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  • Benchmarking Your (HealthTech) Startup? A Framework Around Metrics
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Benchmarking Your (HealthTech) Startup? A Framework Around Metrics

Lisa H. Shelton July 14, 2022 5 minutes read

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You hear these terms all the time. Countless articles (here, here, here) enumerate the various metrics that can quantify the growth of your business. This article attempts to go one step further and colorize these fundamentals within the context of health-tech. Caveat: the below reflects our opinions and the data we see; feel free to take it with a grain of salt! 

Table of Contents

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  • 1) Metrics for Direct-to-Consumer (i.e., patient-facing) Models:
  • 2) Metrics for B2B (i.e., selling to Employers, Providers, or Payers) Models:
  • 3) Benchmarks Regarding Start-up Valuation:
  • About the Author
    • Lisa H. Shelton

1) Metrics for Direct-to-Consumer (i.e., patient-facing) Models:

Take-away: at earlier stages (in the absence of LTV/CAC), focus on engagement. The stickier your product, the better. As you accrue data, focus on optimizing your LTV:CAC ratio. 

  • Actions per session // Average session length: these reflect engagement; more clicks with longer session duration (on the order of minutes rather than seconds) is favorable
  • Daily / Monthly Active Users (DAU / MAU): a measure of engagement; the greater the frequency of engagement, the better: DAU:MAU ideally will be ~1:3 (amazing but we rarely see this), although ~1:5 is more typical amongst the companies we look at
  • Lifetime Value (LTV) to Customer Acquisition Cost (CAC) ratio: a widely cited metric, this multiple reflects the normalized net profit (not revenue) per customer for each dollar invested into acquisition (sales, marketing, etc.). Ideally, it will be ~3:1; although higher multiples are even more appealing for a mature company, at the seed stage we worry that may indicate you’re leaving money on the table (i.e., you would likely benefit from investing more into marketing)

2) Metrics for B2B (i.e., selling to Employers, Providers, or Payers) Models:

Take-away: at early stages (in the absence of revenue figures), focus on sales cycle and contract value. If you have a longer sales cycle, then aim for higher contract values (and longer contracts). As pilots and MOUs (see below) mature, attempt to convert one-time revenues into recurring contracts 

  • Sales Cycle: it is typical to have long sales cycles in healthcare (9mo for providers, up to 18mo for payers, and even longer for pharma). We prefer when founders are able to realize 3-6mo sales cycles (whether through hustle and determination, networks, or sheer luck)
  • Total contract value (TCV) and contract length: typically contracts are 20%/30%/50% over three years; if you’re able to secure a stickier 5 year contract, it’s a major positive
  • Bookings / Contracts: the number, value, and terms of contracts / pilots vary greatly at the seed stage; while some seed-stage startups have managed to close with 1-2 dozen paying enterprise clients (although this is more typical of Series A companies), we’ve invested in companies that have yet to close their first deal (still at the “memorandum of understanding” phase)
  • Annual (Recurring) Revenue: Series A startups typically (ideally) have >$1M in annual revenue. At the seed stage, revenue is anywhere from $0 to <$1M; we frequently see figures in the low hundreds of thousands, although many startups are still in the free pilot phase. For obvious reasons, recurring annual revenue (ARR) is preferred over one-time revenues
  • Churn Rate: the lower the better; single digits per year is really good (aspire for this); not much to add here, we see numbers across the map

3) Benchmarks Regarding Start-up Valuation:

Save for capital and resource intensive sub-sectors of healthcare like biopharmaceuticals, much of the health technology space operates on similar valuation terms as general tech. We’ve expounded on this table below in another article.

Stage Key Proof Point Dilution Valuation as function of amount raised
pre seed powerpoint N/A – convertible 15-20% discount N/A – cap that is 3-5x amount raised
seed early seed = prototypelate seed = pipeline of customers 20-30% 3-5x
series A product-market fit 15-25% 4-7x
series B business model taking off 15-20% 5-7x
series C+ growth 10-15% 7-10x

In general, the “sweet spot” for seed-stage health tech companies is to raise at a post-money valuation of 3-5x – for example, raising $2M on a $10M post-money valuation. For context, at Tau, we generally find founders are successful when raising $2-5M at valuations ranging from $6M up to $20M

Raising at too high of a valuation (i.e., raising $1M at a $12M cap) may be tempting as a founder, however be careful not to underestimate the risks. If you (the founder) are unable to deliver on such high expectations, you run the risk of a weaker future fundraise (i.e., a flat-round or down-round where your valuation either remains constant or declines, respectively). Given the inherent role of speculation and signaling bias in this industry, these scenarios can be devastating. 

Raising at too low a valuation is concerning not only for the founders, but also the investors (severely diluted founder equity and limited upside can frequently lead to founding teams rupturing). 

Of course, the norms (raising valuation, terms, and time taken) vary widely based off geography and market timing (i.e., right now in July 2022).


Primary author is Kush Gupta. Originally published on “Data Driven Investor,” am happy to syndicate on other platforms. I am the Managing Partner and Cofounder of Tau Ventures with 20 years in Silicon Valley across corporates, own startup, and VC funds. These are purposely short articles focused on practical insights (I call it gl;dr — good length; did read). Many of my writings are at https://www.linkedin.com/in/amgarg/detail/recent-activity/posts and I would be stoked if they get people interested enough in a topic to explore in further depth. If this article had useful insights for you, comment away and/or give a like on the article and on the Tau Ventures’ LinkedIn page, with due thanks for supporting our work. All opinions expressed here are from the author(s).

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