--- title: "Cross-Platform Analytics — Cross-Platform Repurposing with Bolta" description: "What metrics to compare across platforms and what not to. The metrics that translate vs the ones that don't. The portfolio scorecard." canonical_url: "https://bolta.ai/university/courses/cross-platform-repurposing/cross-platform-analytics" markdown_url: "https://bolta.ai/university/courses/cross-platform-repurposing/cross-platform-analytics.md" last_updated: "2026-04-27" content_type: "feature" publisher: "Bolta" --- # Cross-Platform Analytics — Cross-Platform Repurposing with Bolta Source: https://bolta.ai/university/courses/cross-platform-repurposing/cross-platform-analytics Last updated: 2026-04-27 What metrics to compare across platforms and what not to. The metrics that translate vs the ones that don't. The portfolio scorecard. ## Summary Lesson from the Bolta University course "Cross-Platform Repurposing with Bolta". The full lesson text follows. ## Who this is for - Founders - Creators - Marketing teams - Agencies ## Limitations and boundaries - Course material describes the product and the platforms at the time of writing; verify current behaviour in the app. - Social network features, limits, and algorithms change independently of Bolta. - Current prices and plan limits must be verified on the Bolta pricing page. ![Banner](/images/university/courses/cross-platform-repurposing/7.png "Cover") ## Lesson 1: Metrics That Translate Across Platforms Some metrics are roughly comparable across platforms. Use these for cross-platform decisions. ### Engagement rate per post Likes + comments + shares + saves divided by impressions. A normalized measure. **Why it translates:** every platform has these signals; the ratio is comparable. **Caveats:** "saves" only exist on some platforms. "Boosts" on Mastodon are different from "shares" on LinkedIn. Don't compare nominal counts; compare ratios. ### Follower growth rate Net follows per week or month, as a percentage of starting followers. **Why it translates:** every platform has followers; growth rate is platform-agnostic. **Caveats:** lagging indicator. Tells you what your content was doing 2-4 weeks ago, not now. ### Reach How many unique people saw your content. **Why it translates:** every platform reports reach (or impressions divided by repeat-views). **Caveats:** Mastodon's reach is harder to measure (no centralized analytics). ### Conversion-adjacent metrics Profile visits, link clicks, DM volume — anything that signals intent to engage further. **Why it translates:** these correlate to business outcomes regardless of platform. **Caveats:** different platforms surface different conversion-adjacent signals. Compare what each gives you. ## Lesson 2: Metrics That Don't Translate Some metrics look comparable but aren't. Avoid the trap. ### Raw follower count A 10K X account isn't equivalent to a 10K LinkedIn account. Audiences are differently composed, engagement is different, conversion power is different. **The trap:** declaring one platform "better" because the follower count is bigger. **The fix:** measure value-per-follower, not raw count. ### Likes / favorites Likes mean different things on different platforms: - **X like:** mostly bookmark-style, doesn't drive distribution. - **Bluesky like:** similar. - **Mastodon favorite:** private, doesn't distribute at all. - **LinkedIn like:** modest distribution signal. - **Instagram like:** modest signal. Comparing raw likes across platforms is meaningless. ### Reply / comment counts A reply on X often means engagement; a reply on Mastodon often means substantive conversation. Same word, different stakes. **The trap:** "I get more replies on X than LinkedIn, so X is better." **The fix:** look at quality, not just count. ### Watch time Reels watch time on Instagram vs Reels watch time on Facebook vs native video on X — the platforms measure differently. **The trap:** comparing seconds-watched as if they were equivalent. **The fix:** watch-through rate (percentage who watched past 3s, 25%, 75%) is more comparable than total watch time. ### Hashtag reach Hashtags on Mastodon route differently than hashtags on Instagram than hashtags on LinkedIn. Direct comparison doesn't work. ## Lesson 3: The Portfolio Scorecard The right way to evaluate cross-platform performance: a portfolio scorecard, not a leaderboard. ### The scorecard structure For each platform, track: 1. **Cadence consistency.** Are you hitting your committed cadence? 2. **Engagement rate.** Trend over 30 days. 3. **Follower growth.** Net follows per week. 4. **Conversion proxy.** Profile visits, link clicks, DM volume. 5. **Effort hours per week.** How much time you spent. 6. **Output count.** How many posts. ### What you're looking for Three things: 1. **Per-platform health.** Each platform compared to itself over time. Trending up, flat, or down? 2. **Effort-to-output ratio.** How much time per platform vs how much it's producing? 3. **Strategic alignment.** Is the platform driving the outcomes that matter to your business? ### The portfolio decision Each quarter, evaluate: - **Which platforms are earning their effort?** - **Which platforms are auto-pilot maintenance with no upside?** - **Which platforms have surprised you (good or bad)?** - **Where should you reinvest the next quarter's effort?** This is portfolio management. Most creators don't do it; most underperforming portfolios don't get fixed. ### Bolta's role Analyst (the Bolta agent) generates per-platform summaries automatically. You don't need to compile metrics manually: 1. Weekly summary across all platforms. 2. Per-platform health signals. 3. Anomalies flagged (e.g., engagement dropped on Bluesky this week). 4. Suggestions for adjustment. Use Analyst's reports as the input to your quarterly portfolio review. ### Common myths 1. *"More platforms = more reach."* Only if each is well-tended. Otherwise it's just dilution. 2. *"I can't compare platforms."* You can — using ratios and trends, not raw counts. 3. *"Analytics are noise."* They're noise *if* you watch daily. They're signal if you watch quarterly. ### Action Steps 1. Build a portfolio scorecard for the platforms you're on. List each platform; fill in metrics from the last 30 days. 2. Identify which platforms are earning their effort. Honestly. 3. Decide one shift for the next quarter — drop a platform to maintenance, double down on a winner, or test a new one. Cross-platform analytics are about portfolio decisions, not platform comparison. Use them deliberately. Last lesson: building a 1-hour-a-week workflow. ## Relevant links - [Bolta University](https://bolta.ai/university) - [Cross-Platform Repurposing with Bolta](https://bolta.ai/university/courses/cross-platform-repurposing) - [Bolta pricing](https://bolta.ai/pricing)