How Much Does Engagement Rate Vary Within the Same Follower Range? — Findings from 487 Performance Records

Let's start with the conclusion. Even when comparing accounts whose follower counts fall within nearly the same range, the engagement rate (ER) on their posts varies this much. This is the result of aggregating 487 records from our performance data where we could compare figures using a consistent denominator: follower count.

Note that all figures in this article are anonymized, aggregate statistics and do not indicate any specific account, brand, or campaign. Of the 870 records for which ER was documented, 94.5% were Instagram posts, so please read the following as findings specific to Instagram.

Why We Examined This Number

When narrowing down candidate accounts, it's common to use follower count "ranges" as a rough benchmark—an intuitive sense that an account with, say, tens of thousands of followers should generate a certain level of response. However, as we reviewed our day-to-day performance records, we became curious about how well that intuition actually holds up. Does matching follower count levels also mean ER levels will roughly match? This time, we tested that question against our performance records.

What We Compared, and On What Basis

When we extracted the records that documented ER, we found 870 applicable records. However, checking these 870 records one by one revealed that the "denominator" used for the reported ER values was not consistent. Values were a mix of those calculated using per-post reach or impressions as the denominator, and those calculated using follower count as the denominator—44% used reach/impressions as the basis, and 56% used follower count. Because reach-based figures use a smaller base, they tend to produce higher numbers. If we compare these two types without separating them, we can no longer tell whether an apparent difference reflects "differences due to follower count" or simply "differences in how the figure was recorded."

So in this article, we limited our scope to the 487 records that could be confirmed as using follower count as the denominator. All figures below are engagement rates calculated against follower count.

Results: Variation Within a Range Is Larger Than Variation Between Ranges

We divided follower counts into four ranges (up to 30K / 30K–100K / 100K–300K / 300K and above) and calculated the interquartile range (IQR—the width covering the middle 50% of the distribution) for each.

Comparing the median values across ranges, the gap between the highest and lowest range is only 1.44 percentage points (ranging from 2.00% to 3.44%). On the other hand, looking within each range, the spread (IQR width) among accounts belonging to the same range reaches 2.52 to 3.80 percentage points. In other words, individual variation within the same range is larger than the difference between ranges.

In other words, even if you match accounts solely on the condition of "around 100,000 followers," the ER of the accounts included in that group is widely distributed, from high to low. Follower count level alone cannot tell you how much response a given post will generate.

Going Further: How Much Information Does a Follower Range Actually Carry?

The idea that "follower count alone isn't enough to decide" may already be well known. What we want to pause on here is what comes next.

The fact that within-range variation exceeds between-range differences suggests that framing candidates in terms of a "follower range" may not carry as much information as we assume. A group labeled "accounts in the 30K–100K follower range" is not, in fact, a sufficiently homogeneous group to justify treating the accounts within it as interchangeable members of the same category.

This is not to say that using follower ranges to narrow down a candidate list is wrong. It functions well as a first-pass filter for building a long list. However, if a follower range is used as the basis for subsequent prioritization or final selection, that judgment ignores the individual variation spread throughout that same range. Narrowing down only becomes meaningful once you look past the range and examine individual performance records.

Distinguishing Where a Follower Range Is Useful

Given these results, the role of follower range information needs to be considered differently depending on the situation in which it's used.

• Building a long list: It remains effective as a first-pass filter for roughly narrowing down the target range according to the scale of a campaign.
• Prioritizing candidates: Rather than relying solely on the range level as justification, a step is needed to check individual performance records—specifically, how much response accounts have generated within that same range.
• Aligning expectations when proposing: Assuming a uniform benchmark such as "this range should generate this level of response" risks diverging from reality once you account for the performance variation that exists within that same range.

While a follower range can function as an entry point for gathering candidates, on its own it cannot serve as the basis for explaining why one particular account was chosen.

The Scope of This Data

This analysis rests on several premises. The data comes from our own company's performance records and is not a sample representative of the industry as a whole. This analysis does not include records that lacked an ER figure (or where a figure was present but could not be read as a numerical value). Additionally, among the 870 records where an ER figure was present, those judged to use reach or impressions as the denominator were also excluded, in order to keep the yardstick consistent. The absence of a recorded figure simply means that, for operational reasons, no record was retained—it does not indicate that the ER was low. Furthermore, the follower counts used here reflect values at the time of recording and may not match the follower count at the time the post was made, since accounts grow over time. We note this explicitly as a caveat that may affect the precision of the figures.

Closing Thoughts

Follower count level can serve as one benchmark for narrowing down candidates. However, it alone cannot predict how much response a post will generate. We believe the next step is to recognize how wide the spread can be within the same range, and to look at individual performance records accordingly.

We plan to continue sharing insights drawn from our performance records in future articles.

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Source: Survey by STATS INC. (performance records from in-house campaigns). Aggregated only from records with a documented engagement rate that could be confirmed as using follower count as the denominator. These records have been statistically processed so that no specific campaign, brand, or time period can be identified.