I query the data, inspect the tracking, and work through what users actually do. I find why a funnel looks wrong, what an experiment hides, and which product decision the evidence supports.
A team can spend months improving activation, conversion, or retention and still be working on the wrong thing.
The cause might be in the user journey, the funnel logic, the experiment audience, the pricing step, the tracking, or a small engineering detail. My first job is to find where to look.
You can bring the symptom before you know the cause. I connect the user journey, raw data, tracking, and implementation to find what deserves attention.
I rebuilt a registration funnel and traced users into login. The investigation redirected attention from the suspected registration step to the first experience and tracking.
Explore →A focused review of one experiment: the audience, assignment, tracking, interpretation, and whether the result applies to the rollout.
Explore →Implementation, release checks, and tracking documentation with someone responsible for keeping them aligned.
A conversion rate, a drop-off, or a winning experiment is a starting point. I connect what users do with what the product measures, what the business needs, and what the team can change.
Understand what users are trying to achieve, where they get stuck, and which drop-offs deserve attention.
Read the evidence in the context of the audience, the journey, and the implementation that produced it.
I inspect the code behind events, query the data, trace differences between platforms, and implement changes. When the investigation finds an engineering problem, I can do that work too.
See the engineering experience behind this ↓Fictional companies and synthetic data. The same structure and depth as my client reports.
Read-only access to where the answer lives: analytics, your data warehouse, App Store Connect or Google Play, logs. Through your VPN if you prefer. Before we start, I send a short list with the exact roles, so your team can set it up quickly.
Investigations don’t follow a script. One finding points to the next table. With direct access I can follow it the same hour instead of waiting days for the next export.
We sign a data processing agreement before I see anything. Data I export for analysis stays on my encrypted laptop, is used only for your project, and is deleted when the work ends. Reports go to you through your own channels.
No AI provider ever gets your users’ data. I use AI as a tool to check queries and research markets. Code is mine: I write and review every line, and AI assists only if you agree.
I work through user behavior, the raw data, and the code that produced it. Sometimes the answer is the next test to run. Sometimes it is a fix in the implementation, and I can make it myself.
Sometimes it is finding out that the team spent weeks fixing a problem that was not real, or reading a metric that measured the wrong thing.
You get a clear answer: what is actually going on, the evidence behind it, and what to do next, or what to stop doing.
How I investigate, what I look for, and what I’ve learned along the way.
A structured way to connect product goals, user value, evidence, and implementation.
Activation ↗How I think about first value, meaningful behavior, and the path to an ongoing habit.
Writing ↗Longer thoughts on engineering, experimentation, analytics, and product decisions.
Focused services ↗Product consultations, experiment reviews, audits, and tracking ownership.
An app that needs building. A migration that needs someone to own it. Numbers that don’t make sense. A product decision your team can’t resolve. Tell me what’s happening. I’ll tell you whether I’m the right person, how I’d approach it, and what the work would cost.
Email Alex ↗alex@x91tech.com
