Omni Assist Redesign Case Study

Overview

Omni Assist is a virtual assistant designed to enhance the Omni workflow by leveraging Generative AI-powered agents. It provides insights, notifications, and recommendations across various stages, including audience development, planning, activation, measurement, and optimization. Omni Assist automates insights, improves collaboration, and enhances user experience by leveraging Generative AI to analyze data, summarize trends, and simplify workflows. It also offers efficient asset management and provides comprehensive training and support to ensure effective use.

My Role

As Director of UX/UI and head of the department, I led the strategy and design of Omni Assist. I collaborated with Product lead to define the requirements, guided a multidisciplinary team through research, design, and implementation, and ensured alignment with user needs and business goals. My work focused on creating an intuitive, scalable interface and collaborating across teams to deliver an innovative, user-centric AI experience, resulting in an innovative assistant that empowers users while maintaining simplicity and trust.

Problem Statement

The current workflow for managing audience development, planning, activation, measurement, and optimization within Omni is highly fragmented and time-consuming. Users face challenges in efficiently extracting insights, managing client/brand assets, and collaborating across various stages of the Omni workflow. This results in increased cognitive load, inconsistent data management, and delays in decision-making processes.

Our Goals

Automate Insights: Develop Omni Assist to quickly analyze large amounts of Omni Audience data and extract key insights that make audience segments unique and actionable for campaigns. This includes recommending similar or related audiences and integrating audience insights from other social, commerce, and retail media platforms.

Enhance Collaboration: Leverage Generative AI to summarize industry and cultural trends, synthesize work from all Omni applications, and improve notifications and alerts. This will foster better and faster collaboration across OMC agencies and with clients.

Improve User Experience: Simplify interactions by reducing the cognitive load on users. We ntroduced features like one-click workflows to pull data and auto-generate flowcharts, progressive disclosure to hide advanced settings until necessary, and automated taxonomy assignment based on campaign parameters.

Provide learning resources: Offer both live and on-demand training sessions to help users understand Omni Assist's functionalities and applications, ensuring that teams can effectively leverage its capabilities.

Building the Foundation

Competitive Analysis

Evaluated each of our major competitors in the market, and pulled out feature comparisons on function, UX patterns, and interaction design to gauge standards and areas where we could innovate without causing users additional cognitive or motor load.

User Interviews

Talked to key users and their teams to learn how the assistant could be most valuable. We realized we needed both a data-connected stand alone, as well as contextual, experience given the complexity of subject matter and user interface.

User flows

By mapping out the different use cases, we defined each of the user flows to assign functionality and define the underlying user experience.

Personas

The Omni platform caters to 7 different personas. Omni Assist directed its focus to a handful of those, creating opportunities to enhance insights-gathering and develop efficiencies around task completion and data-driven decisions. These attributes would address user pain points voiced previously, such as “Omni just creates more work” and “these applications are way too complex to learn and use.”