Real Impact
Real Impact causal modelling tool allows us to prove the correlation between two disconnected data sets.
MoneyGram is a global digital and retail money transfer company, enabling millions of people to send and receive money across borders via app, web and a vast network of physical agent locations in over 200 countries and territories.
When we partnered with MoneyGram, the brand was at a critical turning point. While its global retail network remained extensive, physical agent-led transactions were in decline, and digital channels were only growing at 5% YoY, but that wasn’t enough to offset the dip in physical agent locations (like Post Offices or Walmarts). To hit their targets, MoneyGram needed to rapidly scale its digital customer base, increase customer lifetime value (LTV), and acquire new senders efficiently within strict customer acquisition cost (CAC) guardrails.
There was little performance media activity targeting Europe and the rest of the world, which contained some of the world’s most valuable and emotionally driven remittance corridors. The opportunity wasn’t just to “do more digital”; it was to understand the why behind every transfer: the cultural rhythms, family obligations, and economic pressures that drive people to send money home.
From the start, our partnership was built on a model of empowerment; MoneyGram made it clear they intended to move forward with in-house activation. We leaned into this by acting as a growth engine, building and stabilising the CAC and LTV in those markets, then systematically handing them back to the internal team.
We built a ‘Land and Expand’ performance growth framework to turn that latent demand into scalable, profitable growth. Our strategy focused on two components: the ‘corridor’ mentality and timing in the market. Corridor-first strategy: We didn’t just target countries; we targeted specific corridors (e.g., UK to Syria) and then prioritised spend based on where the Lifetime Value (LTV) was highest. We also weighted our budgets to ’Money Moments’, upping spend during paydays and specific holidays like Eid or Christmas. Across channels, audiences, and creative, we optimised not just for the cheapest acquisition, but for high-LTV customers acquired within target CAC, with structures built to drive repeat usage and loyalty.
We built a performance framework across multi channels (PMax, Competitor, Non-brand), Google App Campaigns (UAC) and Apple Search Ads. We used corridor-level performance and LTV data to rank where every pound should work hardest, concentrating investment in routes that delivered frequent, higher-value transfers and sustainable growth.
While performance KPIs led the strategy, we aligned creative and messaging across the funnel to move people from first transfer to habit. To scale this approach, we built a templated framework for producing creative at scale for both send and receive markets, ensuring content was always in the local language and reflected both the culture and people. This ensured PMax had a robust content engine to deliver relevant messaging across markets. We then developed hyper-relevant, culturally sensitive messaging for each diaspora community. By speaking the way senders really talk about money, family and responsibility, we improved relevance, reduced friction to first transfer, and laid the foundation for higher repeat usage and LTV.
Next, we architected a phased acquisition strategy, first capturing high-intent demand through non-brand generics, then layering in assertive competitor conquesting, and finally scaling into paid social in the most mature corridors. This approach allowed us to grow incrementally while protecting CAC and ensuring each new cohort delivered strong downstream value. We implemented a unified reporting model, enabling the client to have total visibility into Cost Per Acquisition (CPA) efficiency across 14 locations for the first time. This single source of truth turned media from a cost line into an optimisable growth lever, enabling faster decisions on where to invest, where to pull back, and which corridors to scale.
Additionally, we leveraged first-party data from converted users to define what a quality customer looked like – factoring in repeat behaviour, value per transfer and retention. We then used these signals to build lookalike and intent-based audiences, enabling us to find more high-value customers at scale while protecting CAC. We tested and rolled out Performance Max to orchestrate activity across multiple channels and formats from a single, intent-led campaign. This widened our presence across the customer journey, increased effective frequency with in-market senders, and ultimately drove stronger engagement and conversion from the same media investment.
By shifting to a data-led, corridor-first approach, we hit targets. Monthly new-customer volume jumped 22%, and first-time transactions (FTT) increased by 34%. We reduced the cost per FTT by 12%. In Q1 alone, we came in 67% under our CAC targets while still bringing in 2.2% more new customers than originally planned. Because we built that initial trust in the UK and Europe, we’ve since taken over their North American account and are currently scaling into Meta. With five new markets launching in 2026, we’ve turned what was a ‘supporting’ digital channel into the business’s primary driver for global growth. This approach transformed an underinvested region into a growth engine for MoneyGram’s digital business. By combining corridor-level precision with timing and value-based optimisation, we accelerated new customer growth, protected CAC efficiency, and increased the proportion of users who went on to become high-value, repeat digital senders.
FFT increase
new customer volume increase
reduction in CaC QoQ
successful market entries
Increase in average basket size.
ROAS in the first 4 weeks.
Confidence in attributable incremental revenue directly from the paid social test.
Real Impact causal modelling tool allows us to prove the correlation between two disconnected data sets.
Uplift in net new registrations from podcasts alone.
Confidence of causal attribution of impact delivered by podcasts.
ROAS. Podcasts are now an important part of the media mix.
Real Impact causal modelling tool allows us to prove the correlation between two disconnected data sets.
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