From the webpage:
About Everpix
Everpix was started in 2011 with the goal of solving the Photo Mess, an increasingly real pain point in people’s life photo collections, through ambitious engineering and user experience. Our startup was angel and VC funded with $2.3M raised over its lifetime.
After 2 years of research and product development, and although having a very enthousiastic user base of early adopters combined with strong PR momentum, we didn’t succeed in raising our Series A in the highly competitive VC funding market. Unable to continue operating our business, we had to announce our upcoming shutdown on November 5th, 2013.
High-Level Metrics
At the time of its shutdown announcement, the Everpix platform had 50,000 signed up users (including 7,000 subscribers) with 400 millions photos imported, while generating subscription sales of $40,000 / month during the last 3 months (i.e. enough money to cover variable costs, but not the fixed costs of the business).
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Complete Dataset
Building a startup is about taking on a challenge and working countless hours on solving it. Most startups do not make it but rarely do they reveal the story behind, leaving their users often frustrated. Because we wanted the Everpix community to understand some of the dynamics in the startup world and why we had to come to such a painful ending, we worked closely with a reporter from The Verge who chronicled our last couple weeks. The resulting article generated extensive coverage and also some healthy discussions around some of our high-level metrics and financials. There was a lot more internal data we wanted to share but it wasn’t the right time or place.
With the Everpix shutdown behind us, we had the chance to put together a significant dataset covering our business from fundraising to metrics. We hope this rare and uncensored inside look at the internals of a startup will benefit the startup community.
Here are some example of common startup questions this dataset helps answering:
- What are investment terms for consecutive convertible notes and an equity seed round? What does the end cap table look like? (see here)
- How does a Silicon Valley startup spend its raised money during 2 years? (see here)
- What does a VC pitch deck look like? (see here)
- What kinds of reasons do VCs give when they pass? (see here)
- What are the open rate and click rate of transactional and marketing emails? (see here)
- What web traffic do various news websites generate? (see here and here)
- What are the conversion rate from product landing page to sign up for new visitors? (see here)
- How fast do people purchase a subscription after signing up to a freemium service? (see here and here)
- Which countries have higher suscription rates? (see here and here)
The dataset is organized as follow:
Every IT startup but especially data oriented startups should work with this data set before launch.
I thought the comments from VCs were particularly interesting.
I would summarize those comments as:
- There is a problem.
- You have a great idea to solve the problem.
- Will consumers pay you to solve the problem?
What evidence do you have on #3?
Bearing in mind that should, ought to, value is obvious, etc., are wishes, not evidence.
I first saw this in a tweet by Emil Eifrem.