Zuul Criteria Redesign

Zuul Criteria Redesign

Zuul Criteria Redesign

Making a complex targeting tool easier to scan, organize, and trust

Making a complex targeting tool easier to scan, organize, and trust

Making a complex targeting tool easier to scan, organize, and trust

A research-driven redesign of an internal B2B eligibility tool used by Account Managers and Site Analysts to configure, review, and maintain offer rules with greater confidence.

A research-driven redesign of an internal B2B eligibility tool used by Account Managers and Site Analysts to configure, review, and maintain offer rules with greater confidence.

Role

Product Design

Team

Internal Tools

Timeline

4 weeks

Methods

Interviews, audit

Participants

4 internal users

Criteria

Offer Eligibility Summary

Offer Eligibility Summary

Review changes

Understanding the Problem

A dense configuration workflow made review feel risky.

A dense configuration workflow made review feel risky.

A dense configuration workflow made review feel risky.

Zuul Criteria had grown into a long, hard-to-scan rule editor. Users could technically configure offers, but they had to hunt across disconnected fields, compare long lists manually, and reread settings before feeling safe enough to save.

01

Findability

Key settings were buried across a long page, making it difficult to locate the right rule quickly.

02

Scannability

Labels, controls, and values competed for attention, forcing users to parse every line instead of scanning sections.

03

Long-list management

Large include and exclude lists were difficult to review, edit, and compare without making mistakes.

04

Confidence before saving

Users lacked a clear review moment, so saving changes felt dependent on memory and manual double-checking.

Research Snapshot

Account Manager

Owns offer setup and needs quick confirmation before saving.

Account Manager

Reviews criteria across multiple client and affiliate contexts.

Site Analyst

Audits targeting logic and looks for configuration risk.

Site Analyst

Manages dense exception lists and validates downstream impact.

4/4

users wanted a clearer review moment before saving

3/4

users struggled most with long include/exclude lists

2/4

users relied on memory to understand what changed

1/4

user felt the current grouping matched their mental model

Key Insight

The tool didn’t need fewer rules — it needed a clearer way to understand what each rule was doing, where it lived, and whether the final configuration could be trusted.

The tool didn’t need fewer rules — it needed a clearer way to understand what each rule was doing, where it lived, and whether the final configuration could be trusted.

The tool didn’t need fewer rules — it needed a clearer way to understand what each rule was doing, where it lived, and whether the final configuration could be trusted.

Design Goals

01

Make criteria easy to find

Research signal: users described searching through the page as the first source of friction.

02

Create a scannable section model

Research signal: users grouped criteria mentally, but the interface did not reinforce those groups.

03

Support long-list review and editing

Research signal: three of four users called out include and exclude lists as the hardest area to manage.

04

Increase confidence before saving

Research signal: every participant wanted a clearer summary of what was configured and what changed.

05

Make the pattern consistent across criteria

Research signal: inconsistent control patterns increased rereading and slowed down edits.

Final Structure

The redesign organized the tool into seven sections that mapped to how teams talked about criteria during setup and review.

Summary

Purpose: review configured criteria at a glance. Why it matters: creates a confidence checkpoint before save.

Users

Purpose: define who is eligible. Why it matters: separates audience rules from offer and quality logic.

Attributes

Purpose: manage include and exclude attributes. Why it matters: improves long-list scanning and editing.

Pre-Ping

Purpose: configure checks before offer routing. Why it matters: makes upstream eligibility conditions visible.

Affiliate Quality Score

Purpose: group quality scoring logic. Why it matters: prevents specialized controls from getting lost in generic fields.

Analysis

Purpose: expose review and diagnostic criteria. Why it matters: supports analysts checking downstream implications.

Caps

Purpose: manage volume and pacing limits. Why it matters: keeps operational constraints separate from eligibility rules.

Design Improvements

Five changes carried the redesign: clearer grouping, a stronger summary review, consistent include/exclude controls, bulk list support, and a more deliberate visual hierarchy.

Old

Related settings appeared as a long continuous form, making users hunt for the right field.

Updated

Criteria are grouped into clear sections, so users can jump to the right mental category first.

Old

Saving required users to remember what they changed and re-check individual sections manually.

Updated

The Summary section brings the configured logic together for faster review and higher confidence.

Old

Include and exclude patterns changed by section, increasing cognitive load and error risk.

Updated

Consistent controls make each rule family easier to understand, compare, and modify.

Old

Long values were reviewed one by one, making large updates slow and fragile.

Updated

Bulk list support gives analysts a safer way to manage large sets without losing context.

Old

Controls had similar visual weight, making the hierarchy feel flat and harder to parse.

Updated

Section titles, spacing, cards, and blue emphasis guide attention from overview to detail.

Outcome

Findability — Seven sections gave users a predictable way to locate rules.

Scannability — Clear hierarchy made dense settings easier to review quickly.

Review confidence — Summary-first review reduced reliance on memory.

Efficiency — Bulk list support improved long-list management workflows.

Consistency — Reusable include/exclude patterns made criteria easier to compare.

4

participants

2

roles interviewed

7

final sections

4/4

wanted review

3/4

list pain

2/4

memory checks

5

core improvements

Final Thoughts

This project reinforced that complexity is not always the problem. Zuul Criteria needed to support nuanced business rules, specialized roles, and dense operational decisions. The redesign focused on making that complexity legible — giving users a clearer map, stronger review points, and patterns they could trust when the stakes of a configuration mistake were high.

This project reinforced that complexity is not always the problem. Zuul Criteria needed to support nuanced business rules, specialized roles, and dense operational decisions. The redesign focused on making that complexity legible — giving users a clearer map, stronger review points, and patterns they could trust when the stakes of a configuration mistake were high.