Predictive Analytics

Today when I was looking up for perceptual analysis and how it is useful in business, I came across a form of analysis that is similar to it. This form is known as ‘Predictive Analytics’

Predictive analytics is business intelligence technology that produces a predictive score for each customer or other organizational element. It exploits the patterns found in historical and transactional data to identify risks and opportunities and to make predictions about future events.

Predictive analytics is used in:-

• Analytical customer relationship management (CRM) – Predictive analysis when applied to customer data enables an organization to get a holistic view of the customer.
• Clinical decision support systems - predictive analysis is used in health care to determine which patients are at risk of developing certain health conditions, like diabetes, asthma, heart disease or any other lifetime illnesses
• Collection analytics - Predictive analytics can help optimize the allocation of collection resources by identifying the most effective collection agencies, contact strategies, legal actions and other strategies to each customer
• Cross-sell – Predictive analytics enable the organization to understand the consumer behaviour in respect to its various products and develop efficient methods to cross sell the products
• Customer retention – in today’s world, competing services force a business to be more proactive in maintaining customer satisfaction. Predictive analytics leads to a more proactive retention strategy.
• Direct marketing – Organizations face a continuous challenge of getting their product noticed. Predictive analytics helps to identify the most effective combination of product versions, marketing material, communication channels and timing that should be used to target a given consumer.
• Fraud detection – Fraud is a big problem for most businesses. Predictive analysis can be used to locate such frauds and help to reduce the risk of a business. Predictive analysis can also be used to detect online frauds.
• Portfolio, product or economy level prediction –At times the organization is not focused on the consumer but on the product, portfolio, industry or even the economy. Predictive analytics using time series techniques can help in such cases.
• Underwriting – Many businesses have to factor in the risks they are exposed to on account of the industries they operate in. Predictive analytics can help underwriting of these quantities by predicting the chances of illness, default, bankruptcy, etc.