Case Study: Lumos Enhances ROI by 20% Using Apphud's LTV Predictions and Singular Integration

Optimizing marketing campaigns to achieve the highest return on investment (ROI) is essential. Lumos, a developer of utility apps for iOS and Android devices, faced the challenge of enhancing the performance of their new marketing channel - Google Ads. They needed to quickly assess effectiveness and understand which campaigns to stop and which to keep while ensuring efficient budget allocation.

To tackle this challenge, Lumos turned to Apphud's advanced Lifetime Value (LTV) predictions and integrated their data with Singular, a marketing analytics platform. This combination gave Lumos valuable insights into their future revenue streams and allowed for a more accurate ROI calculation for each user acquired through their campaigns.

Lumos is a developer of utility apps for iOS and Android devices with 300K daily active users. Lumos’ apps protect privacy and optimize the performance of mobile devices.

VPN Lumos

Apphud offers advanced predictions through its Cumulative LTV chart, which forecasts future revenue for different customer cohorts over intervals of 30, 90, 180, and 365 days. These predictions are invaluable for making informed decisions about customer acquisition and retention strategies.

For Evgeniya Vaganova, Product Manager at Lumos, understanding these forecasts was crucial, as their team aimed for campaigns that would pay off within 180 days. By focusing on the 180-day LTV predictions, they could strategically allocate resources toward customer acquisition that aligned with their financial goals.

Before fully implementing this strategy, Lumos conducted thorough data validation. The analytics team meticulously cross-checked revenue data from Apphud, spending data from Singular, and figures from the Google Ads account. This step was critical to ensure consistency and accuracy across multiple platforms, as combining data from different tools can often lead to discrepancies. By confirming that the data aligned, Lumos established a reliable foundation for their ROI calculations.

With validated data in hand, the Lumos team proceeded to calculate the ROI for each user cohort based on this formula: 

ROI = (LTV-spend)/spend*100%

They analyzed subscriber retention cohorts and trial subscription conversions from previous campaigns to extrapolate potential outcomes for new campaigns. This analysis enabled them to predict how different user segments would contribute to revenue over the 180 days.

ROI-Based Campaign Optimization

Using the calculated ROI over 180 days, the team implemented a strategic approach:

• Retention and Optimization: Campaigns with ROI greater than -10% were retained and further optimized through creative enhancements and adjustments to campaign settings.
• Discontinuation: Campaigns below -10% ROI were stopped to prevent inefficient spending.
• Geographic Focus: Traffic from countries that underperformed was turned off to concentrate resources on more profitable regions.

The iterative process of analyzing ROI, adjusting campaigns, and reallocating budgets resulted in a significant improvement in their marketing performance. Lumos saw a 20% increase in the ROI of their ad campaigns. This improvement was attributed to their data-driven approach, leveraging predictive analytics provided by Apphud and the detailed spending data from Singular.

This approach showcases the importance of integrating predictive analytics into marketing strategies. For other app managers looking to achieve similar results, Lumos' case highlights several key takeaways:

• Leverage Predictive LTV Data: Utilizing tools that provide LTV predictions allows for a forward-looking perspective on revenue, enabling more strategic decision-making.
• Integrate and Validate Data Across Platforms: Combining data from different sources like Apphud and Singular requires careful validation to ensure accuracy. Consistency in data is essential for reliable ROI calculations.
• Focus on Relevant Metrics: Align marketing goals with specific metrics that matter to the business. For Lumos, focusing on the 180-day ROI was crucial because it matched their payback period targets.
• Optimize Based on Performance: Use ROI thresholds to determine which campaigns to optimize and which to discontinue. Continuous optimization of high-performing campaigns can lead to substantial ROI improvements.
• Adjust Geographical Targeting: Be willing to reallocate resources away from underperforming regions to focus on markets that offer better returns.

Lumos successfully enhanced its Google Ads campaign performance by integrating Apphud's LTV predictions with Singular's spending data to calculate ROI accurately. Their approach involved thorough data validation, focusing on key metrics aligned with their business goals, and making informed decisions based on predictive analytics. This led to a 20% increase in ROI and a more efficient allocation of their marketing budget.

Start using Apphud's powerful tools today to optimize your app's success and achieve results like Lumos.

Nataly

Head of Marketing at Apphud

7+ years in product marketing. Nataly is responsible for marketing strategy development and execution. Committed adherent of the agile methodology.