Reimagining the Creator Experience
OVERVIEW
A Catalogue in Decline
At thortful, rapid growth exposed a fundamental design flaw: a creator base of thousands was being treated as a single audience.
thortful is a two-sided marketplace connecting independent greeting card designers with customers. Creators submit designs, moderation determines catalogue visibility, and royalties are generated per sale. The model depends entirely on a healthy, high-quality catalogue — which in turn depends on creators who understand what the platform needs from them.
During the pandemic, the platform grew rapidly. As growth stabilised and sales began to dip, catalogue quality dropped sharply in step with it. I moved from B2C Content into the creator side of the business, owning strategy end-to-end and working cross-functionally with CX, E-commerce and CRM — the problem was systemic, so the response needed to be too.
The instinctive fix was to ask creators for more: clearer briefs, stronger direction. But the creators who'd joined during that growth weren't one group with one skill level — some were hobbyists, some were building a second income, some had real design experience and many didn't. Asking all of them for more assumed a shared starting point that didn't exist.
My remit was to give creators the clarity and guidance they needed to succeed. What I found instead was a system working against that goal.
01. THE CHALLENGE
A Self-Reinforcing Loop
The lockdown surge had brought a wave of new creators — many motivated by curiosity or financial pressure, looking for creative income during an uncertain time. They were enthusiastic and engaged, but largely inexperienced. Meanwhile, established professional creators began to disengage, put off by a platform that no longer felt curated or commercially serious. The creator base had become two very different audiences, pulling in opposite directions. And we were still communicating with them as one.
The business introduced structured design briefs to address declining catalogue quality — a logical response to the problem. But the briefs exposed something deeper: a self-reinforcing loop that made things worse.
A catalogue gap was identified and new cards were needed. Briefs went out to the entire creator base. Volume submissions flooded in, but not necessarily from creators equipped to fill the gap. The moderation backlog grew and rejection rates rose – typically without feedback. Creators felt frustrated and disengaged. Catalogue gaps persisted. So new cards were needed again.
The briefs weren't solving the problem, they were amplifying it. We were unintentionally training creators to fail by sending them briefs they weren't equipped for.
Even our most capable creators got caught
This wasn't only a problem for less experienced creators. A designer joined the platform with an existing audience of over 100,000 followers — we only found out once she complained that her designs had been rejected.
The work itself was strong. It simply hadn't been adapted to what a greeting card needed commercially, and nothing in the system had told her that before it cost us the relationship. Moderation was technically correct to reject it. But strategically, we had failed her completely — the system had no way to distinguish "skilled, but unfamiliar with this format" from "not yet capable." It only had one lever, rejection, regardless of why a creator's work didn't fit.
The creator experience wasn't built for varying levels of expertise, and this was costing the business top creative talent.
02. THE APPROACH
Designing for Creator Context
The solution required two things working in parallel: a segmentation framework that reflected how creators actually differ, and a targeting logic that could activate the right content for the right person at the right moment.
The Creator Lifecycle Framework
I developed a four-tier lifecycle model based on capability and intent — moving creators from Prospect through Exploration, Development, and Performance into Partnership. Each tier carried different expectations, different support needs, and different commercial value to the platform.
But lifecycle stage alone wasn't enough. Two creators at the same tier could have completely different motivations — and motivation shapes behaviour more than capability does.
Key insight: Same tier, different motivation.
Aspiring Anna: a committed brand-builder. She uploads consistently, seeks mentorship, and responds to deep context and commercial guidance. Success measured through loyalty and consistent growth.
Side-hustling Steve: an opportunistic trend-chaser. He's sporadic, activates around cultural moments, and needs reactive, data-led prompts. Success measured through reactivity and trend capture.
This distinction matters beyond just brief targeting. In a broadcast model, Steve looks disengaged. In a segmented model, we understand he's dormant, waiting for the right trigger. That difference protects metric accuracy and prevents wasting retention effort on someone who doesn't need retaining.
Two-layer targeting logic
The logic here came directly from my CRM background. In CRM, we saw that matching content to prior user behaviour significantly increased engagement — sending a rude Christmas cards launch email to someone who'd bought rude cards before was measurably more effective than a generic broadcast. I applied the same principle to creator targeting: sending a 'cheeky card' brief to creators already strong in humour becomes a personalised invitation rather than a generic call-to-arms.
The goal wasn't exclusion, it was precision. Avoiding over-activation of the wrong audience reduces unnecessary rejection cycles and protects the creator relationship.
Layer 1 — Answers: are they capable?
Eligibility
Filter by lifecycle tier, determined by behavioural and performance data. A brief only reaches creators at the right capability level.
Layer 2 — Answers: are they suitable?
Relevance
Match brief to creative style, determined by dominant moderation style tags. A brief only reaches creators whose catalogue already aligns.
It's illogical to request modern humour from traditional illustrators. When briefs feel irrelevant, creators stop trusting them — and eventually stop opening them.
03. ACTIVATION
What we actually shipped
The strategy ran into a real constraint: implementing the full segmentation model required cross-functional support across product, CRM, and data that, at the time, wasn't resourced. The business was focused on the customer experience — creator lifecycle personalisation wasn't the priority.
So I adapted. The goal shifted from perfect segmentation to making the broadcast smarter — and from there, building the infrastructure that could support proper segmentation later.
Prioritised Personas
Rather than trying to serve all personas simultaneously, I focused activation on two core and two secondary personas — making commercial priorities explicit in every brief rather than leaving creators to guess what the platform needed.
Creator Central
When tailored support wasn't scalable, we built Creator Central: a structured self-serve hub where creators could find onboarding guidance, technical resources, design briefs, and insights without relying on the team for answers. I partnered with customer service to build content around recurring friction points, simplified internal jargon, and ensured consistent terminology across the experience.
The goal was to move from reactive email pushes to a structured ecosystem that supported creators at different stages and reduced dependency on ad-hoc support.
Seasonal Lookbooks
We introduced seasonal Lookbooks as an inspiration tool — giving creators commercial context and aesthetic direction ahead of key occasions. The goal was to shift creator behaviour from reactive to anticipatory, which had a secondary benefit: earlier submissions reduced moderation bottlenecks and gave the marketing team earlier access to fresh content ahead of major campaigns.
04. MEASUREMENT
Correcting the metric
Before measuring the impact of the new system, I had to fix a distortion in how we were measuring creator performance. When I joined the team, performance was largely measured by total sales per creator. This sounds logical until you look more closely.
A single viral card featured in an ad could inflate a creator's perceived performance. We were measuring visibility, not reliability. Celebrating spikes, not consistency.
Engagement
Email engagement (open rate / CTR)
Was guidance becoming more relevant to the people receiving it?
Relevance
Lookbook downloads
Were creators actively seeking commercial guidance, or ignoring it?
Quality
Proportion of 4–5 star moderated designs
Was design quality improving across the catalogue?
Behaviour
Upload timing vs. key occasions
Were creators responding earlier, suggesting better commercial awareness?
I proposed shifting the primary metric to catalogue acceptance rate — the percentage of submitted designs approved for discovery — combined with average sales per approved design. This separated quality from luck, and surfaced a problem the old framework had been hiding: we had many 'one-hit-wonders' whose majority of designs weren't approved, yet who appeared in our list of top creators.
What we measured and why
40%+ open rate on the first seasonal Lookbook — around double the community newsletter open rate
Briefs & Insights consistently outperformed community content on engagement, suggesting increased relevance
Proportion of 4–5 star moderated designs increased across the catalogue
Upload peaks moved earlier ahead of key occasions, reducing moderation pressure before major campaigns
Recurring support queries decreased — suggesting Creator Central was reducing friction
Positive creator satisfaction sentiment and increased social sharing
05. IMPACT
Behaviour Changed Before Revenue Moved
Early indicators validated the directional shift:
These were early signals that things were improving — even before revenue could fully reflect the change. Any revenue impact required longer-term measurement.
06. REFLECTIONS
What This Work Taught Me
Three things I'd carry into every product project from here:
Align ambition with operational capacity early
I came into this role with a lot of ambition — and genuinely believed the business was ready to invest in a structural shift. I've since learned how important it is to sense-check operational capacity before designing the solution, so strategy and constraints are aligned from the start.
Design metrics that reinforce the behaviour you want
Total sales was the headline metric — which meant we were celebrating spikes rather than consistency. Metrics don't just describe what's happening; they influence where attention goes. I'm now much more deliberate about asking: what behaviour are we actually rewarding?
Pair intuitive insight with structured research
Much of the persona work came from lived experience working across the business. But structured research carries weight in a different way — especially with senior stakeholders. I'd formalise those insights earlier next time. Not because the intuition was wrong, but because evidence helps align everybody.
You can't reduce complexity by adding more information. You reduce it by helping people feel confident navigating it.