Google Keyword Volume: Should You Remove Suspicious Months?
No—do not automatically delete months that look suspicious in Google keyword-volume data. First check what the numbers represent and whether the change reflects seasonality, a reporting limitation, or a genuine shift; exclude or annotate data only when you can document a specific error and explain the effect.
What Google keyword volume measures
“Google keyword volume” can refer to different data sources, and that distinction matters before judging a month as an outlier. Google Ads Keyword Planner reports estimates of average monthly searches for a keyword and related settings, such as location and search network. Google Search Console reports impressions and clicks for your own site’s search results, not the total number of searches made by everyone. Third-party SEO tools estimate demand using their own methods and may group close variants or smooth results.
These measures are not interchangeable. A Keyword Planner figure is not a count of visits to your website, and a Search Console impression is not necessarily one unique person or one search. If a spreadsheet combines figures from different sources, locations, match settings, or date ranges, an apparent anomaly may come from inconsistent inputs rather than unusual search behavior.
Why a month can look suspicious
A sudden spike or drop deserves investigation, but it is not proof that the month is wrong. Search interest often changes with the calendar. Searches for “tax deadline” may rise around filing season; “winter coat” may be more popular in colder months; and a product or event can attract attention after a news story or launch.
Other explanations include:
- Partial or mismatched date ranges: A report may cover an incomplete month, or the comparison may use different numbers of days.
- Changed settings: Location, language, search network, keyword match type, or date range may differ from earlier exports.
- Close variants and grouping: A tool may combine similar queries, change its grouping, or show rounded estimates.
- Low search demand: Small numbers can move sharply in percentage terms. A change from 10 to 20 is a 100% increase, but only 10 searches in absolute terms.
- Data processing or export problems: Duplicated rows, missing values, shifted columns, filters, or an accidental formula can create false outliers.
- Real changes in demand: A product becoming available, a trend fading, or a change in how people search can alter volume.
How to check an unusual month
Start by verifying the source and the exact metric. Record whether the figure is from Keyword Planner, Search Console, or another tool, and preserve the original export. Then compare like with like: use the same keyword, location, language, network, match setting, and complete calendar months. Check whether the source reports actual monthly figures or an average over a selected period.
- Inspect the raw data. Look for blanks, duplicate entries, misplaced decimal points, unexpected text, and formulas that include the wrong cells.
- Check the surrounding months. A one-month jump followed by a return to the previous level may suggest an event or a data issue. A gradual rise over several months may indicate a lasting shift.
- Compare related queries. If closely related keywords move together, the change may be a broader demand pattern. If only one row changes, inspect that query and its settings.
- Check an independent source or report. This can help distinguish a broad trend from a problem in one export, though different tools may use different definitions and estimates.
- Write down the decision. Note what you checked, what you concluded, and whether the value remains in the analysis. This makes later comparisons more reliable.
Keep, exclude, or flag the data?
For most analyses, keep the original values and add a note or flag to months that need review. That preserves the audit trail and avoids making the historical record look cleaner than it is. If the data is valid but unusual, include it in the main series and explain the likely cause. If you want to show a trend without one exceptional event dominating the picture, present a second view with a clearly stated adjustment rather than silently replacing the original.
Exclusion is reasonable when you have evidence of a specific defect—for example, a duplicated row or an incomplete reporting period that cannot be compared fairly. Keep the excluded value in a source sheet, state the reason, and show whether the conclusion changes with it included. Do not remove a month simply because it disagrees with an expected pattern or makes a trend less convenient.
A useful distinction is between flagging and deleting. A flag calls attention to a value for review; it does not assert that the value is false. Deletion discards information and can conceal a real seasonal peak or a meaningful change in demand.
How to interpret trends without overreacting
Look at absolute values as well as percentage changes. A large percentage movement from a very small baseline may have little practical significance. Also separate a short-lived spike from a persistent change: one unusual month is weak evidence of a long-term trend, while a consistent pattern across several months is more informative.
For seasonal topics, compare the same month across different years when comparable data is available. Comparing December only with November may confuse normal seasonal behavior with growth. If you calculate a yearly average, decide in advance how to handle missing or partial months, and state that method. Do not fill missing months with zero unless zero is truly what the source recorded; “no data” and “no searches” are different claims.
Finally, keyword-volume estimates are useful for planning and comparison, not guarantees of future traffic. Rankings, competition, search-result features, audience location, and a page’s relevance can all affect whether searches turn into impressions or visits. Treat volume as one signal alongside your own performance data and the search intent behind a query.
Frequently Asked Questions
Should I delete an outlier month from keyword-volume data?
No, not just because it looks unusual. Verify the source and settings first. Keep a valid value, flag it if needed, and exclude it only when you can identify a concrete data problem.
Does Google Keyword Planner show exact monthly searches?
Keyword Planner provides estimates, not a guaranteed count of exact searches. The displayed figures depend on the selected settings and reporting period, so use consistent settings when comparing values.
Why does keyword volume differ between tools?
Tools can use different data sources, update schedules, keyword groupings, locations, and estimation methods. Compare figures within the same tool and setup rather than assuming every provider measures the same thing.
Should I replace missing search-volume data with zero?
Only if the source explicitly indicates zero. A blank or unavailable value means the data is missing or unreported; replacing it with zero can distort averages and trend charts.
How many months should I use to judge a keyword trend?
There is no universal cutoff. Use enough comparable history to account for the topic’s seasonality, and avoid drawing a long-term conclusion from a single unusual month.
Related
Method: the standard formula for this calculation, rounded as each result states. See how the calculators work or report an error.