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.

How does a Marketing Mix Model work?

A Marketing Mix Model (MMM) is a statistical analysis tool used to quantify the impact of various marketing activities on sales and other key performance indicators (KPIs). Here’s how it works:

• Data Sources & Variables: MMM integrates data from various sources such as financial institutions, client TreeBank, and internal databases. It considers both traditional and digital marketing channels, including out-of-home advertising, digital marketing, events, and conferences. By analyzing these data sources, MMM identifies incremental variables and drivers of consumption, enabling a comprehensive understanding of marketing effectiveness.
• Modeling Methodology: MMM employs sophisticated statistical techniques to measure the contribution of each marketing element to sales or desired outcomes. It utilizes concepts like discounted cash flow analysis (DCF), net present value (NPV), and internal rate of return (IRR) to assess the financial impact of marketing efforts. Additionally, it incorporates multi-segment analytics to account for diverse B2B and B2C market dynamics.
• Performance Evaluation & Optimization: MMM facilitates the assessment of marketing mix strategies by calculating return on investment (ROI), sales forecasts, and brand equity. Through analysis of year-over-year (YoY) trends and comparison with key performance indicators (KPIs), marketers can evaluate the effectiveness of different marketing communication strategies and adjust their tactics accordingly.
• Insights & Decision-making: By dissecting the cannibalization effect, product/market trends, and content preferences, MMM provides actionable insights for enhancing marketing strategies. It enables marketers to allocate resources effectively across above-the-line (ATL), below-the-line (BTL), and through-the-line (TTL) marketing activities. Moreover, MMM facilitates campaign analysis and RFM (Recency, Frequency, Monetary) analysis, allowing for continuous improvement and optimization of marketing initiatives.

In essence, a Marketing Mix Model serves as a powerful tool for marketers and finance experts to understand, measure, and optimize the impact of marketing investments on business outcomes, driving informed decision-making and sustainable growth.

Types of Analysis in Marketing Mix Modeling

Marketing Mix Modeling (MMM) involves various types of analysis to assess the effectiveness of marketing strategies. Here are four key types of analysis commonly employed in MMM:

• Financial Analysis: MMM incorporates financial metrics such as discounted cash flow analysis (DCF), net present value (NPV), and internal rate of return (IRR) to evaluate the financial viability of marketing initiatives. By quantifying the expected cash flows and assessing their present value, marketers can determine the profitability and investment attractiveness of different marketing activities. This financial analysis helps in optimizing resource allocation and maximizing return on investment (ROI) in marketing efforts.
• Channel Analysis: MMM analyzes the performance of different marketing channels, including out-of-home advertising, digital marketing, events, and conferences. By evaluating the contribution of each channel to sales and other key performance indicators (KPIs), marketers can identify the most effective channels for reaching target audiences. This channel analysis enables optimization of the marketing mix strategy by reallocating resources to channels that yield the highest returns and adjusting messaging and tactics accordingly.
• Segmentation Analysis: MMM employs multi-segment analytics to understand the behavior and preferences of various customer segments, including both business-to-business (B2B) and business-to-consumer (B2C) markets. By segmenting customers based on demographic, psychographic, and behavioral factors, marketers can tailor their marketing strategies to different segments and enhance targeting and personalization efforts. This segmentation analysis helps in identifying demand drivers, optimizing product launches, and mitigating the cannibalization effect.
• Performance Metrics Analysis: MMM evaluates key performance indicators (KPIs) such as sales forecast, incremental sales, brand equity, and ROI to assess the overall effectiveness of marketing activities. By monitoring year-over-year (YoY) trends and conducting campaign analysis, marketers can measure the impact of marketing communication strategies and make data-driven decisions to optimize future campaigns. This performance metrics analysis enables continuous improvement and optimization of the marketing mix strategy, ensuring alignment with business objectives and driving sustainable growth.

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 helps in analyzing data from past campaigns to plan better campaigns for the future across online and offline channels. To know our portfolio of marketing mix solutions,

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Marketing Mix Modeling Benefits

Marketing Mix Modeling (MMM) is a powerful tool used by businesses to assess the effectiveness of various marketing activities and optimize their marketing strategies. Here are four key benefits of utilizing MMM:

• Comparative ROI across Media Types for Retail Banking Products and Loans: Utilizing advanced regression methods, businesses can conduct comparative analyses of return on investment (ROI) across various media types for retail banking products and loans. By examining historical data and accounting for factors such as advertising spend, audience demographics, and market trends, businesses can determine the effectiveness of each media channel in driving customer acquisition and sales. This analysis enables informed decision-making regarding resource allocation, ensuring that marketing budgets are optimized to maximize ROI and achieve business objectives. Additionally, by identifying the most impactful media types, organizations can refine their marketing strategies to better target potential customers and enhance overall campaign performance.
• Real-time Investment Decision Support System: Implementing a real-time solution for investment decisions provides management with a dynamic decision support system that leverages up-to-date data and advanced analytics techniques. This system enables management to make timely and informed investment decisions by analyzing key metrics, market trends, and simulated scenarios in real-time. By integrating various data sources and employing predictive modeling, the system can forecast potential outcomes and evaluate the impact of different investment options. This empowers management to react quickly to market changes, mitigate risks, and capitalize on opportunities, ultimately driving better investment outcomes and enhancing overall financial performance.
• Improved Decision Making: It integrates data from diverse sources such as sales figures, advertising spend, and market trends to provide a comprehensive view of marketing performance. By analyzing this data, businesses can make informed decisions about resource allocation, identifying which marketing channels and strategies yield the highest return on investment (ROI). This ensures that marketing budgets are optimized for maximum impact, leading to better overall business outcomes.
• Quantifiable ROI: One of the primary advantages of MMM is its ability to quantify the impact of marketing efforts on business outcomes such as sales and revenue. Through techniques like Discounted Cash Flow Analysis (DCF) and Net Present Value (NPV), MMM calculates the financial value generated by each marketing initiative, enabling organizations to measure return on investment (ROI) with greater accuracy. This helps justify marketing expenditures and aligns marketing activities with overarching business goals.
• Granular Insights: MMM allows for a detailed analysis of marketing performance across different segments, channels, and geographies. By examining data at a granular level, businesses can identify key drivers of sales and understand the unique preferences and behaviors of various customer segments. This insight enables more targeted marketing strategies, personalized messaging, and product offerings tailored to specific market segments, ultimately driving higher customer engagement and satisfaction.
• Optimized Marketing Mix: By leveraging MMM, businesses can identify the most effective marketing mix to achieve their objectives. Through analysis of key performance indicators (KPIs) and demand drivers, organizations can determine the optimal allocation of resources across various marketing channels, including out-of-home advertising, digital marketing, events, and more. This ensures that marketing efforts are focused on activities that deliver the greatest impact, maximizing ROI and driving long-term growth.

How MMM helps banking sector?

Marketing Mix Modeling (MMM) offers significant benefits to the banking sector, aiding in strategic decision-making, customer acquisition, and retention efforts. Here’s how MMM specifically helps banks:

• Optimizing Marketing Investments: Banks operate in highly competitive markets where effective allocation of marketing budgets is crucial. MMM enables banks to assess the impact of various marketing channels such as out-of-home advertising, digital marketing, and events on key performance indicators (KPIs) like customer acquisition cost (CAC) and customer lifetime value (CLV). By leveraging MMM, banks can optimize their marketing mix strategy, ensuring that resources are allocated to the most effective channels and campaigns, ultimately maximizing return on investment (ROI).
• Understanding Customer Behavior: Multi-segment analytics provided by MMM allows banks to gain deeper insights into customer behavior and preferences. By segmenting customers based on demographic, psychographic, and behavioral factors, banks can tailor their marketing communication strategies to different segments. This personalized approach helps in enhancing customer engagement, increasing cross-selling opportunities, and improving overall customer satisfaction. Additionally, MMM helps in identifying demand drivers and analyzing product/market trends, enabling banks to anticipate and respond to changing customer needs effectively.
• Measuring Campaign Effectiveness: MMM facilitates thorough campaign analysis, enabling banks to measure the effectiveness of marketing campaigns and initiatives. By tracking key metrics such as sales forecast, incremental sales, and brand equity, banks can assess the impact of their marketing efforts on business outcomes. This allows for data-driven decision-making, enabling banks to refine their marketing strategies, optimize messaging, and allocate resources more effectively for future campaigns.
• Enhancing Brand Equity and Loyalty: Brand equity is crucial for banks in building trust and credibility among customers. MMM helps banks in measuring and managing brand equity by analyzing factors such as brand perception, customer satisfaction, and market share. By understanding the drivers of brand equity and monitoring brand performance over time, banks can take proactive measures to strengthen their brand positioning and foster customer loyalty. This, in turn, contributes to long-term profitability and sustainable growth in the highly competitive banking sector.

In essence, Marketing Mix Modeling empowers banks to make informed marketing decisions, drive customer-centric strategies, and achieve their business objectives in an increasingly dynamic and competitive market environment.

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