Weekly Traction Tracker: Who Is Hottest Among 1,100 Startups?

This post is part of a series on data-driven blogging which includes the Startup Index and Investor Index. I have quantified companies from 500 Startups, Y Combinator, TechStars, Andreessen Horowitz and First Round Capital and would love to hear your feedback on what I should measure next.

I hate subjective top X lists as much as the next guy, and since I’m tracking ~1,100 companies now I thought it would be fun to share the fastest growing folks of the past week. These are this week’s movers and shakers.

*calculated as the delta between the log of the original Alexa rank and log of the new rank. Updated to remove TutorialTab, founder has confirmed the company is no longer operational.

*the @Authy Twitter account followersappear to be primarily spam accounts, they went from 239 followers to 7736 followers in the past week – they say they did not buy followers so they might have been bot bombed.

And my personal favorite, because getting LinkedIn followers is pretty difficult:

And last but not least:

Other Notable Movements in the Data

On LinkedIn companies self-report which bucket company size they are in, and usually this doesn’t move much. However, Task Rabbit and Bizible both bumped up from the 2-10 employees to 11-50 employees size.

  • Epic effort, Danielle. Thank you.

  • Thanks for putting it together! Cool to see us [Sverve] on inbound links list. I believe just the log based difference in Alexa ranking doesn’t do justice to startups that are sitting on decent rankings and still improving it. It took us more than double the increase in traffic to jump from 85k->45K [worldwide] than from 150K->90K. Maybe a threshold [150K and less] and a sliding scale based on tiers [<10K, 10K-50K, 50K-100K, 100K-150k] might work better.

    • Its currently on a log base 10 scale to account for that

      • Log base smoothens out change in rankings but doesn’t take into account much higher increase in traffic required to improve rankings in same proportion for better ranking sites. For example, we had to double our traffic [on a smaller base] to jump from 150K ->70K but had to more than quadruple our traffic [on higher base] to go from 70K->40K. Log base scale will show more improvement in the first case while we did much better in the second case. I think in simple log based scale startups with better ranking might miss out even though they are growing their traffic much faster than others on the list.

        • Thanks for the feedback, I’ll look at how I can better represent this

  • bob

    Cool data, would be awesome if you open sourced your scripts for scraping and analyzing the data!

  • That would be cool to see their business model search progress) Like on http://absly.com

  • red raspberry

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    kind of clever work and reporting! Keep up the great works guys I’ve added you guys to blogroll.

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  • I hope that one day I’ll see TestDome on the list … 🙂

  • Alex

    Thats very well put together! 1 year after its intereesting to see where all those companies are doing now!

    Maybe a part 2 would be interesting!? 😀 Great article!