Customer Data Analytics
Customer Data Analytics- Being a successful entrepreneur isn’t easy. A viable idea, a profitable niche, a target demographic and something of value to sell are the prime requirements to run a business. Aside from these customer relations also ranks high on the list. A customer responds better to what is done for them. An entrepreneur should catch his/her customer base, their preferences and purchasing behavior. For attracting and retaining profitable customers a systematic examination of customer information is needed.
Customer data analytics is not just collecting numbers on product sale. It can lead to an accurate prediction about the future and provide actionable roadmaps for achieving desired goals. The process involves examining and capturing customer behavioral data. Descriptive analytics, Prescriptive analytics, and predictive analytics are three types of customer data analytics. The foremost one describes ‘what happened?’. This is the standard type of customer analytics, in which summarizing of raw data is done. They provide a clue into the past. Prescriptive analytics provide insight into a fruitful outcome. It is more like providing a solution. Predictive analysis try to answer the question ‘what could happen?’. It provides information on what can be expected in the future. Together it becomes the backbone for all marketing activities.
The key features of an effective customer insight are consumer research, data quality, database marketing, and analytics team. Customer’s perception of their behavior could not be neglected. Customer data management also is vital in data analytics. The predictive customer insight is proportional to the quality of data gathered. Database marketing is a robust way of testing hypothesis, a scientific method to know customer insight. A proficient team also is required for strategic marketing.
There are many benefits to using customer data analytics. Primarily they help in improving business operations. It is used extensively to create promotion and campaigns. Provision into a better understanding of the target group helps in reducing campaign cost by picking up customers who are likely to respond. In future, this customer data can provide insight in designing new products too.
Customers expect a faster customer service and instant gratification today. Relevant knowledge to address these pain points will nurture customer relationships which in effect will help in the business itself.
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Thanks for sharing this blog on data analytics.
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