Show whether the pilot changed anything useful.
Import customer-supplied aggregate counts and an agreed outcome measure. Every export identifies its source status. Schema checks cannot verify whether the source figures are true.
Primary outcome figures come from the agreed customer measurement, not from the optional responses below. Use the same question, population and method at baseline and follow-up; retain counts and response rates in the final report.
Self-reported understanding moved from 58% to 76%, a positive change of 18.0 percentage points.
- Eligible audience
- 500
- Interaction rate
- 77.2%
- Completion rate
- 59.6%
- Next-step rate
- 23.7%
69.1% answered yes
162 responses from 87.1% of completed decisions.
- Yes
- 112
- Partly
- 38
- Not yet
- 12
Self-reported understanding is confidence, not a comprehension test. Before/after figures require a comparable customer-agreed measure; they do not establish causation. Funnel rates use loaded sessions, not unique employees.
All exports retain the evidence status shown above. This workflow accepts aggregate journey counts only; calculator values, personal identifiers, free text and raw event records are outside the measurement contract.Customer-owned analytics in, aggregate evidence out.
Add one optional attribute to the normal embed. Plainly pushes only the approved event name, client identifier, campaign identifier, configuration version and contract version. Google Tag Manager or the buyer's analytics team controls collection, consent and retention. The reporting workbench accepts only a strict aggregate JSON bundle: raw events, user records and unknown fields are rejected.
<script
src="https://plainlyfinance.co.uk/embed/plainly-embed.js"
data-plainly-calculator
data-calculator="pension-change"
data-client="customer-id"
data-campaign="approved-pension-change"
data-analytics="dataLayer">
</script>