Product Manager · Canada

I turn messy user problems into clear product decisions.

I'm Lilian Adeiwa, a Product Manager who enjoys understanding why something isn't working and figuring out what should happen next. I work across discovery, prioritization, requirements, and experimentation; turning user insights into product decisions teams can act on. I'm currently expanding my analytical toolkit through Data Analytics.

View my workAbout meContact · résumé
Lilian Adeiwa, product manager
Now
Open to product roles
Problem spaces
B2C discovery · B2B operations · AI
Strongest in
Discovery, scoping, experiment design
Also
Founder, Doxa Gift Atelier

Selected work

Three problem spaces. One way of deciding.

Each project shows the problem, the decision I made, and how I'd test it. Numbers are labelled as baselines, targets or guardrails; never as achieved results.

StreamLine Spotlight — Curing decision fatigue with human curated discovery.
Consumer · B2CSelf directed case study2026

StreamLine Spotlight

Curing decision fatigue with human curated discovery.

Problem
StreamLine's catalogue grew, but overwhelmed viewers were leaving the app to decide what to watch.
Key decision
Introduce a human curated Spotlight rail with mood based entry points; curation before more complexity.
Baseline
11%30+ minute viewing sessions
Experiment target
15%+4 percentage points
Guardrail
≤ 2%Maximum acceptable DAU decline
View case studyView interactive prototype
RouteLogic Velocity — Removing execution friction from the dispatcher's daily workflow.
Enterprise · B2B SaaSSelf directed case study2026

RouteLogic Velocity

Removing execution friction from the dispatcher's daily workflow.

Problem
Fleet Dispatchers were leaving RouteLogic mid workflow to complete time sensitive operational work in external tools.
Key decision
A narrow One click Compliance Checklist inside route assignment; improve dispatchers without breaking Manager reporting adoption.
Baseline
48%Compliance workflow completion rate
Pilot threshold
58%+10 percentage points
Guardrail
≤ 2ppManager Reporting Suite adoption decline
View case studyView interactive prototype
Juno PM Prioritization Copilot — An evidence backed AI copilot that helps PMs prioritize with confidence.
AI · Internal ToolingAI product case study2026

Juno PM Prioritization Copilot

An evidence backed AI copilot that helps PMs prioritize with confidence.

Problem
PMs were synthesizing fragmented signals across support, interviews, Jira, Slack, sales, and docs into defensible prioritization calls; manually.
Key decision
A Level 1 copilot rather than autopilot, with hybrid RAG grounding and a fail safe that escalates when evidence is insufficient.
Autonomy level
Level 1Copilot; the PM decides
Grounding rule
Top 10Attributed evidence segments per recommendation
Fail safe
EscalateNo recommendation when evidence is insufficient
View case studyView interactive prototype

Next

A fourth project, real world product discovery, is in progress. I'll publish it when there is genuine evidence to show. Ask me about it.

Data Analytics

Turning data into questions, patterns, and decisions.

A growing collection of hands-on projects where I use data to investigate questions, uncover patterns, and communicate findings clearly.

Relational evidence
SQLSQLiteJOINsSubqueriesData Investigation

SQL Murder Mystery

Following the evidence through relational data

Started with three clues — a murder, January 15, 2018, and SQL City — and used SQL to follow evidence across multiple tables, identify suspects, and solve the case.

View Case Study

How I think

I start with the problem, not the feature.

The same loop runs through every project on this site: understand, decide, make it tangible, learn, improve.

  1. 01Discover

    Understand before solving

    I learn how users currently work, where the friction is, and what constraints the team is working within; to make sure we're solving the right problem.

  2. 02Define

    Find the signal

    I bring together user insight, business needs, competitive context and available data to identify patterns and separate assumptions from evidence.

  3. 03Prioritize

    Make the decision clear

    I define the problem, prioritize what matters most, make trade offs visible, and align the work around measurable outcomes.

  4. 04Design & align

    Make it tangible

    Flows, wireframes, prototypes and lightweight experiments turn ideas into something people can react to; surfacing weak assumptions early.

  5. 05Test

    Set the bar before shipping

    I define success measures, baselines and guardrails up front, with decision rules agreed before results arrive.

  6. 06Learn

    Learn from what happens next

    The goal is not to defend the original idea. It's to learn enough from behaviour and feedback to make the next decision better.

Product discovery & strategyRequirements, PRDs & scopingPrioritization & trade offsPrototyping & experimentationMetrics & product decisionsGTM & pilot planning

About

I've always been curious about people, problems, and better ways to do things.

Based in
Canada
Founder
Doxa Gift Atelier
Background
Healthcare operations · customer relations
Studying
Data analytics

My path into product management has been shaped by product training and projects, healthcare operations, customer relations, and building my own business. More recently, I've been strengthening my data analytics skills to better understand the numbers behind the problems and decisions I'm working on.

Those experiences put me close to customers, workflows, operations and ambiguity; and taught me that a good idea still has to work for the person using it, that customer needs have to connect with business priorities, and that operational reality often exposes problems a roadmap does not show.

I'm early in my product career and intentional about how I grow; I don't wait to know everything before I start learning, building, testing and improving.

If your team is looking for a product manager who brings curiosity, ownership, and a user first mindset to every product decision, I'd love to help build products that people genuinely value.

Learning & credentials

Chosen to sharpen specific muscles.

Certificates are not the story; they are how I close specific gaps between projects.

  • Product School · July 2026

    Artificial Intelligence Micro Certification

    Generative AI · AI for Product Management · AI UX · ML evaluation

  • Product School · April 2026

    Product Strategy Micro Certification

    Roadmapping · OKRs · Market analysis · Strategic prioritization

  • Great Learning · April 2026

    Product Management

    Discovery · Product planning · User stories · Agile delivery

  • Great Learning · March 2026

    Jira Project Management

    Jira · Sprint planning · Scrum · Cross functional collaboration

  • Udemy · August 2024

    Customer Relationship Management

    CRM · Customer experience · Retention · Customer lifecycle

  • BeTechified · July 2024

    Product Management

    PM fundamentals · Product thinking · Analytical reasoning

In progress

  • In progress

    Google Data Analytics Professional Certificate

    Google · Expected September 2026

  • In progress

    Data Analytics

    DataFrik · Scholarship recipient · Begins August 2026 · expected September 2026

  • In progress

    Data Science

    TS Academy · Scholarship recipient · Begins September 2026 · expected December 2026

I don't pursue certifications to collect them. Each one is chosen to strengthen how I think, make product decisions, and solve meaningful problems.

A little more

Three things worth knowing.

  • What kind of Product Manager are you?

    I am most interested in understanding users, uncovering workflow problems, and turning what I learn into clear product decisions. I enjoy working across discovery and execution: researching a problem, identifying opportunities, prioritizing what matters, making ideas tangible, and learning from how people respond to what we build.

    I am especially interested in products that simplify complexity and make difficult work easier.

  • How do you approach a domain you haven't worked in before?

    I start by learning how the domain works from the people closest to it. I learn the language, understand the users and their workflows, review existing feedback and available data, study the market and alternatives, and make my assumptions visible.

    I ask questions early because I would rather clarify what I don't understand than build confidence around the wrong assumption. I don't expect to become the domain expert overnight; my goal is to learn quickly enough to ask better questions and make increasingly better product decisions.

  • Why are you learning Data Analytics?

    I want to be more confident working with data, not just talking about it. As I grew in product management, I realized that understanding users is only one part of making good decisions. I also want to be able to explore the data behind a problem, spot patterns, ask better questions, and understand what the numbers are actually saying. That's what pushed me to start learning data analytics.

  • What are you looking for next?

    A Product Manager, Associate Product Manager or Product Operations role where I can contribute across discovery, prioritization, experimentation and execution while growing through real ownership.

    I am looking for a team where curiosity is valued, good questions are welcomed, and Product Managers are expected to understand problems deeply rather than simply manage a list of features.