Ten years selling tech. Now I market it.

Bringing global channels to 2 million UK homes

Freesat needed more content to keep viewers and its TV brands happy. My job was to find channels and content owners worldwide, sell them access to Freesat's audience, and get them live on the platform.

Objective

Grow revenue and content on Freesat by signing new channels and apps, and keep existing partners renewing.

Audience

Free-to-air broadcasters and content owners around the world, from news to lifestyle and kids' content.

What I did

• Prospected and sold Freesat's reach to channels such as Bloomberg, Virgin, France 24, Bike TV, Yanga and Best Direct.
• Brought content onto Freesat's connected TV devices as apps and IP channels, including France 24, Eros and Ketchup.
• Generated leads at MIPCOM, IBC, AfricaCom, NATPE Miami and TV Connect, and presented Freesat's cloud-based smart TV solution at conferences.
• Built a retention strategy based on closer relationships with content partners.

Result

We hit our joint target of £8.5 million a year as a team of two, and brought well-known international channels such as Bloomberg and France 24 to UK viewers.

Next test

Launch a partner referral scheme, where happy channels introduce new ones, and compare its win rate with cold outreach.

Growing the OpenWeather Challenge

OpenWeather runs a yearly data challenge for students and researchers. Our brief was to grow it: more participants, stronger sponsors and a clearer position against other data competitions.

Objective

Find the real reason the Challenge was not growing and recommend a plan the team could run with its current resources.

Audience

Four personas: a student, a PhD researcher, a corporate sponsor and an academic partner.

What I did

• Benchmarked the Challenge against NASA Space Apps, ECMWF Code for Earth, CASSINI Hackathons and Kaggle.
• Built three budget scenarios and recommended the middle one, with an extra £1,000 for a nurture email sequence and ambassador stipends.
• Proposed treating sponsors as co-designers of specific tracks, not passive funders. This gives them a reason to stay.
• Split every resource into internal and external, with UK freelance costs where OpenWeather lacked the skill in-house.
• Created the shared deck template and the participant journey map in Miro.

Result

The data showed the problem was completion, not reach. So the plan moved spend from awareness to fixing website friction and supporting people through to submission. We presented it to the OpenWeather team in September 2026.

Next test

A/B test a shorter application flow against the current one and track completion at each step.

Predicting churn before it happens

A plan to lead a marketing team through one innovation: using machine learning to spot customers likely to cancel, then reaching them with a personalised offer before they leave.

Objective

Tackle a real, unsolved retention problem at a subscription business, and show how a marketing department would test, staff and fund the fix.

Audience

Internal leadership and the marketing, data and CRM teams who would deliver the project.

What I did

• Built the case from public evidence: HelloFresh retired its Active Customer KPI in 2024, closed its Nuneaton distribution centre, exited Italy and Spain, and customer reviews describe poor retention experiences.
• Positioned churn prediction as a complement to the existing generic win-back, not a replacement.
• Wrote the experimentation plan, team structure, RACI, budget and risk sections.
• Used the Gartner Hype Cycle and VREA to judge readiness, and situational leadership and Tuckman's stages to plan the team.

Result

A full plan a marketing lead could take to the board, with a phased test before any wide rollout.

Next test

Run the model on one customer cohort with a holdout group, and compare retention against the generic win-back.

Launching a premium current account

A launch campaign for a £16 a month premium account, planned from data rather than guesswork.

Objective

Acquire 80,000 customers in one quarter at a target cost per acquisition of £25.

Audience

Two segments from k-means clustering: tech-savvy millennials and Gen X professionals.

What I did

• Structured the plan with the RACE framework: Reach, Act, Convert, Engage.
• Picked SEO and referrals as lead channels based on past channel performance, and split the budget across five channels.
• Designed sequential single-variable A/B tests on the landing page.
• Set KPIs for efficacy, value and spend, plus GDPR and data deletion rules.

Result

A plan where every channel and pound had a reason. At target, the LTV to CAC ratio is about 7.7 to 1.

Next test

Test two referral reward levels and compare cost per acquisition by segment.

AI video for brands

I write and produce short video with AI tools. It lets a small team test creative ideas quickly, without a full shoot.

Objective

Give small businesses ads that look professional on a small budget, and prove I can take a brief from idea to finished video.

Audience

Social audiences on Instagram, TikTok and YouTube.

What I did

• FerrParts: a product ad for a car-parts company, shared with the client's permission.
• Spec work below: two SaaS products, a tech brand, a premium water, a kids' cereal and a lifestyle mood film. Each one has a different tone, so together they show range.

Result

A growing body of work that shows scripting, visual direction and editing for social formats.

Next test

Test three opening hooks on the same ad and compare the share of viewers who watch past three seconds.

All six are spec pieces. More at framevy.com.