Strategy & Planning

Experiment Tracker

Why use the Experiment Tracker?

Companies and teams spend too much time and money on ideas that don’t work. In a world that is getting filled up with new technologies every day, we can’t reliably predict what will work. We as business, design, and product leaders must inspire our teams and collaborate across the org to drive action in a structured and fact-based manner.

The Experiment Tracker is a simple 5-step process to gain more clarity about what actually works, turning successful outcomes into backlog ready items. Furthermore, I took the canvas and adapted it a bit for myself after years of experimentation with different kind of clients.

How to use the Experiment Tracker

  1. Collect all assumptions besides the canvas. Usually start with "We believe if we do X, we will achieve Y"

  2. Prioritize them by risk: Which one can kill your idea right away. Start with assumptions around the customer, pains, jobs and needs as the riskiest one.

  3. Brainstrom fast ways to test this assumption. From early interviews to live-video prototypes, it's up to you to decide WHAT you want to test with WHOM and HOW.

  4. Define which data you want to measure and which targets you need to meet to call it a success.

  5. Take time to craft the experiment and run it.

  6. Come back and collect all findings. Distill key insights out of it. Any surprises?

  7. Define how you want to continue: Kill this idea right away, give it another chance with some adjustments (pivot) or continue like is (persevere)

  8. Enjoy the journey

Common challenges and mistakes to avoid. Teams...

  • Start with more than one experiment and loose focus

  • Overestimate the success of their solution, keep in mind: If you don't reach the target you might consider to kill the idea

  • Set the bar too low. A good benchmark for eg for measuring interest at IKEA is min. 40% of early adaptors need to like the idea

  • Don't know which metrics to measure: You can use the AARRR framework to get started

  • Are not well mixed and miss out certain perspective (tech, design, product, sales, finance, marketing etc.)

  • Are thinking too big creating the first experiment. What is the minimum thing you need to do to learn?

Watch a video


Thomas Gläser image
Thomas Gläser
Product Innovation & Growth Strategy Lead@XING Events GmbH
Thomas Gläser is a passionate product leader who has more than 10 years experience in building successful digital products. He’s working at the intersection of design, business and technology.

Related boards

Template cover of Assumptions & Experiments
Template cover of The MVP Experiment Canvas