The Product Coalition
JUNE 14, 2020
Lessons from big money tech failures An opinionated analysis of why some hyped products failed Last year, I did a talk, as part of orienting a team of automotive executives in modern way of iterative working, challenging the prevailing belief that perfect pre-planning backed by big money will always be a clear winner. The Zune Is Dead.
The Product Coalition
MAY 9, 2020
There are some warning signs: Reduced market size Low response from customer base Negative press reviews (or no interest from the press) Weakening word of mouth High visibility, but no engagement Products That Couldn’t Find Their Fit We love the schadenfreude of looking at failed products! How Do I Know if I Have No Product-Market Fit?
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The Product Coalition
FEBRUARY 1, 2022
A product or feature might have been successful at the time of release, but technical capabilities improve and user expectations evolve. The dating platform “YouTube” rebranded as a video website and sold in 2006 to Google for USD 1.6 Odeo was a small podcasting startup in 2005. Does the product have an imbalanced cost benefit?
Intercom, Inc.
FEBRUARY 26, 2018
As well as being a critical philosophy behind how we build software, it also represents how I feel about the software industry and technology in general. Innovative startups. The first army are innovative startups. Basic technology execution is becoming easier too. There are more technology jobs than ever before.
The Product Coalition
NOVEMBER 26, 2022
And this is a terrifying and disturbing thought because startups and entrepreneurs invest tons of money to build these products. This brings us to an important question that every product manager and the associated tech teams ask themselves every time they dip their feet in the river of building digital products.
Sachin Rekhi
JUNE 25, 2017
Below is a collection of my favorite vision statements from a variety of successful technology companies over the years. This involves everything from core project management responsibilities, to leveraging analytics for making data-driven decisions, to leading the overall R&D team, and so much more.
Mind the Product
AUGUST 19, 2019
According to Crunchbase, in 2018 there were 5,000 startups relying on machine learning for their main and ancillary applications, products, and services. You forget that your dataset also includes December and Christmas holidays that skew your data due to unusual user activity and behaviour.
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