Smoll : A Dog Walking App

Project Background

Dog owners sometimes require assistance in caring for and walking their dogs, but when it comes to hiring others for this responsibility, trust becomes a significant concern.

This prompts the question:

" How might we design a trustworthy dog-walking application? "

User Research

I conducted interviews with dog owners in Bangkok by asking the following questions to empathize with the users:

Q1. Have you ever used a dog-walking/sitting service?

Q2. What do you usually do when you have to leave your dog?

Q3. Are you open to the idea of using a dog walking service for assistance?

Q4. Under what conditions would you consider using a dog-walking service?

Q5. What are the most important qualities you seek in a dog walker and the services they provide?

Additionally, I attended a group meeting to exchange insights with other students in my group to gain further insights.

Insights Mapping

User Flow

After gathering user insights, it became evident that the booking process plays a significant role for users. Consequently, I designed a user flow to outline the complete process of booking a dog walker.

Wireframes (In-App Solutions)

After that, I proceeded to design high-fidelity wireframes of each screen containing solutions from the insights mapping table.

Visual Design

Please refer to my zeroheight file.

Usability Testing

I used Maze to conduct a test for the initial prototype.

The test includes five tasks that users need to complete:

  1. Sign up

  2. Booking a dog walker

  3. Contact another dog owner

  4. Complete an active walk then rate a review

  5. Booking a recurring walk.

While the majority of the tasks went well, the booking a dog walker process show significant unsuccessful rate due to misclicks on Home Screen.

Therefore, I redesigned that screen and conducted A/B testing.

The consensus from the test was that the B version was preferable, prompting me to adopt design B. This led to an improvement in the misclick rate from 57.4% to 13% and a decrease in the time spent from 78.8 to 16.9 seconds.

Final Prototype

Below is a preview of the final prototype. Feel free to play around here :)

Posted on Nov 29, 2023
Kontharos Manathanya
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