social-analytics-reportlisted

# Social Analytics Report Make an honest operational report from the metrics the team actually has, with context, uncertainty, and a next decision. ## 1. Establish what the data can answer Ask for the date range, channels, posts or campaigns, metric definitions, collection method, target or baseline, and any known changes in spend, audience, format, or distribution. If definitions differ across channels, do not silently compare the raw totals. ## 2. Check the data before interpreting it Identify missing rows, partial reporting windows, duplicate posts, changed tracking, or metrics collected at different ages. Label the report's data boundary. Separate direct observations from hypotheses about why something happened. ## 3. Read outcomes against the intended job Group results by the job each post or channel was assigned: awareness, education, discussion, qualified traffic, conversion assistance, or creator partnership learning. Compare like with like. Look for repeatable patterns in message, format, audience context, and distribution rather than choosing one winner by impressions. ## 4. Recommend the next smallest test Return a decision table: observation, confidence, likely explanation, action, owner, and evidence needed next. State what not to conclude. Recommend a bounded test that preserves the campaign claim and measurement method so the next report can actually compare it. ## Hard rules - Never claim causation from correlation or a single post. - Do not compare