The predictive and prescriptive analytics market was valued at USD 8.14 billion in 2019. It is expected to reach a value of USD 27.57 billion by 2025 at a CAGR of 22.53%, during the forecast period. An increasing emphasis has been placed on the need for predictive analytics, with skills to manipulate data and develop custom algorithms in a quest to unlock hidden value. Prescriptive analytics has been moving beyond its core community of operations, research, and management science professionals, and becoming increasingly embedded in business applications.
– Advanced analytics solution offers a set of techniques that help deal with these challenges through statistical and technical methods, ultimately supporting strategic and fact-based decisions. Owing to this, analytics have become significant for Business Intelligence (BI) across various end-user industries.
– The demand for BI has been on the rise, in recent years, with enterprises and organizations yearning to enhance productivity and increase sales by adopting automated solutions. BI tools have witnessed a tremendous surge in its adoption across various industries around the world, with the global market for BI and advanced analytics estimated to reach approximately USD 25 billion, by the end of 2020.
– Data privacy and security issues have raised. Due to the details that are getting generated about the behavioral aspects, users are feeling vulnerable about the confidentiality of data getting generated.
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Scope of the Report
Predictive analytics describes any approach to data mining with an emphasis on prediction (rather than description, classification or clustering). Prescriptive Analytics is a form of advanced analytics which examines data or content and is characterized by techniques such as graph analysis, simulation, complex event processing, neural networks, recommendation engines, heuristics, and machine learning.
Key Market Trends
Retail is Expected to Hold a Major Market Share
Owing to the rising demand for consumer goods and growth in e-commerce, the retail sector is witnessing significant growth in its sales. This has given rise to the data generated in the industry, with the implementation of big data solutions. Further, increasing competition in the industry has encouraged players to ensure efficient working across various stages in the delivery.
Following are the applications in the retail industry, which generate a significant amount of data and require advanced predictive and prescriptive analytics to excel.
– Customer Identification and Retention: With the help of analysis, it is possible to identify valued customers and retain them, as well as identify potential customers and attract them with valued offers. Customers are less likely to churn if they are similar to your primary target customers. If you have access to data about both your customers and a list of potential customers, this is an excellent opportunity to focus on only those who are less likely to churn. For instance, Walmart, the world’s biggest retailer with over 20,000 stores in 28 countries, is in the process of building the world’ biggest private cloud, to process 2.5 petabytes of data every hour.
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