For SEO professionals and digital marketers, search volume data is crucial for decision-making. However, many don't realise that these numbers aren't as precise as they appear - they're heavily bucketed into predetermined ranges. With the recent landmark victory of the Department of Justice against Google in the antitrust case (August 2024), there's renewed hope for more transparency in search data. The court found that Google illegally maintained its monopoly through exclusive distribution agreements, and this could lead to significant changes in how Google shares search data with the industry.
If anyone reading this happens to know Judge Amit Mehta or Jonathan Kanter, the DOJ’s antitrust division head... our analysis shows that Google could provide much more accurate search volume data without compromising user privacy or their competitive position. The current bucketing system, while clever, artificially constrains the utility of the data for businesses trying to make informed decisions.
In this analysis, we reveal how Google actually buckets search volumes and what this means for your SEO strategy. Understanding these limitations is crucial for making informed decisions, especially given the potential for change in how search data might be shared in the future.
Background on how Google shares keyword demand data
This article examines the different ways Google provides search volume values for keywords and highlights some of the problems with the data it provides.
The research study stemmed from a question a customer asked me. He wanted to know why for certain keywords he would often see static monthly search volumes for many months in a row, yet for others he would see regular month-on-month changes.
To answer his question, I analysed a set of 60 million keywords, across multiple languages and countries from our keyword database, to try and understand how many different ‘Search Volume Buckets’ (See ‘1.b’ below) there are as I could not find this published anywhere.
Google’s Keyword Tools
Google has two main ways of providing data about demand for a given keyword or set of keywords:
1. Google Ads Keyword Planner
You can use the Keyword Planner to collect search volumes data, but the data returned varies depending on whether you are spending any money with Google:
I. ‘Absurd Search Volume Ranges’ – If you do not have a live Ads campaign then Google gives you a set of 7 ridiculous and useless huge search volume ranges that your keyword falls into.
II. ‘Search Volume Buckets’ – If you have a live Ads campaign then Google gives you a much narrower set of around 60 search volume value ranges that your keyword falls into.
2) Google Trends
Freely available – but very limited as it only returns an index from 0 to 100 showing relative demand when comparing up to 5 keywords.
1. i) Google Ads Keyword Planner ‘Absurd Search Volume Ranges’
Google made a change a few years ago which forced you to have a Google Ads campaign running to get ‘exact search volumes’ for your keywords from Google’s Keyword Planner. Prior to this you just needed an AdWords account to use Keyword Planner and get reasonably useful but still bucketed data. Some might even say this was anti-competitive given Google’s monopoly position – but let’s save that for another day.
After this change, if you did not have a live ad campaign running then you would get what I am going to call for the purposes of clarity ‘Absurd Search Volume Ranges’.
Keyword Planner Ranges (Without Active Campaign)
Why These Absurd Ranges Are Problematic
1. They are way too broad to be actionable
2. There’s no way to distinguish between important volume differences for keywords that you might have a chance to rank for
3. This makes prioritisation difficult
4. It entirely masks seasonal trends entirely
So, these are absurd and completely useless.
1. ii) Google Ads Keyword Planner ‘Search Volume Buckets’
Key Research Findings
- Google uses approximately 60 predetermined buckets for search volumes
- The bucket size increases proportionally with volume
- Larger volume keywords require significant changes to show any month-on-month movement
- This system explains why many keywords show static monthly search volumes for many months in a row
Methodology
We analysed over 60 million keywords across all countries, focusing on the most recent month's data. Our process:
1. Extracted all keyword search volumes from Google's API
2. Calculated frequency of each unique search volume
3. Filtered to volumes appearing >100 times to identify systematic buckets
4. Analysed the mathematical relationships between these buckets
The Complete Bucket System
We identified 60 distinct buckets that Google uses for search volumes. Here they are in ascending order:
Please note, whilst we analysed a lot of keywords across many countries, there may be a few search volume bucket ranges even higher than the 7,480,000 top of the range value we have in our database. But if we weren’t tracking these keywords then they may be absent from the data we analysed. I’m not sure it matters in the grand scheme of things, as there won’t be too many of us SEOs optimising for ‘Facebook login’.
Let me first touch on the utility (or lack of) of Google Trends and then I can go into why I'm so animated about Google's irritating practice of bucketing keywords into search volume ranges and why it matters for SEO.
2. Google Trends
What is Google Trends?
Google Trends is a free tool that shows the relative popularity of search terms over time. Unlike traditional Google search volume data, it presents search interest, or demand if you prefer, as a normalized value from 0-100, where 100 represents the peak popularity for the term during the specified time period. It is useful, but it cannot be used on its own to inform and kind of research whether for SEO or otherwise as it does not give you real values and you can only compare a handful of keywords.
Limitation of Google Trends for SEOs and marketing teams
- Relative numbers only (index of 0-100)
- No absolute search volumes
- Limited historical data
- Sampling issues for low-volume terms
- Delayed data (not real-time)
- Limited geographic granularity
- No API access
- Limited to 5 term comparisons
It's free and if you’ve got this far reading this article, then you’ve probably tried it already. If you haven’t then try Google Trends yourself.
Pros and Cons of using Google Trends for SEO Keyword Research
How to interpret Google Trends data - Dos and Don'ts for SEOs
Why This Matters for SEOs
1. Understanding Static Search Volumes
Ever noticed how some keywords maintain the exact same search volume for months? This isn't because the actual searches are static - it's because real search volume changes need to be substantial to move to a different bucket.
For example:
- A keyword showing 1,000 monthly searches needs:
- 30% increase (to 1,300) to show a higher monthly volume
- 18% decrease (to 880) to show a lower monthly volume
- A keyword showing 110,000 searches per month needs:
- 23% increase to show any growth as the next bucket up is 135,000
- 18% decrease to show any decline as the next bucket down is 90,500
- A keyword showing 1,830,000 monthly searches needs:
- 50% monthly increase to show any growth as the next bucket up is 2,740,000
- 18% decrease to show any decline as the next bucket down is 1,500,000
2. Impact on Different Volume Ranges
Low Volume Keywords (10-100)
- Most volatile in percentage terms
- Need 22-100% change in a given month to move up or down a bucket range
- You may pick up emerging trends if you see movement – although at less than 100 searches per month you may not really care!
Medium Volume Keywords (100-10,000)
- Most useful for trend analysis
- Require ~24-308% change to move up buckets and 12% to 23% to move down buckets
- Arguably the easiest range to detect seasonal patterns
High Volume Keywords (10,000-100,000)
- Very stable bucket system
- Consistent ~22% up/18% down pattern
- May mask smaller but significant changes
Very High Volume Keywords (100,000-1,500,000)
- Extremely stable
- Consistent ~22% up/18% down pattern
- Again important trends can be masked
- Best supplemented with other data sources if you want to understand smaller month-on-month changes in demand
Extremely High Volume Keywords (1,500,000+)
- Extremely stable
- Need huge changes in monthly demand to show any month-on-month movement
- This makes spotting minor monthly seasonal movements in demand tricky to find
- Best supplemented with other data sources
Practical Applications for SEOs
1. Keyword Research and Prioritisation
- Understand that keywords in the same broad range may have very different actual volumes
- Use the bucket system to estimate true volume ranges more precisely
- Consider the effort needed to achieve visible growth in different ranges
2. Trend Analysis
- For low volume terms (<100): Use quarterly or longer periods
- For medium volume terms (100-10K): Monthly analysis is reliable
- For high volume terms (>10K): Be aware of the masking effect making search volumes seem stable when they may not be (for head terms you might want to corroborate with Google Trends data)
- Consider seasonal factors based on bucket movement patterns
3. Reporting and Client Communication
- Explain why volumes might appear static
- Set realistic expectations for volume changes
- Use appropriate time periods for different volume ranges
- Be cautious when reporting on monthly changes
The Real-World Impact of Search Volume Bucketing
Obviously, my focus and use of search volume data is primarily concerned with typical SEO and digital marketing use cases. But, it did occur to me how publicly available, free, accurate and timely (ideally near real-time) data could help governments, organisations and businesses and ordinary people in so many fields:
1. Public Health and Research
Current Limitation
- Health-related queries are bucketed, masking important trends
- Example: "flu symptoms" might appear static when actually there was a big spike 24 hours ago indicating a looming problem for the Health Service
With Accurate Data:
- Early detection of disease outbreaks
- Real-time public health response
- Better resource allocation for healthcare systems
- More accurate epidemiological research
- Better prediction of seasonal health trends
2. Economic Planning
Current Limitation:
- Economic indicators from search trends are delayed and imprecise
- Example: Job-related searches fall into too broad buckets to be really useful
With Accurate Data:
- Real-time economic trend detection
- Better unemployment prediction
- More accurate consumer interest tracking
- Enhanced market research capabilities
- Improved regional development planning matching job supply and demand
3. Emergency Response
Current Limitation:
- Natural disaster-related queries get bucketed and are 1 month behind reality which is useless for anything other than a retrospective look after an emergency situation.
- Example: There's a major incident in a city - real-time access to search data could be useful to see how widespread the effect is.
With Accurate Data:
- Real-time emergency detection
- Better resource deployment
- More effective crisis management
- Improved emergency preparedness
- Better public communication timing
4. Business Planning
Current Limitation:
- Seasonal trends are flattened
- Example: "winter boots" might appear to have the same consumer demand for months in a row missing the uptick in demand
With Accurate Data:
- More precise inventory planning
- Better staffing decisions
- More accurate seasonal forecasting
- More effective marketing timing and planning
- Better investment decisions - e.g. For a new startup.
5. Academic Research
Current Limitation:
- Social trend analysis is imprecise
- Example: Cultural phenomena appear in large buckets
With Accurate Data:
- Better social trend analysis
- More accurate behavioural studies
- Enhanced demographic research
- Improved cultural study methods
- Better educational resource planning
6. Government Policy
Current Limitation:
- Policy impact is hard to measure
- Example: All related queries might have the same search volumes (as Google also annoyingly returns the same bucketed value for close variants of the same keyword).
With Accurate Data:
- Better policy effectiveness measurement
- More responsive governance
- Improved public service planning
- Better resource allocation
- Enhanced public communication
7. Market Research
Current Limitation:
- Product interest appears in broad buckets
- Example: It’s difficult to see an accurate uptick in demand for a new brand, product or campaign launch and it shouldn’t be.
With Accurate Data:
- Better product launch timing
- More accurate market sizing
- Enhanced competitive analysis
- Better investment decisions
- Improved ROI measurement
The Cost of Inaccurate Data
The current bucketing system imposes real costs on society:
1. Delayed Response: Health trends might not be spotted until they're already significant
2. Missed Opportunities: Businesses might miss optimal timing for launches or expansions
3. Inefficient Resource Allocation: Organisations might over or under-allocate resources
4. Reduced Innovation: Startups might struggle to identify genuine market opportunities
5. Impaired Research: Academic and scientific research might miss important patterns
A Call for Change
The DoJ's victory against Google presents an opportunity for reform.
If you are reading this and know someone in the DoJ then please petition them to force Google to open-up unfettered access on fair, reasonable and non-discriminatory terms to accurate search volume data. This could;
1. Enhance public health response
2. Improve economic planning
3. Enable better emergency management
4. Foster business innovation
5. Advance scientific research
6. Improve government services
7. Finally, and perhaps most importantly help competitors enter the search engine market whether as direct competitors to Google, or in specific niches where they have an accurate understanding of true demand!
The technical capability exists - it's now a matter of policy and will.
A Better Way Forward: Proposal for Fair Data Access
Proposed Solution: Fair Search Data Access
1. Technical Implementation
Google could provide:
- Real-Time API: REST API with reasonable rate limits
- Granular Data Access:
- Actual search volumes (not bucketed)
- Actual exact data for the exact keyword (no close variants)
- Device breakdown (desktop/mobile/tablet)
- Geographic data (country/region/city)
- Temporal data (hourly/daily/weekly/monthly)
- Demographics (age ranges/gender - aggregated for privacy)
- Click data (organic vs paid, anonymised of course)
- Rising/falling trends
- Related queries with volumes
2. Fair Pricing Structure
Given its monopoly position and the fact that accurate search volume data amounts to an ‘essential facility’ this should be freely accessible to all or at the very least offered for a negligible cost.
3. Privacy Protection
Understandably, there may need to be some privacy protection by applying minimum thresholds for granular data but no more than exists today.
4. Non-Discriminatory Access
- Standard API terms for all users
- Public documentation
- Open access to rate cards
- Transparent and free or negligible pricing
- No exclusive deals
- Equal access speed/quality/volume of data
- Standard SLAs for all
Call to Action: For SEO & Digital Marketing Professionals - Supporting Fair Data Access
The DoJ's victory presents a unique opportunity to reshape how search data is shared.
Let’s petition the DoJ to include access to accurate search volume data in its proposed remedies!
