Predictive Attribution Model

At HockeyStack, we understand the challenge of accurately attributing marketing success. Our proprietary Predictive Attribution Model is designed to cut through the complexity, providing clear, actionable insights into the true impact of your marketing efforts.

How does the model work?

Our attribution engine utilizes a sophisticated multi-shot, Markov-style analysis to pinpoint the genuine, causal contribution of every channel in your funnel. Here's a closer look at what makes our model unique:

• Continuous Learning: The predictive engine continuously ingests the complete history of customer journeys. In each cycle, it refines its understanding by re-weighting three core signals: recency, channel distinctiveness, and verified buyer engagement.

• Model based on accurate lift: By consistently revisiting data and sharpening these signals, our system precisely determines an internal "lift score" for each touchpoint. This score directly answers the critical question: "What would happen to conversions if this channel disappeared altogether?"

• Stable & Reliable: The engine refines its estimates over multiple passes, converging on a stable figure that reflects real-world behavior, not just a fleeting snapshot. This iterative process ensures path sensitivity—respecting where touches occur in the customer journey—without the complexities of a classical Markov approach.

• Streamlined Insights: The outcome is a clear, goal-specific ranking of channels. This ranking distinctly shows where your marketing spend is delivering returns and, just as importantly, where it isn't.

What's the advantage of using the Predictive Model?

Our approach provides the strategic confidence typically associated with traditional Markov removal attribution, helping you identify which programs truly move the needle. However, we achieve this without the heavy computational overhead and complexity often found in legacy models.

In essence, the HockeyStack Predictive Model delivers Markov-grade insights in a streamlined, programmatic package through actionable lift scores. This means you get sophisticated attribution without the headaches, empowering you to make data-driven decisions with confidence.

What are the key use cases where this model is useful?

The HockeyStack Predictive Model is most helpful in scenarios where traditional attribution models fall short or create unnecessary complexity. Here are some key use cases:

• Optimizing Marketing Spend Across Diverse Channels: If you're running campaigns across a multitude of channels (e.g., paid ads, content marketing, email, social media, direct mail) and need to understand the true incremental value of each, our model provides the accurate "lift scores" to guide your budget allocation. This helps you move beyond last-touch or first-touch limitations to see the holistic impact.

• Identifying Underperforming or Overlooked Channels: Our model excels at highlighting channels that might not get credit in simpler models but are crucial for conversions. Conversely, it can expose channels that consume significant budget but contribute minimally to actual conversions, allowing you to reallocate resources effectively.

• Understanding Multi-Touch Customer Journeys: For businesses with complex customer journeys involving multiple touchpoints over time, the Predictive Model's ability to preserve path sensitivity without forcing the complexity of a classical Markov approach means you get nuanced insights into how different interactions contribute at various stages.

• Strategic Decision-Making for Program Effectiveness: When you need to answer the fundamental question, "What would happen to conversions if this channel disappeared altogether?" , our model provides the data-backed answer, giving you the strategic confidence to double down on effective programs and re-evaluate less impactful ones.

• Avoiding Heavy Computational Overhead: For companies that require robust attribution but want to avoid the significant computational resources and expertise often demanded by traditional, computationally heavy Markov models, HockeyStack offers a powerful yet streamlined solution.