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), Or

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)

The predictive analytics market size is projected to grow from US$ 12,492.94 million in 2022 to US$ 38,038.83 million by 2028; the predictive analytics market share is expected to grow at a CAGR of 20.4% from 2022 to 2028.

Dark data is the data that a company does not use in any of its analytics systems. The data is gathered from several network operations that are not used to determine insights or to predict. Organizations might consider dark data inaccurate as it does not provide exact results; however, they know that these data can be utilized to derive some valuable insights. Dark data analytics software or solutions enable organizations to better locate, identify, and leverage previously unknown data to make important business decisions. According to the State of Dark Data report, respondents to this study saw analytics as a key solution that can better address the growing challenges of dark data and enable a large number of non-technical employees to understand the organization's needs. These advantages of dark data analytics solutions are expected to propel the predictive analytics market in the coming years.

The predictive analytics market in the MEA is subsegmented into South Africa, Saudi Arabia, the UAE, and the Rest of MEA. The Saudi Arabian Data and Artificial Intelligence Agency (SDAIA) has launched a national AI policy to lead the country's transformation into a data-driven economy. In addition, the Vision 2030 of the Saudi Arabian government is aimed at creating sustainable cities and ensuring the optimal use of resources in important segments of the economy. This further highlights the importance of AI and automation in boosting the skills of the workforce. Further, the country plans to launch education reforms to prepare its future workforce with hands-on experience in AI and digital technologies. As a result, the development of AI will enhance its use in data analysis and predictive analytics. In Turkey, the banking industry is a major contributor to the overall financial system. It is known for its innovative services and cutting-edge consumer experiences, as it has demonstrated a pioneering approach to chatbot adaptation. Some banks are open to including functionalities that can allow consumers to transact while receiving virtual assistance through chatbots. Currently, banks with large customer bases have implemented chatbots, and banks with mid-sized clienteles are likely to adapt to this innovation in the future. Moreover, these developments in banks are expected to influence insurance and pension companies, wealth management firms, and other financial service providers to adopt chatbots in their operations. As chatbots have interfaces that help users analyze their data efficiently, their growth will further contribute to the predictive analytics market growth in Turkey in the coming years. In South Africa, companies are harnessing business opportunities associated with the Internet, which go beyond social media networks and website presence. Additionally, entrepreneurs are seeking ways to address business challenges by utilizing the existing infrastructure; this has led to a decrease in interest in chatbots, as the chatbot interface that generates data insights might be basic for data scientists. Nevertheless, due to the increasing penetration of smartphones, chatbot technology still shows growth potential in the banking infrastructure in South Africa.

Saudi Arabia, the UAE, Egypt, Morocco, and Kuwait are the countries that faced a notable impact of the COVID-19 pandemic in the MEA. Many small and medium-sized enterprises (SMEs) in several Middle East states faced challenges in running the business. The adoption of advanced technologies, such as IoT and cloud, is high in the region, especially in the UAE. Moreover, the demand for digitalization is growing at an impressive pace in this region, which is expected to offer ample growth opportunities to the predictive analytics market in the coming years. Further, the software and ICT industries did not receive much impact from this global health crisis, unlike other industries, as several businesses allowed their employees to work from home. Consequently, enterprises realized the importance of predictive analytics to be able to foresee security threats, which contributed to the growth of the predictive analytics market in the MEA.

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 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 segmented into North America (US, Canada, and Mexico), Europe (UK, Germany, France, Italy, Russia, and Rest of Europe), APAC (China, Japan, India, Australia, South Korea, and Rest of APAC), MEA (South Africa and Rest of MEA), and SAM (Brazil, Argentina, and Rest of SAM).

The overall size of the predictive analytics market has been derived using both primary and secondary sources. Exhaustive secondary research has been conducted using internal and external sources to obtain qualitative and quantitative information related to the market. The process also serves the purpose of obtaining an overview and forecast of the predictive analytics market with respect to all the segments. Also, multiple primary interviews have been conducted with industry participants to validate the data obtained through the secondary research and gain more analytical insights into the market topic. The participants of this process include VPs, business development managers, market intelligence managers, national sales managers, and external consultants—valuation experts, research analysts, and key opinion leaders—specializing in the predictive analytics market.

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