One of the most common warnings about buying Instagram likes is that they "fall off" — that the engagement you pay for quietly disappears a few weeks later. It is repeated constantly, and almost never with data. So we looked at our own.
This is a small, deliberately bounded study: we analyzed every completed Instagram-likes order in a fixed window and tracked what happened to the public like count on each targeted post for the next 60 days. No sampling, no projection — just every order in the window, followed to day 60.
What we did
We took every Instagram-likes order completed on Likes.io between 28 April and 8 May 2026, then recorded the public like count on the targeted post at four checkpoints after delivery: day 1, day 7, day 30, and day 60. After filtering out orders we could not verify (private accounts, posts removed by the owner, orders flagged for refund, and a handful of test rows), we were left with 65 orders with a complete four-point curve.
For each order we normalized the day-1 count to 100% and tracked the count relative to that baseline. We report the median, not the mean — a couple of posts caught organic momentum and multiplied their likes, which would drag a mean upward and misrepresent the typical order.
Finding 1: 60 days later, the likes are still there
Across all 65 orders, the median post held essentially all of its day-1 engagement for two full months. It actually drifted slightly up through day 30 before settling just below the starting line at day 60.
| Checkpoint | Median likes retained (vs. day 1) |
|---|---|
| Day 1 | 100% |
| Day 7 | 100.5% |
| Day 30 | 100.7% |
| Day 60 | 98.4% |
Put another way: 54 of the 65 orders (83%) still held at least 90% of their day-1 likes after 60 days, and 42 of 65 (65%) held at least 95%. The "your likes will vanish" story simply did not show up in the data. If anything, the paid engagement tends to sit still while organic likes accumulate on top of it.
Finding 2: smaller orders hold better than big ones
The retention picture changes with order size. Smaller orders didn't just hold — they grew, because a modest like count is easier for organic reach to overtake. Larger orders showed the clearest decay.
| Order size | Orders | Median retention at day 60 |
|---|---|---|
| Under 200 likes | 38 | 105.0% |
| 200–999 likes | 21 | 95.7% |
| 1,000+ likes | 6 | 89.9% |
The pattern is consistent with the idea that platform integrity checks are volume-triggered rather than time-triggered: a small bump blends into normal activity, while a large one-shot spike is more likely to be trimmed. It's a hypothesis, not a proof — but it lines up with what we saw.
What this means if you're buying likes
- Retention is not the thing to worry about. Across real orders, the likes stuck around. Worry instead about whether the accounts are real, whether delivery is paced, and whether the provider ever asks for your password.
- Smaller, paced orders behave best. Several modest orders spread across posts held better than one large drop on a single post.
- Treat it as a starter signal, not a strategy. Likes that stick are still cosmetic. They buy first-impression credibility; they do not build a community or drive sales on their own.
Limitations (the honest part)
This is a deep look at a small, real dataset — not a statistically powerful study, and we won't pretend it is.
- N = 65. Enough to see a clear pattern, not enough to publish tight confidence intervals. The 1,000+ tier in particular is only 6 orders.
- One platform, one service. Instagram likes only. TikTok, YouTube, and Instagram followers may behave differently.
- Public count, not paid-only. We measured the post's total public like count over time. We can't separate paid likes from organic ones, so figures above 100% reflect organic accumulation layered on top — not the platform "adding" paid likes.
- All feed posts. The window contained no Reel orders, so we can't yet compare Reel vs. feed retention. That's the next study.
- One 10-day window. Seasonality and algorithm changes could shift these numbers in another period.
Methodology
Data source: Likes.io's own production order records, aggregated and anonymized — no usernames, no order details, only the retention curves. Engagement counts were read from public post data at each checkpoint. Orders for private accounts, removed posts, or refunds were excluded before analysis. We analyzed every qualifying order in the window rather than sampling, so within that window we miss nothing.
We'll re-run this on a larger window and add Reels, TikTok, and followers as the tracked dataset grows.