Employee advocacy analytics: measure adoption
Track employee advocacy adoption, content quality, and useful conversations before optimizing reach or pipeline attribution.
Add quality and intent signals
Layer in relevant comments, profile visits, saves, and qualified conversations. Keep these signals separate from activity metrics so the team can see whether a workflow issue or a content issue needs attention.
Use the report to choose the next action
Review analytics weekly and assign one action: improve the brief, support a contributor, change the topic, add proof, or adjust the format. A report is useful when it changes the next publishing decision.
Delay complex attribution until the baseline is stable
Pipeline attribution can be useful later, but it should not hide weak participation or generic content. Establish a consistent 30-day baseline before comparing assisted commercial signals.
Give each metric an owner
Assign the programme owner, content lead, or contributor coach to each metric. Ownership turns a report into a routine for resolving blocked drafts, weak participation, or unclear topics.
Compare weeks, not isolated spikes
Use weekly cohorts to compare participation and content signals over time. A single reach spike can be useful context, but repeat publishing and relevant conversations are stronger evidence of a healthy programme.
Use consistent formulas for the weekly scorecard
Define the denominator before comparing teams. Participation rate is contributors who completed one agreed action divided by eligible invited contributors. Repeat participation is contributors active in both weeks divided by contributors active in the previous week. Draft-to-publication rate is posts published divided by drafts started in the same cohort and time window.
Read the numbers as a workflow diagnosis
For example, 12 active contributors out of 20 eligible invitees is a 60% participation rate. If 4 of those 12 are active again the next week, repeat participation is 33%. This is a worked example of the formulas, not Orsana customer data or an industry benchmark. A low draft-to-publication rate is a reason to inspect the workflow; it does not prove why contributors stopped.
Separate program health, content performance, and business impact
Health describes whether the program is used: eligible invitees, active contributors, and repeat participation. Performance describes what published posts do: relevant comments, profile visits, or link clicks per post when those signals are available. Impact describes outcomes such as qualified conversations or tracked conversions. Keep the three layers separate so a large reach number cannot stand in for adoption or revenue.
Turn a weak metric into one test
If few invited people start a draft, check whether the brief gives them a clear topic and usable evidence. If drafts start but few posts are published, inspect review delays and the effort needed to personalize a draft. If posts repeat but useful conversations do not, test a narrower audience question or stronger proof. These are diagnostic hypotheses to check with contributors, not causes the dashboard can establish by itself.
Set limits before sharing the report
Use the same definition, eligible group, and time window in every comparison. Record missing posts or analytics rather than treating them as zero. Tracked links show only the conversions they can observe; self-reported influence is useful context but is not verified attribution. There is no universal healthy participation rate that fits every team, role, or posting cadence.
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