Based position It allows you to split attribution

[shaownislam]

It is intended for your brand if you want to know which of your ads close the most conversions. 4.- First interaction In this case, 100% of the conversion value is attributed to the first channel the customer interacted with . This could be used if you aim to increase awareness of your campaigns and ads, and you give more value to early interactions. 5.- Linear model This model gives equal attribution to each interaction on the path to conversion . It could be useful if the goal is to maintain contact and awareness at each stage of the purchase cycle. If you’re looking for a level playing field, this model is ideal. For example, it lets you see where your PPC ads play a role in each conversion path, along with a percentage of what’s attributed to them. 6.


- Time decay This model gives more credit to yahoo email list touchpoints closer to conversion in terms of time, and less to those further away . It's useful if you value those actions that are closer to conversion, or if you have a shorter buying cycle. Decaying time is most useful as a standard option, but if you have a particularly long buying cycle or are concerned that channels like social media receive very little attribution, it could cause problems. However, you can adjust this base model and the half-life of the decay, the lookback window, and thus adjust the credit based on the engagement metrics. 7.- into variable amounts . By default, Google Analytics will assign 40% to the first and last interaction and 20% to the interactions in between. This model is useful if you value the first and last interaction more highly but still want to attribute the touchpoints in between.