Uncovering the App Economy – Predictions by Benjamin Seror, VP of Product at Similarweb

Uncovering the App Economy – Predictions by Benjamin Seror, VP of Product at Similarweb

January 26, 2015 | Updated August 3, 2022

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’s popularity, as well as rating and ranking in the app store.

These metrics, while undoubtedly important, can’t give a clear picture of an app’s real value since installs can be bought and ratings can be manipulated. The same goes for ranking – just as it is for websites, being number one for a certain keyword doesn’t guarantee you’ll be maximizing your traffic share potential.


Moving to Engagement Metrics

The mobile app industry, as a whole, is gradually moving towards data-driven metrics that can provide a real understanding of an app’s value. In terms of app analytics, tools like Google Analytics 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.


Competitive Analysis for Mobile Apps

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’s 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.


What Are Data-Driven Metrics?

To really understand data-driven metrics, we need to divide them into two groups:

  1. Acquisition
  2. Optimization

Acquisitions, in this context, means exactly the same as it does for websites – 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.


Product Development in Light of these Changes

At Similarweb we aim to set a standard for measuring the digital world, and as the VP of Product, I’m always trying to stay updated with the most recent developments.

We identified this trend in the app analysis sector about a year ago. Since then we’ve been collecting massive amounts of data and have released several app analysis tools to correlate with it.  Up 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’s objectives and are now answering the needs of the entire digital world.

To fulfill the goals of app acquisition, we’ve 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 in a category and country, or the top apps receiving traffic from a specific keyword.

Our most recent release is directly connected with what we believe will be the new standard for app valuation. 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.

We’ve 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’ve opened up these features to an exclusive group of beta users and the feedback has been phenomenal. It’s helped us in refining our features and also gave us a good indication of the high level of accuracy we’ve been able to reach.

Together with our own research that’s 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’re happy to see that it paid off. There’s no doubt in my mind that more and more app users – especially the big companies that are making acquisition and advertising decisions – are going to start turning to competitive intelligence data that includes real usage stats.

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