LATEST POSTS

Optimal Matching for Marketplace Startups and the Role of Bias

BY Philip Seifi on October 3, 2019

While matchmaking is a core lever of any marketplace business, data crunched by Uber, Airbnb, and other marketplaces shows that engineering an optimal marketplace sometimes defies common sense. For example. You finish dinner and are ready to head home. You see plenty of Uber drivers, but you’re matched with a car 10 minutes away. It Read more »

Data-driven blunders and how to avoid Them

BY Jorge Rodriguez-Ramos on September 5, 2019

Jorge Rodriguez-Ramos considers how you can best incorporate data-driven decisions into product management. Read more »

Socially Preferable by Nathan Kinch

BY Nikki Gupta on September 3, 2019

In this ProductTank London talk, Nathan Kinch, CEO at Greater Than X, examines the issues of ethics, privacy, and trust. He looks at how product managers can kick-start their ethics journey and ship products that make life better for everyone. The Edelman Trust Barometer is a resource that measures levels of trust in different contexts. It Read more »

They're Just Fancy Averages by Ben Fields

BY George Fletcher on August 22, 2019

In this ProductTank London talk, Ben Fields, formerly Lead Data Scientist at FutureLearn, looks at getting the most from the relationship between product managers and data people, working out people’s background understanding, the benefits of leading with a story, and how best to spread knowledge. There are three key aspects of how data science can Read more »

Lessons From the Space Race: 3 Steps to Better Product Decisions

BY Anna Buldakova on July 9, 2019

What makes a great product decision? The answer to this question is like the Holy Grail of product management: it promises success and prosperity but no clear evidence that it exists. In this post I examine the way I think about the path: what has worked for me and helped me grow as a product Read more »

How to fix Your Product Goals for Better Human Outcomes

BY Rob Boyett on June 27, 2019

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

BY The Product Experience on June 5, 2019

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

BY Annie Witcombe on April 24, 2019

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

BY Alexandre Gabadou on April 23, 2019

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

BY Wes Galliher on April 18, 2019

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 »