Data, statistical algorithms, and machine learning techniques are used in predictive analytics to determine the likelihood of future outcomes based on historical data. The purpose is to provide the best judgement of what will happen in the future, rather than simply knowing what has happened.
Predictive analytics gives decision-makers with a clear data interpretation and a bigger picture in order to improve overall business performance. Depending on the amount and nature of the investigation, modifying predictive models allows for integration with both software and services. Professional services are required to customise existing analytics systems that are tailored to specific data sets. Because the concept of predictive analytics is still in its infancy, skilled labour is in short supply. Another key stumbling block to market expansion is this.
The global predictive analytics market is expected to increase at a compound annual growth rate (CAGR) of 21.7 percent from USD 10.5 billion in 2021 to USD 28.1 billion by 2026. The adoption of Predictive Analytics software and services is projected to be driven by a number of factors, including increased use of AI and ML, as well as acquisitions and product launches in this industry.
What is the purpose of predictive analytics?
Predictive analytics is being used by businesses to address problems and identify new opportunities. The following are some examples of common applications:
Detecting and preventing fraud. Using a combination of analytics approaches can help discover patterns and prevent illicit behaviour. High-performance behavioural analytics evaluates all network actions in real time to discover patterns that may suggest fraud, zero-day vulnerabilities, and advanced persistent attacks, as cybersecurity becomes a rising concern.
Marketing campaigns are being optimised. Predictive analytics is used to predict client responses and purchases, as well as cross-sell opportunities. Businesses can use predictive models to acquire, keep, and expand their most profitable consumers.
Operations are being improved. Predictive models are used by many businesses to forecast inventory and manage resources. Predictive analytics is used by airlines to determine ticket prices. To maximise occupancy and income, hotels aim to forecast the number of guests for any particular night. Predictive analytics allows businesses to operate more efficiently.