AppRecs Alternatives and Reviews

AppRecs sorts through reviews in the App Store and automatically helps you filter out inauthentic results.
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3 Alternatives to AppRecs

  • Product Hunt
    Description of Product Hunt (
  • Zestia
    Description of Zestia (
  • iOSEmus
    Description of iOSEmus (

Pros & Cons of AppRecs


  • Weighs review averages according to numerous metrics
  • Stripped down interface makes it easy to find what you need
  • Diverse filtering options provide you with customized results


  • Bare bones interface isn't particularly pretty
  • Lack of transparency in AppRecs' filtering algorithm
  • Doesn't analyze apps not available in the App Store or Play Store

Features of AppRecs

  • Compatible with both the Apple and Google app markets
  • Functionality to create your own customized app lists
  • Robust filtering options integrated with the search bar

AppRecs Reviews

  • Written by User 1 on 2018-01-17 04:38:41.
    The democratic nature of the internet means that we have an unlimited number of resources at our fingertips, but this also makes it difficult to separate the noise from the sound. The app market can be especially problematic, as paid reviewers and bots flood the marketplace with fake reviews that can throw the whole system into disarray. AppRecs draws from a variety of metrics to automatically review these reviews and filter the results to your level of specification.

    AppRecs is a web app that operates directly through the browser of your computer or handheld device. The interface is intuitive and easy to use. A price drop section lets you see apps that have recently dropped in price, and creating an account with AppRecs allows you to define specific lists that allow you to track the quality of apps in your favored categories. In addition to a favorites list and a wishlist, there are a wide variety of lists created and curated by the AppRecs community. Rather than offering you the star ratings inherent to the App Store, AppRecs automatically adjusts the ratings of the apps in their portal to account for their intelligent analytical algorithms.

    The standard filter used by AppRecs ranks reviews according to seven levels and then adjusts their star levels accordingly. These range in quality from "Organic" reviews, which are long, specific, and seemingly drawn from personal experience, to paid apps, which are usually requisitioned by the app's creator to help boost the prominence of their apps in the marketplace. Additional levels include network-sourced apps which are sourced from friends and family of developers to cherry-picked reviews which are sourced from positive comments reviewers have received directly from their users and routed to the review site.

    While AppRecs hasn't publicly disclosed the algorithm they use to filter their results, they've revealed the basic qualities they use to judge the authenticity of reviews. To achieve the best results, they evaluate the quality of both the reviewer and the review itself. The volume, quality, length, and general quality of the user's reviews are used to create a scaled weight that effects the review's overall placement. They also compare the content of the user's reviews with those of other reviewers, to determine if they are making use of duplicated content. In terms of the quality of the review itself, AppRecs takes into account the relevance of the included content, the star rating offered, and the length of the article. Altogether, these factors are weighed together to produce results that AppRecs claims is more accurate than that used by the App Store.

    Users don't need to rely on AppRecs' default filters. Searches can be adjusted to match their needs with a variety of filtering options. These manual filters allow you to further narrow down your search to take into account only the most reliable reviews and to sort out results according to other factors like price and popularity.

AppRecs Youtube Videos

Unit 9 Test Review For HS Music Apprec

Disclaimer: This video was not made by us, but we found it interesting enough to embed it here.

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