I am a Data/Web Analyst and turn data into action.

Most analytics teams are drowning in data they can't act on.

Manual reports, Dashboards nobody trusts and Metrics that don't connect to revenue.

💡 Here's what I offer:

📊 Automated reporting pipelines: from raw GA4, Search Console, Crawl and Marketing data to dashboards your team actually uses. 

No more Monday morning Excel rituals.

🔍 Custom Analytics Tools: bespoke scripts, apps and tools built for your business

🤝 Group trainings: for agencies or companies that need to upskill and learn how to use web data and build powerful systems to report on their performance

Here's who this is for:

✅ Marketing and analytics teams who've outgrown spreadsheet reporting

✅ Companies investing in Digital Marketing/SEO and Content with no clear way to measure or report it

✅ Leaders who want to stop guessing and start making decisions from real data

📈 What clients get/learn:

🔸 Reporting that runs itself, built on BigQuery, Dataform, and Looker Studio

🔸 A clear picture of what's driving traffic, leads, and pipeline

🔸 Visibility into how you can grow and what your competitors are doing

📩 DM me if you're ready to:

→ Replace manual reporting with automated data pipelines

→ Finally understand what your web data is telling you

→ Save 100s of hours with automation

→ Get ahead of your competitors before it's too late

Marco Giordano

Technical SEO Specialist | Data Analyst Practitioner | Founder of SEO Depths

I am a results-oriented SEO specialist with over 4 years of experience.

For nearly 3 years, I have specialised in technical SEO, focusing on the technical aspects of search engine marketing. My work often involves Python, R, Power BI, and SQL, which I use to support data-informed SEO strategies. Along the way, I have also developed strong web development skills, enabling me to diagnose site performance issues and collaborate with developers.

With a background in digital marketing and web analytics, I challenge myself to bring an analytical mindset that spans across data analysis, machine learning, and web development, allowing me to approach SEO from both a technical and strategic angle.

Simone De Palma

🔔 BigQuery supports AI similarity and embedding generation, but are they worth it? 

Basically, they released new functions you can embed in your SQL queries, including entity extraction, intent classification and sentiment analysis of unstructured text with Gemini 3.0.

I ran a few tests

The AI.embed() and AI.similarity() functions seem to work well if computed on your pre-processed datasets (e.g you ingest title tags, headings, custom extractions)

However, I found the AI.generate() and the AI.classify() prone to hallucinating and requiring extreme computing resources – it took 10 minutes just to extract entities and sentiment for one date for seodepths(.)com. Also, that "Google ADS" reference has nothing to do with that query LOL

TL;DR

❌ Intent classification (AI.Classify) should be a manual task for your keyword research. Still, you can opt for semi-automation with a rule-based classification
⚠️ Using Gemini 3.0 to capture entities and mine sentiment (AI.Generate) may be powerful if you base it on full scraped page content – I'm still on the fence because the process is hardly scalable in Big Query
✅ Using Gemini's text-embedding model (AI.Similarity) to compute cosine similarity between on-page SEO signals and your content should be normalised.
  
If you have access to BigQuery, I'd make sure you're granted permission as a 'Vertex AI User' so you can experiment.

Source – https://lnkd.in/e6KcKAZV

#TechSEO

Technical SEO Manager | Data Analyst | BrightonSEO Speaker | Founder of seodepth.com |

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