The Role
Workplace: White City, London - 2 days a week in the office
The role
We are looking for a proactive, detail-oriented "doer" to become the operational engine of our measurement framework. This isn't a role for a theoretical observer; it's for an orchestrator who thrives on making complex test & learn projects happen. This role will be planning, leading and unifying the cross channel delivery of testing solutions to improve channel effectiveness.
Sitting at the intersection of our Media Channel Leads and our Analytics specialists, you will ensure our Marketing Mix Models (MMM) are fed with the right data and that our Test & Learn ideas are translated into rigorous, actionable experiments. You will be the guardian of "what works," ensuring every lesson we learn is recorded and, crucially, applied to our future media output.
Main responsibilities
1. MMM Operations & Data Stewardship
- Data Supply Chain: Serve as the primary point of contact for all data sharing and queries from MMM partners. In collaboration with them you will manage the timely process of gathering, cleaning, and formatting media spend/ delivery and performance data for our Econometric (MMM) models.
- Accuracy & Quality Assurance: You will ensure all shared data is accurately formatted and reflect the reality of our media activity across all platforms.
- Performance Interpretation and storytelling: Assist in interpreting model results, helping to translate statistical outputs into a clear narrative regarding which channels are over- or under-performing, and where the opportunity for growth lies.
- Agency partner: Act as the supporting daily contact for our econometrics agency. You will manage their workflow, ensure they are adhering to briefs, and challenge their recommendations when they don't align with business needs or processes. Internally you will champion their work and ensure engagement with the output.
2. The Experimentation Bridge (Test & Learn)
- Technical Translation: Collaborating with strategists and analysts to take ambitious ideas from Channel Leads (owned and paid), translating them into technical briefs for specialists to build.
- Initiative Support: Design and set up cross-channel Test & Learn initiatives, including A/B testing, Meta/Google Lift studies, and regional Geo-tests across both owned and paid media.
- Backlog Prioritisation: Own the deployment of the measurement roadmap. You will decide which tests or model updates are most urgent based on the upcoming media calendar and broader business priorities.
- The "Knowledge Bank": Maintain the central Test & Learn Log. You will document every outcome, ensuring that "lessons learned" are never lost and are actively used to programme the following month's media plan.
Skills you'll need (minimum criteria)
- Multi-channel knowledge: proven experience working across multiple media channels.
- Measurement Frameworks: Proven experience working with, Marketing Mix Modeling, Multi-Touch Attribution, and Incrementality Testing.
- AdTech/MarTech Stack: Familiarity with the "plumbing"-how pixels, APIs and Clean Rooms function to collect data.
- Vendor Management: Experience managing relationships with third-party measurement partners.
Other things we're looking for (key criteria)
- The "Translator" Mindset: You understand the fundamentals of marketing measurement and analytics (significance, incrementality, and coefficients) but you speak the language of a Media Planner with multi-channel understanding.
- Operational Grit: You are a "doer" by nature. You don't mind getting into the weeds of a spend file to ensure the data is 100% correct before it reaches the analysts.
- Project Management Skills: You are highly organised and capable of managing multiple workstreams between different teams with competing deadlines.
Experience: You likely have demonstrable experience within a media business. Either agency (Data/Analytics/Planning/ Transformation) or an in-house effectiveness operations role. Ideally you will also have experience with both paid and owned media with an ability to evidence the nuances in their measurement challenges.