Shipping Fast + Shipping Right
In August 2025, Rently assembled a small cross-functional team to quickly validate a new product idea: Rently Pay. The hypothesis was that offering the right perk could get tenants paying rent on our payment rails, with the long-term intent of upselling additional products to them down the line.
I was the product designer on the team. We had a few months, limited dev resources, and a mandate to get a signal fast — one we could communicate to investors.
How One Persona Turned Out To Be Three
We'd launched a new product that allowed tenants to earn airline miles on their rent payments.
We had a working theory about who our early customers would be: mile hunters. I spoke to real users to find out if that held up.
It did, and it didn't. What looked like one segment turned out to be two, and a new segment emerged altogether. Untangling all of that took going back to the interview script more than once, and following threads I hadn't expected to find.
17 users
Total Interviewed
Over 21 interviews
3 personas
Outcome
Research revealing 3 distinct segments
UX Researcher
My Role
Interview design, synthesis, cross-team collaboration
01 The Brief:
Discover Customer Personas
Rently Pay's team hypothesised that most of our early customers would be "mile hunters" — seasoned mile collectors with high miles literacy.
My job was to talk to real users who had signed up for Rently Pay, and find out if that held up. What I learned would shape how we understood our users, and inform what we could do to improve the product.
First, the page displayed a milestone stat — "10,000 miles earned by RentlyPay customers" — prominently above the fold. The product hadn't launched yet. Nobody had earned anything. I completely understand that this is a marketing tactic to hook users into signing up. But beyond being factually false, it was exactly the kind of claim that would erode trust with the users we were asking to hand over large recurring rent payments.
Fake stat, erodes trust
02
Initial Findings
Several interviews in, two groups were surfacing: the first group looked to be textbook mile-hunters. On the surface, it seemed to confirm the team's hypothesis.
But as interviews continued, behavioural and emotional differences surfaced even within that group. I suspected there might be more nuance here than met the eye, so I went back to my interview script and added questions designed to learn more about the specific behavioural and attitudinal differences I'd noticed.
Then I kept interviewing, partly to keep learning, and partly to validate that the nuance I was seeing was real across a larger sample size.
03
Evolving the Research
Along the way, as other stakeholders shared what they wanted to find out about each persona, I continued evolving my interview script to dig deeper.
How did miles-literate users form their pricing benchmarks?
Finance was curious how our high-literacy users thought about pricing, wanting to learn more before we locked in our product's pricing. I called back several mile hunters I'd already spoken to, brought finance in to run that conversation directly, and sat in to moderate the discussion.
Which USPs speak the most to each persona?
Marketing wanted some early insights to inform them on their ad strategy.
Where can we find each persona?
Touchpoint mining became a permanent fixture in every new interview.
After 21 interviews across 17 participants, we had three distinct, colourful, maps of who our customers were. We also had a first glimpse into where to find them, what kind of pricing they'd be willing to pay, and what marketing messages spoke to them.
04
Beyond the Interview Room
Once the personas were solid, I shared them with the wider team. Different people found different uses for them:
Upper management
Used these qualitative insights, together with quantitative data, to create Ideal Customer Profiles (ICPs).
Marketing
Used the personas to make sure ad strategy targeted each persona's relevant pain points.
Product
Designed for each persona's behaviours, and fixed points of friction brought up during interviews.
Finance
Used insights to inform pricing strategy.
To make the personas usable day-to-day, I put together a cheat sheet: each persona's pain points, goals, behaviours, and the kind of messaging that would land with them, condensed onto something a teammate could glance at before writing a landing page line or drafting a pricing tier.
05
A Peek Behind the Curtain
I've put together a separate document detailing my investigative process in analysing the two similar-but-distinct personas. However, due to the confidential nature of this information, it has been gated behind a password — happy to share the password if you're considering me for a role.
(And if you're not either of those, please enjoy these three images that very vaguely relate to the three personas.)
