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So, apparently silicon valley is buzzing about vertical search. I have heard about quite a few start ups that do vertical search in some capacity or the other. I am listing a few here. Most of them seem to be focused on jobs. Indeed.com , simplyhired.com, Workzoo, NimbleCat, Fatlens are a few of the companies that are out of the “stealth mode”. There are couple of other companies that are in the stealth mode but tackling similar problems.

Let me tell you, i have had the opportunity to think about this problem in a specific business context for over an year. Ofcourse, thinking does not mean “solving” and i don’t claim to have solutions for any of the challenging problems involved with vertical search.

How do people find what they want on the internet?
Since the begining of internet, the one thing everyone recognized is how vast internet is, how quickly content was/is coming on to it, and how useful/powerful it can be. However, finding what you want is also very hard on the internet and it’s the quintessential problem that is being solved since 1995.

To provide a service that is useful to users, one has to discover all (meaninful portion of) the content on internet, store/index relevant information, answer queries with best information, build right supportive applications around it and all this should be done in a way that you answer the user in a split second.

At that time, crawl/search based solutions were yielding poor results for several reasons. A lot of them are because traditional search algorithms which were applied trusted content (produced by you or someone trusted) are not really useful when you apply them to un-trusted content (produced by various people some with commercial intent). Human review based solutions yielded better results at that time.
The general problem was how do i help users find “anything” on the internet. However, people realized pretty quickly that a lot of specific industries are moving online and they all have different needs. So a slew of applications (vertical) began to come online - shopping, jobs, classifieds, auctions, health, etc.

That generation of applications, let’s say web 1.0 apps - even though i don’t like web 2.0/1.0 thingy - generally solved problems in the same model as the overall internet search.
These vertical apps typically, collect information through feeds or submissions, build search applications focused on that business/vertical, build supportive applications around those. The land grab was on. The best business has the most submissions/feeds and drove most activity through matching finders with offerers.
The key thing i am getting at is - Web 1.0 vertical apps modelled their products/businesses around the web 1.0 core apps.

This web 1.0 model created silos/islands of applications each of them competing with the other for user’s attention.

Enter GOOGLE.
Google approached core web problem, in a search centric way and created algorithms that infer trust (and hence relevance) from web interlinks. They improved relevance of web results, quality of crawling (discovery) and come up with solid technology to serve this information blazingly fast. With google, users could search through more web pages than ever before and get relavant results.

This and quite a few other technological evolutions influence the web world. For the past few years user habits have been changing. Users are lot more search box friendly and search activity is on the rise. Businesses are more accustomed to search based advertising and the overall search application model is thriving. Big players woke to these trends somewhat early and now we have the big 3 competing in the search space.

Why Vertical Search
Knowing what we know now, if we looked at each of these vertical businesses we might solve the same problem differently. The siloed model of applications means that user’s do not have one single place to find anything and everything. People have to look at few (sometimes 10, sometimes 100s) of sites to find ALL the inventory. Websearch as it is right now, is meant to sort out documents and figure out which is the most relevant web document that matches your query. This is a very generic solution. It’s good for a lot of things, but when it comes to specific tasks i have at hand, it has it’s limitations.

For example, I am looking for honda civic 1999-2003 with in 50 miles of where i am. Well, Since car is a transient product, a web page that is listing this car for sale is in existence for a brief period of time (few weeks) and then it goes away. Using google’s PageRank or other similar methods is not ideal to identify most relavant cars for me. This example can be repeated for tons of other tasks, flight tickets, job search, digital cameras :), tickets search, etc.

So, Tom Evslin continues to think that vertical search is humbug. I remain convinced otherwise.

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