Facebook Ads Frequency Calculator
Frequency from impressions and reach, the share of spend beyond your effective-frequency threshold, and what capping it would free up.
Impressions 1,840,000
Reach 295,000
Frequency 6.24
which is the average times each person saw it, and an average hides a long tail
Audience 1,200,000, so you reached 24.6% of it
Spend $8,400.00
CPM $4.57
cost a person reached $0.0285
click-through rate 0.799%
cost a click $0.57
Against an effective frequency of 3.0
impressions needed 885,000
impressions delivered 1,840,000
beyond the threshold 955,000, 51.9% of the total
spend beyond it $4,359.78
reading over the threshold, so extra impressions are buying less with each one
Capping frequency at 4.0
impressions delivered 1,180,000
impressions freed 660,000
spend freed $3,013.04
extra people it could reach 165,000 at the same frequency
which would be 38.3% of the audience
Frequency at other reach levels, same impressions
reach 147,500 frequency 12.47
reach 295,000 frequency 6.24 ← yours
reach 442,500 frequency 4.16
reach 590,000 frequency 3.12
Frequency is 6.24: 1,840,000 impressions over 295,000 people. It is an
average, and the distribution behind it is skewed: most people saw the
ad once or twice and a small group saw it many times, which is where the
wasted budget and the negative feedback both come from.
The three-exposure rule comes from Herbert Krugman's work in the early
1970s, on television, and it has been repeated ever since. It is a
reasonable prior and not a law: the honest version is that effectiveness
rises steeply for the first few exposures and flattens somewhere in the
middle single figures, and where exactly depends on the medium, the
message and how well known the brand already is.
51.9% of the impressions are beyond your threshold of 3.0, which is
$4,359.78 of spend. Those are the impressions most likely to be buying
irritation rather than attention.
Ad fatigue shows up in the metrics before it shows up in the results:
click-through rate falls, cost per result rises, and negative feedback
climbs. Watching those three over time is more informative than any
frequency target, because the point at which they turn is specific to
the creative.
A frequency cap is a blunt instrument and usually the right one. It
moves spend from the people who have seen the ad many times to people
who have not seen it at all, and the arithmetic above shows how many
that buys.
New creative resets fatigue more reliably than a cap does. The same
message seen eight times performs worse than two messages seen four
times each, which is why rotation matters more than the cap number.
Reach and frequency are platform estimates, not counts. Cross-device
identity, shared devices and logged-out browsing all blur reach, and
every platform measures it differently, so comparing frequency between
platforms is comparing two models rather than two campaigns.
Output is valid and updates as you type.
Fix the highlighted fields to update the output.
Frequency is impressions over reach: the average number of times each person saw the ad. The word average is doing the work. A frequency of 6.24 usually means most people saw it once or twice and a small group saw it twenty times, and that small group is where the budget goes and where the complaints come from.
On the campaign below, 51.9 percent of the impressions are beyond the third exposure, which is $4,360 of an $8,400 spend. Whether that is waste depends on the creative and the category, and it is worth knowing the number either way.
How to use
- Put in the impressions and the reach.
- Set your effective frequency. Three is the classic figure and it comes from television research in the 1970s.
- Model a cap to see what it would free and how many more people that could reach.
Example
Impressions 1,840,000
Reach 295,000
Frequency 6.24
Audience 1,200,000, so you reached 24.6% of it
Spend $8,400.00
CPM $4.57
cost a person reached $0.0285
click-through rate 0.799%
Against an effective frequency of 3.0
impressions needed 885,000
beyond the threshold 955,000, 51.9% of the total
spend beyond it $4,359.78
reading over the threshold, so extra impressions are buying less with each one
Capping frequency at 4.0
impressions freed 660,000
spend freed $3,013.04
extra people it could reach 165,000 at the same frequency
which would be 38.3% of the audiencePitfalls
The three-exposure rule is a prior, not a law. It comes from Herbert Krugman’s work in the early 1970s, on television. The defensible version is that effectiveness rises steeply for the first few exposures and flattens somewhere in the middle single figures, and exactly where depends on the medium, the message and how well known the brand is.
An average hides the distribution. Frequency of 4 with most people at 1 and a tail at 20 is a different campaign from everybody seeing it four times. Most platforms will show the distribution if you ask; the average alone will not tell you there is a problem.
Watch the metrics, not the target. Ad fatigue shows up as falling click-through rate, rising cost per result and rising negative feedback, and those turn at a point specific to the creative. Watching them beats any frequency number.
New creative resets fatigue better than a cap does. The same message seen eight times performs worse than two messages seen four times each. Rotation matters more than the cap.
A cap moves spend rather than saving it. It takes impressions away from people who have seen the ad and gives them to people who have not, which only helps if there is audience left. The figures above show how much that buys.
Reach and frequency are platform estimates. Cross-device identity, shared devices and logged-out browsing all blur reach, and every platform models it differently. Comparing frequency across platforms compares two models.
A small audience forces frequency up. With a narrow audience and a meaningful budget, high frequency is arithmetic rather than a mistake: the only fixes are a wider audience or less spend.
Compatibility
Arithmetic in the browser: nothing is uploaded and nothing is stored.
Frequency is impressions over reach, and the tool refuses reach above impressions, since everybody counted in reach saw at least one impression. Impressions beyond the threshold are the total less reach times the effective frequency, which assumes every person reached the threshold before anybody passed it: that understates the waste, because the real distribution is skewed, so the figure is conservative.
The cap model assumes the freed impressions could be delivered to new people at the capped frequency, which needs the audience to be large enough. The audience field is there to show whether it is.
CPM is spend over impressions times a thousand, and cost per person reached is spend over reach, which is the figure that matters for a reach campaign and is almost never quoted.