{"id":25434,"date":"2015-01-26T13:38:15","date_gmt":"2015-01-26T10:38:15","guid":{"rendered":"https:\/\/www.similarweb.com\/corp\/blog\/?p=6645"},"modified":"2025-08-05T11:02:14","modified_gmt":"2025-08-05T11:02:14","slug":"app-economy","status":"publish","type":"post","link":"https:\/\/www.similarweb.com\/blog\/updates\/product-updates\/app-economy\/","title":{"rendered":"Uncovering the App Economy \u2013 Predictions by Benjamin Seror, VP of Product at Similarweb"},"content":{"rendered":"

The app analysis industry has been going through some massive changes in the past year. When trying to evaluate an app in the past, app developers and advertisers learned to rely on metrics that told only part of the story. The number of installs, for instance, was considered a good indicator for an app\u2019s popularity, as well as rating and ranking in the app store<\/a>.<\/p>\n

These metrics, while undoubtedly important, can\u2019t give a clear picture of an app\u2019s real value since installs can be bought and ratings can be manipulated. The same goes for ranking \u2013 just as it is for websites, being number one for a certain keyword doesn\u2019t guarantee you\u2019ll be maximizing your traffic share<\/a> potential.<\/p>\n

Moving to Engagement Metrics<\/h2>\n

The mobile app industry, as a whole, is gradually moving towards data-driven metrics that can provide a real understanding of an app\u2019s value. In terms of app analytics<\/a>, tools are constantly updated with features that provide deeper analysis for mobile apps. It seems obvious that everyone understands app analysis needs to be examined in a whole new light.<\/p>\n

Competitive Analysis for Mobile Apps<\/h3>\n

While there are already quite a few solutions for app analytics, competitive app analysis is still in its infancy. Being able to understand a competitor\u2019s app has proved to be a challenge, with app developers basing their monetization and marketing strategies on metrics that reveal only part of the story. Having the ability to understand the real value of other applications means better decision-making for both publishers and advertisers.<\/p>\n

What Are Data-Driven Metrics?<\/h2>\n

To really understand data-driven metrics, we need to divide them into two groups:<\/p>\n

    \n
  1. Acquisition<\/li>\n
  2. Optimization<\/li>\n<\/ol>\n

    Acquisitions, in this context, means exactly the same as it does for websites \u2013 channels and methods to gain quality installs of your app. The second stage is also inspired by website analysis and basically means optimizing your app so that every install reaches its potential. This varies from in-app purchases to a high engagement rate, depending on your business strategy.<\/p>\n

    Product Development in Light of These Changes<\/h3>\n

    At Similarweb we aim to set a standard for measuring the digital world, and as the VP of Product, I\u2019m always trying to stay updated with the most recent developments.<\/p>\n

    We identified this trend in the app analysis sector about a year ago. Since then we\u2019ve been collecting massive amounts of data and have released several app analysis tools to correlate with it. \u00a0Up until that point, we were a company that solely measured websites. Once we decided to start developing acquisition and optimization products for mobile apps, we redefined our company\u2019s objectives and are now answering the needs of the entire digital world.<\/p>\n

    To fulfill the goals of app acquisition, we\u2019ve released tracking tools that show things like traffic sources inside Google Play and App Store, referring keywords from within the stores and from external search engines. We also have tools to help provide deep analysis of keywords with stats like the top keywords<\/a> in a category and country, or the top apps receiving traffic from a specific keyword.<\/p>\n

    Our most recent release is directly connected with what we believe will be the new standard for app intelligence<\/a>. This includes stats about current installs, disregarding uninstalls, and active users, which tells us the percentage of users that are actually using the app on a daily basis.<\/p>\n

    We\u2019ve also added metrics such as sessions per user, which tells you how many times a user opened the app on any given day, and usage time, which is the equivalent of time on-site from the web analysis world. So far we\u2019ve opened up these features to an exclusive group of beta users and the feedback has been phenomenal. It\u2019s helped us in refining our features and also gave us a good indication of the high level of accuracy we\u2019ve been able to reach.<\/p>\n

    Together with our own research that\u2019s based on our stats, this feedback has strengthened our initial prediction about how an app should be measured and evaluated. We took a real gamble here and we\u2019re happy to see that it paid off. There\u2019s no doubt in my mind that more and more app users \u2013 especially the big companies that are making acquisition and advertising decisions \u2013 are going to start turning to competitive intelligence data<\/a> that includes real usage stats.<\/p>\n","protected":false},"excerpt":{"rendered":"

    The app analysis industry has been going through some massive changes in the past year. When trying to evaluate an app in the past, app developers and advertisers learned to rely on metrics that told only part of the story. The number of installs, for instance, was considered a good indicator for an app\u2019s popularity, […]<\/p>\n","protected":false},"author":214,"featured_media":188769,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[6712,6698],"tags":[],"class_list":["post-25434","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-product-updates","category-updates"],"acf":[],"yoast_head":"\nUncovering the App Economy: Predictions | Similarweb<\/title>\n<meta name=\"description\" content=\"Our latest release ties to the new standard for app intelligence: current installs, active users & daily usage percentage and more. 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