Marketing Mix Modeling Helps a Leading Bank Gain a Holistic Overview of Their Marketing Spend
Banking Sector Introduction
Customers in the banking sector are well informed and are ready to move to competitors if they receive better services at a lower price. Therefore, it is important for service providers to get customer related information even before their competitors. To target the right customer segments and improve ROI of marketing activities, marketers in the banking sector have started deploying marketing mix modeling. Marketing mix models analyzes data from past campaigns to plan better campaigns for the future across online and offline channels.
Marketing mix modeling helps marketers allocate marketing spend based on the analysis of historical data and determines the contribution of each element towards a brand’s success. Quantzig’s marketing mix optimization team identifies various sources to collect data and apply statistical models to create accurate marketing mix models.
The Business Challenge
To enhance marketing productivity, a leading bank in the US wanted to maintain and increase market share in the banking sector based on optimization of marketing spends. The client’s top three marketing priorities were cross-selling to improve share of wallet, loan growth, and customer acquisition. This created a strong need for financial marketers to plan their future marketing strategies with greater certainty.
Marketing Mix Modeling Methodology
The marketing mix modeling uses two methods; linear and multiplicative relationships between marketing and sales activities. Quantzig’s marketing mix modeling optimization team analyzed various data such as market-level media measure, sales data, fixed marketing expenses, variable marketing expenses, and economic and purchase funnel indicators.
Marketing Mix Modeling Benefits
- Comparative ROI across media types based on advanced regression methods for each product on promotion – retail banking products and loans
- A real-time solution for investment decisions, providing the management with a decision support system
- Future investment decision support based on simulated scenarios
Marketing Mix Modeling Predictive Insights
- Identified drivers of consumption and content preferences to tailor recommendations and advertisements
- Measured customer stickiness based on RFM analysis across devices
- Insight into contribution of brand equity vs. advertising on incremental sales and the ROI from each media type
- Campaign analysis of individual campaign to understand the ROI and incremental sales generated at a granular level – debit/credit cards, home loans, shopping discounts and cash backs.
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