Traction Tracker: Y Combinator Companies With Significant Traffic Growth
daniellemorrill.com
daniellemorrill.com
The author, dmor, is not familiar with the semantics of the Alexa rank. Nor are most readers. We know loosely that low rank is good. But what does going from rank 1000 to 100 really mean? How hard is that? Is it a traffic increase of 10x? 100x? What exponential base does it follow?
So this chart shows the YC companies that have the largest Alexa rank delta. Frankly, the rankings look plain wrong to me, based upon what I know of these companies.
Other commentators have suggested that, given the power law distribution, we actually care about the delta log-rank. A priori, I would agree. But then we get a new ranked list, and we still don't know if we're actually learning something or our log-metric is messed up. That's actually quite pernicious, if the results look vaguely correct at a coarse level, so we trust the results at a fine-grained level, and don't realize that the methodology and results are wrong.
We're all just blowing hot air because we don't really know what Alexa ranks mean. Only SEOs who work with Alexa ranks frequently, understand the undocumented warts, and have a gut sense of what they mean, can interpret this.
But right now, we really have no point of reference and the table leaves us without having gained any insight.
Perhaps I'm actually happy that the results are so clearly wrong and not helpful. At least that way, no one will trust them. It would be much more insidious if the results were commonly thought to be instructive, but in fact were misleading.
Some ways that you could make weaker claims but with more confidence in your results:
* Have an unordered list of companies that are growing. This was your suggestion. I don't know how interesting that is.
* Group companies into five or ten buckets, based upon Alexa ranks. (i.e. 1=low traffic bucket, 5=high traffic) Find the top three movers-and-shakers within each bucket. This makes the weaker assumption that Alexa ranks deltas are comparable within each bucket, as opposed to your original assumption that they are comparable across the entire spectrum of Alexa ranks.
There are a handful of other things you can do that are more complicated. For example, if you can correlate Alexa ranks with Compete unique visitor estimates or some other number (company's exit value). Compete estimates are also biased, but at least people have better intuition of what unique visitor numbers mean.
Crazy idea - javascript startups can put on their site to report their actual data to me?
Plus, these companies are in drastically different markets. Their key metrics are probably quite different, or (at the very least) not directly comparable to growth in value / profitability.
That's my point. This measure is semi-meaningful.
How meaningful is it? Very? Somewhat? Well, we don't know.
The way you determine how meaningful it is, is by connecting the dots with another measure. For example, we have this measure that is cheap to acquire but perhaps inaccurate (Alexa). Can we connect it with another measure that is harder to acquire but more accurate (e.g. exit value)?
if nothing else, I'd wager it's roughly correlated (on average) with market cap and/or exit price. (dmor: this would be a cool graph!)
I would wager that too. But we don't know until you run the numbers.
Grounding your measures is what separates cool hacks from data you can actually draw meaningful inferences from. I think dmor is trying to do something real here, which is why I think it useful to help her actually push the ball forward and really make something much more valuable.
I agree that exit value / market cap is a good auxiliary measure. I think I also suggested this in another comment.
Snipshot's rank rose by nearly 80,000 - that's undeniably good, but 37 of the companies on the list had a previous rank of less than 80,000...
I would suggest comparing the delta of the log of rank, this gives a more interesting (to me) metric...
For example this bumps Newsblur up from a "meh" 23 to 1! And AnyPerk from an exciting 6 down to a not so cool (unless you like catches) 22 (not picking on AnyPerk, it's just the most demoted of the original top 10)
Under this change of methodology the biggest winner is WorkFlowy from 61->24, biggest loser's are Circle (39-67); FundersClub (40-68); and Cloudant (44-72)
UPDATE: Here you go! https://docs.google.com/spreadsheet/pub?key=0ApqWF3CqjgjSdGM...
I'm just saying this is a pretty limited view of these sites, and it'd be difficult to draw useful conclusions from it. Our traffic probably isn't growing faster than more recent YC companies, even if we show up above them on the list. We're a pretty stable entity at this point. Not to say I didn't get a kick out of seeing our numbers getting better at a pretty rapid clip, even knowing more detail about what our traffic actually looks like.
Thanks again.
Instagram has yet to make a single dollar, for an extreme example, and yet nobody would argue it has gained insane amounts of traction since in the mobile photo sharing space since launch. I would use Facebook as an example, but they had small revenue generating efforts early on so it doesn't make as clean of an example.
A better metric would be to divide the companies by traffic into nontrivial traffic(Alexa Rank<10,000) and trivial traffic for the rest. It would require some more research, but it would also be very helpful to separate consumer vs B2B companies and only compare consumer companies on traffic. Many of the companies on that list(including my company MixRank) appear to be doing quite poorly in terms of traffic until one realizes that each visitor to a B2B product is worth orders of magnitude more than a visitor to a consumer product.
The problem is that the results are relative. One way would be to pick a keyword with a relatively high search volume which could be used as baseline. Another issue that I can think of is that companies named after common english words i.e. Pebble will have their results artificially inflated. This process might be hard or tricky to automate.
Growth in followers/likes/tweets/+1 counts could be used as a measure of traction.
Quite interesting that Dropbox jumped an entire spot in a month for a non-content based site.
#1 on this list went from 2xx,xxx to 2xx,xxx - that could seriously be just noise in the Alexa ranking methodology. That sites traffic could have even gone down slightly and still produced that result.
If you combine Alexa data w/ data from Quantcast, Statcounter and others, it would probably be valuable. But even Alexa themselves would tell you their dataset has massive holes in it when trying to use it as the foundation for this kind of thing.
From my personal experience, the numbers from Alexa are complete gibberish.