This model gives all credit to the last touchpoint before the conversion.
- Pros: Last Click is easy to track since it only focuses on one touchpoint. Moreover, you don’t have to worry too much about the set-up. Last Click is known for its simplicity, and it’s the default model in Analytics.
- Cons: A lot of things can happen before the “last click”, and this model completely ignore those activities. Brands don’t know how many times the prospect interacted with them before the conversion or what influences the prospect decision. Not knowing this means you can miss some of the most effective and influential interactions that are helping your prospects convert.
This model gives all credit to the first touchpoint before the conversion.
- Pros: This model provides insights into what introduces your brand to the prospects and how they found you. In addition, just like last click model, since there is only one touchpoint available, it’s easy to track and set-up.
- Cons: This model completely ignores the contribution of other touchpoints that take place in the conversion process after the first click.
This model gives credit evenly to all the touchpoints in the conversion process.
- Pros: Every interaction with the brands are recorded and valued and given equal credit for contributing to the conversion.
- Cons: There’s no difference between the touchpoints so you can’t find out which touch has the biggest impact. Therefore, some touchpoints might be overvalued and some might be undervalued. That means you may end up investing more or less in a particular touchpoint than you should.
In this model, the closer to the conversion, the more credit the touch point will receive. So the last touchpoint receives the most credit, while the first touchpoint receives the least credit.
- Pros: Like the linear model, this model gives recognition to every touchpoint. Plus, this model reflects the majority of customer journey: as the prospects have more interactions with your brand, they become more acquainted with your brand.
- Cons: This model undervalues the first touchpoint, which may have the most impact on the final conversion. After all, first impressions are usually the most lasting.
This model gives 40% credit to each the first and last touchpoint. The remaining 20% will be divided evenly amongst the middle touchpoints.
- Pros: This model helps your brand focus marketing efforts on touchpoint that introduced your brand to the customer and the final touchpoint that drove them to convert, while still giving kudos to the middle touchpoints.
- Cons: Blindly giving a large amount of credit to the first and last touchpoint can be dangerous. Sometimes it doesn’t cost that much to make an impression (i.e. email). Same goes with the last touch point. In short, this model can drastically undervalue the middle touchpoints.
If you are not satisfied with any of the models above, you can consider creating your own model! With a custom model, you can make adjustments to the weight for each touchpoint based on your audience, marketing strategy, and business goals or objectives.
- Pros: You know what influences your prospect from start to finish, and accurately attribute credits to the right touchpoints, which improve the allocation of your marketing budget.
- Cons: Create a whole new model can be…frustrating, complicated, tedious, and stressful. You must do a lot of trials, encounter several errors before getting the right one.
- Sidenote: You can also import already created attribution models in Google Analytics by importing them from the Gallery.