Last click lets you credit the last step or touch point prior to conversion. For instance, in the example in the start of the blog, the RLSA ad click would get credit, if the last click attribution modelling was to be chosen.
First Click, like the name suggests, gives credit to the first touch point in the conversion journey. For instance, value will be attributed to the click/keyword that first drove traffic to your site.
Linear Attribution credits all clicks/keywords, basically all user interactions a user takes before converting, equally. This modelling is super helpful in airing out which channels are worth investing in more, for a business. They are great for multi funnel campaigns that take a user from TOF to BOF, leading them to convert. There is a catch, though. The campaigns need to be running long term, in order to reflect true attribution.
Time Decay attaches more credibility to the last few touch points, prior to a conversion, in the user journey than the initial ones. This modelling benefits brands that need a thorough understanding of their service more, rather than ecommerce brands where product transactions happen fast.
Position Based gives 40% credit to the first and last interactions, while giving 20% to the rest, in a conversion journey. This modeling clearly tells you, instead of hinting, which keywords/clicks are responsible for inspiring and show stopper-ing the buyer journey, and what interactions fell in between.
Data-Driven modeling lets you use machine learning to your advantage. This is based on account performance and intelligent learning of which keywords were the most influential in the conversion journey, with conversion credit being attached accordingly. This is ideal for big spenders where click and conversion volume are likely to be equally high.
*The prerequisites to using it are that in 30 days you should have gathered 15,000 clicks, 600 conversions. For continued use, you should be able to achieve and maintain 10,000 clicks & 400 conversions in the consecutive 30 days.