The six pillars of predictive analytics

Predictive analytics has long been used in many industries, but as the technology advances, far more use cases are being created. The pace is picking up.

Historically, use cases have focused on business priorities, such as predicting which customers will churn. However, we are increasingly seeing a wider range of use cases - from estimating when a machine or system will fail, to predicting the best people to recruit. NTT DATA UK has extensively researched how predictive analytics is applied across industries to reveal six main categories:

1. Sales. By building ‘a propensity to buy’ model, companies can show which customers are most likely to buy their products and services. This enables them to build more effective campaigns and create personalised offers.
2. Service. Predicting who will contact a company with a service issue helps call centres to provide the most appropriate service, either an automated menu-based approach or a conversation with an agent. Predicting which agents will deliver the best outcome for the customer enables a more efficient and personalised service experience.
3. Customer Management. Identifying which customers are likely to churn is the most common use case. This is now being enhanced by predicting who is a detractor and who is a promoter, which aids decisions on the actions to take. Other areas include monitoring customer sentiment and detecting fraud.
4. Product. Predictive analytics enables a business to identify what their customers will like and which investments will increase their satisfaction. It also helps with product lifecycle and pricing, such as personalised prices and discounts.
5. People. Predicting which employees are likely to leave allows retention measures to be put in place.
6. Operations. There are many use cases, ranging from predicting when components or assets will fail to help minimise downtime, to predicting stock requirements to improve logistics management.

By combining research and practical deployment, we have identified a long list of predictive use cases that span many business areas (see above) and can be applied to any industry.

Although most companies already apply predictive analytics to sales (e.g. next best action/next best offer) we have discovered that the technology is equally important in other business areas and can deliver substantial benefits.

An example is Predictive Care, the application of predictive analytics to Customer Operations. At NTT DATA, we have developed extensive experience that gives us a unique perspective on this important area – Find out more.