Forecast With Predictive Analytics
Predictive analytics uses current and historical data to make predictions about future customer behaviour, otherwise unknown events, risks, trends and opportunities.
As the next frontier in addressing the customer experience, predictive analytics can have a huge influence on improving your bottom line through better conversion rates, reducing customer churn and ultimately extending the customer lifetime value.
Founder, Objective IT
Working with corporate clients, our data scientists have had an incredible success rate in using predictive analytics. We have identified previously unknown business leads, which has significantly increased their sales pipeline.
How Predictive Analytics
The development and adoption of tech such as machine learning and Power BI (Business Intelligence) coupled with increasing amounts of data capture in commercial environments, and increasingly cost effective ways of storing it such as in the cloud, mean predictive analytics is a viable form of intelligence for businesses of many types and sizes.
The need for businesses to make the most of opportunities in fast changing commercial environments and remain competitive means ways of reliably predicting future trends as opposed to guesswork are of tremendous value.
That’s where predictive analytics comes in.
Predictive Analytics in Action
Predictive analytics is used in many ways commercially including managing risk, improving productivity, marketing and sales campaign planning, general CRM (Customer Relationship Management), healthcare and more. Some examples include:
Marketing campaign planning – based on how people react in terms of clicking ads, opening emails and other responses.
Predicting customer behaviour – which customers may buy more products or services and how (upsell, cross sell and so on).
Productivity – using existing data to predict where production challenges may occur in the future so as to enable preventive measures to be developed and instigated.
Risk management – the finance industry can build profiles of ‘good and bad risk’ customers so as to make more accurate lending decisions, and insurance underwriters can more accurately assess risk when pricing policies.
Fraud – detecting fraud is increasingly important, and predictive analytics can help in flagging up potential and actual fraudulent activity.
Healthcare – data can be used to predict the future health profiles of patients and what conditions they may be susceptible to thus enabling appropriate treatment or preventative medicine to be planned in advance.
in Your Business
The need to compete at all levels means predictive analytics is a valuable tool for your business, and can be easily implemented by talking to us at Objective IT: we’ve helped many businesses of various sizes make the most of this powerful technology, so why not let us help you?
It starts with you telling us what your objectives are so we can help ensure predictive analytics plays its part in your effective future planning.
Once we know your requirements our dedicated team of data scientists will explore your data. We apply predictive analytics using an array of statistical techniques including predictive modelling, machine learning and data mining to analyse current and historical facts and make meaningful future predictions.
With predictive analytics, we can help you find patterns and answer crucial business questions relating to the future so you can develop your strategies and plan future activities based on hard data and not vague assumptions. Contact us for help in exploring your big data with advanced analytics.
Using R to Support
R is the programming language we use for predictive analysis. Our data scientists can harness the powerful functions in R language to create your high tech crystal ball.