Smart Delivery App
Built age verification into an adaptive, peak-hour system achieving 93% compliance, 90% satisfaction, and consistent 3-minute hand-offs.
Smart Delivery App
Built age verification into an adaptive, peak-hour system achieving 93% compliance, 90% satisfaction, and consistent 3-minute hand-offs.
Smart Delivery App
Built age verification into an adaptive, peak-hour system achieving 93% compliance, 90% satisfaction, and consistent 3-minute hand-offs.
Status & Year
Launched (2024)
Status
Launched (2024)
Status & Year
Launched (2024)
Company
Walmart
Company
Walmart
Company
Walmart
Project type
(0-1) Design
Project type
(0-1) Design
Project type
(0-1) Design
Problem Statement & Challenges
Problem Statement & Challenges
Problem Statement & Challenges
Alcohol pickup verification was a high-stakes within Walmart’s ordering ecosystem. Associates had to confirm legal eligibility under strict compliance standards, yet decision critical signals were fragmented across multiple screens.
Under peak-hour pressure, this increased cognitive load, slowed throughput, and elevated regulatory risk especially in edge cases such as ID mismatches, partial data validation, or manual overrides.
My Contribution
My Contribution
My Contribution
I led the end-to-end design of a multi-modal verification system, defining the interaction model and validating it in store with associates. I translated regulatory complexity and real-world edge cases into clear, decision ready interfaces.
Partnering closely with Operations, Engineering, and Compliance, we delivered a solution that upheld legal rigor without slowing store throughput.
Design
1 Member
Design
1 Member
Design
1 Member
Product
4 Members
Product
4 Members
Product
4 Members
Engg+Data+Ops
8 Members
Engg+Data+Ops
8 Members
Engg+Data+Ops
8 Members
Timeline
3 Sprints
Timeline
3 Sprints
Timeline
3 Sprints
Persona, Need & Wants
Persona, Need & Wants
Persona, Need & Wants
In 18+ associate interviews, we uncovered recurring friction in the verification flow. 3.5% of orders resulted in verification errors, often triggered by unclear prompts and override paths. 25% of customers arrived without valid ID, pushing associates into improvised decisions. During peak hours, step ambiguity led to hesitation contributing to a 7% abandonment rate.
The pattern was clear: The system lacked decisional clarity at high-risk moments.
Delivery Associates:
Store executives responsible for hand-offs, payments, and age verification.
They require fast, guided flows that reduce hesitation and support confident, compliant decisions during peak hours.
Customer Support (B2C & B2B):
Support teams assisting customers aged 20–25+ and bulk buyers with varied pickup behaviors.
They need transparent verification logic and minimal friction to resolve issues quickly while maintaining compliance.
Our North Star
Our North Star
Our North Star
The redesign sought to reduce false hand-offs, support ID-less alternatives, improve accessibility across varying tech literacy levels, bring hand-off time under 3 minutes, and create an experience capable of handling exceptions cleanly and confidently.
Research
18 (User interviewed)
Research
18 (User interviewed)
Research
18 (User interviewed)
Market
EU, US (P1 Market)
Market
EU, US (P1 Market)
Market
EU, US (P1 Market)
Activities
3+ (Sample stores)
Activities
3+ (Sample stores)
Activities
3+ (Sample stores)
Timeline
4 days (Mapping & analysis)
Timeline
4 days (Mapping & analysis)
Timeline
4 days (Mapping & analysis)
Through rapid prototyping and in-store validation, the system evolved into a guided, adaptive workflow supporting both ID and ID-less verification paths.
It introduced stepwise guidance, intelligent exception handling, and real-time validation reducing ambiguity in high-pressure moments.
The goal wasn’t just transaction completion, but confident, compliant decision-making without cognitive overload or fear of error.
Ideate, Test & Measure
Ideate, Test & Measure
Ideate, Test & Measure
Measuring impact beyond the interface.
Measuring impact beyond the interface.
Post-launch metrics showed reduced verification errors and lower abandonment during high-traffic periods.
More importantly, associates reported greater decisional clarity in complex scenarios.
The system proved that compliance and speed are not opposing forces when interaction design is built around context.
From concept to rollout delivering measurable clarity at scale.
From concept to rollout delivering measurable clarity at scale.
The system was deployed across stores with structured validation checkpoints and phased adoption.
Verification errors declined, abandonment reduced during peak hours, and associates reported higher confidence in handling edge cases.
What began as a workflow redesign became a shift in decision architecture balancing compliance rigor with operational speed.
Impact
93% (Compliance achieved)
Impact
93% (Compliance achieved)
Impact
93% (Compliance achieved)
Impact
90% (Task satisfaction)
Impact
90% (Task satisfaction)
Impact
90% (Task satisfaction)
Impact
30+ (Test order samples)
Impact
30+ (Test order samples)
Impact
30+ (Test order samples)
Impact
< 3 Mins (Task time)
Impact
< 3 Mins (Task time)
Impact
< 3 Mins (Task time)
Continue Reading...
Smart Delivery App
Built age verification into an adaptive, peak-hour system achieving 93% compliance, 90% satisfaction, and consistent 3-minute hand-offs.
Smart Delivery App
Built age verification into an adaptive, peak-hour system achieving 93% compliance, 90% satisfaction, and consistent 3-minute hand-offs.
Smart Delivery App
Built age verification into an adaptive, peak-hour system achieving 93% compliance, 90% satisfaction, and consistent 3-minute hand-offs.
Status & Year
Launched (2024)
Status
Launched (2024)
Status & Year
Launched (2024)
Company
Walmart
Company
Walmart
Company
Walmart
Project type
(0-1) Design
Project type
(0-1) Design
Project type
(0-1) Design
Problem Statement & Challenges
Problem Statement & Challenges
Problem Statement & Challenges
Alcohol pickup verification was a high-stakes within Walmart’s ordering ecosystem. Associates had to confirm legal eligibility under strict compliance standards, yet decision critical signals were fragmented across multiple screens.
Under peak-hour pressure, this increased cognitive load, slowed throughput, and elevated regulatory risk especially in edge cases such as ID mismatches, partial data validation, or manual overrides.
My Contribution
My Contribution
My Contribution
I led the end-to-end design of a multi-modal verification system, defining the interaction model and validating it in store with associates. I translated regulatory complexity and real-world edge cases into clear, decision ready interfaces.
Partnering closely with Operations, Engineering, and Compliance, we delivered a solution that upheld legal rigor without slowing store throughput.
Design
1 Member
Design
1 Member
Design
1 Member
Product
4 Members
Product
4 Members
Product
4 Members
Engg+Data+Ops
8 Members
Engg+Data+Ops
8 Members
Engg+Data+Ops
8 Members
Timeline
3 Sprints
Timeline
3 Sprints
Timeline
3 Sprints
Persona, Need & Wants
Persona, Need & Wants
Persona, Need & Wants
In 18+ associate interviews, we uncovered recurring friction in the verification flow. 3.5% of orders resulted in verification errors, often triggered by unclear prompts and override paths. 25% of customers arrived without valid ID, pushing associates into improvised decisions. During peak hours, step ambiguity led to hesitation contributing to a 7% abandonment rate.
The pattern was clear: The system lacked decisional clarity at high-risk moments.
Delivery Associates:
Store executives responsible for hand-offs, payments, and age verification.
They require fast, guided flows that reduce hesitation and support confident, compliant decisions during peak hours.
Customer Support (B2C & B2B):
Support teams assisting customers aged 20–25+ and bulk buyers with varied pickup behaviors.
They need transparent verification logic and minimal friction to resolve issues quickly while maintaining compliance.
Our North Star
Our North Star
Our North Star
The redesign sought to reduce false hand-offs, support ID-less alternatives, improve accessibility across varying tech literacy levels, bring hand-off time under 3 minutes, and create an experience capable of handling exceptions cleanly and confidently.
Research
18 (User interviewed)
Research
18 (User interviewed)
Research
18 (User interviewed)
Market
EU, US (P1 Market)
Market
EU, US (P1 Market)
Market
EU, US (P1 Market)
Activities
3+ (Sample stores)
Activities
3+ (Sample stores)
Activities
3+ (Sample stores)
Timeline
4 days (Mapping & analysis)
Timeline
4 days (Mapping & analysis)
Timeline
4 days (Mapping & analysis)
Through rapid prototyping and in-store validation, the system evolved into a guided, adaptive workflow supporting both ID and ID-less verification paths.
It introduced stepwise guidance, intelligent exception handling, and real-time validation reducing ambiguity in high-pressure moments.
The goal wasn’t just transaction completion, but confident, compliant decision-making without cognitive overload or fear of error.
Ideate, Test & Measure
Ideate, Test & Measure
Ideate, Test & Measure
Measuring impact beyond the interface.
Measuring impact beyond the interface.
Post-launch metrics showed reduced verification errors and lower abandonment during high-traffic periods.
More importantly, associates reported greater decisional clarity in complex scenarios.
The system proved that compliance and speed are not opposing forces when interaction design is built around context.
From concept to rollout delivering measurable clarity at scale.
From concept to rollout delivering measurable clarity at scale.
The system was deployed across stores with structured validation checkpoints and phased adoption.
Verification errors declined, abandonment reduced during peak hours, and associates reported higher confidence in handling edge cases.
What began as a workflow redesign became a shift in decision architecture balancing compliance rigor with operational speed.
Impact
93% (Compliance achieved)
Impact
93% (Compliance achieved)
Impact
93% (Compliance achieved)
Impact
90% (Task satisfaction)
Impact
90% (Task satisfaction)
Impact
90% (Task satisfaction)
Impact
30+ (Test order samples)
Impact
30+ (Test order samples)
Impact
30+ (Test order samples)
Impact
< 3 Mins (Task time)
Impact
< 3 Mins (Task time)
Impact