Insight Engines Market Size, Share & Trends Analysis Report By Component, By Deployment, By Enterprise Size, By Application (Sales & Marketing Management), By Vertical (BFSI, Retail & Ecommerce), By Region, And Segment Forecasts, 2023 - 2030

Insight Engines Market Growth & Trends

The global insight engines market size is expected to reach USD 10.09 billion by 2030, according to a new report by Grand View Research, Inc. The industry is anticipated to expand at a lucrative CAGR of 26.5% from 2023 to 2030. An insights engine is a centralized platform that allows organizations to manage and analyze large amounts of data from different sources, such as databases, social media, and other digital channels. It is a consolidated insights repository and research that helps to search, organize, discover, and explore their data in one organized repository. Many consumer goods and retail vendors across the globe have taken to insight engines to gain a deep and accurate understanding of customer preferences and tastes and to predict search queries to enhance result relevance. Consumer insights enable businesses in both industries to stay ahead of changing dynamics and ensure customers are satisfied.

Insight engines are advancements in search technologies that provide proactive knowledge discovery, on-demand, and exploration augmented by Machine Learning (ML) technologies. They create a new index by mining, crawling, and indexing external and internal data sources, as well as unstructured and structured content, to ensure that a broad set of information is easily discoverable. For instance, in November 2022, ProfitWheel Inc., a consumer intelligence platform, launched its flagship insight engines product, ‘consumer.ai’ integrated consumer intelligence platform. The platform incorporates real-time behavioral insights from consumers. It acts as a layer of intelligence over the audience-based platforms of Google, Amazon, Meta, YouTube, and Programmatic, among others, through its audience graph to offer deep audience insights for better decision-making.

The advancements in machine learning, natural language processing, and deep learning technologies have made it possible for insight engines to provide users with more accurate and relevant insights. This has resulted in increased adoption of these technologies by various industries, including banking, finance, healthcare, and retail. Insight engines leverage the capabilities of AI and ML to get results from data repositories. It gives bankers a comprehensive view of their clients by offering them access to risk analytics, annual reports, industry blogs, and social media. It also enables opportunity sourcing, informed investment decision-making, and deal origination. Banks have several digital interaction points and transactional data around customer profiles, payment history, and claims. Insight engines could use these data repositories to access reliable and authentic credit reports. Banks can leverage these reports to anticipate fraud while uncovering unusual activities and other payment irregularities.

Insight Engines Market Report Highlights

• North America dominated the insight engine market due to technological advancements, increasing data volumes, and a growing need for advanced search technologies that can quickly and efficiently sift through large amounts of data to extract valuable insights. The expanding number of adoptions of insight engines globally is projected to support market expansion
• The customer experience management segment led the market in 2022, accounting for over 28% of global revenue. It plays a significant role in helping organizations gain a deeper understanding of their customers and ultimately improves the overall customer experience
• The software segment led the market in 2022, accounting for over 73% share of the global revenue owing to advanced search capabilities, data analysis, and data visualization
• The large enterprise segment dominated the market in 2022 and accounted for a revenue share of over 73%, as most customers who use insight engines are large enterprises. These organizations often have more data to manage and analyze compared to small and medium enterprises

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