VCs are looking for financial returns. Plenty of data is available for that, generated from tools like Crunchbase, Pitchbook, and other CB Insights. Investment professionals and corporate development teams in large industrial companies use those platforms. But what do they need when searching for relevant startups? They need insights about startups’ actual activity, technology, products, features, models, and real-life concerns. In comparison with all this, financials come second.
However, in startup databases, there is generally little non-financial information. Besides, when you focus on figures and financials, the odds of getting outdated data are much higher: startups evolve and die quickly, with each life step likely to change the data. Staying up to date is very difficult.
Currently, the world counts 472 million entrepreneurs. A new business opens every three seconds. For companies, that makes it very difficult, tedious, and time-consuming to spot the right startups to work with. In big corporations, extended teams can be dedicated to spotting and analysing startup files. Meanwhile, in midsized companies, a single individual does the job who has this task on top of their other duties. It’s either very expensive or it’s inefficient. But either way, it’s not optimal.
When it’s not done on a self-service or opportunistic basis, companies use the following three means for their startup scouting activities: