3 Multi-Touch Attribution Models for a Data-Driven PR Strategy
Data-driven PR may sound like a foreign language, but it’s not as complicated as we often make it out to be. As the digital world rapidly expands, the number of touch points increases, creating a shift in the modern customer’s experience.
As a result, more data needs to be sifted and analyzed to pinpoint which efforts are succeeding and why. Don’t let the volume of data overwhelm you. Instead, make data your friend.
Multi-touch attribution models provide PR professionals with insights by evaluating all touch points. But before you try to impress executives by showcasing PR’s value, you should understand the basics of multi-touch attribution.
The two most common attribution models are rules-based and algorithm-based. Beginners should start with a rules-based model. Its simplicity provides an opportunity to get into a data-driven mindset without inundating them with too many new concepts. Here are three rules-based models to consider when creating your PR measurement strategy.
The name of this model works exactly like how it sounds. The linear attribution model identifies exactly which touch points make up your customers’ buying journey and weighs them evenly. If you’re looking to create an overview of your PR efforts, this is the model to implement.
A position-based attribution model weighs touch points differently. Typically, first and last touches carry more weight than those found in between, and the weight percentage is often pre-assigned by the touch point’s position. A position-based model is perfect if you’re looking to identify the most effective touch points in nurturing prospects.
3. Custom model
While we saved the best rules-based approach for last, don’t enact this model without trying a simpler rules-based model first. You can’t customize an attribution model without first implementing an existing, rules-based approach into your PR strategy. Once you feel comfortable, build a custom model to compare two or three other models efficiently.
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