Payday Improvements screens
Shipped

Payday Improvements

Role
Product Designer, end-to-end product ownership
Team
Weatlth Automated squad (1 product manager, 1 data analyst, 2 frontend + 3 backend engineers).
Timeframe
1 month, shipped Q2 2025

Overview

This project started as part of a wider refactor of Plum’s automation rules, following changes in the design system.

For Payday, we went further than a visual refactor. It was Plum’s highest-impact saving rule, with users saving around £80 each month on average.

The opportunity was not creating demand. It was removing friction from discovery and setup.

The problem

Hard to complete

Payday had the most complex setup of all saving rules, with multiple inputs required. Only 35% of users who started setup completed it, the worst conversion across all rules.

Hard to discover

Payday was not present in onboarding, where automation habits are most likely to form. It was also less visible than Automatic and Weekly, which were surfaced by default.

Where automations surfaced on Home and inside the automations hub, with Payday only reachable from the hub screen

Goals

Move Payday from a high-value but underused rule into a core saving habit.

For the business, this meant growing Payday share from 45% to 50% of automation-active users, while increasing deposits and AUM.

For users, this meant making Payday easier to discover, quicker to set up, and less effortful to trust.

Research insights

01

Payday already had product-market fit

250K+ users had already enabled Payday without onboarding, and 7 out of 10 interview participants were already using it.

That told us the problem was not demand. It was activation.

Source: Automation usage data and New Pockets interviews.
02

Setup friction was blocking adoption

Payday had the longest setup of any savings rule, and only around 30% of users completed the flow.

Confidence and ease of setup also scored only average, showing that automation setup still felt harder than it should.

Source: Setup funnel data, SUS survey, and app usability study.
03

Discovery mattered as much as the flow

Changing the Home entry point reduced Payday conversion from 33% to 26%, even before users reached setup.

That showed surface and framing could influence behaviour as much as the flow itself.

Source: Adoption analysis and pre-launch funnel data.

Exploration & Evaluation

Early exploration

We explored the most effective setup experience for Payday, comparing manual setup, contextual nudges, and bank-linked autofill to minimise effort and maximise adoption.

Manual setup concepts
Manual setup concepts
Automatic setup concepts
Automatic setup concepts

Evaluation

We conducted a moderated usability study with 6 participants recruited through Useberry, all of whom were new to Plum, to evaluate the redesigned setup before implementation.

In-app setup

Users found the setup flow easy once they reached the right screen.

The setup screen was mostly clear, but some users felt it was slightly too packed with information.

The main friction was not the flow itself, but making Payday easier to notice and access.

Usability study insights for the in-app Payday setup flow

Onboarding setup

Users rated the onboarding Payday flow as very easy to complete.

The setup screen was clearly understood by all participants.

Trust around financial data remained the main question, especially around provider familiarity and data analysis.

Usability study insights for the onboarding Payday setup flow

Design decisions

Decision 1

Reduce setup effort

Why: We believed fewer decisions would increase completion.

We reduced setup to two inputs, cutting the average setup time in half with smart defaults and a simpler flow.

0.0s
Old
0.0s
New
Decision 2

Improve discoverability

Why: We believed earlier visibility would increase adoption.

We introduced Payday in the onboarding automation step.

Payday added to the automation onboarding flow, with amount and frequency pre-filled
Decision 3

Keep the experience familiar

Why: We believed consistency would reduce uncertainty.

We aligned the onboarding and in-app setup patterns.

Onboarding setup and in-app Payday setup shown side by side, using the same layout and inputs

Impact

Weekly Payday adoption increased from 55% to 64%.
Monthly Payday users grew from 250K to 265K.
Setup conversion increased from 30% to 39%.
Payday AUM grew from under £19M to over £22M.
All-rules automation adoption increased by 22%.

The honest miss: setup conversion improved, but stayed relatively low. It showed that simplifying the flow was not enough on its own.

Takeaways

Optimising the flow was not enough

Simplifying setup helped, but only after users reached the flow.

Next time, I would spend more time finding the best moment to nudge users to automate.

Discovery needed to be more contextual

Adding Payday to onboarding helped, but onboarding is only one fixed moment.

Next time, I would explore behavioural prompts based on when users get paid, save manually, or show repeated saving intent, instead of relying only on static app surfaces.