Does a buyer visit your blog or website and instantly make a purchase? Although this would be an ideal scenario but it rarely happens.  A customer traverse through multiple channels, interact with the brand on various platforms before finally buying the product.  Assessing the Return on Investment in this scenario can be tricky. It gets difficult for the brands to examine which platform is responsible for shaping the final buying decision. This is where Attribution model can prove to be extremely beneficial for the brands. 

What is an Attribution Model in Marketing?

Attribution Model is a framework which analyzes multiple marketing channels and touchpoints which the user passes through its journey in becoming a customer and assigns credit to each channel. It maps the entire journey, right from the lead to turning into customer taking into consideration each channel where the lead interacts with the brand and what promotes the user to buy.  With this model,  brands are able to assess the return on investment by fragmenting and breaking up the entire customer’s journey into touchpoints and assigning value to them depending on how crucial they were leading up to a conversion.

Types of Attribution Model:

Last click: Also known as “Last Interaction” attribute, this model gives 100% to the last touchpoint.  The communication channel with which the interaction occurs just prior to conversion gets the entire credit. This is usually a default attribution model, quite accurate for measuring direct response marketing. This model is most appropriate for businesses with a short sales cycle. It is extremely easy to implement this model. Being single click model, it doesn’t consider any of the marketing channels prior to the last touchpoint. All sources which assist the lead in getting lead to the last channel are ignored.

Last Click Attribution Model

First click: Also known as “First Interaction “attribution, as the name suggests this model gives all credit to lead’s first interaction with the brand. So, 100% credit goes to the channel with which lead interacts first. Brands which primarily focus on attracting top of the funnel customers utilize this model.  Similar to the last click, this model ignores all marketing channels post first interaction. 

First Click Attribution Model

Last Non -Direct click: This is a variation of the last-click model which assigns 100% credit to the non-direct channel which the lead last visited.  It eliminates direct clicks. If the user has already bookmarked the website, or types the URL in the search bar, it ignores the direct traffic. This model focuses on channels which creates awareness about the brand among leads.

Last Non-Direct Click Attribution Model

Linear Attribution: Linear attribution model takes into consideration all marketing channels which are involved in a customer’s journey and assigns equal credit to them. Being a multi-click model, it provides a balanced look of overall marketing strategy.  The drawback with assigning equal credits is that all channels are treated equal and the ones which play major role in conversion don’t get highlighted.

Linear Attribution Model

Time decay: This model also considers multiple channels but also takes into account which touchpoints occurred closer to the time of conversion. The last interaction gets maximum credit and these credits diminish as further back we go.  The first transaction gets the least credit. Businesses with a longer sales cycle go for this type of model. This model works on 7 days half cycle, which means the touchpoint which occurred 7 days before the last interaction will receive half credit. 

Time Decay Attribution Model

Position: Also known as” U shaped Attribution” , this model assigns credit to all channels but gives the highest % to first and last interactions and rest all touchpoints are weighted equally.  40% credit goes to first and last while remaining ones get 20%. Businesses which have multiple significant touchpoints throughout the sales cycle use this model as it assigns credit to each interaction.

Position Attribution Model

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