w3

To remediate this issue, I worked with the machine learning engineers and user experience researchers to design a smart search suggestion feature to display recommended apps for users for a variety of scenarios. This project was incredibly praised and is currently in the process of implementation. Designs for one scenario are presented below.

We conducted 12 interviews to see how IBMers search for apps and found that most users had a very low tolerance for app searching on w3 and often missed the apps right rail feature and the apps tab. Instead, they defaulted to look at the search results page, which often displays irrelevant search results and do not take the user to the desired apps page. After a quick scan through the results, users would give up and ask peers to help them find for apps. Moreover, many users also download apps through external means, and would disregard our apps page, which is a breach in security for the company.

After conducting 6 additional interviews to determine why IBMers are not utilizing our right rail feature or apps tab, we found that 5 out of 6 users did not see the app suggestion on the right rail because it looked irrelevant, almost like an online advertisement. Therefore, the current suggestion feature lacks visibility.

We proceeded to do a Mural board activity with IBMers by presenting rough wireframes of the w3 search experience and asked them to map out their ideal app search experiences using sticky notes. We split our interview participants into groups and asked each group to map out their ideal experience given one of the four scenarios. This helped us identify trends to determine what users wanted to see to help us increase visibility for our app suggestion feature.

We looked at various search engines to determine how various companies utilize their page real estate with suggestions. We inspected how the following companies went about displaying search results and suggestions.
Search Engines: Google, Yahoo, Microsoft Bing, Ask
E-Commerce: Target, IKEA, Walmart, Amazon, H&M
Video Streaming: Netflix, Hulu, Disney+

From there, we analyzed the relevance of the suggestions features, ranked them, and discussed which methods would be best fit for our scenarios by determining effectiveness and visibility.

The following few graphics are the result of us consolidating our research together to find major themes of our interviews and analyses, and then organizing each major finding based on priority.

I hosted an ideation session with the other interns to sketch all possible solutions and from there, led a meeting to go over each sketch to vote on which sketches/features resonated with us the most.

After numerous rounds of discussions and deliberations, we decided to approach the solution through two major flows, in which the bottom flow was ultimately chosen.

w3 Homepage (Rapid Results):
- Including a tooltip to automatically detect unapproved apps and suggest recommendations
- Revamping the ‘Recommended Tools’ feature

Search Results Page
- Scrapping the right rail and transposing it to the top.
- Creating simpler, more visible app cards to go along with the newly constructed ‘top rail’.
- Tooltips to alert user of unapproved apps.
- Creation of an ‘Apps’ filter tab to search exclusively for apps.

Apps Filter Tab
- Exclusively search for apps, layout similar to the ‘Apps’ tab.

After three extensive design iterations, here are the final designs based on each scenario (click image to enlarge).

Scenario 1: IBM Approved App

Scenario 2: Not Recommended App

Scenario 3: IBM Unapproved App

Scenario 4: Unrecognized Search Query

What an amazing experience- the project was complex, stimulating and impactful. I worked with an amazing set of colleagues and am excited to join IBM again upon graduation. Special thanks to an incredibly fantastic team: George, Cynthia, Amy, Nimsi, Sam and Sara- it was SO MUCH FUN working with you all and I can’t wait to see you all soon again! 😀