Madex · Consultancy project · 2025
AI Product development co-pilot
AI Product development co-pilot
Role
CX Designer / Researcher
Duration
12 Weeks
Responsibilities
UX Research
UX Design
Business Strategy
Product Strategy
Tools
Figma
Miro
Airtable
Context
We set out to fix advertising. The real problem was upstream
Madex wanted to change how advertising worked for a web3 future. The brief was intentionally open—not “build this product,” but “find where the real value is.”
We began by investigating waste and inefficiency across the advertising pipeline. Over twelve weeks, the evidence moved us upstream: products were frequently failing before advertising even began because teams lacked a fast, affordable way to test whether people wanted them. This lead up to develop LAILA—an AI-powered co-pilot that uses synthetic consumer panels to help teams test and refine product decisions in real time.
The pivotal insight
Advertising failure was often product failure in disguise
43 Open Ended Interviews across stakeholders
Product Managers, Product Owners, COOs, Product Innovation
A further discovery interviews revealed the deeper problem: companies were committing to products before adequately establishing whether people wanted them.
Lack of Agility
Slow development means missed trends and outdated products.
Mismatch with Consumer Needs
Products fail when flawed research misses real consumer needs.
Resource and Time Intensity
Product development is too slow and costly for effective iteration.
Inefficiency in Testing
Consumer testing is slow, costly and often produces poor insights.
Pressure testing the concept - Gemi
The concept earned enough confidence to prototype
73 Solution / Wireframe Interviews across stakeholders
Product Managers, Product Owners, COOs, Product Innovation
Before building the polished UI, we put a working proof-of-concept in front of 73 stakeholders — product owners who run concept research the slow, expensive way — and had them react to synthetic-consumer results on live concepts. The signal came back strong enough to commit to the build.
The Product Vision
An AI co-pilot for better decision-making across every stage of product development
The product, now called LAILA, gives teams continuous access to synthetic consumer insight, helping them explore opportunities, test concepts and refine ideas earlier. The first release focused on exploratory research and concept testing—guiding users from a research question to actionable recommendations.
Development
Turning the proposition into a usable workflow
Before designing a finalised interface, we mapped two core user flows—idea exploration and concept testing. These flows and the product roadmap then guided feature priorities, wireframes and high-fidelity prototypes.
Designing the MVP
From a research question to actionable consumer insight
We mapped the exploratory research and concept-testing journeys before moving into interface design. The final workflow helped teams define what they needed to learn, shape a study and review the resulting consumer evidence.
The power of product research from your desktop
A guided consumer-research workflow
A short walkthrough can show the complete journey—from choosing a research method to reviewing the final findings.
Four moments in the final experience
01 - Frame
Start with the right research method
Separating exploratory research from concept testing at the outset gave each journey a clear purpose and allowed the platform to guide the user appropriately.
02 - Refine
Turn a broad objective into actionable goals
LAILA translated the initial research objective into a set of focused goals. Users could review, edit, remove or add goals before continuing.
03 - Define
Build the study in manageable steps
The workflow progressively captured the target audience and research questions, keeping a complex setup process focused on one decision at a time.
04 - Decide
Bring the evidence together
The results view combined comparative measures, rankings, key insights and recommendations so teams could evaluate concepts and identify what to refine next.
Design principle
Use AI to structure the research process while keeping users in control of the goals, audience and questions shaping the study.
Outcome
Validated, not shipped
The team left before release, so there are no launch metrics. But our final direction and MVP earned solid validation:
9.1/10
Net promoter score on the proposed solution
9.3
Pain score for solving product research issues
9/10
comfortable talking to synthetic customers
Reflection
This project taught me that a wrong path can still reveal the right opportunity. Listening closely and looking beyond surface-level feedback revealed the insight that changed the direction of the venture.
Context
We set out to fix advertising. The real problem was upstream
Madex wanted to change how advertising worked for a web3 future. The brief was intentionally open—not “build this product,” but “find where the real value is.”
We began by investigating waste and inefficiency across the advertising pipeline. Over twelve weeks, the evidence moved us upstream: products were frequently failing before advertising even began because teams lacked a fast, affordable way to test whether people wanted them. This lead up to develop LAILA—an AI-powered co-pilot that uses synthetic consumer panels to help teams test and refine product decisions in real time.
The pivotal insight
Advertising failure was often product failure in disguise
43 Open Ended Interviews across stakeholders
Product Managers, Product Owners, COOs, Product Innovation
A further discovery interviews revealed the deeper problem: companies were committing to products before adequately establishing whether people wanted them.
Lack of Agility
Slow development means missed trends and outdated products.
Mismatch with Consumer Needs
Products fail when flawed research misses real consumer needs.
Resource and Time Intensity
Product development is too slow and costly for effective iteration.
Inefficiency in Testing
Consumer testing is slow, costly and often produces poor insights.
Pressure testing the concept - Gemi
The concept earned enough confidence to prototype
73 Solution / Wireframe Interviews across stakeholders
Product Managers, Product Owners, COOs, Product Innovation
Before building the polished UI, we put a working proof-of-concept in front of 73 stakeholders — product owners who run concept research the slow, expensive way — and had them react to synthetic-consumer results on live concepts. The signal came back strong enough to commit to the build.
The Product Vision
An AI co-pilot for better decision-making across every stage of product development
The product, now called LAILA, gives teams continuous access to synthetic consumer insight, helping them explore opportunities, test concepts and refine ideas earlier. The first release focused on exploratory research and concept testing—guiding users from a research question to actionable recommendations.
Development
Turning the proposition into a usable workflow
Before designing a finalised interface, we mapped two core user flows—idea exploration and concept testing. These flows and the product roadmap then guided feature priorities, wireframes and high-fidelity prototypes.
Designing the MVP
From a research question to actionable consumer insight
We mapped the exploratory research and concept-testing journeys before moving into interface design. The final workflow helped teams define what they needed to learn, shape a study and review the resulting consumer evidence.
The power of product research from your desktop
A guided consumer-research workflow
A short walkthrough can show the complete journey—from choosing a research method to reviewing the final findings.
Four moments in the final experience
01 - Frame
Start with the right research method
Separating exploratory research from concept testing at the outset gave each journey a clear purpose and allowed the platform to guide the user appropriately.
02 - Refine
Turn a broad objective into actionable goals
LAILA translated the initial research objective into a set of focused goals. Users could review, edit, remove or add goals before continuing.
03 - Define
Build the study in manageable steps
The workflow progressively captured the target audience and research questions, keeping a complex setup process focused on one decision at a time.
04 - Decide
Bring the evidence together
The results view combined comparative measures, rankings, key insights and recommendations so teams could evaluate concepts and identify what to refine next.
Design principle
Use AI to structure the research process while keeping users in control of the goals, audience and questions shaping the study.
Outcome
Validated, not shipped
The team left before release, so there are no launch metrics. But our final direction and MVP earned solid validation:
9.1/10
Net promoter score on the proposed solution
9.3
Pain score for solving product research issues
9/10
comfortable talking to synthetic customers
Reflection
This project taught me that a wrong path can still reveal the right opportunity. Listening closely and looking beyond surface-level feedback revealed the insight that changed the direction of the venture.
Context
We set out to fix advertising. The real problem was upstream
Madex wanted to change how advertising worked for a web3 future. The brief was intentionally open—not “build this product,” but “find where the real value is.”
We began by investigating waste and inefficiency across the advertising pipeline. Over twelve weeks, the evidence moved us upstream: products were frequently failing before advertising even began because teams lacked a fast, affordable way to test whether people wanted them. This lead up to develop LAILA—an AI-powered co-pilot that uses synthetic consumer panels to help teams test and refine product decisions in real time.
The pivotal insight
Advertising failure was often product failure in disguise
43 Open Ended Interviews across stakeholders
Product Managers, Product Owners, COOs, Product Innovation
A further discovery interviews revealed the deeper problem: companies were committing to products before adequately establishing whether people wanted them.
Lack of Agility
Slow development means missed trends and outdated products.
Mismatch with Consumer Needs
Products fail when flawed research misses real consumer needs.
Resource and Time Intensity
Product development is too slow and costly for effective iteration.
Inefficiency in Testing
Consumer testing is slow, costly and often produces poor insights.
Pressure testing the concept - Gemi
The concept earned enough confidence to prototype
73 Solution / Wireframe Interviews across stakeholders
Product Managers, Product Owners, COOs, Product Innovation
Before building the polished UI, we put a working proof-of-concept in front of 73 stakeholders — product owners who run concept research the slow, expensive way — and had them react to synthetic-consumer results on live concepts. The signal came back strong enough to commit to the build.
The Product Vision
An AI co-pilot for better decision-making across every stage of product development
The product, now called LAILA, gives teams continuous access to synthetic consumer insight, helping them explore opportunities, test concepts and refine ideas earlier. The first release focused on exploratory research and concept testing—guiding users from a research question to actionable recommendations.
Development
Turning the proposition into a usable workflow
Before designing a finalised interface, we mapped two core user flows—idea exploration and concept testing. These flows and the product roadmap then guided feature priorities, wireframes and high-fidelity prototypes.
Designing the MVP
From a research question to actionable consumer insight
We mapped the exploratory research and concept-testing journeys before moving into interface design. The final workflow helped teams define what they needed to learn, shape a study and review the resulting consumer evidence.
The power of product research from your desktop
A guided consumer-research workflow
A short walkthrough can show the complete journey—from choosing a research method to reviewing the final findings.
Four moments in the final experience
01 - Frame
Start with the right research method
Separating exploratory research from concept testing at the outset gave each journey a clear purpose and allowed the platform to guide the user appropriately.
02 - Refine
Turn a broad objective into actionable goals
LAILA translated the initial research objective into a set of focused goals. Users could review, edit, remove or add goals before continuing.
03 - Define
Build the study in manageable steps
The workflow progressively captured the target audience and research questions, keeping a complex setup process focused on one decision at a time.
04 - Decide
Bring the evidence together
The results view combined comparative measures, rankings, key insights and recommendations so teams could evaluate concepts and identify what to refine next.
Design principle
Use AI to structure the research process while keeping users in control of the goals, audience and questions shaping the study.
Outcome
Validated, not shipped
The team left before release, so there are no launch metrics. But our final direction and MVP earned solid validation:
9.1/10
Net promoter score on the proposed solution
9.3
Pain score for solving product research issues
9/10
comfortable talking to synthetic customers
Reflection
This project taught me that a wrong path can still reveal the right opportunity. Listening closely and looking beyond surface-level feedback revealed the insight that changed the direction of the venture.
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