Open Data startups

@heri

What’s a startup?

• For-profit

• Technology based

• With a unique unfair advantage

• Not limited to geographical boundaries

• Scalable, hockey stick curve growth when product-market fit

• e.g. : airbnb, kickstarter, square, songza

Challenges

• Raw data, sometimes not in a machine-readible format

• Open data often related to a country or a city. Hardly scalable

• Open data available to all, low barriers to entry

• Often related to government services

Elements of an open data startup

Clarity of purpose

• Lots of noise in open data. Large diversity of apps

• Be able to summarize what you in the back of a business card... WITH LARGE LETTERS

Painkiller

• Think about delivering something amazing: pick one thing that is a burning importance to a customer (painkiller) then deliver a compelling solution

• Can processed open data solve an existing problem?

Large markets

• Address big existing markets ready for rapid change. A market with a $1 B potential allows for error.

Customers

• Is there anyone willing to pay?

• Listing a few people who pay a premium for your unique offering is a good first sign.

• Often, open data apps can’t identify customers

Think differently

• Challenge what’s existing and take the contrarian route.

• Idea: offer for free what’s sold by existing companies for a high price

Technology is key

• Spend only on great engineering. Be very frugal on everything else

• Focus on stealth and speed of iteration

• Open data ideas: build superior intelligence and integration with other services

Outlook

• very few startups -- land grab!

• lots of interest and “sympathy capital”

• Wealth of data previously unavailable

• Being able to improve society

@heri

heri@madmedia.ca