How media mix modeling helped a dual-brand B2B/B2C retailer unlock profitability by optimizing channel allocation during peak season.
THE CLIENT
A leading specialty retailer serving both business and consumer markets through catalog, digital, and inside sales channels.
Our Results
72%
Net profit increase year-over-year
57%
Gross profit improvement
15%
Reduced marketing spend in January 2026
Challenge
Overcome attribution limitations and integrate margin-based budget optimizations across channels to maximize profitability during peak season.
Like many direct-to-consumer brands, our client faced the challenge of understanding the true impact of each marketing channel on business performance. Traditional attribution models couldn’t capture the full picture, especially the interplay between catalog mailings, inside sales, digital advertising, and external factors like weather patterns that significantly impact purchases of this client’s products.
With digital tracking becoming less reliable due to increased privacy regulations and cookie deprecation, the company needed a sophisticated, data-driven approach to answer critical questions. Which marketing channels were driving the most profitable growth? How should they allocate their budget to maximize returns during their crucial busy season? And how could they account for the complex interactions between different marketing touch points?
Wheelhouse implemented an advanced Media Mix Model (MMM) to quantify the direct, indirect, and joint effects of different marketing channels, providing the insights needed to optimize budget allocation and forecast results with confidence.
Approach
Deploy advanced media mix modeling layered with business intelligence to deliver actionable optimization recommendations that respect real-world constraints.
Wheelhouse built a comprehensive media mix model using open-source MMM technology running within Compass, our proprietary, HIPAA-compliant data infrastructure. Because the data foundation was already structured and integrated within Compass, the model was ready to run faster than a traditional build, and positioned to refresh as conditions evolved. Using 2.5 years of performance data, we created high-fit national and regional models that analyzed the incremental impact of each marketing channel.
We then layered in critical business context to move from model outputs to decisions the client could actually act on:
Data Integration – We incorporated inside sales records, catalog distribution data, and historical weather patterns, recognizing that seasonal factors significantly impact this client’s peak revenue periods.
Margin-Based Optimization – Rather than optimizing for revenue alone, we integrated product margin data to focus on profit contribution, ensuring recommendations drove true business value.
Business-Aware Recommendations – We balanced model outputs with strategic considerations including brand protection, competitive dynamics, margin economics, and seasonal opportunities. The model showed optimal allocations, but our recommendations accounted for real-world factors like the need to defend brand search terms from competitors.
Staged Implementation Plan – We created a detailed execution roadmap with weekly monitoring checkpoints, red-flag metrics, and decision trees, enabling the team to scale successful changes while quickly course-correcting if needed.
Outcomes
MMM-driven budget reallocation delivered 72% profit growth with reduced spend.
The implementation of our MMM-based optimization strategy produced significant improvements across key business metrics. Net profit increased 72.6% year-over-year, while gross profit improved 57%, demonstrating the power of optimizing for profitability rather than revenue alone. Gross profit margin expanded by 12.5 percentage points, reaching 63.5% as budget shifted toward higher-margin products and more efficient channels. Despite reducing overall January marketing spend by 14.9%, revenue grew 6.3%, demonstrating that disciplined allocation outperforms raw expenditure.
The model also surfaced channel-level intelligence that reshaped how the client thinks about their media mix going forward:
- Facebook Conversion campaigns had significant headroom for efficient growth, leading to a 59% budget increase
- Google Brand Search required investment for competitive defense, resulting in a 104% increase
- Google Performance Max showed saturation, enabling a 13% reduction while improving overall efficiency
Beyond the immediate results, Wheelhouse equipped this client with ongoing capabilities to forecast performance, test optimization scenarios, and make data-driven decisions about future marketing investments, ensuring sustainable, profitable growth.
