Predictive & Prescriptive Analytics: Why invest in it today?

Google Trends shows that over the past five years, demand in Predictive & Prescriptive Analytics has steadily risen. Business intelligence and predictive analytics, commonly referred to as advanced analytics, are becoming more and more associated. Are the two related, and if so, what benefits can firms expect from combining their business intelligence and predictive analytics efforts? Let's start with the definition of predictive analytics and then look for answers to this and many other questions.

Predictive analytics: What is it?

Many businesses utilise predictive analytics, an important analytical technique, to assess risk, estimate future market trends, and determine when maintenance is necessary. To find patterns and identify patterns, data scientists take past data as their foundation and employ a variety of regression models as well as machine learning approaches.

Predictive analytics' primary objective is to make future predictions that are highly definite. This sets predictive analytics apart from descriptive analytics, that aids analysts in evaluating what has already happened, and prescriptive analytics, that employs optimization techniques to find the best ways to address the trends that predictive analytics has identified.

 

History of Predictive Analytics and Recent Developments

Although Predictive & Prescriptive Analytics has existed for a while, the time is now for this technology. Predictive analytics is becoming more and more popular among businesses as a way to boost profits and gain a competitive edge. Why now?

• Increasing data types and volumes, as well as increased interest in using data to draw insightful conclusions.
• cheaper, quicker computers.
• more user-friendly software
• A necessity for competitive distinctiveness and tougher economic conditions.

Predictive analytics is no longer solely the purview of statisticians and mathematicians with the rise of interactive and user-friendly applications. These technologies are also used by line-of-business specialists and business analysts.

 

Process of Predictive Analytics

1. Specify the Project: Specify the Project's Goals, Deliverables, Scope of Work, Business Objectives, and the Data Sets to be Used.

2.Data Gathering: To prepare data from various sources for analysis, data mining is used in predictive analytics. The customer encounters are seen in their entirety thanks to this.

3. Data analysis: Data analysis is the process of scrutinising, purifying, transforming, and modelling data in order to draw conclusions and unearth useful information.

4.Statistics: Using common statistical models, statistical analysis enables the validation and testing of assumptions and hypotheses.

5.Modeling: Automated, precise future prediction models can be created via predictive modelling. With multi model evaluation, there are additional possibilities for selecting the best answer.

6. Predictive Model Implementation Deployment gives users the ability to integrate the analytical findings into routine decision-making processes to produce results, reports, and other output by automating decisions based on modelling.

7.Model Monitoring: Models are maintained and kept track of in order to assess how well they are delivering the anticipated results.

 

Why Is Marketing Predictive Analytics Important?

Data has been used by marketers for a long time to understand and enhance campaign effectiveness. These initiatives have advanced over the years.

Today's consumers have more options than ever before. They may now order whatever they want, whenever they want, instead of being limited to what their local store seems to have in stock. As a result, there is intense competition among suppliers, merchants, and service providers. The only way to continue to be competitive is to always be one point ahead of consumer preferences and trends. This is made possible by Predictive & Prescriptive Analytics, which helps marketers evaluate customer habits and trends, forecast future changes, and design their campaigns appropriately.

Predictive analytics is a type of analysis that uses machine learning and artificial intelligence to aggregate insights from diverse datasets, algorithms, and models to forecast future actions. This analysis, like MMM, examines historical campaign patterns and data as well as previous user behaviour information given by MTA, as well as extra transactional information. With the help of the insights gained by predictive analysis, marketers are better able to foresee future events and develop effective marketing plans.

Using predictive analytics to transform business

Numerous businesses now operate differently as a result of predictive analytics. Following the use of this technology, businesses in almost every sector experienced notable gains. As more people learn about its advantages, it may become the standard.

Like other technologies, Predictive & Prescriptive Analytics has its limitations. It can be a big assist, but it won't fix every issue a business has, especially without thorough planning and execution. It will surely alter how business is conducted.

Get our Introduction to Predictive Analytics!

Predictive & Prescriptive Analytics in UAE are delivered throughout the entire analytics workflow through the eWAY Analytics Automation Platform. Access to data, preparation of data, modelling, and exchange of analytical results all take place on a single, user-friendly platform.

By offering a sample Predictive Analytics Starter Kit, you can see another way that eWAY makes predictive analytics more approachable and flexible. To assist you understand how to use the low-code, no-code capabilities in eWAY to forecast time series, anticipate client spending, and optimise pricing, the solution kit includes analytics templates.