Every year, competition in the market intensifies, which forces entrepreneurs to literally fight for every visitor to the site. That is why in consumer marketing, a strategy based on user behavior comes to the fore. This ultimately allows you to increase revenue and increase the number of customers. However, unfortunately, many marketers and site owners simply ignore this truly valuable information about user behavior.
The beginning of a website visitor's conversion journey can now lie in paid media, online advertising, and offline touchpoints (flyers, merchandise, word of mouth). The only way to know which channels are actually driving conversions is to use smart metrics.
Introduction to attribution
Attribution is the definition of the traffic source due to which the conversion was made (target action or sale).
For example, suppose a customer sees your ad on their favorite news site but takes no action. Later, he sees it on one of the social networks, clicks on the ad, but there is no increase in conversion. Ultimately, he sees your call to action on another site, goes to the page and takes the targeted action. Attribution allows you to track this process, identify the most effective channels and, in accordance with the information received, build a marketing strategy.
There are three main steps to include attribution in your marketing campaign.
- Choose an attribution model.
There are many options, but the most used ones are the following:
- Last click. According to a recent survey, 80% of advertisers use this attribution model, despite the fact that they believe it is not effective enough. A variety of factors influence the conversion, but this model covers all channels that “pulled” the client into the sales funnel. The user saw the same ad on four different sites - his interest continued to grow after each viewing, but only on the last site the client decided on the target action.
- First click. This model is an inverse projection of the previous one. In this case, it is the first ad of all that the potential client clicked on that is considered the “main” one, even if its action did not lead to an immediate increase in conversion.
- First and last click. The essence of this model is that the first ad arouses interest in the user, and the last one encourages him to take an action.
- Equal rights. According to this concept, all ads placed and viewed by the client are assigned the same value.
- "Full" sales funnel. In this case, each element of the user's conversion path matters. You can even determine in percentage terms how important the first ad is, what the role of email marketing is and, finally, the call to action, thanks to which the targeted action was eventually completed. This allows you to rank the value of each element of the marketing campaign.
You should test different models to determine which one works best for your business.
- Find an attribution platform.
Depending on the type of campaign you're running, attribution may be built into the system you're using. If it is not, you always have the option to use various services For example, the AdRoll and Perfect Audience retargeting tools have this feature built into the system, as do Facebook and Google’s Double Click Campaign Manager.
To get the most out of attribution functionality, you can use analytics platforms such as Google Analytics, IBM Digital Analytics, and Adobe Site Catalyst. Alternatively, you can hire an attribution specialist to help guide you through the process.
You can also understand the effectiveness of the channel using widgets. For example, due to the fact that the client interacts with widgets: clicks on the “cross”, goes to the recommended one in a pop-up window, or leaves contacts.
The Google Analytics system will calculate the target action (which you need) and find its source. So you can understand that Yandex Direct, for example, brought you 1 e-mail from a client via .
Learn more about how widgets help build sales funnels and measure channel performance.
- A/ BAttribution testing will help you better understand the customer.
Attribution, combined with A/B testing, allows you to pay attention to the channels that perform the best, as well as test various marketing elements, such as call to action, design, use of profitable offers, etc. In essence, it allows you to understand how your actions affect the entire sales cycle.
In order to identify which element of the campaign is more effective, it is recommended to build attribution into each of them. The list includes social media, ad retargeting, email marketing, direct advertising, and more. As a result, you will know for sure that “this banner on this site or this chain of letters in total gives X income.”
Attribution allows you to better understand the conversion path of your customers, which, in turn, will help you correctly calculate costs and optimize your marketing strategy.
How do your advertising channels interact with each other? What is the best way to distribute funds between them? Should I disable an advertising campaign if it does not bring conversions? All of these painful questions can be answered by studying user behavior and their path to purchase. In this article, I'll show you how to do this with assisted conversions and attribution model comparisons in Google Analytics.
What are assisted conversions?
Effective channels attract users who perform targeted actions on the site (transactions, registrations, orders callback and more - it all depends on how the project is monetized). At the same time, sometimes one interaction with the site is enough for the visitor to make a conversion, but not always. The rule of "seven touches" works more often - therefore, a separate tool is used for each stage of the sales funnel. For example, display advertising helps users learn about your product, search advertising attracts already interested users.
Assisted Conversions- target actions, during which the analyzed channel was an auxiliary source (that is, the final interaction occurred after the transition from another channel). Imagine that you are selling children's toys.
1. User saw media advertising and went to your site. Among the assortment of the online store, he liked a toy minion, but the user did not complete the transaction, because at that time he was not interested in buying (since banner advertising this happens often - read).
2. A week later, this visitor was invited to a birthday party and he remembered the toys on your site. Entered in the search for "toy minion", I saw your search advertising and saved the site in browser bookmarks to quickly find it after receiving a salary.
3. Finally, during the third direct visit the user has ordered a toy. By default, all conversions are assigned a conversion value by Google Analytics based on the last indirect source of the visit, in our case, search ads. At the same time, in general reports, we will not see that display advertising was one of the factors due to which the user bought the toy on your site.
If for some of your channels or sources there are no conversions in regular Google Analytics reports, do not rush to refuse it, this can be a key step on the user's path to purchase.
How to view assisted conversions with Google Analytics?
To see if a channel or source was involved in a user's conversion journey or not, use the Multi-Channel Funnels report. To do this, go to the "Reports" tab and select "Conversions" - "Multi-channel funnels" in the left panel. 
1. In the "Overview" sub-item, you can see a general summary and visualization of the ratio of different conversion sources. 
2. In the "Associated Conversions" sub-item, you can see direct information about the channels of assisted conversions, their number and value: 
3. On the "Time to Conversion" tab, provided useful information to find out how many days your users make a purchase decision. This information can be used to fine-tune remarketing. 
Please note that the line "12-30 days to conversion" displays the sum of target actions for the analyzed days. By clicking on the plus next to the line, you will see more accurate information. 
4. The last sub-item is “Main conversion paths”. It displays information about how many interactions with the site users make before making a purchase and which channels they use. In our example, direct visits are also leading through search advertising. 
This is not all the opportunities for analysis of assisted conversions that Google Analytics provides. Next, we'll take a look at the attribution model comparison tool.
What is attribution and what models exist?
Attribution is the distribution of conversion value across all user interactions with the site prior to the transaction.
As I already wrote, by default, in Google Analytics reports, the value is assigned to the last indirect interaction of the user with the site. This information will be useful if most often the user makes a purchase decision after the first interaction. For example, a display ad for a pizza delivery service can generate conversions on the first visit to the site.
Let's consider each model in detail using illustrations from the Google presentation.
100% of the conversion value is assigned to the first interaction. 
This model is well suited for evaluating the effectiveness of display ads, as its goal is to familiarize the user with your offer.
In the interaction chain, 100% of the conversion value is assigned to the last channel, even if it was a direct transition to the site. 
3. Google Ads Last Click Model
Last click on ad Google Ads gets 100% of the conversion value. 
Each interaction is assigned the same conversion value. 
This model can be used when every point of user interaction with the site is equally important.
The closer the interaction is to the moment of the target action on the site, the greater its value. 
The first and last channels in the interaction chain will be assigned 40% of the value, the remaining 20% will be evenly distributed among the remaining channels. 
This model will be useful if you are interested in both the first interaction, when users first learned about your offer, and the last one, when the target action was taken on your site.
With this model, you independently distribute the value of conversions between interactions. You can create such a model directly in the Google Ads interface. 
This model is available in Google Marketing Platform. It distributes value across all sessions in the chain based on the correlation between the presence of the source in the chain and the conversion of the chain. 
The data-driven model can only be used in accounts with a large amount of data (minimum 20,000 clicks and 800 conversions in 30 days).
1. Select the "Reports" item in the top panel, then in the left menu follow the path: "Conversions" - "Attribution" - "Model Comparison Tool". 
2. Choose goals that interest you. For example, you can ignore related actions, such as adding a product to the cart, but only transactions. 
3. In the lookback window, select how many days before a conversion is to be considered for analysis (from 1 to 90 days). 
4. Next, you need to select an attribution model with which the report will be built. 
4.1. You can choose one of the default attribution models.
4.2. You can also create your own attribution model or import one from the Google Analytics Gallery.
4.3. One more important function- selection of several attribution models (maximum - three). For example, let's take attribution models for the last and first interactions. 
5.1. By default, you can analyze by sources, channels and their groups.
5.2. You also have the opportunity to select any parameter from the list of traffic sources, custom parameters and Google data Advertisements. 6. And the last - you can segment the report. For example, compare conversions that occurred as a result of ads in the first or last interaction. 
By applying the segments selected above, you will get the following type of report: 
So you have learned how to use the attribution model comparison tool.
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Conversion attribution is a multi-component concept that consists of the terms “attribution” and “conversion”.
Conversion in business is the completion of a targeted action by a user for the company. For example, if your goal is for a user to make a purchase, then the most important conversion for you will be the transaction.
Conversion is divided into macro and micro:
- Macro conversion is the final action we are aiming for. For example, the same purchase of goods.
- Microconversions are user steps that lead to macroconversions: registering on the site, adding products, etc.
Attribution is the rule of distributed conversion value. Simply put, assigning "points" for a conversion to calculate its effectiveness.
Ultimately, conversion attribution is a method of determining the effectiveness of a marketing channel, calculating the contribution of a specific entity (channel, keyword, landing page) to make the conversion.
Conversion Attribution Models
What is the Google Analytics or Yandex Metrics attribution model - this is a set of rules by which you decide to determine the value of a conversion. There are 7 standard attribution models in Google Analytics and 2 in Yandex.Metrica.
Let's imagine that a visitor came to your site throughad on google, then, after a while, follows the link from the social network, on the same day getting to the site through the mailing list and through the direct link.
- Last Interaction Model (Last Touch): All "points" are given to the last channel in this conversion chain. In our case, this will be a direct transition to the link.
- Model "Last indirect click": In many respects it is similar to the previous model, but with the condition that direct visits are ignored, and all value is assigned to the last channel through which the user came before the macro conversion. In this example, this will be a mailing list.
- Model " Last click in AdWords": All conversion value is invested in the last click on an AdWords ad. We have only one click.
- First Interaction Model: The first channel in the chain, through which the user made the transition, is considered valuable. Here it will again be AdWords.
- Linear model: All channels in the conversion chain are assigned the same value. There are 4 elements in our chain, and each is assigned 25% of the total number of "points".
- Model "Taking into account the prescription of interaction": The closer the user interaction point is to the time of the macro conversion, the more valuable it will be. The concept of "exponential decay" is used here, and the default half-life is 7 days. That is, if the action occurred more than 7 days ago, then it is 2 times less valuable, and more than 2 weeks - 4 times less. Let's say that the transition through AdWords was made 8 days ago from the date of purchase. Then this channel will receive 2 times less value than all the others. The most valuable will be the transition from the mail and the direct transition.
- Position Attribution model: This is a fusion of the first and last touch models. The first and last link in the chain receive 40% of the total conversion value, the remaining 20% is evenly distributed among all participants. In our case, AdWords and direct visits will receive 40% each, 10% - social network and mail.
Yandex metrics attribution models include the first and last transition, the last significant transition.
- In the case of the first option, all the value of the conversion goes to the channel through which the first touch occurred.
- In the second - to the last click that led to the conversion.
- If everything is clear with the first two, then the last one needs to be dealt with more carefully. The last significant transition is similar to the last transition attribution, with the only difference being that the transitions from bookmarks are discarded and only significant sources remain: search, context, social networks.
You can customize your conversion model depending on the conditions of your advertising company.
How to choose an attribution model?
The conversion attribution calculation model is selected depending on the characteristics of your business and advertising campaign:
- The “last interaction” model will suit you if your business is based on purchases and transactions that do not involve a decision-making stage.
- "Last indirect click" is suitable as a baseline for comparison with other models and if you do not want to take into account direct visits to the site.
- AdWords Last Click is used to determine the highest performing AdWords ad.
- If you want to know what sparks interest in your visitors and provides the first touch, then use the First Interaction model.
- If you are constantly in contact with a potential client through advertising all the way from the first click to the conversion, then use the Linear Attribution Model.
- For short-term advertising campaigns, it is recommended to use the "Accounting for interaction age" model.
- If you equally value the first acquaintance of the client with the product and the final conversion, then you should use the attribution “Linked to position”.
- Use the "Last click" model for technical analysis of the site and the detection of pages without a counter code.
- Set up the "First click" model if the user takes a long time to decide on the target action and return to the site from any other traffic sources.
- "Last significant click" for sites with fast conversions occurring within a single visit.
Conversion attribution is powerful tool used in Internet marketing to analyze and adjust an advertising campaign. Using it, you can always find effective advertising channels and reduce business development costs.
Learn how conversion value is distributed across different attribution models.
The following standard attribution models are available in the Model Compare Tool. You can also create your own models.
Description of standard models
In the model Last interaction 100% of the conversion value is assigned to the last channel in the interaction chain.This model is recommended when working with ads and campaigns focused on customer acquisition at the point of purchase, and also if your commercial activity is based primarily on transactions that do not involve a decision stage.
In the model Last indirect click direct visits are ignored. 100% of the conversion value is assigned to the last channel in the interaction chain. Analysts use this model by default for all reports except multichannel funnel reports.Since this model is used by default for all reports except multi-channel funnel reports, it is useful as a baseline for comparison with other models.
In addition, it is suitable when direct traffic comes from users previously attracted through other channels, and should not be taken into account when analyzing customer actions before conversion.
Within the framework of the model Last click in Google Ads 100% of the conversion value is assigned to the last Google Ads ad click in the interaction chain. In the model First interaction 100% of the conversion value is assigned to the first channel in the interaction chain. AT linear model, all channels in the conversion sequence are assigned the same value. If the purchase cycle involves a short stage of customer decision-making, you can choose the model Taking into account the prescription of interactions. This model is based on the concept of exponential decay. The closer a touchpoint is to a conversion, the more valuable it is considered. Within this model, the period half-life the default is seven days. This means that an interaction that occurred seven days before a conversion is half as valuable as an interaction registered on the same day with it, and two weeks before it is four times less valuable. Exponential decay occurs over the entire lookback period (default is 30 days). Position based attribution is a hybrid of the First Interaction and Last Interaction models. Instead of assigning all the value to the first or last channel, you can share it between them. Usually it is distributed as follows: 40% for the first and last channel and 20% for all the rest.When analyzing website promotion and the profit received from advertising campaigns, it is very important to trace the entire user's path - from the moment they enter the site to the moment they make a purchase. This will give us the opportunity to understand how to distribute the budget between advertising channels in the future, how these channels interact with each other, which one is the most effective, and much more.
In practice, such a path may consist of a chain of different traffic sources. For example, a visitor first went to our site through contextual advertising (Paid Search), viewed several pages of the site and left. Later I switched again, but from Organic Search. A few days later I went to the site through a direct source (Direct), entering the address in the browser line, and made an order.
Example of a user journey when buying
Thus, before making a transaction (conversion), the user interacted with the site in three different sources traffic:
- Contextual advertising;
- organic search;
- direct entry;
To which of them will Google Analytics attribute the achieved goal in its reports? To answer this question, it is necessary to understand such concepts as attribution and attribution model. Attribution in web analytics is the rule of allocating the value of a conversion among all interaction stages in a conversion path and assigning a certain number of points (in %) to calculate its effectiveness.
An attribution model is a set of rules by which you decide to determine the value of a conversion. There are 7 in Google Analytics various models attributions:
- Last interaction;
- On the last indirect click;
- Last click in AdWords;
- First interaction;
- Linear;
- Temporary recession;
- Position based.
Last interaction (last click)
All 100% of the conversion value goes to the last channel in the interaction chain. In our example, this direct channel.
Attribution Model - Last Interaction
"Last Crossing".
The advantage of this model is that you can say with 100% certainty which visit resulted in a conversion. However, this also has its drawback - it does not take into account the previous interactions of the user with the site. Thus, according to our example in Analytics reports, we will not be able to understand that the user made his first touch through advertising (namely, we spent money on it and through it the user got acquainted with our offer for the first time), and also we will not be able to see that then he carried out a similar search and again stumbled upon us, but only through the organic. The last source took all the value!
This model is recommended to apply to those projects whose audience is ready to buy immediately and without additional time to think. As a rule, these are goods or services with a quick response - food delivery, taxi call, car evacuation, equipment repair, etc.
Last indirect click
This model is used by default for all Google Analytics reports except multi-channel funnel reports. The difference from the first model is that direct visits are ignored in attribution, and 100% of the value is assigned to the last channel in the chain of interactions. In our example, this is organic search.
Attribution Model - Last Indirect Click
Yandex.Metrica has a similar attribution model called "Last Significant Transition", in which all sources are conditionally divided into significant and secondary (insignificant). Insignificant just include direct visits, internal transitions and transitions from saved pages.
Since it is the base model in Analytics, it should be used when comparing with other models. The model comparison tool is available in the section "Conversions - Attribution". This will be discussed in more detail in the following chapters.
In this model, the downside is that the value of direct interactions is purposefully underestimated.
Last click inAdWords
All 100% of the conversion value goes to the last AdWords ad in the interaction chain. In our example, this does not mean at all that 100% will go to contextual advertising(Paid Search channel), since you can run campaigns in other advertising systems in parallel with Google AdWords.
This model is used if you have an advertising campaign in AdWords, and users from your ads come to the site to complete transactions. And Google, introducing such a model into the list of standard Analytics attribution models, did not think about other advertising services, except for its own.
Web Analytics Guru and Google Evangelist Avinash Kaushik in one of his articles he called this model useless. Therefore, we will follow his advice and move on to the analysis of the next one.
First interaction
All 100% of the conversion value goes to the first channel in the interaction chain. In our example, this is contextual advertising.
Attribution Model - First Interaction
Yandex.Metrica has a similar attribution model called "First Crossing".
Linear attribution model
All channels in the conversion funnel are assigned the same value. In our example, 33%.
Attribution Model - Linear
This model applies when the user is exposed to various channels throughout the conversion cycle and when calculating the effectiveness, all points of interaction with a potential client are important. For example, when analyzing blog posts.
Temporal decline (taking into account the prescription of interactions)
This model is based on the concept of exponential decay, and the value of the target increases closer to the last channel. The term came to Google Analytics from nuclear physics and gives a comprehensive idea of the essence of the time decay model: the closer to the conversion is the point of interaction, the more valuable it is considered. The remaining points lose value as the time interval increases.
In this model, the default half-life is seven days. This means that an interaction that occurred seven days before a conversion is half as valuable as an interaction registered on the same day with it, and two weeks before it is four times less valuable. Exponential decay occurs over the entire period retrospective analysis(default is 30 days).
In our example, the channel closest to conversion is direct entry. He gets the most value, then organic search and the smallest %, taking into account the prescription of interactions, has contextual advertising.
Attribution Model - Temporal Fall
The model is applicable to the analysis of purchases resulting from promotions in order to assign more value to interactions on promotion days. And those that were completed a week earlier will be priced much lower.
However, some marketers use it in their work more often than the classic "On the last indirect click" because it is applicable in almost all subjects. You can argue for a long time about the value of some clicks over others. But everything is quite logical here - the further a particular channel is from the moment of conversion, the less value it should receive. After all, if previous visits to the site were no less effective, then why didn’t they lead to a conversion?
One of the advantages of the Decay Time model is the ability to specify the length of the half-life and compare it with other basic models.
Possibility to set the half-life
Position Based
Based on the position, 40% of the value is assigned to the first and last interactions, and the remaining 20% is equally distributed among the rest. Attribution Model "Based on position" is a hybrid of models "First Interaction" and "Last interaction".
Attribution Model - Position Based
This model is the closest to real life and it is recommended to use it when you need to track all points of interaction: from acquaintance and first interest in your brand, to the last interaction that led to a conversion.
All models listed are standard Google Analytics models. However, users have the option to create their own attribution models. You can do this by setting "Attribution Models", which resides at the presentation level in custom tools and objects.
Presentation Attribution Models
In the initial stages of working with Google Analytics, I recommend that you thoroughly understand the 7 main attribution models and reports on multi-channel funnels (we will consider in a separate chapter), and only then proceed to create your own.
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