What makes a useful insight? 4 Principles
No point carrying out great user research and keeping it a secret.
Good user research is about gaining an in-depth understand of what users want and need and what their current challenges are. That understanding is only useful if it’s effectively communicated. Written insights are a great way of sharing the new found information. Here’s a rough guide to expressing insights in a useful way.
A useful insight is:
- New information to the organisation
- Understandable to someone who didn’t carry out the research
- Actionable by the organisation
- Evidence based
Tell the person reading them something they don’t already know, that has been uncovered by the research. For example: ‘Women from BAME groups use leisure centres less than other groups’ isn’t a new insight, the leisure centre staff already new that, ‘Some women from BAME groups reported preferring leisure centres that have women only sessions available’ is new information.
Useful insights are understandable to someone who doesn’t have an in-depth understanding of the research already. User researchers guide people to the useful information. Insights shouldn’t contain acronyms, imagine someone from outside the organisation is reading them. For example; ‘MMRs are unstructured’ is hard to understand whereas ‘Monthly Medical Reports should follow a uniform format’ makes more sense.
Insights should be positive and actionable, so necessary changes can be easily made to improve the organisation. Focusing on the positive makes is easier to see how things could be improved. For example: ‘Call operators need expert training’ is a more actionable insight than ‘Call operators make many of mistakes’.
This is the most important element in communicating useful insights. They must be backed up by evidence. Quotes and photos which illustrate why you are highlighting the insight are useful. It doesn’t matter whether the quote is anonymised, but information about their demographic and role can give useful context. It’s also vital to include statistics where possible, show that on a micro scale one person had one challenge, then show how many people are experiencing this challenge on a larger scale. This allows people to understand the urgency of the changes that need to be made. It also minimises bias in your research — evidence shows it’s not just you who believes the insight to be true.