Affinity @Amazon

Optimizing Chime’s Mobile Search for Enhanced Cross-Communication

product Design | Summer 2023

Background

Chime is a communications platform utilized by Amazon personnel for seamless coordination of team gatherings, mentor or manager 1:1 sessions, and for engaging with the broader Amazon community within a hybrid business environment.

Search functionality is integral to the Chime mobile/desktop experience, and is one of the key tools needed for developers, product managers, and other Amazonians to collaborate with employees both locally and globally.

The previous filtering experience on Chime: 

  • Utilized a scrollable menu within the search bar

  • Was not a pleasant experience, requiring an employee’s full alias for differentiation

  • Mobile application’s limited functionality/personalization not meet design accessibility standards

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Previous search experience on Chime

User scope and journey

Iconography

Market analysis

key takeaways

Qualitative Research

Low-Fidelity Exploration

Code

Project Scope Graphic

Timeline

CLIENT

2 Months

Amazon PXT

Tools used

Figma

AfterEffects

Python

Ultimately, users require a swift means of locating other Amazon employees using specific criteria, while also having the ability to customize their Chime profiles in an efficient and intuitive manner.

Chime’s primary user is an Amazonian in a corporate or field position communicating with other Amazonians using Chime’s global network. 

For this case study, the focus was placed specifically on the ‘search’ filtering experience utilizing preexisting affinity groups at Amazon. As Chime develops, users will eventually be able to further customize their personalization.

SLACK


  • 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

MICROSOFT TEAMS


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

  • Includes personalization options based on user activity

GOOGLE CHAT


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

KEY TAKEAWAYS

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  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 preexsting technology and resources as a means of increasing connectivity

To visually enhance and personalize the user search experience, I decided to utilize Amazon’s 12 preexisting 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 -like 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.

Search is an iterative process

  • Multiple convenient entry points to filter results

  • Filter category framed in concise/digestible way

Affinity Groups as a Employee Resource Tool for better personalization and community-building opportunities

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My role

Product Strategy

User Experience

Back-End Processing

Usability Testing

code! beep boop beep boop

Final Designs

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Contact Page

Settings Page

Call History

Status Page

Meeting Members Page

Conclusions

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something like "like what you see?”


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