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Direct traffic and attribution models

In this article we will give you a brief introduction of how to measure direct traffic and how the conversion value changes depending on the attribution model you decide to use.

What is direct traffic?

Direct traffic is a kind of traffic source as could be SEM, emailing, Display, Referer or Organic. Direct traffic could be defined as any traffic a webpage receives directly, meaning, either a user has typed the URL and push enter or the user has landed on your webpage by the use of a bookmark.

Attribution models

Attribution models can be described as patterns that allow us to visualize the value that each source or channel posses in regard to the role they perform (Conversions, leads, visits).


Attribution models are useful to optimize and justify our investment in the different traffic sources we use to attract traffic to our web pages. Another advantage of working with attribution models is to assign the right commission to your affiliates or suppliers. Finally, attribution models are of great help to create strategic plans in advance.

There exist different attribution models and therefore, we must bear in mind that each of them has its own goal and provide us with different information. If we would like to measure the conversion from direct traffic, we will have different scenarios depending on which attribution model we use. It is important for you to least have a basic knowledge of the mos used attribution models:

  • First Interaction – It gives the maximum value to the channel that has started the conversion process and therefore, no value to others participants.
  • Last Interaction – It gives the maximum value to the channel where the conversion has occurred, which means the rest of the channels are given zero value for this conversion.
  • Lineal Model – It gives the same value to all the participant channels ( the same value for a user that has to click on a banner, later on, a newsletter, and has converted by a PPC ad)

The most common attribution model for e-commerce or for analyzing PPC campaigns is the last interaction model. Although, as we can anticipate it has its drawbacks. From Analytics, we can measure the amount of traffic and conversions coming from different channels. However, if we look at our data from direct traffic and we use a last interaction attribution model we might misinterpret our results.


In general, if we focus on a first interaction model, we will see that our Organic, SEM, and Display traffic are the channels with more traffics. Although, if we use the last interaction model, we will notice that Direct traffic plays a major role in getting traffic and, in many cases, it ends up being the most common traffic source. This data can be misinterpreted if we give all the credit to Direct traffic as this one may be helping other traffic sources to convert. Therefore the question is, How do we calculate which traffic source has helped us to bring more traffic to our website? What do we do if we want to measure the influence between channels?

For example: Are our Google Adwords campaigns helping to our sales from the Direct channel?

Adinton lets you answer this question in a very simple and effective way. Adinton uses the last attribution model with an added plus, which is that Adinton can measure the influence between traffic channels. Lastly, with Adinton, all this information can be seen in a single screen.

traffic sources 2 adinton

With all this information, we can finally see how much channel A has influenced channel B and therefore if an ad from Adwords has helped us to get a sale from Direct. Another advantage offered by Adinton is that the data is consolidated every day and so we can make decisions almost immediately.

traffic sources 3 adinton

As you can see in the picture, Direct conversion has been assisted 3 times by Referrer and 1 time by SEM. This indicates that a click on an ad (from SEM) that has not become a sale, has helped the Direct traffic source to gain a conversion/ sale.

In the end, with all this information provided by Adinton, we can make more realistic decisions about the weight that each of our traffic sources has. Thereby, we can adjust our budgets to monetize and optimize our visits and conversion ratios.

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