationship management) is, what it means to a company and how the data derived from it is used by the company to provide valuable feedback and help manage customer relations.

What Is CRM?

CRM, or customer relationship management, refers to the processes and techniques used to analyze the interactions between a customer and a company. The main goals of CRM are to help improve the services provided to the customer and to increase the probability that the customer will return to the company. The multiple stages that a customer goes through while considering, purchasing, evaluating and becoming a loyal follower is known as the life cycle of the customer. CRM seeks to analyze the data from the different stages of a customer life cycle with a view to improve customer oriented sales and marketing.

Suppose Sandy needs a new coffeemaker. In the considering stage, she shops around and narrows her choice to one of two manufacturers, A and B. After reviewing the features and price ranges of both manufacturers, she decides on Brand A - this is the purchasing stage. As she begins to use her coffeemaker, she continues to evaluate it and, if she is happy with her purchase, she will recommend it to her friends and family. Later on, if she needs a food processor she would tend to return to Brand A because she now believes in the superiority of this brand and is developing a loyalty to the brand.

What Is Analytical CRM?

Analytical CRM is a subset of CRM in which data is collected by a company about their customer interactions, with the goal of increasing customer satisfaction and their customer retention rate. Analytical CRM is a behind-the-scenes process; the customer is not aware that his or her actions and interactions with the company are being captured and analyzed. Based on the information gathered about customer practices, interactions and the end results of these interactions, companies can predict customer trends and suggest products towards which the customer is most likely to gravitate.

In the above example, when Sandy first purchased the coffee maker the information about what she purchased would be printed out on the receipt from the store and stored in the store database. The next time she purchases from the same brand, the store's database would indicate that she is a customer who has shown a preference for Brand A. This information will be used by the store to send brand specific coupons to Sandy by mail or email. And when Sandy registers the product, the brand manufacturer may send her promotions and information about the other products they carry. They may also send surveys to Sandy so they can learn the strengths and weakness of their product directly from the customer. This helps the stores and the manufacturer to learn about the preferences, likes and dislikes of their customers so that they can provide better products to satisfy the needs of the customer and improve their market share.

A company like Amazon might use technology to capture data about customer preferences, including what the customer purchased, the length of time he or she reviewed an item, and how much favorability he or she expressed towards the items. This would help Amazon identify customer trends, likes and dislikes. Then based on this information, the company can create targeted customer marketing strategies, such as offering promotions on items the customer has previously purchased, and presenting the customer with items similar to things that he or she has recently browsed on their website.

Applications of Analytical CRM

Analytical CRM is an essential part of customer relationship management. Analytical CRM accumulates and analyses different kinds of customer data, including:

  • Sales data: example purchase and return history, brand preferences etc.
  • Financial data: payment and credit history, including payment type, credit scores, etc.
  • Marketing data: customer response rates to marketing campaigns, customer satisfaction data and retention data, etc.

Companies can gather information from this data to find answers to questions that would help them identify important customer relationship strategies. Useful information gleaned from analytical CRM might include which customers are most loyal, or which customers are most likely to respond to certain offers. For example, at checkout many grocery stores will print out coupons for certain products or items based on a customer's purchase history and the frequency with which they purchased related items. This way the coupons received by two different customers will most likely be different, based on the individual purchase history of each customer.

Some applications of analytical CRM include:

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