Procter & Gamble

Product Design for DTC eCommerce

10 weeks, team of 5 | product, ux research
Procter & Gamble (P&G) is a Fortune 500 American company specialized in consumer packaged goods. P&G tasked us with designing an innovative direct-to-consumer (DTC) eCommerce experience for one of their product categories. At the end of 10 weeks, we delivered a minimum viable prototype, a presentation, and a pitch video.
My Role
Design Researcher: I conducted and managed 20 in-context interviews that include in-home visits, card sorting, ranking, and in-depth interviews. I supported with the synthesis and communication of this research to guide the design of our minimum viable prototype (MVP).
Journey Map
Competitor Matrix
In-Context Interviews
Low Fidelity Prototypes
Card Sorting & Ranking

NOTE: This project is under NDA.

To protect the confidentiality of P&G, I can only share my general design process and information already made publicly available.


 The Problem 

How to expand an eCommerce experience?

Currently, Procter & Gamble is looking to expand its eCommerce presence, especially with one of their categories of consumer packaged goods but is unsure with where to begin. P&G is looking for a desirable and viable solution to increase its eCommerce reach while beating its lead competitors.


How might we expand the business of one of Procter & Gamble's product categories through an innovative DTC eCommerce lens?


 The Solution 

Designed for the consumer

This solution was aimed towards a specific demographic who enjoys shopping online. They are socially conscious and want a product that's best for their wallets and the planet.

A digital and tangible experience

After conducting multiple rounds of research, we've used our insights and learnings to design a complete end-to-end experience, including both the digital and the tangible components.


 The Process 


Affinity Map
Journey Map
Competitor Matrix
In-Home Interviews


Design Requirements


Card Sorting
User Testing
In-Depth Interviews



Understanding the Problem Space

We began by conducting secondary research to understand the current landscape and visualized our findings using a competitor matrix. This gave us context as we conducted our primary research.

We conducted a total of 8 in-home interviews to understand the context of our users at the comfort of their homes. We asked them to tell us stories through open-ended, non-leading questions to capture their thoughts and emotions. Then, we downloaded our materials to find patterns and trends during synthesis.

After analyzing the data from our ethnographic research, we created a multitude of frameworks, including a journey map to understand our data through different lenses and visualize emerging themes and patterns. We then generated insights from those frameworks to produce several How-Might-We statements to clearly frame and define our problem.



From persona to prototype

From our research, we developed a primary and secondary persona to organize our research findings. These personas guided us through our prototyping and helped us define the functional and emotional design requirements.

We created 20 low-fidelity prototypes based on these requirements to analyze how users interact with them.



Test to evaluate, not validate

We conducted 12 tests with consumers to understand their actions and thought processes as they interacted with the prototypes.

We used a variety of research methods such as:
-Card Sort
-Photos & Sketch-Ups
-Physical Space Mock-ups

Delivering a minimum viable prototype

After iterating upon our prototypes, we polished our designs and consolidated the design process that allowed us to reach our designs. We delivered these findings and designs through a presentation and a pitch video to our sponsor, Procter & Gamble.


 Next Steps


Conduct further usability testing with refined prototypes.


Test feasibility of the detailed online process.


Further develop brand and marketing strategies.



Context matters in interviews. The environment may show more information than what consumers actually say or claim.
Ambiguity is inevitable. To mitigate ambiguity, ask for feedback and start experimenting with different frameworks to process data.

Ask for user feedback often. Asking for constant feedback helped us make quick design decisions and ensured our design met our users' needs.
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