Senior Lifecycle Data Strategist

About The Company

Technology has revolutionised the world we live in, yet somehow the rail industry has stayed much the same as it was 30 years ago. Seatfrog is here to change that. We're on a mission to build a better future for billions of passengers and the rail companies that carry them. We've already reinvented how upgrading your seat is done - now affordable and lightning fast to over 870 destinations - and enabled customers to effortlessly swap between train journeys. But we're not stopping there! We're on our way to becoming the ultimate travel companion and the only app you'll ever need when travelling by rail in the UK and beyond. We’re building a stellar team to achieve our audacious goals. We strive to create an environment where you can do your best work. Join us, and you’ll be challenged and supported in equal measure. Ours is a culture with spirit and substance and our people are empowered to make the bold decisions others wouldn’t and haven't.

About The Role

Salary band: £75-85k

We are seeking a Senior Lifecycle Data Strategist to lead the data, decisioning and planning capability that underpins lifecycle and CRM growth at Seatfrog. This role is responsible for identifying where growth opportunities exist across the customer journey, understanding the underlying drivers of user behaviour, and translating these insights into a prioritised set of initiatives and experiments designed to drive measurable impact across activation, conversion, retention and repeat behaviour. This role reports into the Head of Growth Marketing and works cross‑functionally with Product, Marketing, Design and Analytics to align on priorities, roadmap, testing and measurable growth outcomes. You will operate at both a strategic and executional level, translating customer insight and behavioural data into clear, actionable plans. This includes defining audience logic, decisioning frameworks and next‑best‑action approaches that enable more personalised and effective lifecycle experiences. This is a role for someone who thinks strategically about data, is comfortable getting hands‑on with the detail, and knows how to move from insight to action. This is a senior individual contributor role with significant influence over strategy, prioritisation and execution.

You will shape how Seatfrog understands and engages its customers by:

• defining the audience architecture that underpins lifecycle activity
• establishing the measurement and experimentation frameworks that guide decision‑making
• designing the decisioning logic that determines how we personalise at scale

You will have direct influence over product, marketing and commercial priorities, ensuring lifecycle strategy is aligned to business impact rather than driven by channel execution alone.

What You’ll Do

Own the data and audience strategy that underpins the CRM and lifecycle programme, covering the full passenger journey from registration through to repeat upgrade behaviour. Design and maintain a lifecycle segmentation framework — defining behavioural, recency and intent‑based audience tiers across never‑transacted, active, lapsing and churned user cohorts. Identify opportunities within customer, behavioural and transactional data to drive activation, conversion, retention and reactivation, translating these into a prioritised initiative roadmap. Build the data planning process: defining audience selection criteria, suppression logic, journey hierarchy rules and frequency caps across all lifecycle programmes. Develop business cases for lifecycle initiatives, sizing the opportunity and estimating expected impact before committing to build.

Lead an audit of existing customer data sources and event tracking to define and validate the lifecycle segments required for activation, retention and reactivation programmes. This is a priority deliverable in the first 30 days. Map the behavioural signals, Amplitude events and Braze attributes currently available against what the lifecycle strategy requires — and produce a clear gap analysis and data requirements brief for Engineering and Analytics. Proactively identify missing data points and drive a development roadmap to incorporate new signals into the campaign management platform. Ensure all audience strategies are structured correctly in Braze, including computed traits, custom attributes and event‑based triggers.

Lead the design and implementation of a next‑best‑action framework — defining the decisioning logic, data inputs, audience rules and channel sequencing that determine which message each user receives at each lifecycle moment. This work lays the foundation for an AI‑powered decision‑ing engine and fully personalised 1‑to‑1 lifecycle experiences at scale. Translate the next‑best‑action framework into a practical decision‑ing architecture implemented in Braze Canvas, using real‑time behavioural signals and event data to trigger and personalise lifecycle messaging. Map out the lifecycle capability roadmap from rules‑based campaigns toward behaviour‑triggered, model‑driven personalisation and drive the sequencing of that evolution in partnership with Analytics and Engineering.

Design sophisticated audience segmentation frameworks using multi‑dimensional behavioural signals — route behaviour, journey proximity and intent scoring — ensuring every lifecycle programme reaches the right users at the right moment. Implement and activate predictive model outputs within audience selection, working closely with Analytics: apply the Upgrade Intent Score to prioritise never‑transacted and lapsing users by likelihood to convert; apply the Point‑of‑Lapse / Churn Model to identify early disengagement signals and trigger pre‑emptive CRM intervention before users lapse fully. Proactively identify gaps in available data and work with Analytics, Engineering and Product to define requirements needed to improve segmentation precision. Ensure all model‑driven and behavioural audience strategies are structured correctly in Braze — including computed traits, intent score attributes, custom events and Canvas entry criteria — so segmentation logic is faithfully executed in every programme. Own the suppression and eligibility logic across the full programme to prevent message collision and protect user experience.

Design and own the experimentation framework for lifecycle and CRM — defining test design standards, sample size requirements, holdout group methodology and statistical significance thresholds. Partner with Analytics to ensure all experiments produce reliable, causal learning — moving beyond inconclusive results toward a structured programme that builds genuine knowledge over time. Champion a data‑led test‑and‑learn culture across the CRM team and wider marketing function.

Define and maintain the CRM reporting framework — ensuring the team has a clear, consistent view of lifecycle performance at both programme and initiative level. Translate data findings into clear, commercially relevant stories for the Head of Growth Marketing, leadership and cross‑functional stakeholders. Partner with Analytics to deliver post‑campaign analysis and feed learning back into the audience strategy and planning process. Champion customer‑centricity across the growth team — ensuring decisions are grounded in behavioural evidence rather than assumption.

Ensure all data capture, audience selection and CRM activity complies with UK GDPR and PECR requirements. Act as the key point of contact for data governance and privacy best practice within the growth marketing function.

What You’ll Need

We are looking for a senior strategic operator — someone who has built and owned data strategy in a complex consumer environment, is comfortable leading cross‑functional conversations, and knows how to translate insight into a plan that a CRM team can actually execute.

• 6-10 years of experience in data strategy, data planning or lifecycle strategy roles within digital consumer businesses.
• Proven track record of designing and implementing lifecycle segmentation frameworks and data‑driven audience strategies that drive measurable commercial outcomes.
• Hands‑on experience with next‑best‑action frameworks or decisioning engine logic — either designing the framework yourself or working closely with a team that implemented one.
• Experience working with MarTech platforms, ideally Braze and Amplitude.
• You do not need to be an engineer, but you need to understand how data flows through these systems and how to instruct others to configure them correctly.
• Strong background in customer lifecycle strategy — you understand what good looks like across activation, conversion, retention and reactivation, and you know how to sequence a programme to get there.
• Experience building and overseeing experimentation programmes — test design, holdout methodology, sizing and statistical interpretation.
• Agency experience is a distinct advantage: candidates who have worked across multiple clients and industries tend to bring both strategic breadth and a strong ability to build and present a clear point of view.

• Ability to move comfortably between strategic thinking and detailed data planning — you are as comfortable designing an audience architecture as reviewing a segmentation brief.
• Strong analytical mindset with the ability to extract meaningful signals from complex, high‑volume data sets and translate them into a clear commercial narrative.
• Excellent communication skills — you can translate data strategy into language that product, creative and commercial stakeholders understand and act on.
• Commercially astute: you think in terms of revenue impact, not just campaign metrics.
• Highly organised with strong prioritisation instincts — able to manage multiple planning workstreams without losing sight of what matters most.
• Collaborative by nature, with experience working in fast‑moving cross‑functional environments.

• Experience with decisioning platforms or NBA tooling (e.g., Hightouch or custom‑built decisioning layers within Braze).
• Familiarity with propensity modelling, behavioural segmentation or intent scoring in a CRM context — either commissioning models or working closely with data science teams to apply them.
• Experience in a subscription, marketplace or travel business where repeat behaviour and lifecycle depth are the primary growth levers.
• Prior agency or consultancy experience where you were responsible for building and presenting data strategy to senior clients.

• An outstanding team culture, where we solve problems together to drive the best possible results
• A competitive salary
• A 4 day working week to ensure the best possible work/life blend (hello 3 day weekends!)
• Private healthcare plan via Aviva, with added gym discounts and incentives to encourage you to get out, get active and stay mentally and physically healthy
• A benefits package that includes salary sacrifice childcare benefit, enhanced parental leave, electric car leasing scheme, and free upgrades with our rail partners
• Engaging, all expenses paid monthly team days to connect and collaborate

The Process

• 30 Minute Screener - with Lucy (Senior Talent + People Partner)
• 60 Minute Technical Interview - with Sheran (Head of Growth) and Ben (Lead Data Analyst)
• 30 Minute Co‑founder Interview - with Iain (CEO), and Dirk (CTO)

At Seatfrog, we consider diversity a strength - inclusion fuels our ability to solve problems we never thought we could. Your application will be considered on its merits, without regard to your race, age, gender, religion, sexual orientation, disability status or anything else. If there is anything we need to know to enable you to fully participate in our interview process, please just let us know in your application. By submitting this application, I agree that my personal data will be collected, processed, and retained by the company solely for the purposes of managing and assessing my candidacy.