Reworking Amazon's Browsing History
Masters in UX Design Case Study Project
If you’ve ever used Amazon’s Browsing History functionality, you may have stumbled a bit because it didn’t exactly fit your shopping workflow. But most importantly, you probably wondered how to get to that thing you really wanted three weeks ago.
Research Plan
How might we empower users to make more informed and efficient purchasing decisions, while minimizing the time spent on browsing and reducing decision fatigue?
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Key objectives
1. Understand potential issues with Browsing History
2. Create recommendations using qualitative methods
2. Create recommendations using qualitative methods
Research method justifications
Cognitive Walkthrough:
Objectively determine points of interest and high priority targets. Combing through tens of thousnads of reviews on App Marketplaces confirmed that a significant percentage of users voiced concerns about Amazon's Browsing History.
Desirability Testing:
Understand users' gut reaction with extremely low cost to see aesthetic design issues (if any)
Literature Review:
After confirming no large and pressing issues, using literature reviews can help point out areas of improvement that aren't critical but can improve the overall user experience.
Objectively determine points of interest and high priority targets. Combing through tens of thousnads of reviews on App Marketplaces confirmed that a significant percentage of users voiced concerns about Amazon's Browsing History.
Desirability Testing:
Understand users' gut reaction with extremely low cost to see aesthetic design issues (if any)
Literature Review:
After confirming no large and pressing issues, using literature reviews can help point out areas of improvement that aren't critical but can improve the overall user experience.
Research Session
1. Cognitive walkthrough
Scenario:I recall a previously browsed item from any time frame while window shopping on Amazon. It is hard for me to remember exactly what I searched to get the item, and I do not remember what the item was called. So I searched through Amazon's typical shopping and browsing experience to no avail.
After stumbling on my Browsing History, I navigate to the exact item I found a couple of weeks ago, but it took me a lot of scrolling and searching.
After stumbling on my Browsing History, I navigate to the exact item I found a couple of weeks ago, but it took me a lot of scrolling and searching.
Core Tasks: 1. Add any desired item from Browsing History to a Wish List
2. Add a recommended item from Browsing History to Cart
2. Add a recommended item from Browsing History to Cart
Evaluative Questions:1. Will the user achieve the right outcome for both core tasks?
2. Will the user notice that the correct action is available to them?
3. Is the link between control and action present?
4. Will the user see progress is being made toward their goals?
2. Will the user notice that the correct action is available to them?
3. Is the link between control and action present?
4. Will the user see progress is being made toward their goals?
2. Informal Desireability testing
A sample of five participants, all shop online via Amazon, responded after quick exposure to screenshots of Amazon's Browsing History at various points. A deck of adjectives and qualitative attributes were provided after each feature, which participants assigned 2-3 words to. The word deck is condensed and adapted from Microsoft's reaction cards.
Annoying
Approachable
Attractive
Boring
Busy
Clean
Comfortable
Complicated
Confusing
Consistent
Controllable
Desirable
Difficult
Distracting
Dull
Easy
Efficient
Effortless
Empowering
Engaging
Essential
Expected
Familiar
Inconsistent
Ineffective
Intuitive
Irrelevant
Ordinary
Organized
Overwhelming
Personal
Relevant
Satisfying
Slow
Standard
Analysis
Literature review
Literature helped inform how we might be able to improve products that don't ahve flow breaking issues. Despite a product being 98% of the way there, how might we bring it to even more elevated levels of experience?
Using notes from my notes and observations from the above research methods, in conjunction with several texts, pointed me to understand Jakob's Law and minimizing repeated elements .
Findings:1. User expectations are met and cognitive walkthrough shows no breaking issues. Most notes from users revolved around layout and aesthetics.
2. Users experience minor inconsistencies between the typical Amazon shopping experience and the Browsing History shopping experience.
Using notes from my notes and observations from the above research methods, in conjunction with several texts, pointed me to understand Jakob's Law and minimizing repeated elements .
Findings:1. User expectations are met and cognitive walkthrough shows no breaking issues. Most notes from users revolved around layout and aesthetics.
2. Users experience minor inconsistencies between the typical Amazon shopping experience and the Browsing History shopping experience.
Recommendations
final mockup:
Change Log:1. Browsing History Grid converted to List view, increasing row height, size, and detailed information
2. Include Timeline (as implemented in the carousel version of the Browsing History in navigation bar)
3. Filtering Sidebar (by dates, by other options)
4. Adding Browsing History to Search Bar Dropdown
2. Include Timeline (as implemented in the carousel version of the Browsing History in navigation bar)
3. Filtering Sidebar (by dates, by other options)
4. Adding Browsing History to Search Bar Dropdown
Reflection and Lessons
Systems integration
How feasible are design recommendations? It is easy to say that the user's experience triumphs over all; however, do all of the user needs align with business objectives? Do they align with budget, regulatory, and compliance?
testing in a vacuum
Isolated research and prototyping implementations of larger systems can be dangerous: tests done outside an organization may not encapsulate the entire story of how an organization conducts their research studies and standards. Taking an example from eBay's A/B testing regarding display density: confirmation on smaller scale studies may not translate to real interactions.
Citations and References
[1] A List Apart
Garrity, Steven, et al. “Design with Difficult Data.” A List Apart, 16 Apr. 2019, alistapart.com/article/design-with-difficult-data/.
[2] Brave new world of visual browsing
“Brave New World of Visual Browsing.” UXmatters, 3 Aug. 2009, www.uxmatters.com/mt/archives/2009/08/brave-new-world-of-visual-browsing.php.
[3] How to build habit forming products
Woods, D. Ben. “Book Review: Hooked: How to Build Habit-Forming Products.” UXmatters, 21 June 2021, www.uxmatters.com/mt/archives/2021/06/book-review-hooked-how-to-build-habit-forming-products.php.
[4] ux strategies for ecommerce success
Nudelman, Greg. Designing Search: UX Strategies for Ecommerce Success. Wiley Pub., 2011.
[5] aesthetics,.., engine interaction
Katz, Adi. “AESTHETICS, USEFULNESS AND PERFORMANCE IN USERSEARCH — ENGINE INTERACTION.” Journal of Applied Quantitative Methods, vol. 5, no. 3, 2010.
[6] jakob's law
Yablonski, Jon. “Jakob’s Law.” Laws of UX, lawsofux.com/jakobs-law/.