Not every startup should optimize for every growth benchmark. Picking the right metrics to optimize is a critical first step to make sure resources are used to their fullest growth potential. Here are a few examples of metrics that matter a lot to certain companies but don’t matter as much to others.
Engineering Team Interactions With Customers
Interactions between engineers and customers gives engineers valuable empathy for customers and transparency into user psychology. But it turns out these interactions aren’t important for every company.
Among high-growth companies, those that have low engineering concentrations actually don’t ask their engineers to talk to customers. On the other hand, those that have high engineering concentration do make their engineers talk to customers frequently.
The higher concentration of engineers a company requires to execute a successful growth playbook, the more dependent that company’s success is on the performance of the engineering team. Ultimately this makes establishing best engineering management practices early on a mission critical KPI.
Customer engagement is a valuable proxy for the value a customer is getting from a product. As a result for many businesses, including top-down enterprise SaaS startups, user engagement is correlated with growth. Among top-down enterprise SaaS startups, 67% of companies we surveyed commanding over 60 minutes of user engagement per day were high-growth. In contrast, only 38% of companies fitting this profile with 60 minutes of engagement or less per day were high-growth.
But engagement isn’t always the best predictor of growth. For transactional businesses (i.e. marketplaces) metrics like CAC, speed to MVP and speed of shipping new features are more correlated with success. Surprisingly, among these businesses, lower growth companies had higher engagement. It’s possible that friction in user experience dragged out engagement at the cost of retention.
Freemium: Demands Establishing Growth
Best Practices Early
Freemium is a high risk, high reward go-to-market strategy for self-serve businesses. Only 18% of freemium companies we surveyed were growing fast. Yet of the high-growth companies successfully executing a freemium playbook, growth averaged 20% MoM.
These companies universally demonstrated top-tier growth metrics including efficient CAC. These businesses reported shipping MVPs in an average of two months, shipping features multiple times per week and having engineers talk directly to customers on a weekly or bi-weekly basis.
Deep Tech: Demands Highly Disciplined
Large Technical Teams
When compared to their less technical enterprise SaaS peers, deep tech companies require both large teams and highly disciplined product and growth leadership.
Only 13% of deep tech companies we surveyed, that were actively selling their product in market, had achieved high growth. These companies averaged 52 employees whereas their lower growth peers averaged only 12 employees. Critically, high-growth deep tech businesses universally employed the best engineering practices of shipping new features and having engineers talk to customers on a monthly or faster cadence. Meanwhile, only 25% of low-growth deep tech companies in our dataset were able to achieve these milestones.
Deep tech companies have to execute on ambitious roadmaps with tight runways, leaving little room for delays. Establishing engineering best practices is essential given these companies, on average, take longer to build MVPs and may have fewer opportunities to iterate with customer feedback.