Making Money From News: The Snip Business Model

Rani Horev
Snip
Published in
2 min readSep 19, 2017

Yesterday we described how Snip is changing the media industry with short and concise news stories, becoming the best way to stay in the know. But having tens of thousands of happy users is not enough, the underlying business has to actually be profitable.

In this post we’ll explain how Snip is going to make money from news while maintaining a great user experience and securing user privacy.

Ryan Jorgensen — Jorgo/ Shutterstock.com

The first and main pillar of our business model is advertising. Ads allow free access to content for everyone, a value we strongly believe in. The larger the platform the more effective ads become, making them a good fit for the large scale (hundreds of millions of users) Snip is aiming for. For those of you who are ideologically against ads or simply bothered by them, we’re offering a paid ad-free version.

The second pillar of our business model are subscription services. Nothing signifies value better than people paying you for your product, which is why we’re so proud of reaching 1,400 paying subscribers in our Israeli service. On the Snip platform we’re offering our users two main subscription services:

  1. A personalized Snip podcast which includes the best stories, read aloud by a professional narrator. This product will be live and available even before the token sale. As the platform evolves the podcast will become more and more personalized to fit user’s preferences.
  2. Professional content — a summary of the current updates in a specific field, written by a verified expert. For example, summary of the latest research on DNA editing.

In the next post we’ll detail how we plan to stay transparent with the Snip community after the crowdsale and as we’re growing as a platform.

Join the conversation on Telegram and reserve your place in the upcoming crowdsale (Sep 29!). We still have a lot of great snippets coming…

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Rani Horev
Snip
Editor for

Learn something new every day. Currently Deep Learning :)