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Brandi AI Case Study

Brandi AI

*The complete case study is best viewed on desktop or tablet. This mobile version is abridged.

Product Design

SaaS Web App

Multimedia CMS

Project Summary
My Role

UX & UI Designer

Skills

Design team collaboration, product management, client relations, UX research, requirements handling, data management, UI design

Team

3 UX Designers

Clients

Gaurav (Founder), Anonymous (Co-Founder)

Timeline

Oct. 2022 - Feb. 2023 (5 months)

Deliverable

SaaS Web Application

Case Study Summary

Problem

How might we help marketing and sales teams to effectively personalize video assets at scale?

Solution

Design an end-to-end SaaS web application for AI-driven video content creation.

Impact

Clients presented the MVP prototype and successfully secured investor funding.

Project Overview

Project Overview

Introduction

My Role

Problem

Solution

Introduction

Who is Brandi AI?

Founded by two former Google employees, Brandi AI is a marketing platform that utilizes NLP models and stable diffusion to transform a single video into numerous variations, with emphasis on hyper-personalized content for digital marketing.


Creating video content is resource-intensive, but automation and generative AI offer cost savings and optimization opportunities. As AI advances in producing realistic imaging and audio content, Brandi AI seeks to leverage generative AI for scalable personalization of video marketing assets.

Problem

What does Brandi AI aim to solve?

"Audio and video AI models are rapidly becoming capable of generating commercial quality content. How can we enable businesses to efficiently leverage AI for the creation and management of hyper-personalized video marketing assets?"

— Brandi AI Founder (paraphrased)

Solution

How we solved the problem

These solution methodologies allowed us to meet the client's short and long term needs, streamlined the design process, and optimized our workflow. These solutions were created using the double diamond framework.

Double Diamond Framework

Using divergent and convergent thinking phases, enables us to understand user needs, ideate creative solutions, and re-iterate. It allows us to solve complex problems while fostering innovation and user-centered outcomes.

Reusable Solutions

We created a versatile UI Kit with components reflecting common design patterns to meet client requirements, improving reusability and streamlining hand-off for future designers.

Custom Solutions

We conducted extensive research, provided comprehensive documentation, and designed customized features, sitemaps, and user flows to meet the specific requirements of a startup, going beyond the common scope.

Jump to MVP Prototype

Discovery & Research

Research Approach

Competitive Analysis

User Interviews & Pain Points

User Journeys

Research Approach

Breaking down the complexities of digital marketing and AI

During the discovery and research phase, we recognized the necessity of going beyond a standard competitive analysis of Brandi AI's direct competitors.

Gain comprehensive insight into the digital marketing world

To meet the needs of our users, we needed a better understanding of how digital marketers launch/manage campaigns and the methodologies different businesses use to hit their goals

Explore the impact of video content on marketing campaigns

Analyze competitor platforms with AI marketing features

Competitive Analysis

Generative video AI competitors often struggle with subpar content quality and a lack of user-centric features

Secondary Research

Discovering the role of videos in digital marketing

Prior to conducting an in-depth competitive analysis, the design team and our clients wanted to double down on understanding how personalized video marketing impacts businesses.


By conducting market research, prior to competitive analysis, we were able to provide a resource that informed our clients goals and increased our understanding the impact of videos in the digital marketing space.

View In-Depth Market Research

Secondary Research

Scoping out the competition

With a good understanding of video marketing, it was time to size up the competition.


From an extensive features matrix, recordings of product testing, screenshots, to design pattern analysis — we analyzed 15 competitors then presented our findings to the clients.

User Interviews

People with digital marketing needs are willing to try new tools if they are priced right, are easy to use, and streamline existing processes

By grouping responses and analyzing the affinity maps using FigJam, we were able to identify common themes and identify pain points for our target audiences.

The main takeaways from conducting user interviews is as follows:

Sample size

Sample size

7 users

7 users

Participants from

Participants from

4 countries

4 countries

With experience from

Working In

5 sectors

5 sectors

Personalized marketing content is utilized often and is great for re-engaging existing customers and generating new leads

While all participants have no experience with the hyper-personalization capabilities AI has to offer, all users have created and launched personalized marketing campaigns. The majority of interviewees stated that personalization ranged from inserting customer and business names into templates or using existing algorithms from a platform (like Shopify) to recommend similar products and services, based on the customer's profile.

Many business owners, sales, and digital marketers outside of the tech industry are not utilizing AI for marketing media. Most participants did not know AI tools for marketing exist.

When asked about AI marketing content, all participants said they had not considered or tried existing AI marketing tools. Some participants stated that it had not crossed their mind to try AI marketing.

Cost and knowledge barriers are a large reason for avoiding AI marketing platforms

For the participants that expressed interest in utilizing AI marketing platforms, many expressed concerns regarding cost and knowledge barriers. When asked why the barriers were a point of concern, many stated that the idea of using AI sounded technically challenging and assumed the service would be expensive.

View User Interview Summary Table

View User Interview Affinity Map

User Personas

Meet the users, ranging from corporate sales to small business owners

Digital marketers, salesman, and business owners are all looking for the path of least resistance to generating leads but tend to pain points specific to their roles.

After grouping common thematic key points from user interviews onto an affinity map, we created personas to represent our 3 target audiences. This allowed us to begin ideating potential task and user flows via the user journeys created to match each persona.

View All User Personas

User Journeys

Identifying differences and similarities between journeys

Despite having similar goals, each persona's user journey is radically different—especially when it comes to the start of their journey.

Each UX designer within the team meticulously crafted user journeys for individual personas. Through insightful discussions and collaborative efforts, we refined and revised our journeys, ensuring a cohesive and consistent narrative across the board.

View All User Journeys

Defining The Product

Product Roadmap & Features

User Flows

Task Flows

Product Roadmap & Features

Narrowing down nice-to-haves versus necessary features

Features Priority Matrix

Identifying and prioritizing the product's features

During stakeholder meetings to brainstorm features, we often encountered an extensive list that surpassed the essential requirements. To align with client expectations and guarantee a polished user experience in the delivered product, we conducted multiple sessions. Employing a priority matrix, we systematically evaluated and compared each feature. Following a comprehensive review, we identified features with high feasibility and impact as crucial components for inclusion in the MVP prototype.

View Complete Features List & Matrix

User Flows

Creating a flow state for the MVP

User & Task Flows

Discovering the role of videos in digital marketing

Having established the priority MVP features for the product, we convened to identify and unanimously select the top three features that form the foundational functionality of Brandi AI. Through a focused prioritization process, we outlined task flows specific to these core features. The primary user flows for Brandi AI's prototype include:

1. Create a new video campaign

2. Record and edit videos

3. Upload, define, and edit variables from datasets

View User & Task Flows

Designing a Foundation for Development

Low Fidelity Wireframes

Brand Kit

UI Kit

Ideation

Visualizing a concept

Low Fidelity Wireframes

From sketches to building a framework in Figma

Leveraging insights from competitive analysis, user interviews, and defined user flows, each designer focused on a specific user flow. My role centered on designing the dashboard for efficient CMS navigation. Critical considerations for the dashboard and its task flows included:

1. Simplified video data visualization for non-tech-savvy users.

2. Coherent visual patterns aligning the Dashboard with Video Editor screens.

3. Consistent UX/UI patterns for streamlined video data management.

View All Wireframes

Branding & UI Kit

Creating an identity and preparing assets for the prototype

Branding & UI Component Kit

From sketches to building a framework in Figma

We showcased diverse brand kit styles and color schemes to capture the product's personality. After client consultations, a consensus on the brand identity was reached. We then proceeded to craft a comprehensive, hand-off-ready UI kit to expedite the development of the high-fidelity prototype.

View Complete Brand & UI Component Kit

Delivering Results

Delivering Results

High Fidelity Wireframe

Prototype

Usability Testing

Reiteration

MVP Prototype

From concept to interactive prototype

High Fidelity Wireframe & Prototype

Creating polished, high fidelity, screens for an interactive prototype

Incorporating months of research, wireframing, and a cohesive brand/UI kit, our team produced an interactive MVP prototype. Designed to test the three main user flows outlined during the definition phase: creating a new video campaign, recording and editing videos, and uploading/defining/editing variables from datasets. The prototype synthesizes user insights, ensuring a dynamic and user-centric design for iterative testing and refinement.

View MVP Prototype

View MVP Prototype

Usability Testing

Putting the design to the test

Usability Testing Affinity Map

Quantifying results from usability testing

The sample from usability testing was primarily drawn from our user interview participant pool. In order to measure our results we employed the following methods for analysis:


  • Live stream, remote, prototype testing

  • Video recordings for gauging participant behavior

  • A follow up questionnaire and open feedback session at the end of usability tests

View Complete Affinity Map & Analysis

Iteration

Refining user and task flows to validate usability testing

  • Testers unanimously struggled with mapping and replacing data while creating and editing videos for mass generation.
  • 4 out of 5 users stated the concept was similar to editing spreadsheets, but felt confused about how to modify and use data from them in our prototype.

Impact

The Outcome

The client secured investor funding! Brandi AI is in development and set to launch in 2024.*

*The product brand name and scope has been changed since the completion of this project. More information available upon request.


After months of in-depth product research, design, and lengthy meetings, our efforts yielded success! We assisted in securing investors and provided:


  • A ready-to-use, robust design system for seamless hand-off.

  • Invaluable design and research to support development and future iterations.

  • Guidance on both initial and future product direction.

After iterating the prototype and conducting an additional round of usabilit testing with both old and new participants, the success rates for user and task flows were as follows:

100%

100%

5 out of 5 users

Successfully created and recorded a video

Users located the primary action button (Create A New Video) and began the video creation process without any issues.

80%

80%

4 out of 5 users

Uploaded and mapped video data with ease

After reiteration, most users were able to upload and map data to the video in the video editor within a reasonable timeframe. Due to the technical nature of training AI, this feature will be refined upon further testing using a working prototype.

100%

100%

5 out of 5 users

Quickly exported their video data using the dashboard

Once the AI had generated personalized videos, all users were able to export their video data via .xls within 30 seconds.

Conclusion

Takeaways

Working on an emergent technology project proved both challenging and enriching, enhancing my analytical skills and research expertise. Designing a comprehensive platform with content management and video editing features demanded innovative solutions and a deeper understanding of an emerging industry.


Researching and designing this deepfake video AI platform advanced my skills in:


  1. Collaboration & Teamwork: Engaging with a design team and multiple stakeholders required effective communication, concise documentation of ideas, adept project timeline management, and justifying design choices with well-researched evidence.


  2. Designing in Parallel: Integrating a dashboard with video editor workflows, aligning with UI patterns and standards set by various designers, honed my ability to apply design thinking and processes within a team environment. In contrast to my solo-unicorn-product designer experience, this project gave me a glimpse of what it means to be a part of a design team.


  3. User Experience Insights vs. Client Expectations: Balancing user experience insights with client expectations deepened my understanding of aligning user-centric approaches with client goals. This experience highlighted the importance of navigating and reconciling potential conflicts between optimal user experiences and client preferences.

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