Real Data Marketing
Making complex marketing data accessible through clearer information architecture and reporting workflows.
Role
Product designer lead
Scope
Research, information architecture, UI, and design system
Focus
Marketing intelligence · Real-time analytics
Year
2021
Detailed
TL;DR
Company & product context
One operating view for modern marketing teams.
Datorama is a marketing intelligence platform that unifies data from paid, organic, social, and business systems.
The project focused on a real-time dashboard used by CMOs, analysts, and performance marketing teams to understand brand status, campaign performance, sentiment, and spend without waiting for manual reporting cycles.
Scale
120K users and 3K brands
Product Role
CMOs, data analysts, and performance marketers
My Role
End-to-end product design and system foundations
02
The business problem
Teams worked in silos and could not connect marketing spend to business outcomes.
Paid and organic data lived in separate tools. Reporting was manual, slow, and already out of date
by the time it reached decision-makers. The dashboard needed to unify the story without flattening
the analytical depth required by specialists.
Business reality
Fragmented data made attribution and budget decisions unreliable.
Design challenge
One product had to support executive scanning and analyst exploration.
03
Research approach
I worked with CSMs and the product team to understand both decision-makers and daily operators.
01
Stakeholder
synthesis
Collected recurring customer questions, reporting pain points, and commercial needs from CSMs and product partners.
02
Persona definition
Defined the CMO, data analyst, and performance marketing manager as distinct decision-making profiles.
03
Journey mapping
Mapped where each persona searched for data, compared channels, created reports, and escalated decisions.
04
Concept validation
Tested low-fidelity flows, then iterated through focus groups and collaborative sketching sessions.
04
Three personas, three levels of depth
The dashboard could not optimize for one role at the expense of the others.
CMO
“Where should we invest next?”
Needed fast brand status, channel performance, and a clear connection between spend and outcomes.
Data analyst
“Can I trust and explain this number?”
Needed analytical depth, filters, comparison logic, and a path from summary to source.
Performance manager
“What should I optimize today?”
Needed campaign-level signals, creative performance, and actionable recommendations.
05
Lo-fi testing changed the direction
The first flows exposed too much structure before users understood the story.
Users struggled to understand where to begin and how overview metrics related to deeper
analysis. We used the failure as a design signal rather than polishing the same structure.
What failed
Too many equal entry points
Every module competed for attention, so users could not tell what mattered first.
What changed
A hierarchy from status to diagnosis
We reorganized the experience around overview, trend, and deep analysis.
How we validated
Focus groups and sketching sessions
Users helped us refine terminology, module priority, and the expected path through the data.
Key design shift
The dashboard stopped being a wall of charts and became a guided analytical narrative.
06
Information architecture
We structured the product around the questions users asked in sequence.
01
Brand status
What is happening across paid and organic channels right now?
02
Campaign analysis
Which channels, audiences, and campaigns are driving the result?
03
Creative analysis
Which messages and assets are contributing to performance?
04
Recommendation
What action should the user take next?
07
A modular design system
The dashboard needed to scale across teams, data sources, and future integrations.
We created reusable patterns for chart headers, filters, comparison states, legends, empty states, and responsive data modules. Teams could customize layout and analytical depth while the experience remained coherent.
Consistency
Shared behaviors across every visualization
Filters, states, and interactions followed predictable patterns.
Scalability
New integrations without redesigning the platform
Modular components could absorb new channels and data types.
Flexibility
Different teams, different dashboard depth
Users could shape the view without breaking the information hierarchy.
08
The final experience
Paid and organic performance finally lived in one real-time story.
Users could scan brand status, understand trend against spend, inspect sentiment and channel
contribution, and continue into campaign or creative analysis without leaving the dashboard.
09
Impact
The system became both a daily operating surface and a scalable product foundation.
Adoption
More than 120,000
users connected
the system to their
Salesforce
environment and
adopted the
Datorama
dashboard.
Growth
10 new integrations supported real-time syncing
Decision quality
Unified paid and organic data improved attribution
Operations
Cross-channel tracking replaced fragmented reporting
Real Data Marketing
Making complex marketing data accessible through clearer information architecture and reporting workflows.
Role
Product designer lead
Scope
Research, information architecture, UI, and design system
Focus
Marketing intelligence · Real-time analytics
Year
2021
Detailed
TL;DR
Company & product context
One operating view for modern marketing teams.
Datorama is a marketing intelligence platform that unifies data from paid, organic, social, and business systems.
The project focused on a real-time dashboard used by CMOs, analysts, and performance marketing teams to understand brand status, campaign performance, sentiment, and spend without waiting for manual reporting cycles.
Scale
120K users and 3K brands
Product Role
CMOs, data analysts, and performance marketers
My Role
End-to-end product design and system foundations
02
The business problem
Teams worked in silos and could not connect marketing spend to business outcomes.
Paid and organic data lived in separate tools. Reporting was manual, slow, and already out of date
by the time it reached decision-makers. The dashboard needed to unify the story without flattening
the analytical depth required by specialists.
Business reality
Fragmented data made attribution and budget decisions unreliable.
Design challenge
One product had to support executive scanning and analyst exploration.
03
Research approach
I worked with CSMs and the product team to understand both decision-makers and daily operators.
01
Stakeholder
synthesis
Collected recurring customer questions, reporting pain points, and commercial needs from CSMs and product partners.
02
Persona definition
Defined the CMO, data analyst, and performance marketing manager as distinct decision-making profiles.
03
Journey mapping
Mapped where each persona searched for data, compared channels, created reports, and escalated decisions.
04
Concept validation
Tested low-fidelity flows, then iterated through focus groups and collaborative sketching sessions.
04
Three personas, three levels of depth
The dashboard could not optimize for one role at the expense of the others.
CMO
“Where should we invest next?”
Needed fast brand status, channel performance, and a clear connection between spend and outcomes.
Data analyst
“Can I trust and explain this number?”
Needed analytical depth, filters, comparison logic, and a path from summary to source.
Performance manager
“What should I optimize today?”
Needed campaign-level signals, creative performance, and actionable recommendations.
05
Lo-fi testing changed the direction
The first flows exposed too much structure before users understood the story.
Users struggled to understand where to begin and how overview metrics related to deeper
analysis. We used the failure as a design signal rather than polishing the same structure.
What failed
Too many equal entry points
Every module competed for attention, so users could not tell what mattered first.
What changed
A hierarchy from status to diagnosis
We reorganized the experience around overview, trend, and deep analysis.
How we validated
Focus groups and sketching sessions
Users helped us refine terminology, module priority, and the expected path through the data.
Key design shift
The dashboard stopped being a wall of charts and became a guided analytical narrative.
06
Information architecture
We structured the product around the questions users asked in sequence.
01
Brand status
What is happening across paid and organic channels right now?
02
Campaign analysis
Which channels, audiences, and campaigns are driving the result?
03
Creative analysis
Which messages and assets are contributing to performance?
04
Recommendation
What action should the user take next?
07
A modular design system
The dashboard needed to scale across teams, data sources, and future integrations.
We created reusable patterns for chart headers, filters, comparison states, legends, empty states, and responsive data modules. Teams could customize layout and analytical depth while the experience remained coherent.
Consistency
Shared behaviors across every visualization
Filters, states, and interactions followed predictable patterns.
Scalability
New integrations without redesigning the platform
Modular components could absorb new channels and data types.
Flexibility
Different teams, different dashboard depth
Users could shape the view without breaking the information hierarchy.
08
The final experience
Paid and organic performance finally lived in one real-time story.
Users could scan brand status, understand trend against spend, inspect sentiment and channel
contribution, and continue into campaign or creative analysis without leaving the dashboard.
09
Impact
The system became both a daily operating surface and a scalable product foundation.
Adoption
More than 120,000
users connected
the system to their
Salesforce
environment and
adopted the
Datorama
dashboard.
Growth
10 new integrations supported real-time syncing
Decision quality
Unified paid and organic data improved attribution
Operations
Cross-channel tracking replaced fragmented reporting
Real Data Marketing
Making complex marketing data accessible through clearer information architecture and reporting workflows.
Role
Product designer lead
Scope
Research, information architecture, UI, and design system
Focus
Marketing intelligence · Real-time analytics
Year
2021
Detailed
TL;DR
Company & product context
Engineering intelligence for the AI era.
Datorama is a marketing intelligence platform that unifies data from paid, organic, social, and business systems.
The project focused on a real-time dashboard used by CMOs, analysts, and performance marketing teams to understand brand status, campaign performance, sentiment, and spend without waiting for manual reporting cycles.
Scale
120K users and 3K brands
Product Role
CMOs, data analysts, and performance marketers
My Role
End-to-end product design and system foundations
02
The business problem
Teams worked in silos and could not connect marketing spend to business outcomes.
Paid and organic data lived in separate tools. Reporting was manual, slow, and already out of date
by the time it reached decision-makers. The dashboard needed to unify the story without flattening
the analytical depth required by specialists.
Business reality
Fragmented data made attribution and budget decisions unreliable.
Design challenge
One product had to support executive scanning and analyst exploration.
03
Research approach
I worked with CSMs and the product team to understand both decision-makers and daily operators.
01
Stakeholder
synthesis
Collected recurring customer questions, reporting pain points, and commercial needs from CSMs and product partners.
02
Persona definition
Defined the CMO, data analyst, and performance marketing manager as distinct decision-making profiles.
03
Journey mapping
Mapped where each persona searched for data, compared channels, created reports, and escalated decisions.
04
Concept validation
Tested low-fidelity flows, then iterated through focus groups and collaborative sketching sessions.
04
Three personas, three levels of depth
The dashboard could not optimize for one role at the expense of the others.
CMO
“Where should we invest next?”
Needed fast brand status, channel performance, and a clear connection between spend and outcomes.
Data analyst
“Can I trust and explain this number?”
Needed analytical depth, filters, comparison logic, and a path from summary to source.
Performance manager
“What should I optimize today?”
Needed campaign-level signals, creative performance, and actionable recommendations.
05
Lo-fi testing changed the direction
The first flows exposed too much structure before users understood the story.
Users struggled to understand where to begin and how overview metrics related to deeper
analysis. We used the failure as a design signal rather than polishing the same structure.
What failed
Too many equal entry points
Every module competed for attention, so users could not tell what mattered first.
What changed
A hierarchy from status to diagnosis
We reorganized the experience around overview, trend, and deep analysis.
How we validated
Focus groups and sketching sessions
Users helped us refine terminology, module priority, and the expected path through the data.
Key design shift
The dashboard stopped being a wall of charts and became a guided analytical narrative.
06
Information architecture
We structured the product around the questions users asked in sequence.
01
Brand status
What is happening across paid and organic channels right now?
02
Campaign analysis
Which channels, audiences, and campaigns are driving the result?
03
Creative analysis
Which messages and assets are contributing to performance?
04
Recommendation
What action should the user take next?
07
A modular design system
The dashboard needed to scale across teams, data sources, and future integrations.
We created reusable patterns for chart headers, filters, comparison states, legends, empty states, and responsive data modules. Teams could customize layout and analytical depth while the experience remained coherent.
Consistency
Shared behaviors across every visualization
Filters, states, and interactions followed predictable patterns.
Scalability
New integrations without redesigning the platform
Modular components could absorb new channels and data types.
Flexibility
Different teams, different dashboard depth
Users could shape the view without breaking the information hierarchy.
08
The final experience
Paid and organic performance finally lived in one real-time story.
Users could scan brand status, understand trend against spend, inspect sentiment and channel
contribution, and continue into campaign or creative analysis without leaving the dashboard.
09
Impact
The system became both a daily operating surface and a scalable product foundation.
Adoption
More than 120,000
users connected
the system to their
Salesforce
environment and
adopted the
Datorama
dashboard.
Growth
10 new integrations supported real-time syncing
Decision quality
Unified paid and organic data improved attribution
Operations
Cross-channel tracking replaced fragmented reporting