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Evaluating Startups: What Metrics Matter the Most?

 
In the previous blog, we have discusses what are the “5 most important questions to ask your organization and yourself before going to bed with startups? Now that you are ready to dive into the startup world, let’s review the essential metrics for startup evaluation to determine how suitable the case is for your needs and how likely it is to survive long-term.

It is important to understand that the company evaluation for early-stage startups and more advanced growth companies (aka scale-ups) can and will differ. The younger (the more early-stage) the company is, the more essential it is to remain focused on finding the first paying customers as soon as possible to find and prove the product-market-fit. Wherein growth companies fight for the firm position on a market space comparing to its competitors, set a steady revenue stream, scale its operations, grow the team and attract new investment/partnership opportunities. Hence, identifying what stage company your corporate seeks for will then determine what metrics matter the most in startup evaluation. Since Catapult’s services rely heavily on data, only more advanced growth companies are to be seen in the data-pool, and consequently to be validated for startup-corporate collaboration. Metrics presented below correspond to the needs of corporates to find and collaborate with more advanced cases.

What metrics matter the most when evaluating a startup from corporate perspective?
 

FINANCE DATA

  • Investments & Investors
  • Turnover
  • Valuation estimations
  • Estimates of the runway with present funding

 
 

TRACK DATA

  • Descriptions of the product/service
  • Growth speed
  • Growth speed of the company compared to competitors
  • Presence in different medias weekly compared to competitors

 
 

TEAM DATA

  • Founders & their success with previous ventures
  • Team members & their background
  • Employees growth
  • Board members & Advisers
 
 
 

In the next blog posts, we’re going to dive deeper into each data-driven metric and understand how to comprehend data to make conclusions on startup evaluation.

 

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