🌱 Nourish

We've always been very open about how OneSub works, how we're planning to operate and how we're getting on...

... but there were a few stats that were just a bit too buried to make public (for weird, nerdy, developer-priority reasons).

From today two really pretty vital stats are now available on our public stats dashboard:

• MRR (Monthly Recurring Revenue)
• MAU (Monthly Active Users)

Note; there's a MRR figure above - but that's only folks paying by credit/debit card. It doesn't include IAPs (In-App Purchases)

Early morning (EST) we were featured on the BetaList homepage and in their daily newsletter.

If you're interested in the impact this had, our stats are publicly available here on @markosaric & @ukutaht's awesome Plausible platform:

• BetaList Sourced Traffic (March 2021)
• Spoiler Alert...
• 70 visitors in 24h
• ~12.5% conversion to "Sign Up"

This is a massive step forward for us... technically version 3.3, internally, this is the first version we would consider to be our Minimum Viable Product:

• A localised, prioritised, personalised news feed.
• AI sub-edited story summaries of top stories.
• Personal "fitness" metrics to manage your news diet.
• Clear signposting for our "💚 Pro" (paid) tier.

We actually launched quietly on Friday night and I can't believe we've been rewarded with a couple of 💚 Pro sign-ups already. We're pretty blown away.

On 15 January 2021 we launched a new public beta to our ~40 or so beta channel users across web, iOS and Android.

The new beta puts two major features into play:

• Automated SubEditing - a new reader experience where we're experimentally subediting directly within the app, with copy personalised to every reader on the fly. Each reader gets an article composed specifically for them, based on their previous reading history, which gives them an overview of the stories they need to catch up on today.

• News Diet Dial - we've also added a 'dial' to give readers a quick understanding of their news diet each day. Three concentric rings indicate how long you've spent reading the news, how many sources you've seen and how many topics & countries you've read about. By completing all three rings a reader can be confident that they've read a healthy, balanced news diet today.

As we (all, like everyone in the world) celebrated the end of 2020 OneSub crept past the 4,000 sign-ups mark. 🙌

OneSub has always enjoyed a regular inflow of new sign-ups and we've kept to an average of about 100 a month since we started.

Some months we have a little bit of press (like this little unsolicited article in The Guardian and that causes a spike.

Most of the sign-ups come from the little social chatter we have going on. For what it's worth - most of the sign-ups are from LinkedIn... or at least LinkedIn's conversion rate seems much higher.

Although our "💚 Pro" accounts at this point are voluntary and in July 2020 didn't really offer much in the way of features we were super-excited to welcome our first paying customer on 1 July 2020.

We also launched into the Apple AppStore with 💚 Pro accounts available under an In-App Purchase.

By the spring of 2020, OneSub had become a working "alpha" prototype, providing a rolling news aggregation service and access to hundreds of different sources simultaneously.

Building in public we have been iterating the underlying modelling and APIs, learning fast and working towards automated subediting of the stories to help improve readers' experience of consuming news.

By the summer of 2019 we had a small proof of concept up and running that showed you what we though was the most important story of the day... and gave you three alternative perspectives to go off and read.

With this basic POC in place we managed to connect with ~200 other people in the UK who saw the value in the idea, raising an average £500 per person to hit a £100k pre-seed raise.

I guess that puts a £1m valuation on OneSub at this point! 💛

In January 2019 we started work on the very first proof of concept.

To begin with the project was a "20% time" for a few of the team and began as a way to prove we could collect and collate stories from lots of sources and begin to model and understand the way each article was being written.