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Zappos - A Remote Usability Study

Zappos - An eCommerce Evaluation

Overview

This report will focus on the findings gathered from six participants who completed three tasks on the zappos.com site. The purpose of this study is to evaluate where customers get hung up on focal points of the site. As I created each task I wanted to be specific enough so that I could perform some detailed analysis. Once I created tasks I formed a hypothesis of each to assume what users will do.


Participants

 I tested 6 participants (one male, two female) who have made online orders in the past. They fell into the demographic below:

Working professionals aged 32–45, browse online shopping sites 2-3 hours per week, and make online purchases (≥2/week). Most had visited zappos.com and a few had made purchases.


User Tasks

We came up with three tasks that would test sections of the site that draws the most attention and traffic.

Task 1

You want a pair of red Nikes. Use Zappos.com to find a pair of red shoes in your size.

Task 2

Search for a pair of black boots. Once you've found them look to where "similar items" would be located on the site and review the results. Add one of the similar items to your cart.

Task 3

Go back to the red shoes you found. Scroll to the reviews of the red shoes and read some of them.


Hypothesis

Before we screened for participants and collected data we hypothesized about the findings for the three tasks

Task 1 On finding red Nikes - Users will be able to find a pair of red shoes using one of the navigating options. (search, tabbed browsing, filtering options)

Task 2 On navigating for similar items - Users will find similar items based on results, but have difficulty in locating initially.

Task 3 On reading customer reviews - Users will have difficulty in finding where to find the red shoes they have added to the cart.

Task 1 Breakdown

You want a pair of red Nikes. Use Zappos.com to find a pair of red shoes in your size.

  • Participants completed the task by filtering or using the search bar.

  • 83% (5) of the participants used the filtering option.

  • 17% (1) of the participants used the search bar to find red Nikes.

 

 

Task 2 Breakdown

Search for a pair of black boots. Once you've found them look to where "similar items" would be located on the site and review the results. Add one of the similar items to your cart.

  • 67% (4) Would have purchased the suggested items.

  • 33% (2) Would not have purchased the suggested items.

 

 

 

Task difficulty is broken down on a scale of 1-5 (very easy to very difficult) respectively.

  • Two participants agreed the task was very easy.

  • The last four participants said the task was easy.

 

Task 3 Breakdown

Go back to the red shoes you found. Scroll to the reviews of the red shoes and read some of them. Are these valuable reviews?

We found that only one participant could not complete task three.

I could not find similar items while on the Boots/Uggs page but did see what others purchased items on the red shoes page afterwards.”

*Findings of this data is pending inconclusive as directions were not explained initially.

In our findings the participants had provided useful information we heard through observance.

my shopping cart doesn’t show a number of items in my cart. I would have expected that.”

“The categories in the sidebar were difficult to scan...I got a little lost trying to find what I wanted.”

“I really like that there is an option to click a button and a support agent from Zappos will call me to discuss shoes”

”theres only two left in stock. Oh thats useful information.

Recommendations

After collecting our findings we have come up with a few recommendations in improving the interaction of zappos.com

  • Limit the number of filters that are available on the left panel by allowing them to cascade once they’ve been initiated.

  • Provide a numerical number that reflects the number of items that are added to the shopping cart.

  • Using distinct text when referencing items that customers have browsed and suggested items relating to the item described.

  • Sorting reviews based on the number of stars an item has received. Instead of the limiting ascending and numerical numbers.

Next Steps

Moving forward on this project I would want to validate my research by testing certain copy that Zappos uses. I'm curious how the conversion rate changes with the scarcity Zappos uses. Humans value more things that have recently become less available to us. Zappos uses this method in effectively practice, but I'd want to research the low and high tolerances when sales drop off. Lastly, I want to research the value of reviews. Do users rely on reviews and do purchases go up as reviews are read?