Attribution Modeling

What is attribution modeling?

Attribution modeling is a mobile measurement framework used to determine which touchpoints, or marketing channels, receive credit for a conversion event. Understanding first-click, last-click, and multi-touch attribution models helps marketers better understand which channels create the most impressions and contribute most to customer conversions like mobile app installs, in-app purchases, etc.  

Attribution models enhance overall business performance and return on investment (ROI) in mobile marketing, SEO, PPC advertising, and social media marketing strategies. This framework involves a solid grasp of attribution windows, which help marketers define the period of time their conversion events can be attributed to each channel.

Marketing touchpoints in attribution models

Marketing touchpoints like websites, social media platforms, email marketing, or personal interactions each play specific roles in the customer’s journey and contribute to conversions. In the context of attribution models, touchpoints act as a roadmap, indicating how consumers move along the buyer journey. They provide valuable insight into what triggers a potential customer to move from the top of the sales funnel to the middle or bottom of the funnel. In the world of mobile apps, they also provide critical insight into which channels are most effective at converting customers into app users. 

Understanding this dynamic is essential for marketers looking to optimize their strategies and enhance conversion rates. By using different attribution models, marketers can enhance the efficiency of these touchpoints by identifying which interactions contribute the most to conversions and optimizing their marketing budgets accordingly.

The customer journey in attribution models

The customer journey includes multiple channels, touchpoints, and steps from brand awareness to purchase. Understanding the customer journey is crucial in attribution modeling as it helps identify the most influential touchpoints and assess their contribution to conversions.

Event-based attribution models are essential in understanding user interaction within a mobile app or website. They assign credit to specific user activities or “events” — viewing a product, adding it to the cart, or reading reviews — that lead toward a conversion. Analyzing these events provides insights into the customer’s decision-making process and identifies critical touchpoints leading to conversions.

Types of attribution models

There are various types of attribution models, each offering a unique perspective on marketing campaigns:

  • First-click attribution: assigns all credit for the conversion to the first touchpoint a customer interacts with. This model can help you understand the effectiveness of awareness campaigns.
  • Last-click attribution: allocates 100% credit to the last channel a customer interacts with before making a purchase or conversion. This approach favors channels at the later stages of the marketing funnel.
  • Linear attribution: gives equal credit to all touchpoints in the customer journey, offering a balanced view of all marketing efforts.
  • Algorithmic/probabilistic attribution: leverages machine learning and complex algorithms to assign credit to different touchpoints, providing precise insights based on actual impact and performance.
  • Position-based attribution: credits 40% to first and last interactions, with 20% split among others, which improves understanding of all interactions.
  • Multi-touch attribution: distributes conversion credits across multiple touchpoints on the customer journey, useful for understanding the complex interplay of various marketing channels.
  • Time-decay attribution: gives more credit to touchpoints nearer to conversion, ideal for short sales cycles.
  • Data-driven attribution: uses machine learning and algorithmic analysis to distribute credit, considering all possible marketing scenarios and interactions.
  • Shaped attribution: customizable based on the marketer’s discretion, allowing for nuanced assessment in complex customer journeys.