A few examples of CRM and lifecycle work I've led.

CRM was run through Mailchimp — a generic email tool with no behavioural segmentation, no journey automation, and no ability to trigger communications off real customer actions. New customers had no structured onboarding: activation and early retention were left to chance rather than design.

Led the migration from Mailchimp to Optimove, an enterprise-grade CRM and personalisation platform, from platform selection through full technical and campaign migration. Designed a 14-day behavioural onboarding framework — triggered communications based on what a new customer actually did in their first two weeks, not a single generic welcome series.

• Full CRM platform migration, including data migration, segmentation rebuild and campaign re-platforming
• Built the 14-day behavioural onboarding framework from scratch
• Established the segmentation model that later lifecycle campaigns were built on

Meaningful growth in first-time depositor conversion alongside a reduction in customer acquisition cost — more of the customers already being acquired converted and stuck, rather than needing more acquisition spend for the same outcome.

Sportsbook and fantasy welcome offers were being exploited — sign-up and deposit bonuses were attracting bonus abuse rather than driving genuine new-customer retention, creating both a margin problem and a compliance exposure.

Led a restructuring of the welcome offer strategy end-to-end: redefined eligibility and structure to reduce abuse while keeping the offer genuinely attractive to real new customers, coordinating delivery across engineering, the affiliate team, and the CRM platform vendor's customer success team.

• Redesigned sportsbook and fantasy welcome offer structure and eligibility rules
• Coordinated implementation across engineering, affiliate partnerships and the CRM vendor
• Aligned affiliate-facing communications so partner-driven traffic wasn't disrupted

Reduced bonus abuse exposure while preserving the welcome offer's effectiveness at converting genuine new customers — protecting margin and reducing compliance risk without withdrawing the offer or making it materially less attractive.

New-to-active migration in the first 14 days was underperforming benchmark. The easy fix would have been more welcome messages or richer offers — the real question, not yet answered, was where in those 14 days behaviour actually diverged.

Ran a cohort diagnostic before touching a single campaign, then rebuilt the journey around the customer's changing objective across two distinct weeks, rather than treating "new customer" as one segment for the full fortnight. This is a deeper, more technical look at the onboarding framework referenced above.

• Cohort diagnostic that surfaced three genuine decision points instead of fourteen arbitrary send days: a short second-deposit window, an experience-driven churn signal, and a late-week attrition cliff
• Two-phase journey: Week 1 focused on establishing the relationship and prompting the right next action; Week 2 focused on catching early lapsing signals before they hardened into churn
• Segmentation logic branching by deposit/product history on Day 2, by experience state on Day 7 (with a value guardrail), and by risk level on Day 11 — with Day 13 following up only non-responders
• A full operating model behind each decision point: audience definition, trigger, exclusion logic, contact policy, and a measurement plan matched to each campaign's actual objective

A structured, evidence-led journey that replaced a single generic onboarding sequence with three decision points genuinely earned by the data — each customer receiving only the intervention their actual state called for.