Month-over-month growth calculator
Every step in the series, not just the last two months.
The steady rate that would take the first value to the last one over the same number of steps.
Runs entirely in your browser — nothing is uploaded, nothing is stored. Updated 2026-09-05.
Month-over-month growth is (this month − last month) ÷ last month, as a percentage. Going from 148 to 176 is growth of 18.9%.
Computing that from the last two months is the standard and it is where the metric misleads: a single strong month reads as a trend, and a single weak one reads as a collapse. Enter the whole series below and the calculator returns each step alongside the compound average growth rate across all of them — the figure that tells you what has been happening rather than what happened once.
MoM growth = (current − previous) ÷ previous × 100
On a small base, month-over-month growth is noise
Going from 4 signups to 6 is 50% growth and means nothing — one extra customer would have made it 75%. The percentage amplifies exactly the variation you should be ignoring.
Below roughly a few hundred events per period, read the absolute change and leave the percentage alone. Percentage growth becomes informative when the base is large enough that a single event cannot move it noticeably.
Months are not equal units
February has 28 days and 20 working days; July has 31 and 23. A B2B metric that fell 8% from January to February may have grown per working day. Retail runs into the same problem in reverse each December.
Two fixes, both cheap: normalise to a daily rate before comparing, or use year-over-year for anything with a seasonal shape and keep month-over-month for the fast-moving operational metrics where seasonality is not the dominant term.
Compound average against the last step
The compound figure above answers "what steady rate would have produced this?" — it is the honest summary of a series. The last step answers "what just happened?" and is the right number for an alert.
Reporting only the last step is how a flat six months gets presented as growth, because one month in six will be good by chance. Show both, and the shape of the series stops being arguable.
Computing this from your own accounts
Every calculator on this page takes numbers you typed. The version that keeps working is the one that reads them from the accounts themselves — which is what TableBI is: connect Google Ads, Meta Ads, GA4 or Search Console once, and the series becomes a query you can run from your terminal.
# the same series, straight out of your connected sources tablebi ask "SELECT date_trunc('month', date) AS month, SUM(clicks) AS value FROM metrics GROUP BY 1 ORDER BY 1"
The pinned answer is a live URL that refreshes on its own — here is one running now. No hosted model does the reasoning; your own Claude Code or Codex drives the CLI, which is why there is no inference bill attached to it.
Questions people ask about month over month calculators
How do I calculate month-over-month growth?
Subtract last month value from this month value, divide by last month value, and multiply by 100. From 148 to 176: (176 − 148) ÷ 148 × 100 = 18.9%.
How do I calculate average month-over-month growth across several months?
Use the compound rate rather than the arithmetic mean of the monthly percentages. Divide the last value by the first, raise it to the power of one over the number of steps, subtract one and multiply by 100. Averaging the percentages overstates growth whenever the series is volatile.
Why does my month-over-month growth swing so much?
Usually a small base or unequal months. Below a few hundred events per period a single event moves the percentage several points, and calendar length alone can produce a 10% swing between a 28-day and a 31-day month.
When should I use year-over-year instead?
Whenever the metric has a seasonal shape. Year-over-year compares like calendar periods and removes seasonality; month-over-month is better for fast-moving operational metrics where the latest change matters more than the seasonal pattern.
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