Technology creates, culture connects. By bringing technology and culture together, I work out what your product actually means to people.
From positioning and messaging for an early-stage VC-backed product, through B2B product growth, to consumer go-to-market. Every project here is one I owned, and every one has a result to show for it.
Shorter engagements, same habit. Expand any of them.
Found the problem in the product format rather than the promotion, and designed a reusable landing-page hub to replace time-bound livestreams.
Back when TikTok was still seen as just a teenager app, I was tasked with expanding our French user base on a tight budget. I drove 266M views and grew our target demographic from 9% to 20% by organic, paid and earned channels and creative A/B testing. Mainly on Meta.
A new app product launched with no budget and no agency. I brought in 80,000 downloads through cold-pitching to Apple's editors with the brand story, positioning and messaging. It was featured on the App Store's official banner globally in 17 countries, and ranked number 1 in the Productivity category.
Entering a new market with a product the category had already written off, by changing what the product was understood to be.
Project owner of the whole programme. I conceptualised the positioning and ran the go-to-market end to end, secured the budget from zero, and scaled a cross-functional team from nobody to fourteen people across product, creative, partnerships and events, leading entirely through influence rather than line management.
Technology tells you what it can do. Culture tells you why it matters.
When Effect House came to France, the story of AR had already been written by the tech giants who got there first. It was either a complex utility for engineers, or a three-second filter for a selfie. It had virality. It had utility. It had no prestige.
Meanwhile a generation of young artists was watching, and wanted none of it. They did not need another digital toy. They were looking for a canvas: a medium that respected their ambition.
So the problem was never distribution. It was cultural:
How do you elevate AR from a technical feature into a cultural medium?
Early research came back with a low NPS, which told us something was wrong but not what. In-depth interviews did: the people who mattered were young designers, and what they wanted was not a better tool. It was exposure and a way to earn from the work.
That reframed the product. Effect House existed to solve three problems at once: not enough effects to meet user demand, brands wanting their own branded effects with no path to get them, and designers with nowhere to monetise what they made.
The original message described the product. The new one described what the product was for.
A powerful, easy-to-use AR and VR design tool.
True, generic, and says nothing about who it is for or why they would bother.
The AR tool for designers, with TikTok's audience behind it and brand partners paying for the work.
Names the audience, the exposure and the money, which is what the interviews said they actually wanted.
Create, Monetize, and Connect with Billions.
People do not engage with a tool by learning what it does. They engage by using it to say something about who they are.
So the question stopped being how to teach AR, and became: what would make a young design student pick it up not as a software exercise, but as an artistic statement?
The answer wasn't a tutorial. It was a stage.
A stage needs three things: a reason to create, the right audience, and a space that gives the work meaning.
An open contest inviting creators to reinterpret the heritage of the Grand Palais in AR, turning a technical exercise into a creative statement.
Off existing AR creators, tech communities and mature designers. Onto art and design schools, aspiring creators and young designers.
Selected works exhibited inside the Grand Palais, placing AR where it could be seen, shared and taken seriously. Creators didn't just show work. They met, and became a scene.
What we built was a context, where AR could be experienced as culture.
None of this had a budget or an owner when it started. I held no management title over anyone involved, so every one of the fourteen joined because the case was worth joining, not because it was assigned to them. That was the hardest part of the project, and the part that does not show up in the numbers.
What started as a product launch became a cultural moment. The French press covered it as an event about technology and culture rather than a feature release, and one of the contest prizes was awarded for the effect most beneficial to culture. Three thousand people came to the Grand Palais, at an acquisition cost well below what paid channels would have charged for the same attention.
The programme also seeded a creator ecosystem that kept running after it closed: over a thousand new effects a month, four in five of them originating here, and a twenty percent increase in monetisation opportunities, which was the thing the designers had said they wanted in the first place.
Creator effects made for the contest and after it, unprompted and unpaid.
Engagement was the target and livestreaming was the method. The research said the method was the problem, so I designed a different product instead.
I was the only product marketer on this. I found the opportunity, ran the research across both artists and users, designed the system logic and the prototype, and got product, design and the label partnership aligned behind a format that did not exist yet. The build was the team's; the case for building it was mine.
TikTok wanted to hold its position as the music platform of choice, and the way to get there was more music content being made on the platform. But engagement with music content was low on both counts that mattered: how long people stayed, and how much they made.
At the same time the label partners had their own problem. Artist growth was hard, and the formats available to them were not solving it.
So the question was not how to promote music better. It was: where is the product-led growth opportunity for music on TikTok?
Music on TikTok has two customers, not one: the artists who make the content and the users who watch and remix it. They want different things from the same moment, so I ran user research and built a persona for each before touching the solution.
Then I mapped the existing journey against those personas. The map showed something specific: users' emotions dipped during music livestreams. Interest fell exactly where engagement was supposed to be highest.
We had already tried lifting engagement at the other touchpoints, repeatedly, without success. That pattern is usually the signal that the problem is not in the execution.
Livestreaming is time-sensitive and crowded. It asks everyone to show up at the same moment, it competes with everything else happening at that moment, and when it ends there is nothing left to return to. For an artist trying to build a fanbase over time, that is the wrong container.
So rather than promote the format harder, I designed a new one.
A landing-page driven music hub, built around two properties the livestream did not have.
Landing-page based rather than live, so it stays up, stays findable, and can be templated for the next artist instead of rebuilt.
Missions that turn watching into making, with points and a lucky draw that bring people back rather than letting them bounce after one track. Making was the behaviour the brief existed to move.


I led a team of six on product-led growth, reporting to the Head of Product. I owned the research that defined what we were actually solving, the pricing and packaging that came out of it, and the go-to-market that put the new plans in front of users across five channels. The hardest part was not any single fix: it was turning a research finding into a price, and then into a launch other teams would commit to.
Facing rising churn on a $50M ARR product, the company needed a new pricing plan to protect retention. By cross-referencing user interviews with actual usage data, I found that daily users were not always the buyers, and the loudest requests were not the real problems. Cutting through the noise, I identified the single core feature users returned to weekly, paid or not, and anchored our new pricing model directly on it.
Two major churn drivers were product flaws that no amount of marketing could mask. I partnered with engineering to overhaul our matching algorithm and redesign the onboarding flow, letting users experience the product’s core value before demanding heavy setup. This tripled algorithm accuracy and boosted onboarding completion by 24%. We deployed these product fixes first, rather than rushing into the pricing launch.
The old access-based pricing was broken: small accounts overpaid for unused capacity, while large ones extracted massive value at a flat rate. I replaced this with a usage-based model that scales naturally alongside the customer’s own growth. I also redesigned the packaging into six distinct “Jobs to be Done” tiers. By keeping the core value in the entry plan and mapping a crystal-clear upgrade path, moving to a higher tier became a frictionless, logical progression rather than a penalty.
Free-to-paid conversion. Not sign-ups, not reach, not a launch-week spike. One goal settles every argument that comes after it, and it decides which activities are worth booking at all.
Each one carried a conversion target of its own. Target divided by the channel’s historical rate gives the audience that channel has to reach; if the reachable pool is smaller than that, the plan is already broken, and it is better to know in week one than in the retrospective.
Seven workstreams, six functions, one launch date. Both of these were agreed before the first asset was briefed, which is the only reason the date held.
| Workstream | PMM | Marketing | Data | Eng | CS | Ops | Affiliates |
|---|---|---|---|---|---|---|---|
| Research & pricing model | A | C | R | I | C | I | – |
| Packaging & plan build | A | C | C | R | I | C | – |
| Pricing page & billing | A | C | I | R | I | R | – |
| Lifecycle email | A | R | C | I | I | I | – |
| Community, in-app & PR | A | R | I | C | R | I | I |
| Affiliate co-marketing | A | C | I | I | I | C | R |
| SEO · pain-point keywords | A | R | C | C | I | I | I |
Freemium to paid conversion and upsell carried the ARR lift. The churn and onboarding numbers are what made that possible: the product work came first so that the pricing launch had something solid to stand on.
The company was using one website page, one message for all audiences. My job was to find out who our audiences were, and show each of them a different value.
I built the product marketing function from zero, reporting to the CMO. I ran the research that decided who the product was actually for, wrote the positioning and the messaging for each audience, and rebuilt the website around them. The search ranking moved because the positioning moved, not because of a keyword list.
One headline, one subhead, one button, written for a reader who did not exist: the average of three very different people. A page like that is not badly written. It is written for a composite, and a composite never signs up.
Three pages, three different first verbs. Everyday users are told they can swap, liquidity providers that they can earn, developers that they can build. The same protocol underneath, three different reasons to care, and three separate pages rather than three paragraphs on one.
“The trusted crosschain trading platform. Swap BTC, ETH, SOL and more, with excellent pricing.” Two routes in: Swap now, or How it works.
“Earn liquidity fees and native Bitcoin yield.” The page opens on a live portfolio, so the product is shown doing it before the claim is made.
“Integrate our SDK with ease… whilst fully customising your fees.” Two routes in: Build, or Get in touch.
Positioning that stays in a deck is a point of view. Positioning that ships is a decision, because a live page has to choose who it is talking to.
Most marketers write briefs about AI. This is the part where I make things with it.
A short AI-generated film with my creative conceptualisation.
A short AI-generated ad for “zoning out”, with my creative conceptualisation. Concept, script, visuals and cut, end to end, on my own.
Turns a product image and a few attributes into listing copy that holds one brand voice across hundreds of items.
Custom agents that take repetitive operational work off a team: intake, routing, drafting, filing. Built for partner companies and running in production.
Prune this to what you actually use. A stack list that cannot survive a follow-up question costs more than it earns.
From viral content on social media to B2B technical content.
Zhihu is China's long-form question and answer platform, somewhere between Reddit and Quora. Editor's picks are selected by the platform; the brand ranking is against every brand account on it.
Hey, I'm Marina, an experienced digital marketing strategist who loves Europe and is currently based in Milan. I'm keen on solving problems and building smart, strategic solutions, whether that means technical capability, creativity or commercial strategy. My strengths are in product strategy, with a focus on growth, content and branding. I am good at helping products find their voice and their audience. I speak fluent English, French and Chinese. I also know a bit of German, and I am currently learning Italian.
When I'm not working, you'll most likely find me exploring creative activities like acting, writing, filmmaking and design projects, or heading to an AI event. In terms of sports, bouldering has become a favourite of mine since I realised it mixes problem solving with courage.