Li Jin and D’Arcy Coolican, writing for Andreessen Horowitz:
Network effects are one of the most important dynamics in software and marketplace businesses. But they’re often spoken of in a binary way: either you have them, or you don’t. In practice, most companies’ network effects are much more complex, falling along a spectrum of different types and strengths. They’re also dynamic and evolve as product, users, and competition changes.
They go on to outline sixteen ways in which network effects can be measured, grouped into five categories:
Acquisition
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Organic vs. paid users
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Sources of traffic
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Time series of paid customer acquisition cost
Competitors
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Prevalence of multi-tenanting
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Switching or multi-homing costs
Engagement
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User retention cohorts
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Core action retention cohorts
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Dollar retention & paid user retention cohorts
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Retention by location/geography
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Power user curves
Marketplace metrics
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Match rate (aka utilization rate, success rate, etc.)
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Market depth
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Time to find a match (or inventory turnover, or days to turn)
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Concentration or fragmentation of supply and demand
Economics-related
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Pricing power
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Unit economics
I love it when somebody adds granularity and nuance to a concept I previously understood only in binary terms. This post does that for network-centric businesses.