This is an interesting departure from the “old” web 2.0 model, which has been to build a basic version of the service, raise a small amount of venture capital (less than $5 million) , build the user base, and then raise a larger round once you have traction in the marketplace. I am personally a fan of this model as it ties fundraising to market traction. The other benefit is that you can only go so far (in terms of development) before you have to validate yourself with the market.
Larger rounds prior to launch are really interesting. A company can build a lot more technology before bringing the product to market. The advantage is that this private time can be a great way to make progress on technology without the glare of user feedback. It can be a great opportunity to deliver a more fleshed-out product that ends up being more defensible. The downside, however, is that companies who build products in “stealth mode” for long periods of time, you can end up developing features, interfaces, and functionality that ends up missing the mark. Worse, not only have you absorbed the opportunity cost associated with building features your users don’t want, there is work that needs to be undone in a very public way.

1. The money is available, so entrepreneurs are taking it. There is certainly venture capital money in the market today looking to fund ambitious projects. That money is likely looking for a home, so the venture community (or particular venture capitalists) might be looking to fund entrepreneurs who are looking to take larger rounds. For shorthand purposes, we’ll call this the “push” model.

2. These are ambitious engineering projects that will take a lot of hard work and expenditure before they’re ready to be shared with consumers. The other alternative is that these projects are really hard engineering projects that require substantial amounts of venture capital investment and product development before you can show a decent alpha/beta product to users on the open Internet. This is certainly possible. For shorthand purposes, I’ll call this the “pull” model.

I really don’t know which of these two is actually at work here. It could be a combination of both. Regardless of which model is at work, I will be interested to see how these extended betas turn out. I am generally not a fan of keeping things secret for secrecy sake — the benefit of getting feedback early and often before you’ve baked too much code into the service can often outweigh the benefits of keeping things secret.

Feel free to share your thoughts in the comments.
Update – I wanted to point to a post that Jeremy Liew at Lightspeed did on the pros and cons of being in stealth mode. Click here if you want to read more — it’s good stuff and worth a read.

I have been doing a lot of thinking about vertical search engines lately, especially because I find them to be very useful in getting information in categories where general search doesn’t always give me the right answer right away. As useful as vertical search engines can be, I often wonder whether any of these vertical search engines are garnering enough traffic to be viable standalone properties.

Why does this question matter? Well, from my point of view it looks like vertical search sites who can’t generate enough organic traffic of their own through SEO, other techniques that will drive higher organic search results in Google or Yahoo, or having a great destination site that brings users directly to the front door will be destined to be in the “powered by” category offering white label syndicated solutions to partners. I don’t want to denegrate the “powered by” model — it has made a ton of money for Google and its partners and is an effective way to distribute great technology. However, given the amount of venture capital invested in this sector, my hunch is that investors are looking for ways to build meaningful, standalone companies who can be destinations of their own given that very few vertical search engines have been acquired in the web 2.0 world (I am excluding all of the web 1.0 comparison shopping and job sites that got acquired).

In order to answer this question of whether vertical search sites are stalling out in their eventual aim to become destination sites of their own, I took a look at some Alexa data on some of the most prominent vertical search sites. Yes, I realize that Alexa data is imperfect, skewed, etc. That being said, it’s publicly available and easy to access. I took a look at the Alexa ranking for as many vertical search sites as I could think of and took note of their current Alexa ranking. The next step was to then bucket them into categories (top 500, top 1000, and top 10000). The results of this mini-exercise can be seen below.

If you don’t want to scroll down, here’s the punchline — only two “web 2.0″ vertical search properties cracked the Alexa Top 1,000. Yes 1,000 is an arbitrary number to choose. Yes Alexa data is iffy. But with all of those things in mind, we are only talking about 2 companies (of the 12 I found in the top 1,000) who made that cutoff.

Looking at this data tells me two really important things. First, it is really hard to build a vertical search engine that gets significant amounts of traffic. Looking at the clustering of sites that managed to crack the top 10,000 shows a serious weighting toward sites where the underlying topic of interest (travel, product comparison, jobs and recruiting) is a market where significant amounts of money change hands.

The other major thing I take away from this data is that more and more vertical search engines ought to be looking to “power” the search of other folks unless they have some really clever ways to generate organic traffic — it’s really hard to become a highly ranked vertical search property.

Feel free to leave me a comment or point me toward any search property I might have missed.

Raw Data Appendix Below (Global Alexa Rank as of March 19, 2007)

In the Alexa Top 500

IMDB (#35)
LinkedIn (#178)
Technorati (#215)
Monster.com (#327)
Careerbuilder.com (#375)
Shopping.com (#440)
Nextag (#471)
TripAdvisor (#494)

In the Alexa Top 1,000

Expedia (#400)
Travelocity (#574)
Orbitz (#597)
Citysearch (#734)

In the Alexa Top 10,000

Shopzilla (#1,403)
Zillow (#1,542)
Kayak.com (#1,561)
Yelp (#1,738)
ZoomInfo (#2,364)
Indeed.com (#2,386)
Trulia.com (#4,995)
Oodle (#8,056)
Blinkx (#8,250)
Become.com (#8,335)
SimplyHired (#9,054)