Accurately analysing data is one of the most important parts of an effective SEO strategy. But in practice, with so many moving parts, SEO data is sometimes easy to misread.
Many of these factors can be overlooked, leading to incorrect analysis and consequently, wrong conclusions made about what is or isn’t working. This can lead to misguided decisions, wasted budget, or unnecessary changes to strategies that were actually doing their job.
In this article, we go through the most overlooked factors that tend to skew SEO data, seeking to help you interpret your data more accurately and make better decisions.
Analytics Configuration
Before analysing performance, it’s worth checking whether your analytics setup is giving you a reliable foundation in the first place. Misconfigurations are surprisingly common and can affect data for years without being obvious.
Typical issues include:
- Duplicate tracking tags inflating session counts.
- Conversion goals measuring superficial actions instead of meaningful outcomes (e.g., enquiries or purchases).
The worst part is that these things don’t raise obvious red flags, and you might not notice them distorting your data. This is why it’s important to regularly review your setups, so that small tracking issues don’t warp your SEO reporting over time.
Simplistic Attribution Models
Many analytics platforms default to last-click attribution. That means the final interaction before a conversion gets all the credit, even if SEO played a crucial role earlier in the journey.
In reality, many customer journeys look more like this: an organic search introduces the brand, a direct visit follows days or weeks later, and a paid advert finally triggers the conversion. When all the value is attributed to that last click, SEO can appear far less effective than it truly is.
This is especially misleading for higher-consideration products and services, where research and comparison are part of the buying process. Without a broader attribution view, SEO often ends up undervalued.
Visibility Without Clicks
With featured snippets, FAQs, and AI summaries on SERPs, users are now often able to find what they’re looking for without clicking any links.
Given this, it’s little surprise that almost 59% of US and EU Google searches resulted in zero clicks in 2024. As a result, a page can rank well and have strong visibility, but still get fewer clicks than you might hope.
In your data, this can show up as traffic plateauing or even declining – despite rankings and impressions improving.
Changes to Search Results Layout
Another change to SERPs is how frequently they adjust how results are displayed. Additional ad placements, AI-generated summaries, video carousels, and map listings now all compete for attention with traditional blue links.
This means that you shouldn’t see a drop in organic click-through rate as necessarily indicative of weaker rankings or declining content quality.
In many cases, it actually reflects increased competition on the results page itself. However, without context it can look like a performance issue when it’s actually a change in how search results behave.
H2>Data Sampling and Reporting Thresholds
We now have stricter regulations about data privacy. As a result, analytics platforms now tend to rely more on data sampling – only analysing a portion of the data and then extrapolating – and reporting thresholds – limiting how much detail gets shown.
Sampled data can mask real performance issues, such as specific devices, regions, or pages underperforming. Reports may look clean and complete, but the detail needed to spot problems simply isn’t there.
Understanding when data is sampled, and when it isn’t, is critical before drawing firm conclusions.
Bot Traffic and Non-human Sessions
Bots and automated crawlers now regularly access websites, which means not all organic traffic represents genuine customers. These can result in inflated traffic numbers that make your SEO performance seem better than it actually is.
If left unchecked, this can inflate session numbers and create a misleading sense of growth. Maintaining filters to exclude non-human traffic helps ensure performance reporting reflects actual user behaviour, not automated noise.
Network and Access Variables
SEO data can also be influenced by how users access your website. Remote teams, international visitors, agencies, and third-party suppliers might seem like real users in your analytics, even though they aren’t actual potential customers.
Take, for example, split tunnel vs full tunnel VPN users. They can skew your geographic data by seeming like visitors from a different location than where they actually are.
When this isn’t accounted for or filtered out, it can quietly distort your location reports and mislead your strategy around targeting or local SEO.
Over-reliance on Third-party SEO Tools
Third-party SEO tools are invaluable for research and diagnostics, but they do not measure real user behaviour on your site. Metrics like estimated traffic, keyword difficulty, and visibility scores are based on models and assumptions.
These numbers are useful indicators, not facts. When they’re treated as definitive, they can distract from what actually matters: enquiries, sales, and revenue. First-party data should always carry more weight than external estimates.
Content Cannibalisation
Content cannibalisation happens when multiple pages on your site target the same or very similar keywords. Because they’re competing with one another, you actually limit how much visibility they can give you, diluting your rankings in the process.
This can lead to specific pages – like key product or service pages – underperforming even if site-wide traffic looks good. When businesses don’t notice this, they often respond by, say, tweaking on-page SEO elements without realising the real problem.
Real-world Factors
Things like seasonal demand (holidays, back-to-school periods) or broader economic or political changes (tariffs) or industry shifts (new technology, like AI) can all have large effects on your SEO.
For example, it’s reasonable to expect a dip in searches for “accounting services” during August (summer holidays) and a spike during January (tax season).
Failing to account for these things might lead a business to think something is wrong with their SEO when there isn’t – or, conversely, not realise that there’s a genuine drop in performance.
Essentially, don’t forget SEO doesn’t exist in a vacuum.
Final Thoughts
SEO data is powerful, but only when it’s interpreted carefully and in context. Misleading signals are common, and many of them come from factors outside rankings or content quality.
By understanding what can skew your data, and by questioning what you’re really seeing, you’re far better placed to make informed marketing and business decisions based on reality rather than assumptions.
