Redesigning Lloyds goals
Creating a goals journey to make saving feel achievable.
My role
As squad lead and senior content designer, I owned the end-to-end content strategy, journey design, and cross-functional coordination. I worked closely with my UX and UI designers throughout, taking the lead on shaping the experience's structure, language, and the expectations it set from the very first interaction.
Discovery and direction
The brief was to redesign the goals journey to be easy to use, easy to understand, and actually useful. In practice, it felt more complex than it needed to be.
Data showed us that users were creating goals and not returning to them. A significant proportion of goals were left unlinked, meaning they weren't linked to any savings account and therefore didn’t do anything for the customer.
Research pointed to two root causes: the first was a mental model problem. Our users were primarily under 35 and Monzo or other neo-bank customers, which meant they arrived with a Monzo Pots frame of reference.
Goals weren’t pots! They didn't move money or create a new account, but the existing experience did nothing to correct this assumption.
The second was a language and consistency problem. To understand the scale of this, I used AI to audit how goals were referenced across the Lloyds app. The results showed that goals were described in different ways across different journeys, with no consistent framing. For a concept that was already confusing, this made it worse.
To understand how people actually thought and spoke about goals, along with the design researcher, I ran multiple rounds of language testing. We used AI to process the transcripts and surface recurring language patterns. This gave us a richer picture of the vocabulary customers naturally used when they were thinking about saving.
Designing the content experience
Fixing the mental model
The core challenge was setting the right expectations before someone got lost. I designed a new onboarding experience built around one idea: Goals tracks your balance against a target amount. It doesn't move your money or create a new account.
This ran through every touchpoint. We moved away from language like "link an account", which meant little to most users, and described what was actually happening in plain terms.
The account selection page was a particular sticking point, which surfaced interest rates, sort codes, and account numbers. The detail and design were previously based on the payment journey, making setting up a goal feel like a transaction. I stripped it back to just the account name and balance, making it visually and functionally distinct from payment tiles. One page, one decision, one action. Links to other journeys, such as the save-and-invest calculator, were removed entirely to keep the focus clear.
Keeping content consistent and accessible
To make sure content hit the right reading age for our audience, I used AI-assisted tools to check public-facing content against readability targets throughout the project. This gave us a consistent, objective check at each stage, which was really useful given the volume of content involved and the financial confidence levels of our core users.
Outcomes
Over 200,000 active goals, with around 75% now linked to a savings account
Around 60,000 new completed goals
Users began setting more realistic savings targets, which is a measurable behavioural shift
Satisfaction score of 4 stars, up from 3.25
Learnings
Mental models are more powerful than features
The problem wasn't the product; goals did work. The problem was the gap between what users expected and what they got. Closing that gap was almost entirely a content problem. We needed to gett the language, framing, and sequence right from the first screen.
Removing content is a design decision
The biggest improvement to the account linking page wasn't something we added; it was everything we took out. Knowing what to cut is as important as knowing what to say.
AI changes what's possible in research
Using AI to process transcripts and surface language patterns wasn't just a time-saver. It had a big impact on the quality of our work. We were able to analyse more data, in more depth, than would have been feasible manually. For content designers working on language and terminology, this is one of the most valuable places to use AI in a project, and something I’ll definitely take forward into other projects.
