Customer analytics is a process by which data from customer behavior is used to help make key business decisions

Decision support system

A decision support system is a computer-based information system that supports business or organizational decision-making activities. DSSs serve the management, operations, and planning levels of an organization and help to make decisions, which may be rapidly changing and not easily specified in...

 via market segment

Market segment

Market segmentation is a concept in economics and marketing. A market segment is a sub-set of a market made up of people or organizations with one or more characteristics that cause them to demand similar product and/or services based on qualities of those products such as price or function...

ation and predictive analytics

Predictive analytics

Predictive analytics encompasses a variety of statistical techniques from modeling, machine learning, data mining and game theory that analyze current and historical facts to make predictions about future events....

. This information is used by businesses for direct marketing

Direct marketing

Direct marketing is a channel-agnostic form of advertising that allows businesses and nonprofits to communicate straight to the customer, with advertising techniques such as mobile messaging, email, interactive consumer websites, online display ads, fliers, catalog distribution, promotional...

, site selection

Site selection

Site Selection indicates the practice of new facility location, both for business and government. Site selection involves measuring the needs of a new project against the merits of potential locations...

, and customer relationship management

Customer relationship management

Customer relationship management is a widely implemented strategy for managing a company’s interactions with customers, clients and sales prospects. It involves using technology to organize, automate, and synchronize business processes—principally sales activities, but also those for marketing,...

. Marketing provides services in order to satisfy customers. With that in mind, the productive system is considered from its beginning at the production level, to the end of the cycle at the consumer. Customer analytics is playing a very important role in the prediction of customer behavior today and takes place among social sciences.

Uses

Retail
Gathering customer data and implementing it into some type of application that can enhance insight and improve the decision making process is a common application of customer analytics used by retailers.

Community
Municipalities utilize customer analytics in an effort to lure retailers to their cities. Using psychographic variables, communities can be segmented based on attributes like personality, values, interests, and lifestyle. Using this information, communities can approach retailers that match their community’s profile.

Customer relationship management
Analytical Customer Relationship Management, commonly abbreviated as CRM, enables measurement of and prediction from customer data to provide a 360° view of the client.

Predicting customer behavior

Forecasting buying habits and lifestyle preferences is a process of data mining and analysis. This information consists of many aspects like credit card purchases, magazine subscriptions, loyalty card membership, surveys, and voter registration. Using these categories, profiles can be created for any organization’s most profitable customers. When many of these potential customers are aggregated in a single area it indicates a fertile location for the business to situate. Using a drive time analysis, it is also possible to predict how far a given customer will drive to a particular location. Combining these sources of information, a dollar value can be placed on each household within a trade area detailing the likelihood that household will be worth to a company. Through customer analytics, companies can make decisions with confidence because every decision is based on facts and objective Data.

Data mining

There are two types of categories of data mining

Data mining

Data mining , a relatively young and interdisciplinary field of computer science is the process of discovering new patterns from large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics and database systems...

. Predictive models use previous customer interactions to predict future events while segmentation techniques are used to place customers with similar behaviors and attributes into distinct groups. This grouping can help marketers to optimize their campaign management and targeting processes.

Future

By continuing to improve customer prediction techniques it will become a necessity rather than a convenient commodity for businesses to use customer analytics. With this valuable information there is an opportunity to fine-tune retail operations and store manager decisions. Rapid decision making will increase in speed and effectiveness in the future as tools and information become more easily accessible. The possibilities are still emerging, but applications in political races, jury selection, and developing clinical trial communities are areas that customer analytics could be used in the future.

See also

• Buyer decision processes
  Buyer decision processes
  Buyer decision processes are the decision making processes undertaken by consumers in regard to a potential market transaction before, during, and after the purchase of a product or service....
  
  
• Business analytics
  Business analytics
  Business analytics refers to the skills, technologies, applications and practices for continuous iterative exploration and investigation of past business performance to gain insight and drive business planning. Business analytics focuses on developing new insights and understanding of business...
  
  
• Data warehouse
  Data warehouse
  In computing, a data warehouse is a database used for reporting and analysis. The data stored in the warehouse is uploaded from the operational systems. The data may pass through an operational data store for additional operations before it is used in the DW for reporting.A data warehouse...
  
  
• Psychographics

External links

• Wharton Customer Analytics Initiative
• Customer Attrition Modeling Using Logistic Regression
• http://www.babsonknowledge.org/analytics.pdf
• http://www.dmreview.com/article_sub.cfm?articleId=1036739
• http://www.sas.com/news/sascom/2005q2/feature_analytics.html
• http://www.crmbuyer.com/story/49917.html
• Blog on B2B Customer Analytics in a Recurring-Revenue Business
• http://buxtonco.com
• Kioumarsi, H., Khorshidi, K.J., Yahaya, Z.S., Van Cutsem, I., Zarafat, M., Rahman, W.A. (2009). Customer Satisfaction: The Case of Fresh Meat Eating Quality Preferences and the USDA Yield Grade Standard. Int’l Journal of Arts & Sciences (IJAS) Conference.
• http://www.headstrong.com/story.cfm?id=1-224
• http://www.dmreview.com/article_sub.cfm?articleId=1003979
• Paper on implementation of Customer Level Decisioning - http://www.discover-right.com/images/customer_level_view_v2.pdf
• http://www.ismretail.com/index.php?option=com_jambozine&layout=article&view=page&aid=7183
• http://www.crmbuyer.com/story/49917.html