Data has long been lauded as a competitive moat for companies, and that narrative’s been further hyped with the recent wave of AI startups. Network effects have been similarly promoted as a defensible force in building software businesses. So of course, we constantly hear about the combination of the two: “data network effects” (heck, we’ve talked about them at length ourselves).
But for enterprise startups — which is where we focus — we now wonder if there’s practical evidence of data network effects at all. Moreover, we suspect that even the more straightforward data scale effect has limited value as a defensive strategy for many companies. This isn’t just an academic question: It has important implications for where founders invest their time and resources. If you’re a startup that assumes the data you’re collecting equals a durable moat, then you might underinvest in the other areas that actually do increase the defensibility of your business long term (verticalization, go-to-market dominance, post-sales account control, the winning brand, etc).
Data is fundamental to many software companies’ product strategies, and there are ways it can contribute to defensibility — but don’t rely on it as a magic wand. Most of the narrative around data network effects is really around data scale effects, and those sometimes have the opposite effect if not planned correctly. But don’t even assume you have a data network effect (you likely don’t), or that the data scale effect will last in perpetuity (it almost certainly won’t).
Instead, we encourage startups to think more holistically about defensibility. Greater long-term defensibility is more likely to come from packaging differentiated technology; understanding the domain and reflecting that in your product as you verticalize across industries; dominating the go-to-market race; and winning the talent war to build a world-class team. These efforts will pay off in defending and winning in the markets far more than data alone.