open data startups. heri rakotomalala, @heri

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Open data startups @heri

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Slides presented at Open Data Exchange 2013, April 6 2013, Montreal, Canada. ODX13.com. Sponsored by Trudat.co

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Page 1: Open Data Startups. Heri Rakotomalala, @heri

Open data startups

@heri

Page 2: Open Data Startups. Heri Rakotomalala, @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

Page 3: Open Data Startups. Heri Rakotomalala, @heri

Challenges•Raw data, sometimes not in a

machine-readible format

•Open data often related to a country. Hardly scalable

•Open data available to all, low barriers to entry

•Often related to government services

Page 4: Open Data Startups. Heri Rakotomalala, @heri

Elements of an open data startup

Page 5: Open Data Startups. Heri Rakotomalala, @heri

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

Page 6: Open Data Startups. Heri Rakotomalala, @heri

Painkiller

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

•Does any published data solve an existing problem?

Page 7: Open Data Startups. Heri Rakotomalala, @heri

Large markets

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

Page 8: Open Data Startups. Heri Rakotomalala, @heri

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

Page 9: Open Data Startups. Heri Rakotomalala, @heri

Think differently

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

•Idea: offer for free what’s offer by big companies for a high cost

Page 10: Open Data Startups. Heri Rakotomalala, @heri

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

Page 11: Open Data Startups. Heri Rakotomalala, @heri

Business models

Page 12: Open Data Startups. Heri Rakotomalala, @heri

Open Source parallel

•Open Source: first a movement for programmers, then an asset for startups

•Deliver open data, charge monthly support (saas)

•Sell access to a superior version, designed for professional environments (freemium)

Page 13: Open Data Startups. Heri Rakotomalala, @heri

Other business models

•Advertising or donation. Necessity to build enough traffic

•Affiliate. e.g real estate data <=> real estate companies

•Combination?

Page 14: Open Data Startups. Heri Rakotomalala, @heri

Outlook

•very few startups -- land grab!

•lots of interest and “sympathy capital”

•Wealth of data previously unavailable

•Being able to improve society

Page 15: Open Data Startups. Heri Rakotomalala, @heri

Questions?

•@heri

[email protected]