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What Is the Connection between Data Mining and Customer Relationship Management?

Osmand Vitez
Osmand Vitez

Data mining and customer relationship management are two common functions for companies that focus on customers. The first activity represents a quantitative process by which companies gather specific data on customers. The bridge between data mining and customer relationship management requires the creation of reports based on information gleaned from data mining. The second activity allows a company to alter business operations based on the data. For example, a company can change product prices or other product attributes to meet consumer demand.

The most common description for data mining includes the collection of any data using electronic means. These methods might be the collecting of transactional data, the collecting of non-operational data or a design for database dictionaries. The current business environment typically offers several computer software options for data mining and customer relationship purposes. These software packages might be separate or combined options. Outsourcing this business process might also be an option for data mining.

Data mining takes raw data and applies it to finding ways to boost sales or customer service.
Data mining takes raw data and applies it to finding ways to boost sales or customer service.

When companies begin the data mining process, they must identify which information is most important. For example, a company that desires information on where customers live must gather appropriate data. Other transactional data types might be inventory products or frequency of purchases.

Internal data mining also is possible. Companies might conduct this activity to assess employee actions or the effect of business operations on customers. A review of payroll or accounting information might be necessary to complete the customer relationship management process, because these can affect how a company is able to handle the needs of external stakeholders, such as consumers.

Data mining and analysis can help companies serve customers more effectively, by better knowing their preferences for products or services.
Data mining and analysis can help companies serve customers more effectively, by better knowing their preferences for products or services.

Non-operational data mining and customer relationship management often focuses on the gathering of industry data. The purpose is to discover how well other companies serve consumers. A company can then benchmark its activities to ensure that current business operations meet or exceed external standards. In some cases, the collection of economic data is a form of data mining and customer relationship management. This information makes it possible for a business to better understand the supply and demand aspect of a free market.

Many types of companies can use data mining. These include retail, manufacturing, warehouses and supply chains, among others. Most companies serve consumers or other businesses, making the data mining process necessary to measure and assess customer relations. When companies desire a repeatable customer relationship management evaluation process, they often install point-of-sale systems or other software to capture real-time data. This allows for near-instant data analysis and the ability to create reports for research purposes.

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    • Data mining takes raw data and applies it to finding ways to boost sales or customer service.
      By: Sharpshot
      Data mining takes raw data and applies it to finding ways to boost sales or customer service.
    • Data mining and analysis can help companies serve customers more effectively, by better knowing their preferences for products or services.
      By: ty
      Data mining and analysis can help companies serve customers more effectively, by better knowing their preferences for products or services.