Experience Design, User Research, UX Mechanism Generation and Implementation

Dates: January 2023 - November 2023 

Project Owner: Chloe Chen

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My Measurable Impact 

• Amazon Robotic’s product catalogue has no lovable products- with an average score of 67.88% and labeled as only minimally viable. This means there's a lack of UX incorporation in the product development process.

• UXHM Protocol in its first 6 months covered 33% of the product catalogue, demonstrating its ease of implementation and low-lift data collection for non-UX experts.

• UX Research Data Collection efforts measured out to be over 450 participants across North America, via both on-site usability observations and online surveys

• Over the span of 11 months, I spearheaded the UXHM strategy development, developed a UR Protocol, created and maintained a data -driven dashboard for over 15 Amazon borne products.

• The UXHM was documented and handed over to UX team after my departure, with well equipped documentation to continue data collection and implementation.

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Creating and Driving Product Ownership

At Amazon Robotics, I aimed to drive usability ownership across the orgnaization. This project focuses on creating a closed looped mechanism to measuring usability of products in the Amazon Fulfillment ecosystem. 

I created a test protocol and scoring system that detects high and lower performing products in terms of usability and desirability. Currently (as of November 2023), there has been data collected for 14 native products.

The UXHM serves as an educational resource for engineering teams by providing examples of good/bad UX, teach them effective protocols to measure product UX, translate data into user needs and next steps, and overall UX training. The UX leaderboard will ultimately have scores for all AR products that demonstrate how products rank against each other in terms of usability and clear up the ambiguity between on how usable products looks. The scores will provide a general insight onto what users like and disliked about the system and offer a chance for teams to reiterate or revisit features of the products. This can empower teams to engage with or own UX at each development phase. Product Management, Product Launch, Customer Success, and L-team will be able to make data-informed decisions on where to focus UX efforts for maximum impact.

 

Why do we need a Usability Health Meter (UXHM)? 

The UXHM is survey collection strategy that gives product owners a cohesive understanding of the usability of Amazon Robotics borneproducts. The survey, with metrics of all UX areas, is designed by UX experts but implemented by non-UX experts. Non-Design memberscof Customer Success and Product Launch can run these ten minute surveys tests with low-lift. That way, we can drive usability across other teams throughout product development and feasibly collect user feedback across all launched products.

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What is the UXHM Survey?

The UXHM is a seven-question survey that consists of usability metrics that are specific enough to measure single products but versatile enough to be applied across ALL AR products. These metrics help find the most usable products among the AR catalog to better recognize poor usability of the existing products. This serves as a resource/template that determines how “usable” a product is for Amazon employees. The Usability Score Board combines usability metrics, standardized surveys, and organized data collection to build a ranking system of existing AR products and their usability levels. The templatized survey measures user experience criteria like desirability and usability to successfully frame and build a product score that outlines holistic user experience. Metrics like System Usability Scale, Usability Metric for User Experience, Customer Satisfaction Score, and Task Load Index are built upon each other to gather quantitative data from users.
This system gives opportunities for different product owners to understand their product’s ranking in the AR ecosystem and improve their usability in that context.​

To hear more about this project, please reach out to Chloe at cc985@cornell.edu