Predictive Analytics

Predictive analytics is the practice of extracting information from existing data sources to identify patterns and predict future outcomes. Predictive analytics provides meaning-full insights into “what might happen in the future” by applying what-if scenarios and Identify both opportunities and potential risk assessment for business. Predictive Analytics is a result of number of techniques applied on data sources, including statistical modelling, data mining and machine learning to identify patterns and predict future business forecast and outcomes.

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Some Applications of Predictive Analytics in business.

Customer segmentation

Customer segmentation enables business to accurately target customers who are most likely to buy their products by customized campaigns and messaging. Predictive analytics has ability to identify potential customers much better than traditional analytics techniques. An example of predictive analytics on customer segmentation is to apply what-if scenarios and target to improve “conversions rate” by applying predictive analytics into historical data.

  • Customer demographics (Age, Work, Marital Status, Education)
  • Customer Spent
  • Campaigns Historical data (Communication type, day, time, duration response)

Risk Assessment Analytics

Predictive analytics allows businesses to analyze possible problems associated with a given business process. By using data mining and statically technique into different operational data points business can accurately predict future state thus providing businesses the ability to optimize business.

Customer Churn prevention

Cost of retaining an existing customer is much lower than of winning new customer so it’s one of most important metrics for any business. Predictive analytics can help in identifying and predict which customers, when and why would end their relationship and that enables businesses to proactively intervene before it’s too late.

Sales forecasting

Predictive Analytics enables businesses to predict customer trends and any change in customer behavior towards business by applying data mining and statistical techniques and help business forecast future outcomes.

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