AI, Data Science, Pipelining, & Tools

Your answers are out there, it’s just about getting them to the right place at the right time.

I get teams the insights they need, when they need them. Sometimes that’s about accessing data they couldn’t, sometimes it’s just giving them a new way to understand things they already know.

Dominic Woodman

Dominic Woodman

Founder, Piped Out SEO data warehouse company

Robin is one of the most talented consultants I've had the pleasure of working with.

He's excellent with data (SQL, python, forecasting, MMM etc.) and thorough, he doesn't miss things.

His communication and organisation are top notch and most importantly he's result driven and honest about it. He'll tell you if something isn't possible and I've seen him regularly turn down work if it won't add anything.

Show, don’t tell

This is by no means everything, but here’s a small selection of the projects I’ve delivered.

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On-demand opportunity analysis and topic clustering

Millions of pounds in sales and retainers rely on Keyword Navigator to identify SEO opportunities, saving tens of thousands of pounds in billable hours.

Python Google Big Query Google Vertex AI Streamlit Data for SEO Gitlab
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Challenge: Consultants were spending hours trying to figure out what content to create. It was hard for them to understand what topics should be grouped together, and how much business impact they could have.

Solution: I built Keyword Navigator, which does the heavy lifting of grouping keywords, and prioritising them by business impact – all in an interactive and visual web-based tool. It does so by scraping search results, calculating click through curves and conversion rates, highlighting the most important competitor domains, and clustering keywords using ML and recursive SQL.

Secure Google workspace add-on

Saving thousands of pounds in billable hours by making it easy to launch small tools that save people time.

Google Apps Script Meta Prophet Google Big Query Anthropic Claude
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Challenge: Often consultants waste time on small tasks in Google Sheets. Releasing tools to speed them up would save consultants time, but the time required to build, track, and release new tools to handle those little tasks mean it’s often hard to justify.

Solution: I created Utility Belt – a workspace add-on that can “hold” as many tools as we want to release. Every time we want to create a new tool, we add it to Utility Belt and it is available for every consultant the next time they opened their browser, with tracking and error handling baked in.

The add-on cut our development time from weeks to hours. In the first two months we used it to release a series of tools which saved £ thousands in billable hours.

We are regularly adding more to Utility Belt – from simple tidy up and restructuring of deliverables for clients, to Machine Learning forecasts, AI-based formula generation, or automating AI fine tuning and RAG.

Impact measurement with machine learning

Finding over $130K in wasted spend, and learning new information about how quickly customers convert.

Python Google Colab Gitlab
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Challenge: An ecommerce client was spending lots of money on advertising but didn’t know how well it was working.

Standard tracking methods were disagreeing with each other – some claiming lots of impact, others saying that advertising was having no impact at all. Big fluctuations in seasonality made it hard for them to run tests.

Solution: I worked with them to strategically switch on and off campaigns. Using Machine Learning tools to handle seasonality – I measured the true impact of the ads.

Through testing we found an opportunity to stop over $130K worth of monthly ad spend without losing revenue. We also found over $45K of additional uplift, and gathered new information about how customers were behaving.

3.2 billion rows of search data processed and saved

Saving months of client data and forming the foundations of analyses that made hundreds of thousands for clients.

Google Search Console Google Cloud Functions Google Cloud Tasks Google Big Query
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Challenge: Google Search Console offers crucial insights into how websites are performing and top opportunities. But the default data available is severely limited – around 10% of the real picture.

Solution: I created a data pipeline which automatically extracts Search Console data, and puts it into a secure database for use in multiple, flexible reports.

Video demonstration

Video we shared publicly explaining one way we use this data.

Personalised AI “Watchdog”

A personalised knowledge database – generating client-specific answers and sense-checks across £100,000s of retained clients

Python Google Apps Script Pinecone Vector Database Anthropic's Claude
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Challenge: Knowledge loss is one of the biggest threats to agencies and their clients. As consultants move around – even the most comprehensive handover documents can be lacking. With each misstep in communication or unnecessary question – trust is eroded, and time is lost. Often clients leave agencies out of frustration, having to start again and face the same issues with a new contract.

Solution: I created Watchdog – a personalised AI tool, using LLMs and a RAG approach. Consultants can use the tool to ask questions about specific clients, and, with the integrated GMail extension, sense-check messages they are about to send clients before they go across.

Tag Manager and analytics error-spotting

Helping thousands of users to avoid analytics problems worth tens of thousands of dollars.

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Challenge: A client had a huge number of businesses with different websites trying to use the same tracking platform. When something broke it took a lot of time to work out why.

Solution: I created Tag Mapper which helps visualise the dependencies in a Google Tag Manager account. It helped us quickly avoid and fix tracking issues that could have cost the client tens of thousands, and the tool has been used by analytics practitioners across the globe.

Tag Mapper Tree View transform

SQL learning web app

More than 60K players getting better insights from their data.

SQL Angular Midjourney Github AWS Cloudflar
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Challenge: Lots of databases rely on SQL as a way to give users data. It’s a really powerful language, and with tools like BigQuery, lets us process millions of rows of information, easily. I’ve worked with many consultants who say they want to learn but it can be hard because SQL is quite dry, not always very clear, and it can be hard to have an excuse to practice (or the data to practice on).

Solution: I created Lost At SQL – a rich learning game with a story mode that takes players from the absolute basics all the way to advanced multi-step SQL queries, as well as challenge modes where players can pit their skills against others from around the globe.

Speaking and training

From classes of 10 to audiences of thousands.

Python Google Big Query Google Analytics
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Challenge: I have long had a passion for teaching and sharing knowledge, but topics like Python and data processing can be intimidating.

Solution: I have given conference talks designed to get audiences excited about coding (they have ben called “one of the best talks for the last 10 years”). I’ve also created in-person and on-demand training to help people learn.

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