Use Case: ATU (Awareness, Trial, Usage) Tracking in Pharma 

Objective

To evaluate the awareness, trial, and usage patterns of competing pharmaceutical brands among healthcare professionals (HCPs), identify drivers of adoption, and segment HCPs for targeted strategy.

Methodology

Data Source

Quantitative survey of 300 physicians across multiple specialties and regions.

Key Variables

  • Aided Awareness of Brand A, B, C

  • Trial Status (whether HCP has prescribed the brand)

  • Current Usage (whether brand is currently prescribed regularly)

  • Other Factors: Specialty, Region, Rep Visit in past 3 months, Efficacy Perception

Analytical Techniques Used

  • Cross-tabulation: Awareness, trial, and usage by region and specialty

  • Statistical Tests: Chi-square test for group differences

  • Predictive Modeling: Logistic regression to identify drivers of Brand A trial

  • Segmentation: KMeans clustering based on ATU patterns

  • Visualization: Heatmaps and bar charts to summarize insights

Key Findings

Awareness & Adoption

Metric Brand A Brand B Brand C
Aided Awareness ~70% ~60% ~40%
Trial Rate ~52% ~38% ~22%
Usage Rate ~34% ~25% ~10%
 
Brand A leads in awareness and trial, but retention (usage) drops, indicating an opportunity for better value communication.

Brand C has low awareness but a niche group of loyal users.

Statistical Insights

Logistic Regression (Brand A Trial):  

Variable Coefficient P-Value
Efficacy Perception Not significant (p > 0.05)  
Rep Visit (last 3 months) Not significant (p > 0.05)  

Indicates that other factors may drive trial more than rep interactions or general perception in this dataset.

Chi-Square Test:

  • No significant difference in Brand A trial rates across regions (p = 0.35)

Segmentation Insights (KMeans Clustering)

Segment Characteristics
0 Moderate trial; high Brand C usage → Brand C loyalists
1 High Brand A usage, low Brand C → Brand A adopters
2 Balanced adoption across brands → Brand B engaged segment
 
Strategic Recommendations

  • Segment 0: Highlight Brand A’s differentiation against Brand C through efficacy or safety data

  • Segment 1: Strengthen retention programs or messaging to maintain loyalty

  • Segment 2: Focus education and sampling efforts to convert trial into usage