Synthesising Research
Two weeks in, LunchLoop's designer has six interview transcripts, 620 survey replies, notes from two kitchens and a folder of heatmaps. It feels like a lot of knowledge. It is not yet. A pile of findings changes nothing until someone turns it into a few clear statements the team can act on. That work is synthesis.
The rule
Observations into clusters, clusters into insights, insights into decisions.
Four layers, each built on the one below:
- Observation: one fact from one source, written plainly. "P4 learned about a client lunch at 10 a.m. and could not cancel." No interpretation yet.
- Cluster: observations grouped by shared meaning, often on a wall of sticky notes (an affinity map). Group by what notes mean, not by the words they use, and name each group with a short sentence: "Plans change in the morning."
- Insight: the pattern plus why it matters, a truth about people that was not obvious before. "Plans change later than the app allows, so people pay for lunches they already know they will not eat, and they resent it."
- Decision: what the team will now do differently. "Explore a morning change window and test it with cooks."
An insight is stronger when different methods agree, which is called triangulation. Interviews, a survey and a heatmap saying the same thing are far harder to dismiss than one vivid quote. Record contradictions too; they often hold the next question.
The shortcut
Test each candidate insight with "So what?" If the answer changes a decision, you have an insight. If it only restates a fact, keep digging.
Observations
"P2 got a lunch meeting invite at 9:40 a.m." "P5 decided to work from home at 8 a.m." "Survey: 70% found out on the morning itself." "Rage taps on the locked tile after 9 p.m."
The trap is stopping at the cluster. "Changes arrive late" is a true summary, but only the insight explains why it matters, and only the decision moves the product.
Drills
Answer fast — trust the rule.
Which of these is an observation, not an insight?
How should notes be grouped in an affinity map?
Why is an insight backed by interviews, a survey and a heatmap stronger than one backed by interviews alone?
"Users want a better app." Why is this a weak insight?
Remember
- Observations into clusters, clusters into insights, insights into decisions.
- Shortcut: ask "so what?" of every insight; if no decision changes, keep digging.
- Trap: stopping at a cluster label, or trusting one vivid quote over agreement across methods.