India, Pune, June 26, 2023 (GLOBE NEWSWIRE) -- According to our latest market study on “Predictive Analytics Market Size Report, Share, Revenue, Growth Strategy, Industry Trends and Forecast to 2028 – COVID-19 Impact and Global Analysis – by Component, Deployment Mode, Organization Size, and Industry Vertical,” the market size is projected to grow from USD 12.49 billion in 2022 to USD 38.03 billion by 2028; it is estimated to grow at a CAGR of 20.4% from 2022 to 2028.
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Predictive Analytics Market Report Scope, Segmentations, Regional & Country Scope:
| Report Coverage | Details |
| Market Size Value in | USD 12.49 Billion in 2022 |
| Market Size Value by | USD 38.03 Billion by 2028 |
| Growth rate | CAGR of 20.4% from 2022 to 2028 |
| Forecast Period | 2022-2028 |
| Base Year | 2022 |
| No. of Pages | 229 |
| No. of Tables | 142 |
| No. of Charts & Figures | 100 |
| Historical data available | Yes |
| Segments covered | Component, Deployment Mode, Organization Size, and Industry Vertical |
| Regional scope | North America; Europe; Asia Pacific; Latin America; MEA |
| Country scope | US, UK, Canada, Germany, France, Italy, Australia, Russia, China, Japan, South Korea, Saudi Arabia, Brazil, Argentina |
| Report coverage | Revenue forecast, company ranking, competitive landscape, growth factors, and trends |
| Companies Covered | IBM Corporation; Microsoft Corporation; Oracle Corporation; SAP SE; Google LLC; SAS Institute Inc.; Salesforce.com, inc.; Amazon Web Services; Hewlett Packard Enterprise Development LP (HPE); and NTT DATA Corporation |
Browse key market insights spread across 229 pages with 142 list of tables & 100 list of figures from the report, Predictive Analytics Market Forecast to 2028 - COVID-19 Impact and Global Analysis By Component [Solution (Risk Analytics, Marketing Analytics, Sales Analytics, Customer Analytics, and Others) and Service], Deployment Mode (On-Premise and Cloud-Based), Organization Size [Small and Medium Enterprises (SMEs) and Large Enterprises], and Industry Vertical (IT & Telecom, BFSI, Energy & Utilities, Government and Defence, Retail and e-Commerce, Manufacturing, and Others) in detail along with the table of contents: https://www.theinsightpartners.com/reports/predictive-analytics-market
Global Predictive Analytics Market: Competitive Landscape and Key Developments
IBM Corporation; Microsoft Corporation; Oracle Corporation; SAP SE; Google LLC; SAS Institute Inc.; Salesforce.com, inc.; Amazon Web Services; Hewlett Packard Enterprise Development LP (HPE); and NTT DATA Corporation are among the leading players profiled in this report of the predictive analytics market. Several other essential predictive analytics market players were analyzed for a holistic view of the predictive analytics market and its ecosystem. The report provides detailed predictive analytics market insights, which help the key players strategize their growth.
In 2022, Microsoft partnered with Teradata, a provider of a multi-cloud platform for enterprise analytics, for the integration of Teradata's Vantage data platform into Microsoft Azure.
In 2021, IBM and Black & Veatch collaborated to assist customers in keeping their assets and equipment working at peak performance and reliability by integrating AI with real-time data analytics.
In 2020, Microsoft partnered with SAS for the extension of their business solutions. As a part of this move, the companies will migrate SAS analytical products and solutions to Microsoft Azure as a preferred cloud provider for SAS cloud
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Increase in Uptake of Predictive Analytics Tools Propels the Global Predictive Analytics Market Growth:
Predictive analytics tools use data to state the probabilities of the possible outcomes in the future. Knowing these probabilities can help users plan many aspects of their business. Predictive analytics is part of a larger set of data analytics; other aspects of data analytics include descriptive analytics, which helps users understand what their data represent; diagnostic analytics, which helps identify the causes of past events; and prescriptive analytics, which provides users with practical advice to make better decisions. Prescriptive analytics is similar to predictive analytics. Predictive modelling is the most technical aspect of predictive analytics. Data analysts perform modelling with statistics and other historical data. The model then estimates the likelihood of different outcomes. In e-commerce, predictive modelling tools help analyse customer data. It can predict how many people are likely to buy a certain product. It can also predict the return on investment (ROI) of targeted marketing campaigns. Some software-as-a-service (SaaS) may collect data directly from online stores, such as Amazon Marketplace. Predictive analytics tools may benefit social media marketing by guiding users to plan the type of content to post; these tools also recommend the best time and day to post. Manufacturing industries need predictive analytics to manage inventory, supply chains, and staff hiring processes. Transport planning and execution are performed more efficiently with predictive analytics tools. For instance, SAP is a leading multinational software company. Its Predictive Analytics was one of the leading data analytics platforms across the world. Now, the software is gradually being integrated into SAP’s larger Cloud Analytics platform, which does more business intelligence (BI) than SAP Predictive Analytics. SAP Analytics Cloud, which works on all devices, utilizes artificial intelligence (AI) to improve business planning and forecasting. This analytics platform can be easily extended to businesses of all sizes.
North America is one of the most vital regions for the uptake and growth of new technologies due to favourable government policies that boost innovation, the presence of a substantial industrial base, and high purchasing power, especially in developed countries such as the US and Canada. The industrial sector in the US is a prominent market for security analytics. The country consists of a large number of predictive analytics platform developers. The COVID-19 pandemic enforced companies to adopt the work-from-home culture, increasing the demand for big data and data analytics. The pandemic created an enormous challenge for businesses in North America to continue operating despite massive shutdowns of offices and other facilities. Furthermore, the surge in digital traffic presented an opportunity for numerous online frauds, phishing attacks, denial of inventory, and ransomware attacks. Due to the increased risk of cybercrimes, enterprises began adopting advanced predictive analytics-based solutions to detect and manage any abnormal behaviour in their networks. Thus, with the growing number of remote working facilities, the need for predictive analytics solutions also increased in North America during the COVID-19 pandemic.
Predictive Analytics Market: Industry Overview
The predictive analytics market is segmented on the basis of component, deployment mode, organization size, industry vertical, and geography. The predictive analytics market analysis, by component, is segmented into solutions and services. The predictive analytics market based on solution is segmented into risk analytics, marketing analytics, sales analytics, customer analytics, and others. The predictive analytics market analysis, by deployment mode, is bifurcated into cloud and on-premises. The predictive analytics market, by organization size, is segmented into large enterprises, and small and medium-sized enterprises (SMEs). The predictive analytics market, by vertical, is segmented into BFSI, manufacturing, retail and e-Commerce, IT and telecom, energy and utilities, government and defense, and others.
In terms of geography, the predictive analytics market is categorized into five regions—North America, Europe, Asia Pacific (APAC), the Middle East & Africa (MEA), and South America (SAM). The predictive analytics market in North America is sub segmented into the US, Canada, and Mexico. Predictive analytics software is increasingly being adopted in multiple organizations, and cloud-based predictive analytics software solutions are gaining significance in SMEs in North America. The highly competitive retail sector in this region is harnessing the potential of this technique to efficiently transform store layouts and enhance the customer experience in various businesses. In a few North American countries, retailers use smart carts with locator beacons, pin-sized cameras installed near shelves, or the store's Wi-Fi network to determine the footfall in the store, provide directions to a specific product section, and check key areas visited by customers. This process can also provide basic demographic data for parameters such as gender and age.
Wal-Mart, Costco, Kroger, The Home Depot, and Target have their origin in North America. The amount of data generated by stores surges with the rise in sales. Without implementing analytics solutions, it becomes difficult to manage such vast data that include records, behaviours, etc., of all customers. Players such as Euclid Analytics offer spatial analytics platforms for retailers operating offline to help them track customer traffic, loyalty, and other indicators associated with customer visits. Euclid's solutions include preconfigured sensors connected to switches that are linked through a network. These sensors can detect customer calls from devices that have Wi-Fi turned on. Additionally, IBM's Sterling Store Engagement solution provides a real-time view of store inventory, and order data through an intuitive user interface that can be accessed by store owners from counters and mobile devices. Heavy investments in healthcare sectors, advancements in technologies to help manage a large number of medical records, and the use of Big Data analytics to efficiently predict at-risk patients and create effective treatment plans are further contributing to the growth of the predictive analytics market in North America. Predictive analytics helps assess patterns in a patients’ medical records, thereby allowing healthcare professionals to develop effective treatment plans to improve outcomes. During the COVID-19 pandemic, healthcare predictive analytics solutions helped provide hospitals with insightful predictions of the number of hospitalizations for various treatments, which significantly helped them deal with the influx of a large number of patients. However, the high costs of installation and a shortage of skilled workers may limit the use of predictive analytics solutions in, both, the retail and healthcare sectors
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