SEO Data Analysis

Data analysis that tells you
what to do next.

Most businesses are collecting more data than they know what to do with. GA4 events, Search Console impressions, rank tracker exports, CRM records, and advertising platform metrics, all sitting in separate platforms telling different parts of the same story. The problem isn't a lack of information. It's that nobody has stitched it together into a coherent narrative that helps you make better decisions about where to invest your time and budget.

I approach data analysis as an SEO practitioner first and an analyst second. When I see a traffic drop, I know whether to investigate algorithm updates, technical issues, or seasonal patterns. When conversion rates shift, I can distinguish between a tracking problem and a genuine performance change. That contextual understanding is what separates useful analysis from pretty dashboards that raise more questions than they answer. I also bring Python scripting to the table, which means I can automate repetitive analysis, process datasets that would break a spreadsheet, and build custom pipelines that connect your platforms into a single source of truth.

What's Included

What does SEO data
analysis cover?

📈

GA4 Analysis & Interpretation

Deep-dive analysis of your Google Analytics 4 data. User behaviour flows, acquisition channel performance, engagement metrics, and audience segmentation, translated into recommendations you can act on rather than charts you file away.

  • User behaviour flow analysis
  • Acquisition channel breakdown
  • Engagement metric interpretation
  • Audience segmentation
  • Landing page performance
★

Search Console Deep Dives

Comprehensive analysis combining Search Console data with rank tracking and on-site analytics. Understand exactly which pages, keywords, and content types are driving your organic growth, and which are underperforming relative to their potential. The Grass case study is a good example of what this analysis looks like in practice, where Search Console data helped identify the opportunities behind 850% traffic growth.

  • Query and page performance analysis
  • Click-through rate optimisation
  • Content type benchmarking
  • Keyword portfolio tracking
  • Organic trend identification
⚙

Custom Looker Studio Dashboards

Bespoke dashboards that pull data from multiple sources into a single, live view. Designed for your specific stakeholders with interactive filtering, date comparisons, and automated reporting so you're never working from stale numbers.

  • Multi-source data integration
  • Stakeholder-specific views
  • Automated data refresh
  • Interactive filtering
  • Shareable live links
🔍

Conversion Funnel Analysis

Detailed examination of your conversion paths from first touch to final action. Identify where users drop off, which channels deliver the highest-quality traffic, and where small changes to the tracking setup or user journey can yield disproportionate returns.

  • Full funnel mapping
  • Drop-off point identification
  • Channel quality comparison
  • Attribution modelling
  • Micro-conversion tracking
🎯

Python-Powered Analysis

Custom scripts and automation for tasks that go beyond what manual analysis can handle. Large-scale URL analysis, API data pulls, statistical correlation testing, keyword classification models, and repeatable pipelines that deliver insights automatically.

  • Large-scale data processing
  • API integration and automation
  • Statistical analysis
  • Custom classification models
  • Repeatable analysis pipelines
Why Work With Me

What makes this data
analysis different?

SEO Context, Not Just Numbers

Data without context is noise. I interpret your analytics through the lens of search behaviour, algorithm patterns, and competitive dynamics, because I've spent over fifteen years working in the channels that generate the data. The difference between "traffic dropped 20%" and "traffic dropped 20% because Google re-evaluated intent for your primary keyword cluster" is the difference between panic and a plan. That contextual understanding is also what connects analysis to demonstrating real ROI from your SEO investment.

Python When Spreadsheets Can't

When Excel hits its limits, I don't. Custom Python scripts let me automate analysis workflows, process datasets at scale, and build repeatable pipelines that turn raw data into insights without manual effort. From API integrations to statistical modelling, the technical depth is there when your data demands it.

Cross-Channel Perspective

SEO doesn't exist in isolation. I connect data from organic search, paid media, social, email, and CRM systems to give you the full picture of how your channels interact and influence each other. Understanding that interplay is often where the most valuable strategic insights live. This analysis capability is also available through my white-label SEO service for agencies that need analytical depth without building an in-house data team.

How It Works

How does the analysis
process work?

01

Data Audit

I start by reviewing what data you're collecting, how it's structured, and where the gaps are. There's no point analysing data that isn't accurate, so we get the foundations right first and fix any tracking issues before drawing conclusions.

02

Define Questions

What do you actually need to know? I work with you to define the specific business questions the analysis needs to answer, ensuring every hour of work is commercially relevant and directly connected to decisions you need to make.

03

Analyse & Connect

I dig into the data, cross-reference sources, identify patterns, and build the visualisations that make complex information accessible. This is where Python scripting and custom dashboards earn their value.

04

Recommend & Automate

Findings are distilled into prioritised, actionable recommendations. Where appropriate, I build automated dashboards and reporting pipelines so the insights keep flowing beyond the initial engagement.

Common Questions

Data analysis
questions answered.

I work with GA4, Google Search Console, Ahrefs, SEMrush, Moz, Screaming Frog log data, Looker Studio, BigQuery, and most rank tracking platforms. If a tool offers API access or data exports, I can integrate it. I also connect CRM data, advertising platform data, and e-commerce transaction data where cross-channel analysis is needed.

Python handles tasks that would be impractical in spreadsheets: processing hundreds of thousands of URLs for crawl analysis, automating data pulls from multiple APIs, running statistical tests on ranking correlations, building custom classification models for keyword intent, and creating repeatable pipelines that deliver insights without manual effort. It's particularly valuable for large sites where the data volume exceeds what manual analysis can handle.

Not at all. Part of the service is translating complex data into language that makes sense for your role and experience level. Whether you're a marketing director who wants strategic context or a business owner who wants to know if SEO is working, I tailor the output to your level of technical comfort. You don't need to be data-literate; you just need to be clear about the business questions you want answered.

Reporting tracks and presents known metrics on a regular schedule: rankings, traffic, conversions. Data analysis goes deeper, investigating why things are happening, identifying patterns across datasets, and uncovering insights that regular reporting doesn't surface. Think of reporting as the dashboard and analysis as the investigation you run when the dashboard shows something unexpected. Both are valuable; they serve different purposes.

Yes, and that's often one of the most valuable deliverables. I build Looker Studio dashboards that pull live data from your connected sources, with filtering, segmentation, and date comparison built in. They're designed to be self-service: your team can explore the data, answer their own questions, and share views with stakeholders without needing to wait for the next scheduled report.

Ready to Start?

Turn your data into
revenue decisions.

Got data you're not using, or revenue you suspect is hiding in your analytics? Let's find out where the money is and what's blocking it.

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