Data Driven Product Management
There are many ways in which data-driven product management is described but, put simply, data-driven product management means making decisions based on real-world information. Understanding data-driven product management can help you to use the right data, uncover the right insights, and ultimately build the right product.
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Building Product in a Post-GDPR World
Keep Calm and Manage Data Responsibly because, in this blog post, I’ll try to unpack what I consider to be the implications of GDPR on how we build products. Don’t panic – I’m not going to go into an exhaustive breakdown of exactly what GDPR is, there are plenty of perfectly good posts about that. […] Read more »
How can you Respond to the Rise of the Privacy-Conscious Consumer?
When Elon Musk hopped on the #deleteFacebook bandwagon, it became clear that, in light of Facebook’s issues with Cambridge Analytica, public perception of internet privacy is changing. As a researcher on attitudes to digital privacy and an advocate for user-friendly privacy practices, I’m excited by these developments. I’ve been following the conversation and have started to see evidence […] Read more »
Life Beyond Google Analytics: Pick the Best Tools for the Job
Google Analytics as Your Default Platform? Sure, if it’s 2010… A product manager’s role as an analyst is sometimes forgotten or not recognized. As a product manager, the impact of your business decisions will be measured by your product’s front-end data. It is your obligation to be able to implement an analytic platform, analyze […] Read more »
The Fundamentals of Building Better Data Products
Data is the world’s most valuable resource, according to The Economist, and the companies that primarily deal in data – Google, Amazon, Facebook and the like – are among the most valuable in the world. Data and data products have been part of my professional career for a long time – from advising telco providers […] Read more »
Why Data Science and UX Research Teams are Better Together
In this talk from ProductTank San Francisco Chris Abad, who’s currently VP of product and design at User Testing, shares insights into how bringing together qualitative user research and quantitative data science teams is crucial for companies because it can help them to see the complete picture and inform critical product decisions. Chris shares real-world examples […] Read more »
Why you Need Quantitative AND Qualitative Data
Qualitative versus quantitative data: we’ve all been involved in a conversation debating their respective merits at some point in our careers. We’re often flipping backwards and forwards between letting feedback from a handful of customers drive all our product decisions or requiring everything to be backed up by statistically significant data. So which type of […] Read more »
Four Ways to Make NPS a More Actionable Metric
It’s been nearly 15 years since Bain’s Fred Reichheld first introduced the Net Promoter System (NPS), a simple calculation of customers’ willingness to recommend a brand. By asking a single question, “How likely are you to recommend us to a friend?”, NPS distilled the complex topic of customer satisfaction into a single number. And a decade […] Read more »
3 Ways to Enlist Your Usage Data to Drive Product Development
Recently, Gartner revealed its top predictions for IT organizations for 2018. Among the expected buzz around technologies like artificial intelligence, blockchain, and the Internet of Things, was something a bit surprising to me. Gartner predicted that by 2022, most people in mature economies will consume more false information than true information. “Fake news has become […] Read more »
7 Ways Cohort Analysis can Optimize Company Performance and Results
Businesses are constantly in search of useful tactics that improve their brand’s performance and bottom line. Cohort analysis is often overlooked, but it can yield insightful information and actionable advice to improve acquisition, retention and monetization. By definition, a cohort is a group of people who have a common characteristic during a period of time. […] Read more »
Data-Driven Mobile App Iteration: Seeing the Wood From the Trees
Imagine a lumberjack wanting to cut down a tree with his chainsaw. It’s a pretty simple, straightforward task. But what if the lumberjack never knew that he could turn the chainsaw on? Or that he cut down 1,000 trees when he needed just one specific tree? Not quite the ideal way to use the tools […] Read more »