In my work life prior to being a data human I was a product manager and I loved talking to users and conducting user research sessions. Now, as a data practitioner I love being able to wear both hats - doing qualitative & quantitative research together to get a more robust understanding of a topic/problem/etc.
This is a template I use for synthesizing my research findings so that I can share it with other folks on engineering or people on other teams across the business.
😎 TL;DR
[Summarize up to 5 bullet points/findings from your research ]
📝 Overview
[What was the goal of this work? What problem or opportunity was this research addressing? What method was used]
Example:
The goal of this research is to help us to understand why there is such a large drop-off in the onboarding flow for users creating a database. Our hypothesis is that users’ feel like they need to have a fully formed project idea before creating a database and don’t see PlanetScale as the type of product they could play around and learn with.
🔍 Detailed findings
[Provide a summary of the key findings. If you started with hypotheses use them to organize the presentation of the findings. Include direct user quotes if possible.]
Example:
Hypothesis: Users’ are confused about database creation and the drop-off in onboarding between the content and creating a db is because they don’t understand what they could specifically use the product for.
👍 The evidence largely supported this hypothesis. The participants were confused and hesitant about taking the next step in creating a database without having a fully formed idea about what to use it for and expressed concern
[If possible include user quote to back up these detailed findings!]
🗣️ Other feedback
[You may have gathered more feedback than what you asked for specifically. Summarize what yo
u heard and add a quote and link to when the reader can find more information.]
🚶♀️Next steps
[Were any of our hypotheses inconclusive? If so, how will we follow up to get the answers we need? Will this research be able to inform a specific product decision or help kick-off a new project based on what we heard?]
🔗 References
[ Link to raw notes, question docs, anything that might be relevant]