Turning Brand Health into Budget Confidence: Vuse’s Success Story

Attribution Blindspot: Unable to Separate Brand v/s Paid Impact

When Vuse approached Lifesight, they were at a stage where they could not distinguish and quantify orders driven by organic brand health versus those generated by paid marketing campaigns. Without this visibility, the team risked over-investing in channels that only captured existing demand rather than creating new orders.

Unclear Impact of Brand Health on Channel Performance and Costs

Brand health is an important north star metric of the industry. BAT looked to go deeper into understanding what influenced brand health (measured through “Vuse” search volume) and the impact of fluctuations in this metric on other variables, contextual factors. They wanted to understand:

• How brand health interacted with paid channels
• The causal relationship between brand awareness and CPA
• Whether certain channels benefited more from high brand health periods

Inefficient Budget Allocation and Forecasting

For the financial year 2026, BAT was looking to decrease their paid media budget spend by 71% while maintaining revenue targets. In order for this to happen, their marketing team needed to understand:

• Month-to-month budget allocation strategies for maximum impact from paid channels 
• Outcomes (orders, revenue) for multiple budget scenarios ranging from conservative to aggressive
• Consider contextual factors like pricing changes and promotional calendars in forecasting

BAT aimed to build a data-driven marketing strategy for Vuse Peru by:

• Establishing a clear view of incremental orders to guide smarter channel investment.
• Quantifying how brand health influences acquisition efficiency and channel performance.
• Creating 2026 budget scenarios with actionable month-by-month allocation plans to balance reduced spend with sustained growth

Building a Customized Marketing Mix Model (MMM):

The engagement kicked off with data preparation and deep research by our product and marketing science teams who worked closely with the BAT team to understand which metrics would have a meaningful impact on the MMM model.

Given that Vuse is a habitual product with consistent purchase patterns, traditional seasonality and holiday effects were excluded in favor of trend analysis and contextual micro-factors. Within 30 days of launching the model, the BAT team began extracting actionable insights – demonstrating rapid time-to-value.

Key Metrics & Framework

• Primary KPI: Number of orders
• Micro-Factors Identified: Pricing, store footprint (large vs. small stores), and promotional campaigns
• Contextual Analyses:

• Pricing elasticity → impact of price changes on order volume
• Store expansion → contribution of new distribution points on revenue
• Promotions → separating true incremental lift from discount-driven switching
  

Once deployed, Lifesight’s MMM helped BAT with:

1. Incremental Channel Contributions
   The ‘Contribution’ feature isolated the true incremental impact of each paid channel, over the organic baseline demand. It went a step further with understanding saturation levels of their paid channels so they could reallocate budget between paid channels accordingly.
   
   
   Key Insights:
   • Quantified that 25-30% of attributed orders would have occurred organically, preventing over-investment in non-incremental channels
   • Highlighted Brand health’s incremental contribution as a variables with highest contribution
2. Understanding diminishing returns of channels
   The model’s saturation feature helped BAT understand when paid channels were reaching their limit. By plotting incremental orders against spend, we identified where diminishing returns set in. This allowed BAT to optimize their budget by capping saturated channels and reallocating spend to those with higher growth potential.
   
3. Establishing & Quantifying Interaction Effects
   The Interaction Effect feature within the model quantified the positive and negative overlaps between channels. This proved critical in revealing insights about brand health.A Strong Synergy indicates that both variables independently drive orders, so increasing them together amplifies results. For example, Brand Health combined with pricing strategy, paid media spends, store visits, and promotions contributed positively to order growth.

   A Strong Cannibalization effect indicates that variables compete for the same orders, so scaling both reduces efficiency and only one should be prioritized at a time. This was the case with events and creators spends

   
   
   Key Insights:

   • Brand Health inversely related to Blended CPA
     When Vuse search volume was high, paid channels acquired customers more efficiently. During strong brand health periods, blended CPA dropped 18–22%, showing reduced friction in acquisition. Conversely, when brand health declined, paid media costs rose as campaigns had to work harder to deliver the same order volume.
     
   • Paid x Organic channel interaction effects
     The interaction analysis revealed that paid channels had strong synergies with contextual and organic variables. Consequently, a portion of the orders attributed to those variables should have been re-attributed to paid. Simply put, paid channels accounted for a minimum of 15–17% of total orders.
     

Planner Tool: Turning Insights into Action

What would have taken BAT a couple of days and a team of multiple data scientists to generate, was now generated in a span of minutes with Lifesight’s Planner:

1. Scenario-Based Planning:
   BAT aimed to reduce its paid media budget by 71%, and the Planner helped generate multiple budget scenarios to achieve this goal:
   • Manual: This mode gave complete control to BAT to assign target budget values and play around with budget allocations across the channels.
   • Conservative: Focused on maintaining a steady, risk-averse approach to spending, ensuring minimal impact on revenue while gradually shifting budget towards high-performing channels.
2. Strategic Reallocation: Meeting 51% of Orders Despite 71% Budget Reduction
   • The Planner provided month-by-month spend recommendations for each channel, ensuring strategic budget allocation.
   • Despite a 71% reduction in paid media spend, the Planner successfully guided BAT in reallocating budgets to the most efficient channels. Strategic Reallocation: Meeting 51% of Orders Despite 71% Budget Reduction.
   • This optimized reallocation allowed BAT to achieve 51% of forecasted orders, even with the significant budget cut, maximizing return on investment.
     

Lifesight’s Marketing Mix Modeling and Planner tools transformed BAT’s approach to marketing investment – moving from attribution confusion to incrementality clarity, and from siloed decisions to integrated brand-performance strategy.

By quantifying brand health’s influence on acquisition efficiency and providing month-by-month budget guidance across multiple scenarios, BAT Peru now operates with unprecedented confidence. The team successfully navigated a major budget reduction while preserving revenue impact, armed with a data-driven roadmap.

This partnership demonstrates that modern marketing measurement isn’t just about reporting what happened, it’s about confidently planning what comes next.