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How to be the go-to engineer for product analytics

Mixpanel

As data-driven product development continues to balloon in popularity, so does the need for accurate and sophisticated implementation of analytics tracking in software products. All over the code, you have ugly calls to complex analytics APIs littered amongst your views and business logic. You’d be celebrated.

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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., This is a very compelling story (especially if you’ve got only one or two engineers or developers on your team who may or may not include yourself). If you don’t get your features built, you won’t have an app to launch, right?

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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. When your team is trying to build something that doesn’t currently exist, the development process is full of moments of uncertainty. Hand it off to your developers and design team, and let them execute on it.

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The Disproportionate Impact of Coaching on Startup Survival

Bain Public

MAIN: Developing Entrepreneurship in Quebec. MAIN , also known as Mouvement des accélérateurs d’innovation du Québec, states that their mission is "to improve the cohesion and efficiency of the business incubator and accelerator ecosystem and to increase its impact on the development of entrepreneurship and innovation in Quebec.".

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

Mixpanel

Here are eight reasons you should always implement your analytics in the same sprint as your feature development and not at a separate time after development is complete. When engineers implement features, they write code. Implementation is better with less context-switching. This is a multi-team waste fest!

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Data thinking vs. product thinking

Mixpanel

Data has fundamentally changed how we design and develop products, but there’s a difference between simply reacting to data points and applying the level of analytic rigor needed to yield meaningful results. There’s an enormous amount of ambiguity when it comes to developing products. Here’s how. Create counter metrics.

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The Podcast Ecosystem in 2019 – a16z’s 68 page analysis (Guest essay by Li Jin)

Andrew Chen

Apple Podcasts played a pivotal role in the development of the industry and remains the dominant app for listening. In order of descending audience sizes, these categories are: Media companies that have internal podcast departments , whose goals in podcasting can range from audience development to diversifying revenue. Audioblogging?