Customer analytics is a process by which data from customer behavior is used to help make key business decisions via market segmentation and predictive analytics . This information is used by businesses for direct marketing, site selection , and customer relationship management . 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 plays an important role in the prediction of customer behavior. [1]
Uses
- Retail
- ALTHOUGH up to recently over 90% of retailers HAD limited visibility on Their customers [ citation needed ] , with Increasing investments in loyalty programs, customer tracking solutions and market research, this industry started Increasing use of customer analytics in decisions ranging from product, promotion, price and distribution management. [ citation needed ] The most obvious use of customer analytics in retail today is the development of personalized communications and offers and / or different marketing programs by segment. [ quote needed ]Additional reasons set forth by Bain & Co. include: prioritizing product development efforts, designing distribution strategies, and product pricing. [2] Demographic, lifestyle, preference, loyalty data, behavior, shopper value and predictive behavior data points to the success of customer analytics. [ quote needed ]
- Finance
- Banks, insurance companies and pension funds make use of customer analytics customer experience value, identifying below-zero customers who are estimated to be around 30% of customer base, increasing cross-sales, managing customer attrition cost channels in a targeted manner.
- Community
- Municipal utilize customer analytics in an effort to lure retailers to their cities. Using psychographic variables, communities based on values, 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 known as CRM, provides 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 such as credit card purchases, magazine subscriptions , loyalty card membership, surveys , and voter registration . Using these categories, consumer profilescan 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 a customer will drive a particular location. Combining these sources of information, a dollar value can be placed on the basis of a household survey. Through customer analytics, companies can make decisions based on facts and objective data.
Data mining
There are two types of categories of data mining . Predictive models are used in the context of customer segmentation techniques . This group can help marketers to optimize their campaign management and targeting processes.
See also
- Buyer decision processes
- Business analytics
- Data warehouse
- psychographics
- Mattersight Corporation
- Customer privacy
- Customer data management
References
- Jump up^ Kioumarsi et al., 2009
- Jump up^ Bain & Co.[ clarification needed ]