SEO Analysis

I start every SEO analysis by pulling a baseline. That means 3–6 months of data from Google Search Console: clicks, impressions, average position, and CTR. I also export organic traffic from [Google Analytics](/google-analytics/) if it is configured correctly. Without a baseline, you cannot measure whether anything you do later actually moved the needle. A common mistake is to jump straight into a crawl tool and start flagging errors, but that misses context.

Next, I run a technical crawl using Screaming Frog on the free tier (500 URLs). I look for 404s, redirect chains, broken internal links, and pages that block crawling. I also check page speed with Google's PageSpeed Insights, not to chase a perfect Lighthouse score but to spot pages that load slowly on mobile. Google's SEO Starter Guide emphasises crawlability and canonicalisation, so I verify that every page intended for indexing has a self-referencing canonical and is not blocked by robots.txt or noindex tags.

After technical health, I move to content. I export the pages with the most impressions from Search Console and check whether each page matches the search intent behind its top-ranking queries. For example, if a page ranks for "best running shoes" but is a category page listing products without reviews or comparisons, it is probably underperforming because searchers want editorial content, not a catalogue. I also review internal linking: are the pages I want to rank well receiving enough link equity from other pages on the site?

Then I do a [competitor analysis](/seo-competitor-analysis/). I pick two or three sites that already rank for my target keywords and compare their content depth, page structure, and backlink sources. Tools like Semrush help here, but I also manually review top-ranking pages. The goal is to spot gaps: topics they cover that I do not, or formats (video, guides, tools) that I could adopt.

Finally, I prioritise. I list every issue I found and estimate the impact on traffic or conversions for each. I aim for 5–10 concrete tasks. Analysis without action is busywork.

The biggest trap is treating SEO analysis as a one-time event. I used to run a full analysis, fix everything on a spreadsheet, and then not look again for months. Three months later, Google had updated its algorithm, a competitor had published a better guide, and my rankings had slipped. SEO changes constantly. I now schedule a lightweight analysis every month and a deep one every quarter.

Do not fixate on rankings alone. A page can rank number one for a query with zero conversions because the query is informational and your page is transactional. Connect rankings to business outcomes. Use Google Analytics or a conversion tracking tool to see whether organic traffic actually leads to sign-ups, purchases, or leads. If you are not measuring [Conversion Rate Optimisation](/conversion-rate-optimization/) on your organic landing pages, you are flying blind.

Another watch-out: data noise. Small sample sizes in Search Console (under a few hundred clicks) can show wild swings. Do not act on a 20% drop in clicks over a week; wait for a month of data before drawing conclusions. Similarly, tool scores (like PageSpeed Insights) are diagnostic hints, not verdicts. A page with a 45 mobile score might still rank well if it has strong content and backlinks. I also avoid relying on a single [rank tracking](/rank-tracking/) tool without cross-checking against Search Console.

Analysis paralysis is real. It is easy to keep digging: more tools, more filters, more reports. I stop when I have a prioritised list of actions that I can actually execute within the next week. If a fix will take longer, I add it to a backlog but do not let it stall the current cycle.

I have made several mistakes in SEO analysis over the years. The first: I used to start with technical fixes because they felt concrete and satisfying to cross off a list. But often the biggest opportunity was content. I once spent a week fixing 404s and improving page speed on a client site while ignoring that their core service page was a thin 200-word paragraph that did not answer any of the questions searchers asked. After I rewrote it to 1,500 words with a clear structure, traffic increased 40% in two months. Now I always check content before reaching for the crawl tool.

Second mistake: I used to fix everything I found. Every broken link, every missing alt tag, every meta description that was too short. That is a waste of time. Not all issues matter equally. A broken link on a page nobody visits is not urgent. A missing canonical on your highest-traffic category page is critical. I now score issues by potential impact and only act on the top few.

Third mistake: ignoring mobile usability until the end of the analysis. In 2025, most searches are mobile. If a page has good content but a terrible mobile experience, it will not rank. Now I check mobile usability early using Google's Mobile-Friendly Test and resize my browser to test interactivity myself.

Fourth: I used to rely solely on automated tools for competitor analysis. Tools give you metrics, but they do not tell you why a competitor's page works. I now manually read their top pages, note how they structure information, and ask myself what I would do differently.

These admissions shaped how I run analysis today. I still catch myself slipping into old habits, but the key is to keep the customer's problem—not the tool's output—as the centre of the investigation.