What are Data Models?
Data Modeling is a specific use case of Predictive Data Modeling or Predictive Analytics. According to Gartner, at a high level, these predictive models are a “commonly used statistical technique to predict future behavior.” In the world of marketing, Data Models take historic customer transactions or behaviors and help predict the likelihood of similar behavior happening again.
At LiftEngine, we build Marketing Data Models with machine learning and artificial intelligence to help brands leverage effective target audiences to increase marketing performance and boost campaign ROI (return on investment).
Types of Data Models
Three main types of Marketing Data Models are acquisition, retention, and reactivation.
Modeled Audiences for Retention
With rising paper costs and digital CPMs, it is important for advertisers to keep their offline and online campaigns relevant and effective. Retention models help accomplish this.
A Retention Model can be built based on first-party data such as email activity and purchase history, as well as the promotional details about the upcoming campaign. Each customer is scored based on their propensity to respond to the upcoming marketing campaign. Those with the lowest scores are dropped while those with the highest scores will be the new marketing campaign audience. Retention Models decrease campaign costs without sacrificing response, revenue, and ROI.
Modeled Audiences for Reactivation
Similar to retention models, reactivation models predict which customers are most likely to purchase from you after a long lapse in their activity. This is done through a combination of analyzing those customers who have lapsed and most recently came back to you and those who are buying from your competitors. Because it is significantly less expensive to win back lapsed customers than it is to obtain new customers, leveraging reactivation models is an effective way to significantly reduce your marketing campaign costs and build a higher average customer LTV.
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Why are Data Models needed?
Reliable data is essential to any successful marketing campaign. It can provide insights into customer behavior, reveal marketing opportunities, and help interpret campaign results. However, not having a full understanding of the data can make it difficult to utilize it properly.
A marketing data model can help solve this problem by eliminating guesswork and rounds of expensive testing. Machine learning coupled with artificial intelligence creates a high-performing marketing audience. Marketing strategies are often based on intuition, but if you want to improve your campaign’s success rate then it is important to incorporate data analysis. A marketing data model can help brands pinpoint the best offer, creative and audience to maximize campaign response and ROI.
Who uses a marketing Data Model?
All types of businesses, industries, and organizations utilize marketing data models. Marketing data models have multiple purposes such as maximizing engagement, creating customer personas, enhancing product development, and optimizing campaigns. All great tools that every business and organization need to stay relevant.
Marketing is an art and science that requires data to be successful. It is impossible to know who your customer is and make informed decisions without relevant data and the ability to interpret and leverage that data. Contact LiftEngine to discuss how we can help you grow your business with our modeled audiences for retention, reactivation, and acquisition.
Published on Aug. 09, 2022, Last Updated on Nov. 08, 2023