Set bidding strategies, budget allocation frameworks, and creative testing cycles that reduce dependence on any single signal or format
Own campaign performance end-to-end: from brief to launch to optimisation to reporting
Tracking, Attribution & Technical Infrastructure
Architect and own the full measurement stack: Firebase / GA4 event taxonomy, Google Tag Manager configuration, and server-side event pipelines
Lead the implementation and ongoing integrity of Conversion APIs and enhanced conversions to maximise signal quality sent back to Google
Define the attribution model — evaluate last-click, data-driven, and custom models against Moniepoint's funnel reality, and own the decision with clear reasoning
Partner with engineering and data teams to ensure event data flowing to Google is accurate, complete, and timely — treating signal quality as a competitive asset
Build audit protocols for tracking coverage and attribution consistency; surface gaps before they distort decisions
LTV/CAC Economics
Own the economic model for Google acquisition: define CAC targets by product, segment, and channel variant; set the inputs, assumptions, and review cadence
Understand the LTV/CAC relationship at a structural level — not just as a ratio to optimise, but as a function of product retention, monetisation curves, and cohort behaviour
Build and iterate on payback period models that account for Moniepoint's emerging market context: irregular income patterns, higher churn risk, and longer monetisation timelines
Design bidding and budget logic that reflects true LTV signals rather than proxy metrics, working closely with data science to enrich Google's Smart Bidding with offline conversion data
Proactively identify when CAC is drifting against LTV thresholds and lead the diagnosis — channel mix, audience quality, creative fatigue, product-market fit — before it becomes a financial problem
Governance & Reporting
Build a channel reporting system that surfaces reality clearly — not dashboards that flatter performance, but views that drive better decisions
Establish review cadences with clear owners, metrics, and follow-through mechanisms
Translate channel performance into business language for senior stakeholders: what is the cost of growth, is it sustainable, and what would change the trajectory
Emerging Market & Fintech Context
Adapt Google acquisition strategy for the realities of emerging market users: variable device penetration, low-bandwidth environments, trust barriers to financial services, and diverse
language/literacy contexts
Navigate platform constraints specific to fintech advertising on Google: financial services policies, verification requirements, and creative compliance
Bring genuine insight into what acquisition patterns distinguish sustainable fintech growth from subsidised growth in markets like Nigeria
To succeed in this role, you should have
6+ years of hands-on paid acquisition experience, with the majority of that time spent on Google UAC / App Campaigns at meaningful scale
Deep, demonstrable technical knowledge of Google's campaign infrastructure: bidding algorithms, audience signals, creative specs, and the mechanics of Smart Bidding
Proven ability to architect and own the full measurement stack — Firebase, GA4, GTM, Conversion APIs — not just configure it but understand why each component matters
Fluency in LTV/CAC modelling: you have built the models, owned the assumptions, and used them to make real budgeting and bidding decisions
Experience operating in a fintech or financial services context, with direct knowledge of the acquisition compliance and trust dynamics unique to financial products
Experience managing budgets larger that 10 Million USD annually
Strongly Preferred
Experience running Google acquisition in Sub-Saharan Africa or comparable emerging markets — Nigeria specifically is a significant advantage
Familiarity with server-side conversion APIs, offline conversion imports, and enhanced conversions as mechanisms for improving signal quality in cookieless or app-first environments
Experience working with data science or analytics teams to build custom bidding signals and offline LTV imports into Google's systems
Prior work on dual-product or dual-segment acquisition (e.g., consumer and SME / business) with separate funnel logic
What Success Looks Like
In the first 90 days
Full audit of existing Google campaign structure, tracking integrity, and attribution model completed — with a written assessment and prioritised improvement plan
Measurement stack gaps identified and remediation underway with engineering
LTV/CAC baseline model built with documented assumptions, reviewed with Growth and Finance
First governance cadence established — weekly performance review with clear owner, metrics, and follow-through log
In the first year
Google channel operating as a reliable, scalable growth engine with predictable CAC across both personal and business banking segments
Signal quality measurably improved — higher match rates, cleaner conversion data, reduced reliance on last-click proxies
Attribution model validated against actual cohort data and actively used in budget allocation decisions
Playbook documented: campaign architecture, bidding logic, audience strategy, and economic model all institutionalised — not living in one person's head
A team (or foundations for one) built with clear ownership, development paths, and no single point of failure
What to expect in the hiring process
A preliminary phone call with the recruiter
A technical interview with the hiring manager
A Case Study
A behavioural and technical interview with a member of the Executive team
All interview stages are virtual
