ClickUp AI Credits
Project overview
This project focused on designing the end-to-end experience to support the launch of AI Credits for ClickUp. I led the design across the full customer journey, including paywalls, checkout, billing management, usage dashboard, and upsell flows. By transitioning from a SaaS add-on to a consumption based credit system, the launch introduced a new revenue stream and drove incremental growth for the business.
Tool
Figma
Baymard
UserTesting
Method
Competitor Research
User Survey
Wireframe
Prototype
Role
Lead product designer
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Timeline
October - November 2025
Design Deliverables
Paywall
Checkout​
Value Dashboard
Billing & Upsell
Usage Dashboard
Gamification
Project Impact
$2M+
new revenue from AI Credits in the first month of the launch
1.6x
Increase in checkout conversion rate
(51.5%) compared to the average CVR of existing paywalls
10.6%
Increase in paywall click through rate for AI Procuts
Project Background
Context
The existing ClickUp AI add-ons operated on a flat subscription model, which created limitations in scalability and monetization opportunities. To support the broader launch of ClickUp premium AI features, the company decided to transition to a consumption-based pricing model powered by AI credits. This shift required rethinking how customers discover, purchase, manage, and understand AI usage across the product lifecycle.
Challenges
This project required operating under significant ambiguity and speed, as the new pricing strategy, business rules, and technical constraints were still being defined while design and development were already in progress. Decisions needed to be made quickly to meet an aggressive launch timeline. I helped bring clarity to the ambiguity by defining core experience principles and scalable patterns early, enabling the team to move fast while maintaining a cohesive end-to-end experience.
Design Process
Competitor Analyze
I partnered closely with the Pricing & Packaging teams to define the underlying business logic, including credit structure, pricing tiers, and packaging strategy.
In parallel, I started by analyzing the competitive landscape across SaaS products that use consumption-based or credit models to understand industry patterns, terminology, pricing structures, and UX approaches. This collaboration ensured the experience would accurately reflect the business model while remaining intuitive for our customers.
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User Research
To validate early assumptions, I created rapid wireframes exploring how customers would select and purchase a consumption-based add-on within a SaaS environment. The research focused on key questions:
- Do users understand the value of credits?
- How do they interpret usage and cost?
- What information is needed to make a confident purchase decision?
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Vibe Code
Given the speed of the initiative, I leveraged AI-assisted tools such as Google Studio, Lovable, and Cursor to quickly generate interactive prototypes and explore multiple concepts in parallel. These prototypes enabled faster stakeholder alignment on information architecture, feature scope, and user flows.
I also used low-code prototypes to run quick usability tests with users, validating assumptions and reducing risk before engineering investment. This approach significantly accelerated iteration cycles and decision-making.
Iterations
During the iteration phase, I explored visual directions to make the AI credit experience feel distinct and premium within the product ecosystem. We experimented with customization and new color pallets for AI products, to create a sense of innovation and differentiation from the core product UI.
The goal was to balance novelty with usability, ensuring the experience stood out while still feeling cohesive with the overall design system.
MVP
To support an aggressive launch timeline, I partnered with the PM to define the minimum viable experience required to enable monetization. The MVP focused on three core components:
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AI paywalls and upgrade entry points
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Checkout for purchasing credits
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Billing and credit management
We leveraged the existing design system to accelerate delivery while maintaining consistency and reducing engineering overhead, enabling a faster path to launch.
Post Launch
After launch, the focus shifted from enabling purchase to demonstrating ongoing value. Early insights showed that customers needed better visibility into how credits translated into outcomes, not just costs.
I began designing improvements such as value dashboards and usage insights to help customers understand ROI, build trust in the consumption model, and encourage continued adoption.
