Various Google Analytics Attribution Models

How to evaluate your advertisement performance? The most productive way is to adopt one of the various attribution models and simultaneously analyze your marketing campaigns. The question is, “Which model works the best?”

Here, we will list the different models for you to explore and use for your business research. Follow the link to get a detailed description for each model and a few recommendations from OWOX specialists:

The Attribution’s Purpose

To assess your ad campaigns, you have to compare the results you gain from each. The process is called attribution: it allows marketers to have hard data on which customers are more loyal, productive, and profitable to the brand. Typically, you can categorize your campaigns as the ones that attract new customers (those are more expensive and have a broader coverage ) and those that motivate customers to remain loyal to your brand (this is cheaper, aimed at the portrait of the specific customer and their behavior). Which campaign works best and brings the most results? How to compare different stages? That’s what attribution is used for.

As with any tool, selecting the model that fits your enterprise best allows you to increase efficiency and reduce the advertisement’s costs.

Four main attribution categories

Generally, we can divide the models used for attribution into four main categories. The divide happens in different stages of analyzing customers’ association with your brand, which typically occurs in four steps – Falimiarization, Selection, Conversion, and Repeating.

Should we analyze the exact step of the client’s association, then we use a position-based model.  Analyzing all information about the client and their journey would require an algorithmic model.  And the last two: single- or multi-channel models, are used to learn the distribution of a specific value among the channels in your sales funnel.

Standard Models used in Google Analytics

  • The first interaction is used to attribute the single (and the first) source that allows the customer to familiarize themselves with your enterprise and products. Calculate which source is the most productive, and focus your traffic and advertisement on there.
  • The last interaction is almost the same, focusing on the last source in the chain, bringing the client to you. Usable for calculating sales effectiveness and keeping in touch with the audience.
  • The last interaction (non-direct). Analytics set this model automatically, and it is a bit more accurate than the previous one. If clients go directly to your service to buy something, it means that there was no chain in place, and you need to analyze previous steps taken by the user.
  • If your goal is to analyze all channels in the transaction equally, go with the Linear model. The whole chain leading the client to you is analyzed, and each step is attributed equally.
  • A bit more progressive model is called Time Decay. It also analyzes every step partaken by a customer, but the first step is considered the most general and the least valuable, progressively leading to the most important channel – the last one, as the one that contributed the most.
  • And the position-based models highlight two sources. It helps not to focus your research on a single position, analyzing multiple steps that lead the potential customer to you instead.

Why are Standard Models so Popular, and What Can be Done About it?

Each model we highlighted has its pros and cons, and neither is capable of drawing a full picture of the user’s journey. Analyzing the behavior is more complicated, and all models in Analytics (especially the Last Click, as the most popular one) are simple yet limited. For example, using the algorithmic models can help you delve deeper into the client’s mind and offer unique advantages for each group, thus increasing the revenue; it is done by uniting the offline data with offline sales, analyzing and generalizing different sources of revenue. Take a look at our list of other models to see if that’s precisely what your business needs.

Three main algorithmic models

Previously, we looked at the free aspects of Google Analytics. Yet, there’s a much more complex and honest system available for marketers who decide to invest in their research and purchase a premium package. Analytics 360 provides you with a Data-Driven model that doesn’t need any pre-set parameters, as it combines all the data you uploaded into Analytics and researches into various channels in your sales funnel not by order but by the value they bring. Combine it with free models and receive a reasonably objective picture.

But it can’t help you to link your online data with offline purchases. To do so, you may use Markov Chains. This algorithmic model allows you to see deeper into your data and determine which channel is the most effective by analyzing your funnel and determining the probability of the sale if you remove one or more steps from the chain.

There’s one single problem with it. Using Markov Chain requires a lot of time, effort, and skills. Luckily, several online services can simplify the process, like the attribution from OWOX BI. You still have the same advantages from the previous model, but now it comes with convenient visualizations and takes all your data into account. Look at the results each step brings you, analyze your research altogether, and draw conclusions from the concrete, comparable data gathered from the user’s journey.


It is your choice which model to select. Remember, though, that attribution is useful and should be applied by any marketer who decides to use it. There’s no better way to determine how and when your service becomes clear and appealing to various groups of customers, thus focusing your future efforts on proven and effective channels.

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