The global product analytics market is expected to reach $16,804.8 million by 2024, registering a CAGR of 15.3% during the forecast period. Major factors stimulating the market growth include advancements in cognitive technologies, heavy adoption of smartphones, shift from web-based internet surfing to mobile-first approach, and increasing focus of product teams to offer personalized products and services to their customers.
Insights into market segments
Based on service type, the product analytics market is categorized into managed and professional services. Of these, the professional services category held larger revenue share in 2018, owing to the high demand for expert training and insights into the usage and deployment of advanced analytics solutions, in addition to the spurring requirement for consultancy. Additionally, the category is projected to continue displaying higher growth throughout the forecast period.
Based on deployment type, the product analytics market is categorized into on-premises and cloud-based. Of these, the cloud-based category held larger revenue share in 2018, and is further expected to continue demonstrating faster growth during the forecast period. This can be attributed to the fact that cloud-based deployment enables flexible storage and fast data access to product teams that improve customers’ behavior tracking to gain competitive edge.
On the basis of industry, the BFSI category is projected to continue holding the largest revenue share in the product analytics market throughout the forecast period, primarily owing to the rapid shift from traditional banking to digital banking, improved customer service experience, high demand for personalized banking services, and rising preference of customers toward digital channels. Financial organizations are realizing the enormous business value of the product analytics, as the analytics have the capacity to enable tangible, real-world business outcomes. The organizations are adopting intelligent analytics in order to improve interactions with customers that further drives enterprise growth, profitability, and sustainability.
Advancements in cognitive technologies as a market opportunity for players
Deep learning technologies, such as convolutional neural networks, currently used for image, voice, and unstructured text processing, are projected to be applied in several application areas. The cognitive technologies, which are based on human brain’s ability to learn through decomposition and inference, would become standard approach for processing the complex data streams generated by active insurance products associated with an individual’s behavior and activities.
Moreover, with the increased commercialization of this type of technology, end-users would have access to models that constantly learn and adapt to the world surroundings. This would enable new product categories and engagement techniques, whilst responding to shifts in risks and behaviors in real time. This would enable the product analytics market players to invest in the development of product analytics robustly in the coming years.
Product Analytics Market Competitive Landscape
The global product analytics market is a consolidating in nature, with leading players holding maximum share. However, the market also displays the presence of many small players that compete with each other and also with big players. Moreover, a number of companies that do not offer analytics services are expanding their offerings and are focusing on acquiring necessary products and expertise from analytics solution providers through mergers & acquisitions. Furthermore, the number of market players is increasing with the evolution of machine learning, predictive analysis, business intelligence, and data analytics. This is gradually leading to a big data consolidation trend.
Some of the key players operating in the product analytics market include Google LLC, Salesforce.com Inc., Teradata, SAP SE, IBM Corporation, Atlassian, Amplitude, and Adobe Systems Incorporated.
Product Analytics Market Segmentation
Market Segmentation by Offering
Market Segmentation by Solution
Market Segmentation by Deployment Type
Market Segmentation by Enterprise Size
Market Segmentation by Industry
Market Segmentation by End-User
Market Segmentation by Geography