From time to time I work with promising, small startups who are not ready for their first PM but are looking for product expertise to guide them towards product-market fit.
Recently, I was working with a startup that focuses on helping their enterprise clients identify employee engagement issues. Since they felt comfortable in their current core product, they were interested in expanding their product into something they believed would be complementary to their core value proposition: providing advice to corporate leaders on how to take action to fix/mitigate/reduce HR/personnel issues, which would then boost employee satisfaction.
Being a bootstrapped and small startup, expanding their product line would be risky, especially as they have a small developer team and could either work on improving their core product, or work on this new advice system that would enhance their product value, deepening their retention hooks, and further differentiate themselves from their competitors.
The team was also very excited about incorporating machine learning into their advice system, allowing them to scale the service to match their current customer base and their future base.
After internally talking through the risk of working on a new product feature and the opportunity risk of not exploring the new product feature, the team was confused on how they should proceed.
That’s when they called me…
Once I was caught up, I could see the dilemma they were in. There was a lot of value in guiding corporate leaders on next steps, and if they could prove their system did provide such value, they could use their core product to measure the change in employee satisfaction based on their advice!
So how could they potential explore this new advice system and reduce the huge risk of getting it wrong?
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