LinkedIn Analytics Report Template for B2B Content

Metrics answer different questions. Impressions describe distribution. Reactions and comments describe interaction. Profile views and followers gained describe movement toward the author. Conversations and opportunities describe business relevance. Combining them into one score hides useful differences.

Performance numbers alone cannot tell you what to repeat. Add the choices made before publication: content pillar, audience, format, hook type, source type, author, call to action, and posting date. These fields turn the spreadsheet from a scoreboard into a learning system.

Use a small controlled vocabulary. If one person tags a post as founder story and another calls the same structure personal narrative, the report cannot group them reliably.

Engagement rate can be useful, but teams calculate it differently. Choose a numerator—often reactions, comments, and reposts—and a denominator such as impressions or reach, then document the formula and keep it consistent. Saves and sends may deserve separate analysis because they signal different behavior.

Never delete raw counts after calculating a rate. A 10% rate from a tiny sample does not carry the same evidence as a similar rate from a widely distributed post. Report totals, averages, and medians where appropriate.

A monthly review is frequent enough for operational changes but long enough to reduce reaction to a single post. Compare similar authors, topics, and formats over a rolling period. Seasonal events, posting frequency, audience growth, and one unusually large post can distort simple month-over-month comparisons.

Lead with the objective, what changed, the strongest evidence, and the action it supports. Put detailed tables underneath. A stakeholder should understand the recommendation without reading every row.