Conversion model

A conversion model is a framework used to analyze the effectiveness of marketing campaigns. Conversion models are essential in digital marketing, as they help advertisers understand the factors that influence user behavior and optimize their campaigns to drive better results such as sales, registrations, and subscriptions. 

Conversion models involve tracking and evaluating user interactions with marketing campaigns, websites, and mobile applications to identify the most effective strategies for driving conversions. They are essential for businesses to maximize their return on investment (ROI) in marketing efforts and improve overall customer acquisition.

Conversion models are used across various digital marketing channels, including search engine marketing, social media advertising, display advertising, and mobile app marketing. 

These models help advertisers identify the most effective strategies for reaching their target audience and driving conversions. They help marketers identify the touchpoints contributing to conversions and allocate marketing resources more effectively. 

There are several types of conversion models, each with its own approach to attributing credit to marketing channels and defining touchpoints.

Attribution modeling

One of the primary applications of a conversion model is in attribution modeling, which involves determining the value of different marketing touchpoints in driving conversions. By analyzing user behavior and conversion data, advertisers can identify the most effective channels, ad formats, and creative elements that contribute to conversions. 

This information helps them allocate their marketing budget more efficiently and optimize their campaigns for better performance. Google Analytics, for example, offers several attribution models that advertisers can use to analyze their conversion data. Some examples of attribution models include:

a. Last-click attribution model

The Last-Click Attribution Model assigns 100% of the credit for a conversion to the last touchpoint before the conversion occurs. This model is simple to implement and understand, but it can be misleading as it ignores the impact of earlier touchpoints during the customer journey. As a result, it may undervalue the role of awareness and consideration stages in the conversion process.

Note: most mobile app install campaigns have historically used last-click models.

b. First-click attribution model

The First-Click Attribution Model gives all the credit for a conversion to the first touchpoint in the customer journey. This particular model emphasizes the importance of initial interactions with marketing campaigns but may not accurately represent the influence of subsequent touchpoints that contribute to the final conversion.

c. Linear attribution model

The Linear Attribution Model distributes credit for a conversion equally among all touchpoints in the customer journey. This model acknowledges the role of multiple touchpoints in driving conversions but may not accurately reflect the varying impact of different touchpoints.

d. Time-decay attribution model

The Time-Decay Attribution Model assigns greater credit to touchpoints closer to the actual conversion event. This particular model recognizes that touchpoints closer to the conversion may significantly impact the customer’s decision-making process.

e. Position-based attribution model

This model allocates a specific percentage of credit to the first and last touchpoints, with the remaining credit distributed equally among the other touchpoints. This model acknowledges the importance of both initial and final interactions in the customer journey while also considering the role of intermediate touchpoints.

Predictive modeling 

Conversion models can also be used for predictive modeling, which involves using historical data to forecast future user behavior and conversion rates. By analyzing patterns and trends in user behavior, advertisers can identify potential opportunities and risks, allowing them to make more informed decisions about their marketing strategies. 

Personalization and targeting 

Another application of conversion models is in personalization and targeting, where advertisers use data-driven insights to deliver more relevant and engaging user experiences. By understanding the factors influencing user behavior and conversions, advertisers can create more personalized and targeted campaigns that resonate with their audience and drive better results. A report by Econsultancy revealed that 94% of companies agree that personalization is critical to their current and future success.

Singular helps advertisers optimize their marketing campaigns and drive better results by creating conversion models in SKAdNetwork and, soon, Privacy Sandbox.

Here’s how Singular enables conversion models:

Advanced attribution: 

Singular offers advanced attribution capabilities that help advertisers understand the value of different marketing touchpoints in driving conversions. By leveraging conversion models, Singular provides insights into the most effective channels, ad formats, and creative elements contributing to conversions, enabling advertisers to optimize their campaigns and allocate their marketing budget more efficiently.

Cross-device attribution

Singular supports cross-device attribution, enabling businesses to track and analyze customer interactions across multiple devices. This comprehensive view of the customer journey allows marketers to identify the most effective strategies for driving conversions and allocate resources accordingly.

Predictive analytics: 

Singular also includes predictive analytics that allow advertisers to forecast future user behavior and conversion rates based on historical data. By using conversion models to analyze patterns and trends in user behavior, Singular helps advertisers identify potential opportunities and risks, empowering them to make more informed decisions about their marketing strategies.

Fraud prevention: 

Singular’s Fraud Prevention Suite helps advertisers protect their campaigns from fraudulent activities that may negatively impact conversion rates and overall campaign performance. By leveraging machine learning algorithms and advanced detection techniques, Singular identifies and blocks fraudulent traffic, ensuring that advertisers’ campaigns are only shown to genuine users and that their conversion data is accurate and reliable.

Singular uses conversion models to help advertisers optimize their marketing campaigns and drive better results. By providing a comprehensive suite of tools and features, as well as expert guidance and support, Singular empowers advertisers to maximize the impact of their marketing efforts and achieve their goals using proven data-driven techniques.