As your startup scales it's not enough to know what to measure - you have to know WHEN to measure. Metrics that are important in one growth phase might not be in the next.
To help us make sense of it all, we invited Laura Tacho onto the show. Laura is a VP of Engineering & Leadership Coach, and an expert when it comes to startup growth and metrics, having worked with over 125 different companies.
We love this episode because it takes a team-first approach to metrics and then relates those metrics back to the growth of your organization. Whether you are a seasoned engineering leader or an IC trying to understand where your team is headed, this unique take on metrics will set your team up for success - and happiness - in 2023.
Episode Highlights:
- (2:53) How Laura got her start in engineering
- (6:56) Why companies grow and mature like people
- (11:58) How bad habits get baked into companies
- (17:35) Common growing pains during scaling
- (19:54) Advice for eng teams at scale-ups
- (23:29) CEOs who get attached to bad metrics
- (31:21) Metrics for mature orgs
- (36:48) Justifying metrics to your board and your team
While you’re here, check out this video from our YouTube channel, and be sure to like and subscribe when you do!
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Top comments (2)
Really important topic because measuring the wrong metrics can push startups in the wrong direction early on. Retention, activation, engagement, and customer behavior often reveal more than vanity growth numbers.
Foundersbar helps startups stay focused on meaningful metrics so decisions support sustainable growth and product progress.
This is such an important point because a lot of startups become obsessed with tracking metrics without understanding context.
Early-stage founders especially tend to measure everything at once: DAUs, retention, CAC, LTV, NPS, activation, churn, velocity, deployment frequency, burn multiple 😵💫
But the reality is that different stages demand different priorities.
At the beginning, speed of learning usually matters more than optimization. Later, efficiency and scalability start mattering more. Then eventually operational stability, team health, retention, and execution consistency become critical.
A metric without timing is almost noise.
What’s also interesting now is how AI is changing startup execution itself. Teams can ship features faster than ever, but faster shipping also creates new problems like more technical debt, more review overhead, noisier analytics, premature scaling, and pressure to optimize before true validation.
That’s actually something we think about a lot at foundersbar.com too. A lot of founders come in focused entirely on growth dashboards and vanity metrics, but the bigger challenge is usually figuring out what actually matters at their current stage. Sometimes the issue isn’t growth at all, it’s unclear positioning, weak feedback loops, poor onboarding, or trying to scale before there’s real product-market fit.
The best startups usually aren’t the ones measuring the most metrics. They’re the ones measuring the right metrics for where they are right now and using those insights to make better decisions consistently.
Really interesting perspective here overall, especially the team-first approach to growth and engineering metrics 👏