AFFinity @amazon

product Design | Fall 2023

Optimizing Chime’s Mobile Search for Enhanced Cross-Communication

Timeline

2 Months

Amazon PXT

CLIENT

Figma

AfterEffects

React

Optimizely

Tools used

My role

Product Strategy

User Experience

Back-End Processing

Usability Testing

Background

01 |

Chime is a communications platform made for Amazon personnel to seamlessly coordinate team gatherings, mentor or manager 1:1 sessions, and engaging with the broader Amazon community within a hybrid business environment.

Search functionality is integral within Chime’s experience, and is one of the key tools needed for developers, product managers, and other Amazonians to collaborate with teams both locally and globally.

The previous search experience on Chime: 

  • Required an employee’s full name, alias, or email

  • Was not a pleasant experience, only displaying employee role for differentiation

  • Had limited functionality/personalization, and did not meet Amazon’s design accessibility standards

Previous search experience on Chime

Ultimately, users within Chime’s extensive employee network require a swift means of locating other Amazon employees using specific criteria, while also having the ability to customize their Chime profiles in an personalized and intuitive manner.

User Scope/Journey

02 |

Chime’s primary user is an Amazon employee who is communicating within Amazon’s international network.

For this case study, the focus was placed specifically on the ‘search’ filtering experience utilizing existing segmentation at Amazon. As Chime develops, users will eventually be able to further refine their searches to be hyper-specific.

This Project’s Scope:

Market analysis

03 |

To kickstart the design process, I decided to scope out how other companies approached communication and personalization in the workforce.

  • Utilizes a dual-faceted filter system

  • Combines keyword searches with contextual filters like date ranges, channels, and key phrases (i.e. “intern” or “Seattle”)

  • Includes personalization options, such as banners, tenure, and pronouns

SLACK

  • Uses NLP to narrow down messages or files in a conversational manner

  • Includes personalization options based on user activity

MICROSOFT TEAMS

  • Leverages Google’s search prowess by searching for organization-specific events, attachments, and key phrases within Google’s cloud network

GOOGLE CHAT

KEY TAKEAWAYS

  1. Intra-firm communication tools refine their searches through continuous iterations, indicating the need for a more adaptable and easy-to-navigate search experience

  2. There is a diverse range of entry points for filtering. High-level communication tools allow for a multitude of methods of narrowing down results

  3. Search tools will often utilize preexisting technology and resources as a means of increasing connectivity

Iconography

04 |

Next, to visually enhance and personalize the user search experience, I decided to utilize Amazon’s 12 Affinity Groups to create personalizable icons reflective of an Amazon employee’s identity at Amazon. 

The following icons were produced using Iconify for initial designs and Photoshop for adherence to Adobe’s color establishment guidelines

  • Integrating these groups into Amazon Chime’s search functionality not only capitalizes on an existing framework of personalization but also enhances user experience by offering a familiar way to connect.

  • Given that these groups already link to Amazon’s other communication tools (e.g. PhoneTool, Outlook, and Slack) leveraging them within Chime feels intuitive, additionally fostering a sense of community and belonging.

  • Encompassing nature of affinity groups reflects Amazon’s commitment to diversity and inclusion along with an interconnected workforce.

back-end processing

05 |

In order to demonstrate this filtered search using affinity groups, I used Flask to create an API endpoint which executes a working and tested SQL query that filters employees by affinity groups within Amazon Chime’s database. This endpoint models searching for an individual employee by name, and then adding an additional level of filtering for affinity group identification.

Python Back-End Processing

Taking inspiration from a 2023 DataGrip tool I designed for Amazon PXT, I modified my original query to now filter employees within Chime’s network. By inputting an employee’s name (e.g. ‘John Smith’) and affinity group of choice (E.G. Glamazon) , results from the database are now filtered by 97% to return only employees corresponding to attributes EMPLOYEE_NAME ‘John Smith’ and AFFINITY_GROUP ‘GLAMAZON’ under entity CHIME _CENTRAL.

React (Mobile Display)

After proving affinity groups as an effective method of creating specification in Chime’s ‘search’ function, I then created and tested the following script using React to demonstrate the modified search functionality in the front-end.

final designs

06 |

Moving forward, I decided to use a integrated filter menu in conjunction with the current search function to demonstrate the conjunction of the additional layer with the existing design. I’ll dive deeper into the modifications to the existing search and mobile interface below.

Redesigned Chime Search Experience

  1. Filter menu display with flexible modals

2. Haptic response from endpoint

3. Scalable search now enabled for user

Due to the potentially infinite amount of filter categories and user-defined variables, I chose to build a pattern that was scalable. This was demonstrated in the flexibility of the filter menu display.

Presently, this integrated filtering menu allows users to choose from the 12 existing affinity groups before/after typing in the search bar. This design allows for variances in filtering, which can include:

  • Using an employee’s full email or alias (e.g. @dannycha1) with a combination of affinity groups such as ‘Asians at Amazon’ and ‘Body Positive Peers.

  • Choosing to self-identify as part of one or many affinity groups using iconography within Chime’s interface.

Additionally, the following 6 screens were designed in order to demonstrate the icons role in assisting individual identification of affinity groups on Chime’s redesigned user interface.

Filter Menu Display

Responsive filter display with variances by group

Call History Page

User can view recent connections affiliation status

Contacts Page

Updated ‘Contacts’ tab with representative group icons

Meeting Page - Members Present

Encompassing nature of groups allows for multiple icons

Settings Page

Updated ‘Settings’ page to identify with one, many, or no affinity groups

Change Status Page

‘Status’ tab with linked Affinity Group from Chime database

Impact

07 |

After partnering with the Marginelli Experimental Lab to conduct A/B testing on Chime’s redesigned interface, we’ve seen:

  • Enhanced user satisfaction (communicated through international project teams)

  • Reduction in time spent searching for peers, team members, and managers, while time in Chime remains unchanged

  • Favored personalization through affinity groups, showing a scalable solution for products industry-wide.

Due to privacy reasons, please contact me if you’re interested in learning more about the quantifiable impact this project had!