DIGITAL PRODUCT DESIGN

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Transcription:

DIGITAL PRODUCT DESIGN MAT THEW ALDRICH SIA

Project Overview Purpose The purpose of this product challenge is to design a product feature for CarsDirect Mobile, an online automotive research portal and car buying service. The product is a Used Car Analysis, a feature that will allow users to receive instant reports on specific used cars and compare them to other used cars. This feature is built for users who shop for cars on-the-go, using their mobile phones as an assistant. Objective The deliverables of this project are high fidelity wireframes and user flows. The challenge also asks to think about the following: Factors when considering similar cars nearby How to measure user satisfaction 2

Table of Contents 02. Project Overview 04. Strategy 05. Low-Fi Wireframes 06. Hi-Fi Wireframes 09. User Flows 10. Other Thoughts 3

Strategy Business Mission and Goals Aside from what was already provided in the prompt, I strived to learn more about the CarsDirect brand in order to create a product that would be aligned with its strategy. This was done through simple online research of its website and relevant articles. User Needs The user I imagined to be using this product is based on assumptions, which were made by studying the CarsDirect brand. The user is generally an adult aged 22-30 looking for a used car, and this user is not a car enthusiast but also isn t inexperienced with cars. To put myself in the shoes of the user, I took some time to walk around a used car parking lot to imagine the car shopping experience and its pain points. 4

Low-Fi Wireframes 00. Home 01. Analysis 02a. Report 02b. Email 03. Search 5

Hi-Fi Wireframes 00. Home The home page is where the analysis form is found as this is the starting point of the entire product. 01a. Analysis Form The Analysis Form is built so that users can quickly input vehicle information. For price and mileage, a slider is used to make the input easier and faster. Alternatively, users can tap the slider circle to manually input the number. 6

Hi-Fi Wireframes 01b. VIN Reader For the VIN, users may use the camera app to quickly read the VIN from the dashboard of cars (instead of typing 17 characters). 02a. Analysis Report The Analysis Report uses the given information to identify all of the vehicle s information, including but not limited to year, make, and model. The report can transfer this information to a used car search so that users can view similar cars nearby. Users can also go back to analyze a different car. 7

Hi-Fi Wireframes 02b. Email Report Users can input their email addresses to receive a detailed report in pdf form. 03. Similar Cars Nearby The View Similar Cars Nearby feature allows users to compare the inputted vehicle to similar vehicles nearby. 8

User Flows View User Flow 9

Other Thoughts Similar Car Search Factors The phone s location or user-inputted zip code is used to find cars that are nearby. The search uses price, mileage, year, make, and model as the most important factors when searching for similar cars. The user can then sort and filter more specific information, similar to the already-built used car search function. 10

Other Thoughts Ways to Measure User Satisfaction One way to measure user satisfaction is to send users an online survey (after one week). The survey would be sent to the users who generated and received a report. The following are example questions: On a scale from 1-5, please rate this feature s helpfulness. On a scale from 1-5, please rate how confused this made you feel. Choose what most similarly resembles your situation: I found and bought a used car using this. I bought a used car, but did not use this. I haven t bought a car, but plan to do so. I decided not to buy a car. None of the above. 11

Other Thoughts Ways to Measure User Satisfaction Another way to measure user satisfaction is to use Google Analytics. Setting up the Send button on the Email Report page as the goal would allow us to measure conversion rates. A funnel visualization would help in understanding which pages have the highest exit rates. By looking at behavior flows, we can also notice the number of times a user tends to use these features. 12