Precision Marketing Measurement for an Insurance Leader

The Challenge: Untangling a Complex Full-Funnel Strategy

In crowded insurance market, where consumers shop across multiple brands before selecting a policy, one major car and home content insurer faced a pressing question:

"How can we generate more insurance quotes without significantly increasing our marketing budget?"

The brand was running one of the industry's most sophisticated media mixes, spanning:

• Traditional channels: TV, radio, outdoor, print, cinema
  
• Digital channels: Search, social, display, online video, affiliates

But three critical challenges stood in their way:

1. Data Disorganization at Scale

Despite working with established media agencies, the brand's media data was trapped in:

• Inconsistent Excel files with mismatched date formats
  
• PDF reports that required manual extraction
  
• Disconnected affiliate tracking systems

The marketing team was spending 40% of their time on data wrangling rather than strategy.

2. Granular Measurement Requirements

The key metric—insurance quotes—needed to be analyzed across multiple dimensions:

• Product type: Car insurance vs. home & content
  
• Demographics: Different conversion patterns for 25-40 vs. 41-65 age groups
  
• Geography: Varying performance across states

Traditional marketing mix models couldn't handle this level of detail.

3. Budget Optimization Under Constraints

With a mandate to limit budget growth to just 3% annually, the team needed to:

• Identify the most efficient channels for each product / age group / state
  
• Predict how reallocations would impact quote volume
  
• Maintain brand-building while driving immediate quote submission

The Solution: A Custom Hierarchical Measurement Framework

1. Streamlining the Data Foundation

More Than Data implemented a robust data processing system that:

• Automated ingestion of agency reports using Python-based cleaning scripts
  
• Established consistent cost tracking across all channels
  
• Integrated affiliate data with owned media performance

This reduced data preparation time from weeks to days.

2. Multi-Dimensional Performance Modelling

The custom-built marketing mix model accounted for:

• Channel effectiveness by product type (e.g., search worked better for car insurance)
  
• Regional variations (OOH performed best in metro areas)
  
• Age-based conversion patterns (social drove younger quotes, radio influenced older demographics)

3. Key Insights Uncovered

• Cinema ads generated 3% more car insurance quotes among 25-40 year old
  
• Radio drove 8% higher conversion rates in regional Queensland
  
• Affiliate partnerships accounted for 18% of high-intent quotes

4. Dynamic Budget Allocation System

The team could now:

• Test scenarios like "What happens if we shift 15% from print to YouTube?"
  
• See predicted quote impact before making changes
  
• Set budget rules and constraints to protect brand-building channels

The Results: Doing More With the Same Budget

✅ 11% increase in marketing efficiency (surpassing the 6% target)

✅ 5% more quotes generated with just 3% additional spend

✅ Ongoing partnership as the brand's marketing effectiveness advisor

"Before working with More Than Data, we were making million-dollar decisions based on incomplete information. Their hierarchical modelling approach finally gave us the clarity we needed to optimize across products, regions and age groups. The 11% efficiency gain wasn't just a number—it translated directly to our bottom line."

Why This Matters for Insurance Services Marketers

• Insurance Purchases Are Complex – Different products appeal to different demographics through different channels
  
• Every Dollar Counts – In a low-margin industry, small efficiency gains create big impacts
  
• Static Models Aren't Enough – Consumer behavior changes constantly
  

The Real Competitive Advantage

What set this solution apart wasn't flashy technology, but rather:

• Deep understanding of insurance purchase journeys
  
• Rigorous methodology for hierarchical measurement
  
• Practical tools that marketers could actually use

Key Lessons for Marketing Leaders

• Clean data comes first – No model can overcome poor inputs
  
• Granularity matters – Average performance hides important variations
  
• Scenario testing is essential – The market changes constantly

For brands ready to move beyond guesswork, this is how modern marketing measurement works.