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Case Study
How Aprila Bank Increased Applications by Over 37% with AI-Driven Marketing Mix Modeling*
Company: Aprila Bank is a fast growing Norwegian fintech company offering innovative digital banking solutions for small and medium-sized enterprises (SMEs). They provide fast, flexible, and tailored financing options to help businesses optimize cash flow and drive growth.
A fast-growing fintech offering innovative digital banking
Company: Aprila Bank is a fast growing Norwegian fintech company offering innovative digital banking solutions for small and medium-sized enterprises (SMEs). They provide fast, flexible, and tailored financing options to help businesses optimize cash flow and drive growth.
Industry: Fintech / Digital Banking
Market: Norway
Challenge: Optimizing marketing spend across multiple channels with limited visibility into true performance
Cross-channel budget allocation
The budgeting process balanced brand building and performance activities, with the latter utilizing last-click attribution and channel-specific reports. Some channels showed signs of diminishing returns.
Exploring different budget scenarios
Estimating accurate sales impact with different budget allocations across channels was highly challenging, especially due to increased competition and distrust in channel-specific reports.
Building reliable models internally
Aprila had a data-driven marketing team, and wanted to start leveraging modern MMM models. Still, developing effective models internally was time-intensive and strained limited data science resources.
Aprila Bank utilized the Odins platform for:
Online and offline marketing data collected and structured
In a matter of days, all of Aprila's marketing data was structured in Odins. Marketing data is structured in real time, and flows back to Aprila's own data warehouse.
Marketing Mix Modeling
The model suggested allocating marketing budget to more profitable channels, and identified saturated channels at current spend levels.
Decisive and open to experimentation
Aprila Bank was able to take action and experiment quickly, leveraging the insights to the fullest.
Using AI-driven Marketing Mix Modeling in Odins, Aprila Bank identified overinvested channels and reallocated budgets
The model identified channels where additional spend had diminishing returns, and channels with untapped headroom. By reallocating budget from saturated channels to those with better marginal returns, Aprila was able to significantly improve overall performance without increasing total spend.
The insights were specific enough to act on immediately — not vague strategic recommendations, but concrete budget shifts with expected outcomes.
Marketing intelligence that drives growth
With AI-driven Marketing Mix Modeling, Aprila Bank increased total loan applications by over 37%
This data-driven approach helped Aprila Bank enhance marketing efficiency, gain deeper insights into channel performance and marginal returns, and make more informed decisions when budgeting and planning for the future.
Period: Q7.10.24 – 26.01.25
Comparison: The cost per loan adjusted for spend changes, accounting for ~15% increase.
The results speak for themselves — but more importantly, Aprila now has a system for continuous optimization. The model retrains monthly, recommendations stay current, and the marketing team can make evidence-based decisions every month, not just during annual planning.
