Google Ads is one of the most powerful tools for a marketer, and almost the only one that harmoniously combines advertising and analytical skills. Among the hundreds of Google analytics capabilities, one of the most compelling is attribution modeling. The tool allows you to objectively assess the value of a particular conversion, which means the effectiveness of individual ads and the return on investment in advertising.
Attribution modeling: simple on complex
The term “attribution” can be replaced by more understandable “attribution”, “authentication”. By choosing one of the attribution models in Google Ads, we indicate to which user steps we give value on the way to completing the targeted action.
For example, you sell equipment for a professional kitchen, and according to your ad, the chef of a local restaurant went to the site in search of your ad and immediately bought a brand new mixer. In this case, Yandex.Metrica can attribute 100% of the conversion value to the last click, the first or the last significant one (in this case, the visit in which the purchase was made may have less value than the previous click from the search). Most likely, the chef had to go through a difficult path from the idea of a new mixer to its purchase. Analyzing this path can help the seller improve their interactions with downstream buyers.
Conversion value metrics in Google Ads will differ from Yandex.Metrica, since the system takes into account many factors prior to the purchase.
And before the decisive click, there could be several visits to the site from organic and advertising results, viewing product and brand ads, mailing, promotions and other events conducted by your marketers.
Therefore, those wishing to see the real picture can look into the “Settings” on the top panel of Google Ads and select “Attribution in the search network”. Of course, the instructions are valid for campaigns with conversion tracking set up.
Five Attribution Models – Five Analytics Scenarios
Google Ads usually suggests by default last click attribution (Last Click attribution). It happened historically: it is this model that is standard for many analytics tools only because at the time of its implementation it was technically impossible to track the entire user’s path from interest to conversion. From the name it becomes clear that 100% of the value is assigned to the ad or request that was clicked on prior to the target action.
Why is Last Click attribution not the best option?
- If we attribute all the credit to the last click, then we automatically mean that there was nothing before it. That is, the aforementioned chef for the first time thought about buying a mixer, entered a request, followed the ad to the site and sent the product to the cart. In essence, an impulsive action was taken. However, according to a report from Invesp, only 40% of online retailers make impulse purchases. The rest need time to think, compare several offers, carefully study the information about the product. Only then will they return to the store to make the desired purchase. By using Last-click attribution, we are not counting the actions of 60% of netizens.
- Last click for Google Ads and Google Analytics are slightly different concepts. For Google Ads, this is the last ad click, and for Analytics, it can be a transition from organic search. For example, if the chef didn’t make a purchase right away, but returned a day later using a direct link or entered the name of an online store in the search, for Google Analytics the conversion will be attributed to organic traffic, and for Google Ads – to advertising. Therefore, to obtain reliable data, it is better to use a more complex attribution model.
The possibilities of Google are almost endless, and they must be used. Let’s keep up with the times and deal with the rest of the models.
- First click attribution (First Click attribution). By choosing this model, you will give all the value to the ad or request that the user clicked on. Whether it makes sense to give all the value to the first interaction depends on the company. For example, if an advertising campaign has high hopes for social networks and is aimed at brand awareness, then First Click attribution is quite justified, as is Last Click for short-term campaigns launched during promotions and sales.
- Linear (Linear attribution). The logic behind this model is to evenly distribute value among all the sources that participated in the conversion path. There is also a weakness in the application of this model: it does not take into account how each of the sources influenced the decision to buy or the implementation of another target action.
- Attribution based on age of interactions (Time decay attribution). The model, like the previous one, takes into account all points on the path to conversion. However, he assigns them a different value, which increases with approaching the moment of conversion.
- Position-linked attribution (Position-based attribution). In fact, this model is the golden mean between all the previous ones. It takes into account the importance of the first and last click, attributing 40% of the influence to them, and does not deny the intermediate actions of the user, distributing the remaining 20% between them. In Google Analytics, you can distribute these percentages yourself.
- Data-Driven Attribution (Data-driven attribution). The implementation of this model is possible thanks to Google machine learning and a large amount of data in an ad campaign, namely 15,000 clicks on ads in search and 600 conversions per month. Having received enough information about site visitors, Google analyzes which user actions led to the targeted action. This makes it possible to evaluate the importance of clicks in achieving conversion in different ways. Today, this model is the most objective and gives the advertiser a real idea of which queries and ads have the greatest impact on the customer on their journey to purchase.
Attribution and Google Analytics
Google Analytics offers advanced settings to track the value of a buyer’s action.
By choosing a linear attribution model, you can distribute value across different channels, search and media traffic, social media, organic search, individual keywords, and more, all within a time window before the conversion occurs (maximum 90 days).
Attribution data for individual campaigns can be matched against the smart bidding strategies that have been defined in those campaigns. This will allow you to analyze the effectiveness and appropriateness of the use of different strategies.
For example, by choosing the Target Cost Per Conversion strategy, you challenge Google to raise the bid and ad positions for promising clicks and lower it for those that are unlikely to turn into a purchase. At the same time, by including individual requests, ad formats, bounces and other parameters in attribution, you can find out how valuable a particular indicator is. In accordance with this, you can remove some queries and reconfigure the time, place of display, or even switch to a different strategy (for example, “Cost per conversion optimizer”).
Who needs attribution models?
Anyone who thinks that saving on advertising means cutting their budget can leave the default attribution model Last Click.
Selecting and comparing different models will show the significance of each conversion source’s contribution, its contribution to ad performance, and its value to the business.
Attribution can justify the high cost per click and show when the ad will be more beneficial. Suppose two advertisers are willing to buy clicks at a cost calculated as 10% of the expected profit. Including multiple traffic sources in attribution can justify twice the recommended cost per click. Having correctly analyzed the data, the advertiser will know how to invest more and get the maximum profit.
Attribution reports are a platform for rational advertising budget planning.
Is it profitable for Google to create such complex algorithms? Yes. After all, attention to the needs of customers and giving them the opportunity to properly manage money – all this only increases the loyalty of advertisers, and therefore, financial injections into Google Ads.