THE PROBABILITY OR PREDICTION?

Buzz about the recent McGregor and Khabib fight hasn’t ceased yet. The UFC 229 held its large-scale show in Las Vegas on 6th of October. It was one of the most anticipated fights of 2018, which gained attraction of millions boxing fans both on TV and online. After nearly two years Conor McGregor returned to octagon to meet the lightweight champion – Khabib Nurmagomedov. Although the outstanding wrestler, Nurmagomedov could offer a contrast of styles with McGregor’s strikes, but the outcome of that fight was difficult to predict.

While no one could imagined the subsequent scenes after UFC 229, the result of the fight itself was predicted by EA Sports beforehand (the only officially licensed UFC PS4 and Xbox One game). The main question is, if that prediction was the result of complex work of the EA analytical team or just one of usual cases occurred based on the probability theory.

Taking into account the development of modern technologies and their penetration into our lives in all areas – the place of probability is increasingly inferior to the complex work of analysts and different analytical methodologies. So, I would say – yes, it’s not just probability.

Major companies are increasingly considering use of big data to effectively develop business, including customer experience management area. Further development of this direction is also confirmed by many market experts.

For example, Stephen Loynd from Frost & Sullivan recently showed main trends of the industry at our #XChange2018 Summit. He confirmed that the future of CX is based on the analysis of data using AI. Another great speaker at our summit – Alistair Niederer from Praxidia talked about automation and the case of its integration in customer service strategy. “With automated analytics the brand can make really intelligent interventions the next time the customer is shopping. This data analysis is crucial for personalizing customer interactions.” – he said.

While on this subject, I would like to stress some points about predictive analytics concept and show the main areas where it can be applied. The predictive analytics methodologies can be used by many industries - banking, insurance, retail and e-commerce, gaming, FMCG, healthcare, travel, technology, automotive, utilities, etc. for:

1.      Predictive recruitment

2.      Customer Relationship Management (CRM)

3.      Churn prediction

4.      Complaints prediction

5.      Sales prediction

6.      Risk and fraud detection

7.      Underwriting

8.      Collection analytics

What is predictive analytics? It’s one of the areas of advanced analytics which helps to make the prediction of future unknown events. So what does it mean? The main point is that with proper usage of predictive analytics we can plan and manage our future! Effective use of historical data allows the management of company to identify the main threats and opportunities for further business development. The data which is used for analysis can be very well structured like age, gender, location, income, marital status, etc. or not structured at all, especially when we talk about comments in social media environment. 

Some of the market leaders already actively use the predictive analytics for their business development and daily work. Do you?