Ominchannel
Data to grow sales
Omnichannel data to grow sales
Data to grow sales
Walmart is a global retail leader with thousands of stores and a growing online marketplace, focused on affordability and efficient supply chains.
My role
UI/UX Intern
Contains
Data analysis, product design
Team
1 Senior designer, 2 marketing,
30%
Smoother cross-dept collaboration as everyone views the same metrics
50%
Richer customer insights by merging online and offline behaviour data.
Solution summery
What did I do?
(Use these for quick navigation)
Problem identification
current problems with data
current problems with data
Problem identification
current problems with data
Too Much Data, No Direction
Walmart collects lots of data from multiple sources, but there’s no meaningful analysis drawn from it.
Too Much Data, No Direction
Walmart collects lots of data from multiple sources, but there’s no meaningful analysis drawn from it.
Too Much Data, No Direction
Walmart collects lots of data from multiple sources, but there’s no meaningful analysis drawn from it.
Tough to Decode
Finding insights or patterns becomes time-consuming and complicated.
Tough to Decode
Finding insights or patterns becomes time-consuming and complicated.
Tough to Decode
Finding insights or patterns becomes time-consuming and complicated.
Insights Stuck in Silos
Teams see only part of the data, so insights stay limited and hard to scale.
Insights Stuck in Silos
Teams see only part of the data, so insights stay limited and hard to scale.
Insights Stuck in Silos
Teams see only part of the data, so insights stay limited and hard to scale.
UX RESEARCH
DATA ORGANISATION
UX research
Data organisation
UX research
data organisation
1.
What the data really tells us?
Drivers are caught between the road and their phones. Messages keep pinging while they’re told to “stay on schedule.” They face traffic, no safe spots to stop, and sometimes messages that don’t even go through.
They just want clear, quick updates that don’t make them choose between safety and staying informed.
2.
What It Means Structurally
From social media scrolls to website clicks, TV ads, Black Friday events, and in-store experiences, every channel tells a part of the customer story.
Each medium can be used to collect unique data.
3.
Where It Happens in Practice
Every medium speaks a different language of data.
Social media shows who’s engaging and why, billboards show where attention lives, TV tells how far reach goes, and stores reveal what actually sells.
Together, these signals help Walmart close the loop from awareness to action creating a full-circle view of the customer journey.
1.
What the data really tells us?
Drivers are caught between the road and their phones. Messages keep pinging while they’re told to “stay on schedule.” They face traffic, no safe spots to stop, and sometimes messages that don’t even go through.
They just want clear, quick updates that don’t make them choose between safety and staying informed.
2.
What It Means Structurally
From social media scrolls to website clicks, TV ads, Black Friday events, and in-store experiences, every channel tells a part of the customer story.
Each medium can be used to collect unique data.
3.
Where It Happens in Practice
Every medium speaks a different language of data.
Social media shows who’s engaging and why, billboards show where attention lives, TV tells how far reach goes, and stores reveal what actually sells.
Together, these signals help Walmart close the loop from awareness to action creating a full-circle view of the customer journey.
1.
What the data really tells us?
Every number hides a story.
Location data reveals 'what sells where'.
Demographics show 'who’s buying and why'.
When combined, these scattered data points turn into patterns which help predict needs, personalise offers, and sell smarter across every channel.
2.
What It Means Structurally
From social media scrolls to website clicks, TV ads, Black Friday events, and in-store experiences, every channel tells a part of the customer story.
Each medium can be used to collect unique data.
3.
Where It Happens in Practice
Every medium speaks a different language of data.
Social media shows who’s engaging and why, billboards show where attention lives, TV tells how far reach goes, and stores reveal what actually sells.
Together, these signals help Walmart close the loop from awareness to action creating a full-circle view of the customer journey.
1.
What the data really tells us?
Every number hides a story.
Location data reveals 'what sells where'.
Demographics show 'who’s buying and why'.
When combined, these scattered data points turn into patterns which help predict needs, personalise offers, and sell smarter across every channel.
2.
What It Means Structurally
From social media scrolls to website clicks, TV ads, Black Friday events, and in-store experiences, every channel tells a part of the customer story.
Each medium can be used to collect unique data.
3.
Where It Happens in Practice
Every medium speaks a different language of data.
Social media shows who’s engaging and why, billboards show where attention lives, TV tells how far reach goes, and stores reveal what actually sells.
Together, these signals help Walmart close the loop from awareness to action creating a full-circle view of the customer journey.
Problem statement
Problem statement
Problem statement
How might we create an omni-channel tool which help us analyse and leverage data collected to boost Walmart’s growth
How might we create an omni-channel tool which help us analyse and leverage data collected to boost Walmart’s growth
How might we create an omni-channel tool which help us analyse and leverage data collected to boost Walmart’s growth
Omni-channel
Omni-channel
Boost sales
Boost sales
Data analysis
Data analysis
Ideation
Data visualisations explored
Flexible Comparison for Deeper Insights
The feature lets users mix and match parameters (e.g., Gender F 10–14 vs Gender M 10–14) to analyze how the same data point behaves across segments.
Compare Multiple Metrics Side-by-Side
By comparing several data points together, users get an overview of how different segments behave and can add more metrics for deeper detail.
Compare Multiple Metrics Side-by-Side
By comparing several data points together, users get an overview of how different segments behave and can add more metrics for deeper detail.
PERSONA PAGE
Flexible Comparison for Deeper Insights
Users can be grouped by buying patterns, interest areas, product types, and platform interaction.
The system auto-generates persona names, which users can customise.
Each persona can be explored in detail, and two personas can be compared side-by-side for deeper analysis.
UX research
Data organisation
UX research
data organisation
User testing
What worked, what didn't?
What worked, what didn't?
Problem identification
current problems with data
Final experience
The simplified dashboard
Final experience
Here's the solution
Final experience
The simplified dashboard
