TOP OF FUNNEL · 100% AUDIENCE

KHALID
ALSUWAILEM

I work in marketing, mostly the parts of it that involve data — paid acquisition, attribution, tracking, figuring out what actually caused a sale. Somewhere along the way I started building the tools instead of buying them, and that turned into a side of my work that looks more like engineering than marketing.

These days I split my time between marketing consulting, research on how you measure whether a system is any good, and building things I’m curious about.

ENTER THE FUNNEL Skip to the About section

STAGE 01 · AWARENESS → INTEREST · 62% REMAIN

About

I’ve spent about eight years in marketing. Most of it on the performance side — running paid campaigns across Google, Meta, TikTok and Snapchat, managing budgets in the hundreds of thousands of riyals a month, and dealing with the usual problem that every platform claims credit for the same conversion and none of them will tell you the truth.

That problem is what pulled me sideways. I got tired of arguing with dashboards, so I built my own attribution — proper multi-touch tracking, code-level instrumentation, following a visitor across sessions and channels rather than trusting whatever the last platform reported.

Because once you take attribution seriously you stop being able to accept most of what marketing tells itself. I analysed a few hundred thousand ads trying to extract real patterns and mostly learned why the question is harder than the industry admits.

What I do now

Marketing and MarTech consulting, mainly the measurement and acquisition side. Attribution setups, tracking that survives contact with reality, campaigns where someone actually knows what’s driving the numbers.

Alongside that, research. My current interest is narrow and probably niche: how you would ever prove that a monitoring system is trustworthy.

How I think about the work

I’m sceptical by default, including of my own results. Most of what I’ve published lately is things that didn’t work. I publish those partly because they’re more interesting than the successes, and partly because a method that never gives you an answer you didn’t want hasn’t really been tested yet.

Background

MSc Marketing Management & Communication, Toulouse Business School. CDMP. Started out in hotel management, which is a longer story.

STAGE 02 · INTEREST → CONSIDERATION · 34% REMAIN

Work

You built your own instruments to see in the dark. Specimens observed through the viewport.

Attribution Systems

Measurement / MarTech

Multi-touch tracking and code-level instrumentation that survives contact with reality. Built for marketing teams that want to know what’s actually driving the numbers, not what the platforms claim.

Agent Systems

Agents / Engineering

An agent system that runs a live site end to end. Started as ‘I wonder if’ and got out of hand. The live site is the demonstration.

Sensor & Certification Research

Research / ML · Methods

Building small models that watch larger automated systems for failures. The interesting part isn’t the models — it’s how you test something whose whole job is noticing when things go wrong, when its own failure is invisible by definition.

STAGE 03 · CONSIDERATION → INTENT · 17% REMAIN

Writing

Mostly what didn’t work.

Most of what I’ve published lately is things that didn’t work — partly because they’re more interesting, and partly because a method that never gives you an answer you didn’t want hasn’t really been tested yet.

SPECIMEN 02 · PRESERVED

ESSAY · ML

The Guard I Couldn’t Build

A guard I couldn’t build without breaking legitimate inputs, and a detection rule that turned out to be statistically indistinguishable from chance.

Open specimen · · 1 min read

SPECIMEN 03 · PRESERVED

ESSAY · Evaluation

Close to Perfect, Useless in Practice

A component that scored close to perfect on its own tests and was useless against real outcomes. On the gap between what you can measure and what you can claim.

Open specimen · · 1 min read

ALL SPECIMENS →

STAGE 04 · INTENT → CONVERSION · 6% REMAIN

Now

Working on

  • Marketing and MarTech consulting (measurement and acquisition side)
  • Attribution tooling and tracking that survives reality
  • The agent system running a live site end to end
  • Small models watching larger automated systems

Open to

  • Consulting on attribution, tracking, paid acquisition
  • Conversations about measurement and ML evaluation
  • Building, if the problem is interesting