Insights from BV4's startup database - Market
In this series of articles, we will look at different data-driven insights that BV4 gathered from startups. In this article, we will have a look at important qualitative aspects of the market and how they correlate with each other.
Let's start with a recap of the BV4 proprietary model:
BV4 built a qualitative scorecard model which focuses specifically on such qualitative aspects (e.g., team complementarity, previous founding experience, development stage, scalability potential or the go-to-market strategy of a startup). Thus far, BV4 has scouted over 13'000 startups of which more than 3'000 were assessed. Over 200 parameters have been considered to perform the assessments to obtain the scores in four distinct dimensions: product, business model, team, and market. BV4 assesses several qualitative parameters within each dimension. The following graph shows some parameters of the BV4 model:
The result is a score which represents the risk profile of the startup at its current stage. The colored rating scale on the right side shows that a high score indicates that the startup is an attractive case for the average investor. Startups should achieve a higher score over time as their products get closer to the market and they gain more traction, clarity on the business model as well as important target clients.
The analysis of the data on the market can be found below:
Startups in our database show two important relationships when it comes to the penetrated markets:
· Both startups and investors are attracted to fast-growing markets, raising prices in those markets. These market characteristics attract investors which is why we can observe a significant positive relationship between the market growth and the respective multiples within these industries.
· Large markets force startups to create strong USPs to disrupt the industries and capture market share. Our data shows that such attractive markets come with the price of increased competition which forces the startups to develop a clear USP in order to not only set foot, but also to gain a significant market share in the long-run.
It is important to understand that the data sample consists of 496 startups of which the majority operate in the field of Med/HealthTech, FinTech, EnterpriseTech and DeepTech. The startups were mainly operating in the Seed stage. While the data sample represents only a fraction of the overall ecosystem, it already gives insights into some points that founders should consider when building their ventures.