However, popular doesn\u2019t always mean \u201cbest\u201d or \u201cideal\u201d. In fact, to understand the pros and cons of last click attribution, you need to understand attribution models in general. So, let\u2019s dive into that for a bit.<\/p>\n
What is an attribution model in the first place? <\/strong><\/h3>\nAn attribution model is basically a strategy that determines the way you assign credit for\u00a0 conversions across various customer touch-points.<\/p>\n
An attribution model may encompass paid search, email, social media, organic search, referrals and other digital channels. It also attempts to measure the impact that each of these channels has on the achieved conversion.<\/p>\n
![\"An](\"https:\/\/demandzen.com\/wp-content\/uploads\/2020\/03\/last-click-attribution-1.jpg\")
<\/p>\n
Last click attribution is the most popular channel because its implementation and usage are incredibly simple. This might be okay for a small business, but if you are in charge of a medium-sized or big business, you really need to utilize the different models when appropriate. So, let\u2019s look at some of them right now.<\/p>\n
Different Types of Attribution Models<\/strong><\/h3>\nFirst-Click attribution<\/b><\/h4>\n
Designed to tell you which channels are most effective in increasing awareness of your brand or services. It does this by attempting to let you know where your client first came in contact with you.<\/p>\n
This model doesn\u2019t care if the client has gone through countless other touch points prior to the first purchase. It assumes that the first touch point is the crucial one, and that your marketing dollars should go there.<\/p>\n
Last-Click attribution<\/b><\/h4>\n
LCA assigns 100% of the generated revenue to the last click point made before the purchase.<\/p>\n
Let\u2019s say that you send out a newsletter to your list and you announce your latest service. You include a banner announcing a promotional discount for the first 50 businesses that sign up. If people click that banner and purchase a plan, the banner gets all the credit.<\/p>\n
The beauty of last-click attribution lies in its elegant simplicity and the fact that it provides you with a rather decent way of knowing which campaigns are most effective in converting prospects into purchasing customers. It’s also very easy to track and set up.<\/p>\n
The downside of last-click attribution is that it completely steals the spotlight from earlier touch points which might have been just as crucial, or even more crucial in encouraging a person to make a purchase.<\/p>\n
Let\u2019s say that you get a really big business as a customer. Last-click attribution tells you that they clicked on an AdWords ad right before purchasing your enterprise plan.<\/p>\n
However, what if this decision maker has actually been reading your newsletter for months? Your email marketing encouraged them to purchase. It\u2019s just pure convenience that they were reminded by your AdWords ad to get it done. In such a scenario, LCA would falsely attribute credit to a channel that had little to do with their decision.<\/p>\n
Some marketers prefer using linear attribution<\/b><\/h4>\n
Linear attribution provides an overview of the process that prospects go through before they make the decision to buy. This model aims to tell you which campaigns\/channels are most used and most effective in moving prospects along the purchase funnel.<\/p>\n
It does this by mapping out all of the touch points that happen between first click and last click, and assumes they are all equal in value.<\/p>\n
For example, let\u2019s say that your customer approached you 4 times before scheduling a sales meeting. Once via email, another time via social media, a third time via an AdWords ad, and a fourth time via third party content syndication. Linear attribution would credit each of these with 25% of the credit for the sale. Or in this case, for creating that sales lead.<\/p>\n
![\"Linear](\"https:\/\/demandzen.com\/wp-content\/uploads\/2020\/03\/last-click-attribution-2.jpeg\")
<\/p>\n
There\u2019s also the positional model<\/b><\/h4>\n
This is a model that combines the logic of all previously discussed models. It accepts that the first click and last click are indeed important. In fact, it assumes they\u2019re the 2 most important points. But, it also assumes that other touch points in between deserve some credit, and it gives them credit in a linear way.<\/p>\n
The exact percentage will depend on your analytics software. In general, though, a common formula is 40-40-20. This means that 40% of the credit is given to the first click, another 40% is given to the last click, and 20% of the credit is distributed evenly across all the other interactions.<\/p>\n
The crucial difference between first-click and last click attribution<\/b><\/h2>\n
In essence, these two simple models have a different aim. First click aims to easily provide you with the information on how someone learned about your brand in the first place. On the other hand, last click intends to reveal what closed the deal. If you consider both metrics to be just as important, then the positional model is right for you.<\/p>\n
The \u201cTime Decay\u201d attribution model<\/b><\/h4>\n
This is a model which assumes that the closer (in time) a touch point is to the sale, the more influence it has on that sale.<\/p>\n
There is a notable difference between this model and the linear one. The older the marketing campaign, the less credit it will receive under a time-decay model. This is unlike linear distribution where each point gets an equal amount of credit.<\/p>\n
The time decay model is valuable if you consider each touch point important, but after a certain point, you want to devalue past marketing efforts or give higher value to more recent ones. This model might be better for certain kinds of long campaigns. It really depends on your business model.<\/p>\n
In some cases, the \u201clast non-direct click\u201d variant will be your attribution model of choice<\/b><\/h4>\n
This is a neat compromise that takes the simplicity of last click attribution while adding an additional element. It assumes that the most important touch point is the last one the customer made before they came to your website to purchase. Let\u2019s illustrate this with an example.<\/p>\n
<\/p>\nFirst-Click attribution<\/b><\/h4>\n
Designed to tell you which channels are most effective in increasing awareness of your brand or services. It does this by attempting to let you know where your client first came in contact with you.<\/p>\n
This model doesn\u2019t care if the client has gone through countless other touch points prior to the first purchase. It assumes that the first touch point is the crucial one, and that your marketing dollars should go there.<\/p>\n
Last-Click attribution<\/b><\/h4>\n
LCA assigns 100% of the generated revenue to the last click point made before the purchase.<\/p>\n
Let\u2019s say that you send out a newsletter to your list and you announce your latest service. You include a banner announcing a promotional discount for the first 50 businesses that sign up. If people click that banner and purchase a plan, the banner gets all the credit.<\/p>\n
The beauty of last-click attribution lies in its elegant simplicity and the fact that it provides you with a rather decent way of knowing which campaigns are most effective in converting prospects into purchasing customers. It’s also very easy to track and set up.<\/p>\n
The downside of last-click attribution is that it completely steals the spotlight from earlier touch points which might have been just as crucial, or even more crucial in encouraging a person to make a purchase.<\/p>\n
Let\u2019s say that you get a really big business as a customer. Last-click attribution tells you that they clicked on an AdWords ad right before purchasing your enterprise plan.<\/p>\n
However, what if this decision maker has actually been reading your newsletter for months? Your email marketing encouraged them to purchase. It\u2019s just pure convenience that they were reminded by your AdWords ad to get it done. In such a scenario, LCA would falsely attribute credit to a channel that had little to do with their decision.<\/p>\n
Some marketers prefer using linear attribution<\/b><\/h4>\n
Linear attribution provides an overview of the process that prospects go through before they make the decision to buy. This model aims to tell you which campaigns\/channels are most used and most effective in moving prospects along the purchase funnel.<\/p>\n
It does this by mapping out all of the touch points that happen between first click and last click, and assumes they are all equal in value.<\/p>\n
For example, let\u2019s say that your customer approached you 4 times before scheduling a sales meeting. Once via email, another time via social media, a third time via an AdWords ad, and a fourth time via third party content syndication. Linear attribution would credit each of these with 25% of the credit for the sale. Or in this case, for creating that sales lead.<\/p>\n
<\/p>\n
There\u2019s also the positional model<\/b><\/h4>\n
This is a model that combines the logic of all previously discussed models. It accepts that the first click and last click are indeed important. In fact, it assumes they\u2019re the 2 most important points. But, it also assumes that other touch points in between deserve some credit, and it gives them credit in a linear way.<\/p>\n
The exact percentage will depend on your analytics software. In general, though, a common formula is 40-40-20. This means that 40% of the credit is given to the first click, another 40% is given to the last click, and 20% of the credit is distributed evenly across all the other interactions.<\/p>\n
The crucial difference between first-click and last click attribution<\/b><\/h2>\n
In essence, these two simple models have a different aim. First click aims to easily provide you with the information on how someone learned about your brand in the first place. On the other hand, last click intends to reveal what closed the deal. If you consider both metrics to be just as important, then the positional model is right for you.<\/p>\n
The \u201cTime Decay\u201d attribution model<\/b><\/h4>\n
This is a model which assumes that the closer (in time) a touch point is to the sale, the more influence it has on that sale.<\/p>\n
There is a notable difference between this model and the linear one. The older the marketing campaign, the less credit it will receive under a time-decay model. This is unlike linear distribution where each point gets an equal amount of credit.<\/p>\n
The time decay model is valuable if you consider each touch point important, but after a certain point, you want to devalue past marketing efforts or give higher value to more recent ones. This model might be better for certain kinds of long campaigns. It really depends on your business model.<\/p>\n
In some cases, the \u201clast non-direct click\u201d variant will be your attribution model of choice<\/b><\/h4>\n
This is a neat compromise that takes the simplicity of last click attribution while adding an additional element. It assumes that the most important touch point is the last one the customer made before they came to your website to purchase. Let\u2019s illustrate this with an example.<\/p>\n
![\"In](\"https:\/\/demandzen.com\/wp-content\/uploads\/2020\/03\/last-click-attribution-3.jpg\")
<\/p>\n