Web Analytics-Attribution

Let's first start by explaining what attribution is defined as in terms of web analytics.

For example:

Let's say you are scrolling through social media and see an ad for a product you have been wanting to purchase and this ad gave you the motivation to finally do it.

This is an example of an ad conversion.

A business can than see that this one ad was responsible (can be attributed) to the purchase made by the consumer. Companies use different methods to attribute conversion rates to specific ads and other advertising methods, but the 3 most common are Last-Click, Linear, and Time Decay attribution.

Last-Click Attribution

The first method will be the last-click attribution method. In the example above the consumer was only exposed to one ad that led to their purchase. In reality, as consumers, we may see hundreds of ads for different products in a day. So, what if in the previous example they saw multiple ads for the same product. The last click attribution model says that the most recent advertisement will be responsible for the conversion rate for that consumer. So, for example, if you see 3 ads for a new phone than the last ad you see will be deemed responsible for your eventual purchase. This seems to be the most common method because it is the easiest to track and the simplest way for a company to attribute successful ads.

Linear Attribution

It is not really ideal to say that one ad is responsible for a consumer to be persuaded to make any given purchase. The Linear attribution method is the idea that all ads a consumer sees for a product should be attributed equally to the conversion rates for that customer. This model makes more sense as a consumer because we know that it wasn't just one ad that persuaded us to buy that new phone or new coffee maker. Different ads have different ways of persuading consumers that they should make that purchase.

Time decay Attribution

Both of the previous methods are used to track which ads are most influential in the customers purchasing process. Both methods have different ways to specify the most important ads. The last method is the Time decay attribution which basically combines both the linear and last-click attribution models. We know that every ad we see daily gives some sort of influence on us when we eventually make that next purchase but the more ads we see, the more likely we are to be persuaded to buy that product. The time decay attribution method is the idea that the most recent the ad, the more influence it has on our purchases. So, the most recent would have the most significance and the first would have the least.

As business owners it is always in your best interest to know 2 things when it comes to advertisement

1. which ones are the most influential on consumers?

2. why are they the most successful?
   

Using attribution models can help you allocate(attribute) the credit of conversion rates to different ads so that you can analyze which ones are the most influential. Advertisement is something all businesses use but in order to optimize the effects of ads you must know how and if they are influential enough to persuade your consumers to make their next purchase.