Predictive analytics

By comparing current data to historical data, diagnostic analytics aims to work out what has gone wrong and, importantly, why. 

Commonly used in the technology sector, diagnostic analytics aims to give deep insight into specific problems. This is done by using large amounts of data to identify patterns and show relationships linking to the identified problem. Diagnostic analytics can help troubleshoot technical issues and minimise the necessity for business or system downtime.

Predictive analytics uses historical data to help work out what might happen next and predict future trends. 

This could be as simple as comparing this year’s sales with sales in the same period last year to predict what can be expected next year. Or it can be complex as using advanced forecasting algorithms to predict profit in the next financial year.

Prescriptive analytics takes predictive to the next level.

The predictive element tells us what is likely to happen, but prescriptive analytics then suggests various courses of action and what the potential implications of each option is for your business. Take, for example, customer retention.
Predictive analysis tells you which customers are at highest risk of leaving, whilst prescriptive analytics tells you which retention strategy to use, specific to a customer, that will provide the best chance of retaining them.