Data-Driven Decisions

with Mike Greenfield

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How to Grow

How to make your numbers bigger


Instructor
Mike Greenfield

Founder, Data Geek, Entrepreneur

Lessons Learned

It is not enough to build a great product. You have to figure out how to grow.

You need a scrappy mindset when it comes to user growth. Hack your way to great numbers.

Look at what is happening on your site already. Where is the activity & where do people fall off?

Transcript

Lesson: Data-Driven Decisions with Mike Greenfield

Step #10 How to Grow: How to make your numbers bigger

A decade ago nobody was talking about growth. Reid Hoffman founded LinkedIn and was investing in consumer startups. I think he was one of the firsts to ask the question of any startup, including his own, “How are you going to grow?” Because I think there was a mentality in Silicon Valley companies for a long time that, “We’re just going to build a great product and it’s going to grow on its own.”

My sense is that that is actually part of the reason that Google founders have not done as well, at least per capita, as PayPal founders. PayPal had a very scrappy mentality of, “We need to figure out how to grow. We need to hack our way to growth.” Google had an amazing product and, seemingly at least, it grew more or less on its own because people just loved it and they would share it by word of mouth, whereas PayPal had to engineer that growth.

LinkedIn did very much the same thing, figured how was it that we can grow, what is that is going to lead people to invite their friends and for their friends to sign up. In LinkedIn’s case, the messaging was more about the person enjoining the person than it was about signing up for this professional network then you probably had never heard of in 2005. I think it was Reid’s mindset of how do you grow and I formalized some of math and some of the logic around, “How can we do A/B testings?” and, “How can we grow our audience more quickly?”

I worked on a whole bunch of things but a lot of my time I spent looking at user behavior and where are people doing different things on LinkedIn and where people are dropping off and what’s effective and what’s not. LinkedIn actually was not as A/B testing-focused as I would have liked. But we had a lot of interesting data and while I was there — I left in early 2007 when it was still a fairly small company — I think we were starting to pull out some pretty interesting nuggets from LinkedIn and that was the start of people you may know, which is driving a lot of re-engagement with LinkedIn.

Then over time, LinkedIn has does more and more with the data than it has and has seen its growth escalate pretty rapidly.

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