Machine Learning Models
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  • The machine learning models are similar to algorithm models. But in this case, you actually rely on the historical data. That means you can easily assign the conversion credit to every touchpoint. Not relying on predetermined formulas makes this a lot better and certainly a lot more accurate. You get more control over the experience and results really shine because of that.

    It’s a lot better to have unique data you can rely on instead of using some arbitrary rules. Of course, the main focus has to be on delivering the right results and value, but as long as you get unique data things are becoming a lot better. You don’t have to focus on obsolete and maybe incomplete data. You rely on stuff that’s way better and certainly a lot more professional.

    It’s all a matter of knowing how you can rely on Machine learning for attribution. The attribution process is way better because machine learning actually identifies things and makes the process more personalized. It’s definitely not going to be simple to achieve that, and if you do it properly it can pay off big time. You will cherish the information a lot more because it will be very dependable and it will bring you the benefits and quality you want while also giving more control.

    The single-touch models are rule-based all the time, but the multiple touch ones can be rule-based or they can rely on machine learning. Each one of these options comes with its fair share of pros and cons. Machine learning for attribution is important because you can start attributing certain values and certain ideas to every category. Automating this really helps the process because not all of us have time to spend on these menial challenges. And the more you do that, the better it will become. You just have to understand how machine learning works and evolves, and based on that it will convey the information towards you.

    Rule-based attribution models

    As the name suggests, this type of model is relying on predetermined formulas in order to allocate ideas adequately. It doesn’t rely on historical data, which is a very important aspect to keep in mind. the rule-based model is great because it assigns the credit to your last touchpoint. That brings in front some creative options and it does deliver a very good experience all the time because of that. It also encourages you to use it because it’s very simple. 

    The downside with such an approach is that the system itself can end up not being overly reliable. You always want to have a good and reliable system to make it work, and in the end, that’s a crucial aspect to focus on no matter the situation. It’s the adaptability of this that has its own pros and cons, but once you understand how everything is worked on and improved, things will become better and better every time. The idea is to commit to the process and just make it work in an adequate manner. That definitely has its fair share of challenges. Because this attribution model is less reliable, it’s not bringing the type of success and results you want, so you have to take that into consideration and use it to your own advantage no matter the situation. It’s a good idea to keep in mind, so just consider it and it will be worth it. 

    If you are unsure how to explore this further, contact us at NextBee and we will be glad to work with you.

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