Most teams collect both - but they tend to live in different rooms. Analytics dashboards sit with the growth team. Research notes sit in a Notion page nobody opens after the kickoff. The result is a gap: a number nobody can explain, or a story nobody can size.
What analytics is good at
- Spotting where in a journey people leave.
- Showing how a change moves a measurable outcome.
- Comparing groups - new versus returning, mobile versus desktop, one product against another.
Analytics is excellent at the "where" and "how many". Drop-off happens between step three and step four. Twelve per cent more people convert when the page loads under two seconds. These are facts a team can act on.
What analytics misses
The reason. Analytics will never tell you that the customer left because the headline used a word they didn't recognise, because the call-to-action sat below a confusing legal notice, or because they were tired and the form felt long. It also tends to hide vulnerable customers inside an average - the people most likely to be harmed are the same people whose behaviour rarely shows up as a clean trend line.
What research is good at
- Sitting next to a customer and watching them try to do something.
- Reading support tickets and chat transcripts for patterns.
- Asking five people the same question and noticing what comes up.
- Catching the moment somebody says "I gave up because I wasn't sure that was the right link."
Research handles the "why" and the "how it felt". It surfaces the texture analytics can't - confidence, confusion, frustration, the half-second hesitation before clicking.
How they work together
Analytics finds the cliff. Research finds the cause. The teams getting this right use analytics to decide where to look next, run small studies on those moments, then go back to analytics to check whether the fix moved the number.
For Consumer Duty in particular, neither alone is enough. Numbers don't prove harm; quotes don't scale. You need both - the size of the problem and a believable account of what it cost a real person.
Where UXDuty sits in this
UXDuty is the layer between the two. We pull journey shapes from your analytics - the routes customers actually take - then run accessibility and UX checks on every step. The output is the same as what good research produces: a specific issue, on a specific page, written in plain language, with the consumer impact spelled out.
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