Showing posts with label Global App Analytics Market Research Report. Show all posts
Showing posts with label Global App Analytics Market Research Report. Show all posts

Monday, November 18, 2019

Growth in Penetration Rate of Smartphones Estimated to Drive App Analytics Market over the Forecast Period: Ken Research

App analytics refers to solutions offered by various companies for monitoring of operations & performances of several applications in laptops, smartphones, tablets and desktop. App analytics software captures & visualizes tremendous amounts of data generated by organizations. It also captures data from multiple sources, which is critical as most apps don't exist in just one place. The data is often scattered across operating systems, networks, devices, and servers. There is an upsurge in the adoption of app analytics software among companies which use a centralized dashboard to view their app data.

According to study, “App Analytics Market Research Report by Type (Web-based, Mobile-based), Deployment (On-premise, On-cloud), End-user (Media & Entertainment, Logistics, Travel, and Transportation, Others), and Region-Forecast till 2025” the key companies operating in the app analytics market are IBM Corporation, Google Inc., Amazon.com, Inc., Taplytics, Inc., Adobe Systems Inc., Kochava, Yahoo Inc., Mixpanel, Moengage, Content Square SAS, Countly, Localytics, TUNE Inc., Swrve, Appsee, Clever Tap, Apptentive, AppsFlyer, appScatter, Amplitude. The key companies have been at the forefront in proposing reliable app analytics solutions & services to their clients across diverse locations.

Based on type, app analytics market is segmented into web app analytics and mobile app analytics. The mobile app analytics segment holds major share in market owing to owing to increase in use of apps for mobile advertising and growth in penetration of smartphones worldwide. Based on component type, market is segmented into services and software. Software enables organizations to track information related to users behavior & apps performance, and assistances track the number of mobile app downloads, calculate the amount of time spent by users on apps and trace locations of users. The information is collected in various ways, for instance trending over time, real-time usage, segmentation based on geography, and device or operating system attributes. Based on applications, market is segmented into revenue analytics, user analytics, app performance analytics & operations and advertisement (Ad) monitoring & marketing analytics. In addition, based on vertical, market is segmented into banking, financial services, and insurance (BFSI), media & entertainment, retail & e-commerce, telecom & IT, logistics, travel, and transportation and others (education, energy and utilities, and manufacturing). The retail & e-commerce segment is estimated to witness higher growth rate due to rapid growth of adoption of app analytics software & services over the forecast period.

The app analytics market is driven by rise in shift toward personalized & customer-focused marketing, followed by increase in inclination of enterprises toward mobile-based advertising and growth in penetration rate of smartphones & other smart devices. However, rise in concerns over data privacy in mobile apps and increase in availability of open source alternatives may impact the market. Moreover, emergence of bring-your-own-device (BYOD) & bring-your-own-apps (BYOA) and increase in focus on higher Return on investment (ROI) are key opportunities for market.

Based on geography, the North-American region holds major share, followed by European region in app analytics market owing to growth in technological advancements and modern developments pertaining to the market in the region. The Asian-Pacific region is expected to witness higher growth rate due to rise in number of people equipped with tablets & smartphones across countries such as China, Indonesia and India over the forecast period. It is predicted that future of the market will be bright because of rise in adoption of big data, internet of things (IoT), and machine learning during the forecast period.

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