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Case study · Experimentation · Aplos (now Velora) · Raisely · 2 min read

Fee Opt-In: Winning the Moment Donors Change Their Mind

An A/B test on the moment a donor edits their fee. The winning design took opt-in from 75% to 92%.

Role
Senior Product Designer
Company
Aplos (now Velora) · Raisely2026
Team
With PM, Engineering, and data partners
Tools
Figma, Cursor, MagicPatterns, A/B Testing, Pendo
75% → 92%fee opt-in, A/B tested
4variations tested, including the existing control
12–20%of donors click Edit, the moment the redesign targets
Problem
A redesigned fee box looked like a win, 75% to 82%, but hid a leak in the fallback flow donors landed in.
Decision
I argued to pause the rollout, redesigned the moment a donor edits their fee, and tested four variations in Pendo to find the highest-return option.
Outcome
Fee opt-in reached 92%, with conversion and average gift size held steady.
Principle
Design the decision, not the default.
Fee Opt-In: Winning the Moment Donors Change Their Mind

The screens on this page are white-labelled recreations for a fictional charity. The real product is confidential.

Stakes

The Deceptive Win

A redesigned fee box on Raisely had just lifted opt-in from 75% to 82%, near the 90% benchmark. But the 12–20% of donors who clicked "Edit" mostly dragged the fee to the minimum or opted out. Awareness wasn't the problem. The opportunity was decision design: the few seconds after a donor decides to change something.

Reframe

Reframing the Problem

The easy move was to ship the 82%. I argued to pause: the edit box dropped donors into an older fallback that nudged them toward the smallest contribution. The new question: how do we make the easiest path a fair one, without it ever feeling coercive? Donor trust is the product.

A phone checkout with the old Edit box open, empty, beside three problems and the 12 to 20 percent of donors who click Edit
Before: Edit dropped donors into an older box that started empty, so doing nothing meant no fee.
Experiment

Designing the Decision, Not the Default

I designed three variants grounded in defaults, anchoring and soft-decline (a slider, toggle buttons and a segmented dropdown) and tested them against the existing control in Pendo. Each was built production-ready, so the winner could ship platform-wide the day the test closed.

The variants
Three phone checkouts with the fee editor open: a slider, four amount buttons, and a dropdown
The three contenders, each starting at the full fee: a slider, set-amount buttons, and a dropdown.
Legacy fallbackRedesigned fallback
1Fragmented. The new edit box dropped donors into an older UI that looked and behaved differently.One consistent control, built production-ready so the winner could ship platform-wide.
2A slide to the smallest amount. The fallback quietly nudged donors toward the minimum.Anchored at a sensible default. "A little less" feels like a small step, not a cliff to zero.
3A blank-slate field. Donors had to invent an amount.Pre-framed choices in the toggle and dropdown variants, with a soft decline kept in reach.

Try itA white-labelled rebuild of the checkout, after my MagicPatterns prototype. Pick a fallback, click Edit on the fee, and compare what you chose with what donors did.

Prototyping

Prototyping With AI

Instead of static mocks, I built interactive prototypes in Cursor and MagicPatterns where PMs and engineers could change thresholds, defaults and fallback logic and watch the outcome. It cut alignment time and surfaced constraints before high-fidelity design. You can still try the version 1 prototype and the future-state concept.

The MagicPatterns prototype: a checkout modal over a campaign photo, with a design controls panel for layout, colours, fee visibility and editor style
Instead of static mocks, a control panel: PMs and engineers could switch the editor style and fee visibility and watch the checkout change.
The next version of the prototype, with controls for the default fee level and a thank-you message when the slider reaches the full fee
The next version: teams choose the default fee level, and donors who cover it all get a thank-you instead of silence.
Hypothesis

The Hypothesis

Introducing a modernized fallback control when a donor clicks "Edit" will increase the average fee opt-in value while maintaining or improving the existing conversion rate.

Result

What Happened

The Slider lifted fee opt-in from 75% to 92%, past the 90% benchmark, while conversion and average gift size held steady. It shipped as the fallback across the platform.

Bar chart of fee opt-in: 75 percent with the original box, 82 percent with the new box and old fallback, 92 percent with the slider, past a 90 percent benchmark
The winning Slider variant cleared the 90% benchmark, without trading away conversion or average gift size.

Improving how a user changes their decision can be just as effective as improving the default itself.

What's next

Mobile, Where 60% of Giving Happens

Next is mobile, where 60%+ of donations happen and nested scrolling hides the fee-and-total review.

Two phones: today, a form that scrolls inside the page with Donate below the fold; proposed, one scroll with the fee and Donate in the footer
Next: rebuilding the fee-and-total review for mobile, where the majority of giving actually happens.

Thanks for reading.