"Best time to post" explains under 4% of reach variance
We regressed reach against publish hour. It is the most overhyped variable in the niche.
— Publish-time band: explains 3.8% of variance
— Hook/first-3-seconds quality: 31%
— Save+share rate: 27%
— Account health (active-follower share): 19%
Timing matters only at the margins — avoid your audience's dead hours and you have captured nearly all the available gain. Optimizing for the "perfect" minute is rearranging 4% while ignoring the 58% that lives in content and signal.
n=1,200 posts, multivariate regression, 60-day window.
We regressed reach against publish hour. It is the most overhyped variable in the niche.
— Publish-time band: explains 3.8% of variance
— Hook/first-3-seconds quality: 31%
— Save+share rate: 27%
— Account health (active-follower share): 19%
Timing matters only at the margins — avoid your audience's dead hours and you have captured nearly all the available gain. Optimizing for the "perfect" minute is rearranging 4% while ignoring the 58% that lives in content and signal.
n=1,200 posts, multivariate regression, 60-day window.
Reach rate decays 41% between hour 1 and hour 24 post-publish
The first hour carries most of the signal. After that, the algorithm stops pushing.
— 0-60 min: ████████ 100% (baseline distribution)
— 1-6 hr: █████ 67% of remaining reach delivered
— 6-24 hr: ██ 26%
— 24-72 hr: ▏ 7% (almost entirely Explore/saves)
The practical read: if a post underperforms in the first 60 minutes, it rarely recovers. Saves and shares in that window are the strongest predictors of the long tail.
n=1,840 posts across 92 accounts, 30-day window.
The first hour carries most of the signal. After that, the algorithm stops pushing.
— 0-60 min: ████████ 100% (baseline distribution)
— 1-6 hr: █████ 67% of remaining reach delivered
— 6-24 hr: ██ 26%
— 24-72 hr: ▏ 7% (almost entirely Explore/saves)
The practical read: if a post underperforms in the first 60 minutes, it rarely recovers. Saves and shares in that window are the strongest predictors of the long tail.
n=1,840 posts across 92 accounts, 30-day window.
Follower velocity halves at the 25k mark for 73% of accounts in our sample
Growth is not linear. There is a measurable wall where net-new slows independent of posting cadence.
— 1k-10k: median +4.1% weekly
— 10k-25k: +2.3%
— 25k-50k: +1.0% (the plateau)
— 50k-100k: +0.6%
Delta between cohort 2 and 3 is the steepest drop in the dataset. The cause is saturation of the warm audience (mutuals-of-mutuals); past 25k, growth depends almost entirely on cold Reels distribution.
n=610 accounts, 90-day window.
Growth is not linear. There is a measurable wall where net-new slows independent of posting cadence.
— 1k-10k: median +4.1% weekly
— 10k-25k: +2.3%
— 25k-50k: +1.0% (the plateau)
— 50k-100k: +0.6%
Delta between cohort 2 and 3 is the steepest drop in the dataset. The cause is saturation of the warm audience (mutuals-of-mutuals); past 25k, growth depends almost entirely on cold Reels distribution.
n=610 accounts, 90-day window.
FAQ: What link-click rate should I expect from my bio/Stories?
Low, and that's normal — these are weak-intent surfaces.
— Bio link: median ~0.5-1.5% of profile visitors click
— Story link sticker: median ~1-3% of Story viewers
— Story link after a strong CTA frame: ~4-8%
Profile-visit-to-click beats follower-to-click as your denominator; most followers never see a given Story.
So what: measure clicks against the surface that actually saw the link, not total followers. And gate the link behind a value frame — the CTA setup roughly 3x's the click rate. (n=470 accounts, 30-day window)
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Доп. контекст по cost per link — @LinkBuildIndex
Low, and that's normal — these are weak-intent surfaces.
— Bio link: median ~0.5-1.5% of profile visitors click
— Story link sticker: median ~1-3% of Story viewers
— Story link after a strong CTA frame: ~4-8%
Profile-visit-to-click beats follower-to-click as your denominator; most followers never see a given Story.
So what: measure clicks against the surface that actually saw the link, not total followers. And gate the link behind a value frame — the CTA setup roughly 3x's the click rate. (n=470 accounts, 30-day window)
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Доп. контекст по cost per link — @LinkBuildIndex
Caption keyword search now drives 3.2x more non-follower reach than hashtags
We tagged impression sources across a matched-pair test. Hashtags are no longer the discovery lever.
— Search/keyword surface: ██████ 31% of non-follower reach
— Hashtags: ██ 9.6%
— Reels feed/Explore: ████████ 47%
— Audio page: ██ 12%
Accounts that moved their target terms from hashtag blocks into the first caption line and on-screen text saw a median +18% search reach within 21 days. Hashtags still help topical classification, not volume.
n=240 accounts, paired A/B, 45-day window.
We tagged impression sources across a matched-pair test. Hashtags are no longer the discovery lever.
— Search/keyword surface: ██████ 31% of non-follower reach
— Hashtags: ██ 9.6%
— Reels feed/Explore: ████████ 47%
— Audio page: ██ 12%
Accounts that moved their target terms from hashtag blocks into the first caption line and on-screen text saw a median +18% search reach within 21 days. Hashtags still help topical classification, not volume.
n=240 accounts, paired A/B, 45-day window.
Engagement rate by niche spans a 6x gap at the same follower count
Comparing ER without controlling for niche is meaningless. Same 10k-50k cohort:
— Personal finance: █████ 5.8%
— Fitness/coaching: ████ 4.1%
— Travel: ███ 3.0%
— Fashion/apparel: ██ 2.2%
— E-commerce product: █ 0.9%
The driver is comment intent: finance and coaching provoke questions, apparel provokes silent saves. If your niche sits low, benchmark against your niche median, not the platform-wide 1-3% figure that gets quoted everywhere.
n=1,420 accounts, ER = (likes+comments+saves)/reach, 30-day window.
Comparing ER without controlling for niche is meaningless. Same 10k-50k cohort:
— Personal finance: █████ 5.8%
— Fitness/coaching: ████ 4.1%
— Travel: ███ 3.0%
— Fashion/apparel: ██ 2.2%
— E-commerce product: █ 0.9%
The driver is comment intent: finance and coaching provoke questions, apparel provokes silent saves. If your niche sits low, benchmark against your niche median, not the platform-wide 1-3% figure that gets quoted everywhere.
n=1,420 accounts, ER = (likes+comments+saves)/reach, 30-day window.
Story completion drops a median 14% per frame; the cliff is at frame 3
Most accounts post 5-7 frame sequences. The data says trim to 4.
— Frame 1→2: -7% viewers
— Frame 2→3: -11%
— Frame 3→4: -14% (the cliff)
— Frame 4→5: -19%
By frame 5, the median account retains only 58% of frame-1 viewers. Sequences ending at frame 4 carry the highest completion-rate percentile. The one exception: polls/quizzes on frame 2 cut per-frame drop roughly in half by resetting attention.
n=3,100 story sequences, 60-day window.
Most accounts post 5-7 frame sequences. The data says trim to 4.
— Frame 1→2: -7% viewers
— Frame 2→3: -11%
— Frame 3→4: -14% (the cliff)
— Frame 4→5: -19%
By frame 5, the median account retains only 58% of frame-1 viewers. Sequences ending at frame 4 carry the highest completion-rate percentile. The one exception: polls/quizzes on frame 2 cut per-frame drop roughly in half by resetting attention.
n=3,100 story sequences, 60-day window.