Want More Funding? Machine Learning!

Crystal ball, what's on the investors' mind?

Parker Barrile posted on What VCs Talk About After Your Pitch yesterday and as suggested in the intriguing subject line, he has let all the entrepreneurs in on one of the most prized secrets in the startup world. 

All businesses chase after product market fit and in the same sense there's no intel more valuable than what investors are in fact looking for when evaluating an investment opportunity. In Parker's article, he pointed out two things to focus on not only in business plans but also in pitch decks:

1. The problem the business is solving
2. Building the moat

And Buffett agrees.

How to build a moat with machine learning

Machine learning can do the heavy lifting for you and turn your big data into a moat around your business castle. 

With machine learning, Netflix has come a long way from a DVD rental business to world's leading internet television network and from a content aggregator to an original content producer. Quite a moonshot accomplishment if you ask me! Youtube is catching up. With all the top influencers and the attached fan base in their pocket, they even have more interesting flavors added into the big data cookbook.

Machine learning can also turn the most bland business ideas into brilliant products that consumers can't live without. I've personally fallen in love with gmail's priority inbox feature. It takes into consideration several dimensions of data features:

1. Social features to examine the relationship between the sender and receiver based on open rate
2. Content & Thread feature to determine the recency and relevancy of email content to what receiver has acted on in the past
3. Label feature indicates preference explicitly expressed by the user

Last but not least, machine learning isn't all science and no art. Gmail team skillfully balances user need on minimizing the false negative rate - users will likely have vastly different levels of emotional response to an urgent email ending up in the junk box vs. a spam message occasionally slips through the priority inbox.

So, ready to adopt machine learning yet, my entrepreneur friends? Or shall I rephrase, ready for a big fat paycheck from your next investor? When you're face to face with investors, discover how to effectively engage an audience and work a room.

No Machine learning expert? No problem. Learn step by step on how to work around it.

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