Amazon Cars is an e-commerce store that allows you to shop for cars online. Unlike physical car stores, Amazon Cars has a broad selection of cars, is trustworthy, and more convenient.
Role
Product Manager
User Experience (UX) Researcher
Duration
2 Weeks
Tools
Figma, Miro
Overview
Challenge
Goals
The objective is to enhance the convenience and speed of the car shopping experience.
Process/Timeline
Here's How I Worked
Discovery and Research
Who are our customers and what do they want?
Identifying assumptions
The product is an Amazon Car e-commerce store. Based on this, I hypothesized the problem using the Customer’s Problem approach. The following questions were our focus:
- What need (s) does the product fill?
- Are there any problems or pain point it solves?
- Who would benefit most from the product?
Are there any problems or pain point it solves?
The product
- gives a wider range of choice
- appeals to people who live where limited car choices are available
- is fast
- provides delivery
- is trusted
- has a large price range to meet your budget
Who would benefit most from the product?
We’ll know this is true when
- people use and recommend it
- online car sales take a surge and almost matches physical car sales
- other competitors copy the product
What need (s) does the product fill?
Amazon Cars
is an e-commerce store
That allows you to shop for cars online
Unlike physical car stores, Amazon Cars has a broad selection of cars, is trustworthy, and more convenient
These pointed me to the following assumption statements:
- Do customers want a range of cars to choose from?
- Do customers want to shop for cars online because customers live far away from physical car shops.
- Are customers too busy to go to physical car shops?
- Do customers find online shopping easier?
- Do customers want the convenience of online payment because of the paperwork that comes with physical payment.
- Do customers want to shop according to their budget?
- How can we measure the success of the product?
Product Assumption Map
I sorted the assumptions by how much I know about them and how critical they are to the success of the product.
User Research
The assumptions were used to create research questions. My research was led with the inquiry, “What kind of car shopping experience do customers need?”. I distributed open-ended survey questions to get qualitative data from respondents. A few questions were close ended for quantitative data. 6 respondents living in Nigeria provided these quality data. 33% of them are experienced buyer ands 66% are prospective buyers
Key Insights
From the user survey, I arrived at these key insights. Based on users’ answers on he survey, the app must have the following:
Full Car Specification
- Users should be able to see a car’s full specifications
- Users should be able to speak with a real person to ask questions about the car
- Users may have the option to request for a physical inspection before purchase
- Users should be able to filter cars based on their specs
Time Saving/Convenient
- Users should be able to save time with the product
- Users should find the product convenient
- Users should be able to decide on either delivery or pickup
- Online payment would create more convenience
Trust
- The product should appear trustworthy
- Users’ ratings can be used to help people gauge their trust for the product
Budget and Preference
- Users should be able to sort cars based on their budget
- Users should be able to sort cars based on their preference such as colors and brand
Minumum viable produt (MVP) and Features
What features do we build first?
Features and user stories
Here, I turned the key insights gained from my customer research to user storis. The users stories explain the value that each of the feature will bring to customers. The next step was to prioritise the features based on importance and effort.
Prioritization
The features were prioritiesed based on thier value and the estimated effort required for implemention. I adopted Must have, Should have, Could have, and Will not have right now (MSCW) Framework for value prioritization and the T-Shirt Framework for effort estimation
Ranking Rationale
- The must have features were chosen because they match what most users wanted in the product to have based on the survey. 100% of the users want to either see car specs, brand, or price.
- The should have features are product improvement needs some users highlighted. However, the product can still function without them
- The could have feature was a need only 20% of users highlighted. While this is a great feature, it can be substituted with the “physical car pick up” feature. If users trust the product well enough, they may not need this feature at all.
<span data-metadata=""><span data-buffer="">T-Shirt Framework
<span data-buffer="">Value-Effort Map<span data-metadata="">
Strategy and Results
How do we determine success?
Here, I defined the product vision, strategy, and roadmap. This section details the future projection of Amazon Cars.
Objectives and key results
First, I defined the product’s objective and highlighted three sets of key results that serve as a benchmark to determined the product’s success
Primary, Secondary, and Health Metrics
Then, I adopted the Primary, Secondary, and Health Metrics to define all features.
Growth Metrics (AAARR)
Finally, I created an AAARR Funnel as a growth metrics to measure each stage of the funnel.
Wireframes
Landing Page
Categories Page
Car Descripion Page
Thank You
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