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My Biggest Takeaways?—?Being a Product Manager at an Early Stage Startup

The Product Coalition

Being a Product Manager at an Early Stage Startup In my previous article , I reflected on a few things that I would tell myself if I could travel back in time and the concept of “three waves of changes.” In this post, I want to talk about the three most important lessons I have learned so far as a Product Manager at a startup.

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Why it’s never too early to add product analytics to your app

Mixpanel

So it’s tempting to think the additional add-on of measuring user events in your code (i.e., implementing product analytics) is something that can wait until your team is bigger, until you have more users, or until you have more money. With product analytics, you can know the difference.

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How to be the go-to engineer for product analytics

Mixpanel

The point is that some of these might be catchable by non-technical team members whose job it is to analyze the data, but a lot of cases could only ever be noticed by someone who understands how the implementation actually works on a technical level: an engineer like yourself. Keep the product folks technically up-to-date.

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The Disproportionate Impact of Coaching on Startup Survival

Bain Public

FUN FACT: It is actually thanks to the coaching service for innovative and technological SMBs (PMEit) administered by MAIN that we’ve been able to work with some of our incredible clients, Wastack , LiveScale , Blaise Transit and Enkidoo , and provide them with product management, consultancy and coaching support.

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How to Deal With Unknown Unknowns in Project Planning

Amplitude

This is a guest post from Dillon Forest, cofounder, CTO & product manager at RankScience. Do some user research. But when you’re building a product with lots of technical or business unknowns—something many startups and product teams are doing—this process breaks down.

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Data thinking vs. product thinking

Mixpanel

There’s an enormous amount of ambiguity when it comes to developing products. UX design, branding, feature-set, nuanced differences in user perspectives, and a million other variables can impact (with varying levels of influence) whether our products get used or ignored. Understand the role of data with nuance.

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Always implement analytics as part of feature development. Here’s why.

Mixpanel

They need to be actively aware of all of the requirements, why those requirements exist, and the nuanced value the feature intends to deliver to the user. Engineers are technical. They tend to process technical information better than less formal information, and that’s where analytics comes in. This is a multi-team waste fest!