Data Mining with CRM can Create a Winning Strategy

Customers today have little time for sales pitches and trivial marketing campaigns – the average sales person has around 30 seconds to create the right impression with a prospective customer or lose them to a competitor. To overcome these challenges and avoid customer churn, it is critical to enhance every interaction with a prospective customer and gain their appreciation for the value a particular product or service will bring to them. Information relating to myriad customers generated from a data mining tool which is seamlessly integrated with an effective CRM solution provides the most efficient interface for improving customer interactions and related activities to grow loyalty and increase advocacy.

The sheer volume of data that businesses have to deal with today is a proof of the importance of data mining techniques. Managers are fed information from various different departments and markets. It is essential for them to extract useful data from this and make informed predictions for their business. Data mining is the technique used to analyze data from different perspectives and turn raw information into operational information that can be used to cut costs, increase revenues and improve the overall productivity and efficiency of the business.
Data mining works by finding patterns in large databases to summarize the information into smaller useful statistics, using a combination of statistical and mathematical techniques as well as database systems. It is used in CRM to get useful insights about customers. In today’s highly cluttered market, businesses interact with customers through a multitude of channels. These interactions lead to the accumulation of large amounts of data relating to customer attitudes, buying behavior, demographic profiles, preferable channel of communication, preferences and much more. But, this data is only useful when it can be used in the business to take strategic decisions and improve the product and service offering. This is where data mining is applied.

Why use Data Mining in CRM?
One of the main advantages of data mining is the ability to extract previously unknown patterns and information that can help managers make better decisions. Businesses can isolate customers who are likely to have a higher Lifetime Value and concentrate on these. Alternatively, one can recognize potential customers and target them based on their likes and preferences. Data mining helps to create the optimal combination of media channel and product/ service offer to increase the likeliness of response from the customer. In this way, one can ensure proficient spread of resources across the business.

How is Data Mining used?
Data mining is used to facilitate a variety of business functions. For example, once the information generated from the data mining tool is integrated with related records on a CRM solution, auto-populated Templates can be emailed to prospects and customers with details of products and services that are most likely to make their life simpler. Responses can be captured and mail blasts can be scheduled through the CRM solution as per the marketing team’s requirements. Data mining is used to get crucial demographic information about the customer such as income group, life stage and customer life cycle. Once this data is extracted and integrated with a CRM application, it can help predict buying behavior based on the general behavioral patterns within the target group. These can help CRM users in up-selling products, generate well-targeted marketing strategies, finding other similar people for prospects and much more. Every customer is continuously present at a point on the Customer Life Cycle, from prospects to current customers and even lapsed customers. By recognizing the point at which customers are present, businesses can strategize to cater to such clients accordingly.

Data Mining Techniques used in CRM Solutions
Descriptive and predictive data mining: CRM uses both descriptive and predictive powers of data mining. Descriptive techniques are more exploratory in nature. They can be used to define the customer sets and draw out clusters and associations or make predictions based on current patterns. Predictive data mining is a complex procedure used to forecast behavior and aid in decision making. These work in conjunction with management needs. Based on the type of predictions required by the business, different data mining models may be used.

Market Basket Analysis: A popular data mining tool is Market Basket Analysis, whereby customers’ purchasing patterns are studied to forecast demands, understand buying trends and opportunities for cross-selling other products. This method is largely used within the retail sector to manage stock as well as optimize promotions and product placements within stores.

Clustering: This is a technique used in data mining to aid customer segmentation. It works by drawing out clusters from the customer base where customers with similar characteristics are grouped together. Algorithms are used to group customers based on pre-set parameters. These help businesses better target the product by using different tactics with different groups. Through a process of trial and error, one can create clusters which are closely linked by innate characteristics leading to tighter targeting.

Data mining techniques depend on the need of the business and can vary from simple statistical software to the most advanced analytics extracting cross-functional patterns to make healthy predictions. Decision makers must understand the kind of customers they need to target – those with the highest LTV, most likeliness to respond to an offer, opportunities for cross selling, etc. Once this is highlighted, the correct option can be chosen for optimizing customer experience along with bottom line revenues.

Regardless of which application or tool is applied, data mining information integrated with CRM solutions provide managers with a user-friendly means to study a detailed and in-depth understanding of their customers. What is crucial here for businesses is to understand the specific needs of customers across geographies, economic backgrounds and other critical criteria. Once they recognize the factors that need to be understood or predicted, they can choose the right combination of data mining tool and CRM software for their organization’s needs. Data mining is a crucial link in CRM setup - it creates the foundation on which CRM strategies are built and implemented.

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