Audience Builder is a product designed for employees of Ibotta to build advertising segments with. 30,000 employee hours are projected to be saved by this tool.

Summary

It takes an Ibotta employee 4 hours to create one kind of targeting rule in the current system. Audience Builder's MVP addressed this problem first. With the current number of requests, this fix alone would save 30,000 employee hours. 

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Challenge

Designing a product from scratch that works well visually and functionally in the current enterprise ecosystem. It must be future-proof to accommodate new feature releases and simple enough so that a new employee can use it in their first week. 

Audience-Builder-IA
IA of the tool existing in the overall ecosystem

Research

Interviewed stakeholders to understand what we know about the problem and what else we need to know.  Mapping information architecture and user flows was the goal in order to establish a framework of what is needed for MVP. Validating the current hypothesis was important for me to be confident that I'm solving the correct problem.

userflowsketch2
Paper draft of user flow
Audience-Builder-MVP-User-Flow-1
User flow of all possible options and identified happy path
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Initial concept

The information architecture of Audience Builder was core to its value. My first thought was to use radio buttons to select mutually exclusive options in order to provide safeguards against confusing logic strings. 

Setup-draft-2-1
Setup screen v1

Results

Users found the flow to be demanding and distracting, requiring them to think through the inputs in a way that read differently than what was in their heads. Specifically, the radio button options were distracting. 

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First usability testing

To reduce the cognitive load of the form fields I broke out the exclusionary logic into a tabbed slider and replaced radio buttons with dropdowns. The tabbed slider was used to expose the exclusion logic upfront, since this was a common parameter for audience building.  Dropdown options used natural language, so the entire "Condition" read as a sentence. This was supported by the review page where inputs were laid out in plain text. Testing revealed a slowdown in form field completion and a constant re-checking of dropdown selections.

Setup-1b
Setup screen v2
Review-1a
Review screen v1

Results

Testing revealed a slowdown in form field completion and a constant re-checking of dropdown selections. Click path movement and selection from the first dropdown to the last produced different results with different people.

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Refinement

Previous versions had a Z-shaped field format and contributed to long completion times and sustained confusion. This version aimed to remove extraneous features, like the colored population bubbles, to take advantage of the extra space by utlizing an L-shaped format where the inputs could read like a sentence. 

Setup-1b_v2
Setup screen v3
Review-1a_V2
Review screen v2

Results

Technical limitations for the given launch timeline inhibited features from making it to MVP, like estimated population sizes, exported audience formats, and logic operators. Additionally, the L-shaped field format caused responsive design issues where fields would end up vertically stacking anyways. 

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MVP

Phase 1 was a quick fix and a large pivot from the original goal of the MVP. The pivot included a large visual change as well as a major functional change. Visually, a three-column format that fully disclosed all options, as opposed to the progressively disclosed single-column format in previous iterations, was used. Functionally, the output of the tool was a JSON code string, as opposed to an end-to-end system handshake.  

MVP-Phase-2-Audience-Builder
MVP

Results

Ultimately, test results were positive! Time to create a targeting rule that originally took up to four hours was reduced to an hour. Phase 2 would be the longer term fix that visually aligned better with the enterprise ecoystem, as well as introduce some of the functionality stripped from the original plan.

Phase 2

The goal of phase 2 is to more closely align with the overall enterprise ecosystem and make a full end-to-end solution. A history log of built audiences that can be re-used and QC'd, a dynamic setup screen that progressively discloses options to lower cognitive load, and a review screen that summarizes all inputs into plain-text English with supporting visuals to verify inputs produced the expected audience size.

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Home - history of audience builds
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Setup screen phase 2
A2-Review
Review screen phase 2

Role & Responsibilities

I was the lead designer on a squad with a Product Manger, Engineering Manager, and four engineers. User research, usability testing, information architecture, prototyping, and handoff to development were my responsibilities. Collaboration between other designers on the team to ensure parity across the enterprise ecosystem was an important part of this process. 

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Designed & built by Chris Del Bene

© 2020