Selecting the Right Attribution Model
Choosing the right attribution model is a critical step in accurately measuring the effectiveness of your podcast advertising campaigns. The model you select can significantly impact how you understand your audience's journey from exposure to conversion. This decision should be informed by several key factors, including your advertising strategy (e.g., focusing on one show versus multiple), the average order value (AOV) of your product (high consideration vs. low consideration products), and your overarching marketing goals. Here's a straightforward guide to help you navigate the selection process.
Podscribe enhances this decision-making process with its real-time data and flexible analytics capabilities. Here's how to customize your choice to meet your brand's specific needs, making the most of Podscribe's sophisticated features:
1. Understand the Different Attribution Models
Before deciding, it's essential to have a clear understanding of the primary attribution models available:
First-Click Attribution: Credits the first podcast ad a listener hears. It's ideal for evaluating which channels are most effective at generating initial awareness.
Last-Click Attribution: Assigns credit to the last ad a listener hears before making a purchase, useful for understanding which channels drive conversions.
Multi-Touch Attribution: Distributes credit across all the ads a listener hears, acknowledging that each touchpoint contributes to the decision to convert.
Multi-Touch Time Decay: Gives more credit to ads heard closer to the conversion, highlighting the importance of engagements nearer to the decision-making process.
2. Consider Your Podcast Buying Strategy
Single Publisher or Show Strategy: If your strategy focuses on advertising within a single podcast, you might lean towards a first-click or last-click model, depending on whether your goal is to build awareness or drive conversions.
Cross Network and Show Strategy: When advertising across multiple podcasts, a multi-touch model can help you understand how different shows contribute to your campaign's overall success. This approach is beneficial if your strategy aims to engage listeners at various stages of the customer journey.
3. Analyze the Average Order Value (AOV) of Your Product
The AOV of your product and the degree of consideration it demands before a user purchases are crucial in selecting an attribution model:
High Consideration Products: For products with a high AOV, such as luxury goods or services requiring significant investment, a multi-touch or time decay model may be more appropriate. These products often involve a longer decision-making process, where each interaction plays a crucial role in guiding a potential customer toward a purchase.
Low Consideration Products: For products with a low AOV, which are typically impulse buys or require less deliberation, last-click attribution might be more suitable. It helps identify the ads that effectively drive immediate conversions.
4. Define Your Marketing Goals
Building Brand Awareness: If your primary goal is to introduce your brand to new audiences, first-click attribution can highlight which podcasts are most effective at generating initial interest.
Driving Conversions: If your goal is to increase sales or specific actions, last-click attribution can help you identify which ads and shows are most directly contributing to these outcomes.
Understanding the Customer Journey: For a comprehensive view of how each podcast ad influences your audience throughout their journey, a multi-touch model provides valuable insights. This approach is particularly useful if your campaign spans multiple stages of the marketing funnel.
5. Utilize Tools for Enhanced Insight
Incorporating tools like Podscribe can provide detailed analytics and insights to support your choice of attribution model. These platforms can track listener interactions across different podcasts and ads, offering a more nuanced understanding of your campaign's performance.
Did you know Podscribe lets you see performance results across any attribution model in real-time?
Simply go into your dashboard and dynamically select the attribution model or window you want to look at and see how results and conversion weights change in real-time!
Other Thoughts to Consider
Adjust Your Attribution Window - See how your results vary when you shorten or lengthen the conversion window
A standout feature of Podscribe is the capability to modify attribution windows on the fly! This enables you to see how changes in the attribution timeframe affect credit assigned to shows, campaigns, and ads. This adaptability lets you experiment with different periods to pinpoint which best reflects your customers' behaviors and purchasing cycles, granting deeper insights into podcast listeners' conversion paths.
Analyze Results by “Individual Conversions” — See what campaigns/episodes are getting what % of credit
In Podscribe you can export your performance data by “Individual Conversions”. This allows you to see what episodes are getting what percentage of credit when it comes to each conversion. This feature allows for an examination of individual orders and the percentage of partial credit attributed to specific shows and episodes across your buys, providing detailed insights into the success of each episode and where it fell in the funnel. This detailed analysis supports informed decision-making, helping you to more accurately distribute your marketing budget and refine your podcast advertising strategy.
Conclusion
By aligning with your marketing goals, understanding the customer journey, evaluating product consideration levels, and leveraging Podscribe's dynamic functionalities, you can select an attribution model that not only complements your current strategy but also adapts to future shifts, optimizing the effectiveness of your podcast advertising efforts.