April 30, 2009
Mashable panel at 92YTribeca
posted by philip in Snooth
Mark and I spoke at a panel on “Lessons from the Local Startup Community” held by Mashable at the Tribeca 92Y.
It was great to speak alongside some great companies: Behance, SavvyAuntie, Aviary and of course Mashable. Our slides (just 3 of them, as we were trying to be short and punchy) can be seen here. Our key points were:
- A startup is like a race car – not only is it fast, its likely to break after 500 miles, and to get anywhere on your limited resources (time, money, manpower) you need to focus like a laser.
- When you are a new startup, its hard for an outsider to tell if you have any prospects, as a result getting the first deal is key. To close that deal, you do what it takes: beg, borrow, negotiate, compromise.
- With software most of what you’ll need already exists, and its generally free (open source). Leverage what you can before you start building things that you could have picked up from elsewhere.
- Get involved in your community, give back and help others – be it geographically local (NYC and San Francisco for us), or thematically similar (wine and open source for us). Not only is it beneficial to the company, its the right thing to do.
No audio unfortunately, so let me know if anything’s unclear in the slides.
The Snooth presentation looks good, Philip (from the slides, anyway ;-) ). Who else had useful things to say there?
It was a really good group actually. In particular, Scott from Behance is a very smart guy – I really like their company, its a beautiful site and already has well over 1 million users per month.
Good to hear some insights into how you guys started up. Your use of open source software is inspiring. Can you say more about what systems you’ve used and how you changed them to fit with what you need?
Nick – one good example of this is the way we adapted the open source search algorithms. Search (google for example) is optimized to search text documents, and the higher the keyword density in a document the better the presumed match.
However the database representations we have for wines do not become better matches because they repeat the keywords more frequently. Once a wine is 100% Cabernet is can’t any more cabernet-y.
So the search algorithms were modified very heavily to what becomes parametric search. When a user types “Cab” we assume they are looking for the varietal (or at least one of the Cab varietals), and not for a Taxi Cab. Once we know that its easy to simply search for a single presence of the Cab in the varietal field.
This parametric search allows our site to be faster and return more accurate results than using a search algorithm out of the box.