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.
FEATURED CONTENT
LATEST POSTS
How to fix Your Product Goals for Better Human Outcomes
Hello product designers, this is for you. I want to talk to you about product goals, metrics, and how they get muddled in the product design process, leading to some less than humane outcomes. But first a little story. In the early 1970s, two behavioural scientists working at Princeton University set out to investigate the psychology Read more »
Killing Zombies - Lisa Long on The Product Experience
Ash Williams (Evil Dead); Columbus, Tallahassee, Wichita and Little Rock (Zombieland); Shaun (Shaun of the Dead); Alice (Resident Evil); Lisa Long (ProductTank). All have killed zombies, and entertained us as they did so… but only Lisa did so on stage at London’s ProductTank, giving us practical advice on how to kill off zombie features and Read more »
Talking About Data Science by Jenessa Lancaster
Jenessa Lancaster is a data scientist at Ocado Technology. In this ProductTank London talk, she discusses the importance of communicating data concepts to non-specialist audiences. We live in promising times for data science in business development. Many organisations are increasing investments to their data science and machine learning departments, acknowledging the valuable insights that these Read more »
Why Data is key in Building a Company That Learns
Facing uncertainty is a company’s biggest challenge. It doesn’t matter whether you’re in a startup or an established company, when you start work on a product, you need to validate your problem, your solution, and find your market. When you scale, uncertainty arises in the form of change – your market changes, your users’ needs Read more »
Embrace Uncertainty: the art of Applying a Scientific Approach
The rollercoaster ride that is product development is inherently chaotic and ever-changing. So, as process-oriented professionals, we product managers look to the structure and predictability of a scientific approach for certainty. Our inputs into such a scientific approach, however, are based on assumptions – either individual or corporate – that contain significant amounts of uncertainty. Read more »
Strategies to get Started with Predictive Analytics
I believe that predictive analytics is poised to enable businesses in ways we didn’t think were possible several years ago. It’s starting to play critical roles in solving inventory problems, loan prediction, user personalization, customer segmentation, propensity to churn, product pricing, and many other areas, with the goal of enhancing customer experience and the bottom Read more »
Unlocking Data Science to Build the Future of Work by Mike Hyde
Mike Hyde leads data science and data engineering for Workplace, Facebook’s new enterprise product for company connectivity. He is passionate about using data and insights to create innovative company cultures, so he spoke at ProductTank London about data for growth. How do we attach data science and analytics to product development and management? There is Read more »
Silence the Squeaky Wheel through Feature Prioritization
Prioritization is challenging and stressful. Sometimes it’s because of micro-prioritization such as bug triage and moving one small fix in front of another. Other times it comes from the macro level: deciding to target new user growth versus lifetime value; spending time on user research or analytics; handling your manager’s feature request versus the tech Read more »
Nail your Backlog Priorities by Figuring out Return on Effort
Prioritization of work is hard: it’s often more an art than a science. Unless you work in an organization that has mastered the delicate balance of work from a prioritized roadmap as well as customer requests, you too may often be faced with squeaky-wheel prioritization: The customer yelling the loudest (or the one who last Read more »
How can Enterprise Product Managers Attain Maximum Insight From Limited Datapoints?
Not surprisingly, when you’re looking for customer validation for B2B products, there simply aren’t as many datapoints to draw from in enterprise product management as there are for consumer products. Therefore, every interaction counts and your enterprise sales force becomes one of your closest allies when gathering requirements and validating product assumptions. The following are Read more »