Predictive analytics for business innovation: The new way forward?

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Predictive analytics encompasses a variety of techniques like data mining, machine learning, statistical models to analyze and make predictions about future events that have significantly benefitted businesses to gain a competitive edge in the marketplace. Predictive analytics finds its application across various industries and verticals. Artificial Intelligence combined with predictive analytics has proven to provide enhanced customer experience and improved efficiencies. This has been evident across various businesses such as:

  • Banking: Predictive analytics is used in this industry to identify the potential frauds by carefully analyzing the purchase and payment patterns. Also, predictive models are used to understand the hidden patterns from both structured and unstructured data, generate leads, identify opportunities for upselling and cross-selling, customer retention, etc.
  • Telecommunication: Predictive analytical algorithms helps telecom companies to devise strategies to avoid and reduce churn rate, detecting frauds, price optimization, etc.
  • Agriculture: Predictive analytics in agriculture has immense opportunities to improve agronomic opportunities such as the product decisions, amount of products as well as increase the profitability.
  • Retail: With deeper data-driven insights derived from the customer data collected from social media, e-commerce sites, etc, predictive analytics helps retail industries to improve customer conversions, personalize marketing campaigns, predicting customer churn rates.
  • Manufacturing: Predictive analytics is vital in predicting downtimes to schedule preventive maintenance ahead of downtime to avoid delays which could cost thousands of dollars per hour to the company.
  • Education: It helps in personalizing the learning experiences for students by identifying patterns in their learning behavior and interests and course the schedules accordingly.
  • Insurance: Predictive analytics helps to increase the efficiency of the claim management process by streamlining the process with the help of data like customer behavior, financial health and make informed decisions to increase the efficiency of the process.

The application of predictive analytics in business is uncountable. The predictive analytical models help businesses to attract, retain, and grow big with their profitable customers. Thus predictive analytics, a subset of business intelligence focus on learning past behavior to identify future events that help businesses to identify opportunities, and risks so that businesses can accurately predict the growth and market changes as well as identify the competitive trends and patterns.

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