Use three layers: platform-level engagement norms from published benchmark studies, industry-specific averages for each client's vertical, and the client's own trailing performance as the primary yardstick. Benchmarks orient expectations; the account's own trend line is what you actually manage against.
Benchmarks answer the question every client eventually asks: is this good? The trap is treating any single benchmark as a grade. Used well, benchmarks are a three-layer context system, each layer more relevant than the last.
Published studies converge on rough platform-level engagement norms, follower-based rates around 1 to 3 percent on Instagram, under 1 percent on Facebook, 1 to 2 percent on LinkedIn, several times higher on TikTok. These set the floor of expectations and stop a client from judging their Facebook page by their TikTok numbers. Refresh them yearly; platform behavior drifts.
Within a platform, industries differ enormously. Entertainment and food run hot; finance, insurance, and B2B services run structurally cooler, and a client in a low-engagement vertical needs to know that before they compare themselves to a restaurant. Most major benchmark publishers break results out by industry; cite the source and year in the report footer so the comparison is auditable.
The benchmark with the least noise is the client's trailing average. Same audience, same industry, same measurement method. Management decisions, what to make more of, what to stop, should run off this layer, with the external layers reserved for expectation-setting. A useful report convention: show each KPI against the client's own trailing three months, with the industry figure as a footnote rather than a headline.
Different studies use different denominators and samples, which is why the same client can look great in one table and mediocre in another. Pick one reputable source per year, apply it consistently across clients, and keep the calculation method identical to the benchmark's, or the comparison is fiction.
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