Advertisers want to know which advertising investments will have the greatest impact. In her blog post, Alena Selimović, an analyst at iPROM, debunks the myths and truths surrounding attribution models used in marketing. It is not always easy to identify the advertising channels where spending advertising budgets makes sense. When making marketing decisions, many rely solely on data found in Google Analytics. But to truly understand the sources of traffic to your website and sales, you should not rely solely on the ubiquitous Google solution.

Expert Debunks Myths and Truths about Attribution Models in Marketing: Why Relying Solely on Google Analytics Can Be Misleading and How Advanced Attribution Models Can Give a More Accurate Understanding of the Impact of Display Ads - iPROM Expert opinions - Alena Selimović

Advertisers want to know which advertising investments will have the greatest impact. Each consumer’s life cycle consists of several stages that the consumer goes through before buying or re-buying a product or service. Some advertising investments do not produce immediate results or direct conversions. It is important to consider the complexity of the purchasing process and the broader context in which the user researches and makes decisions about a product.

Given the variety of available options, advertisers want to know which investments will contribute more and which strategies they will use to attract the right customers. They can achieve this using attribution models that determine the contribution of individual advertising channels to the final conversion.

Why Relying Solely on Google Analytics Can Be Misleading

The last-click attribution model is used by Google Analytics in both its basic analytical reports and the “multi-channel funnels” reports. The main shortcoming of the free version of this analytical service is that it only focuses on ad clicks and not on ad impressions, which does not give the full picture of the role that advertising plays. Even the paid version of Google Analytics 360 only takes into account the views of Google’s display and video formats and not of other display formats that do not come from the Google network. So, how should you determine the impact of display ads?

Since Google dominates organic and paid search advertising, it mainly handles the aforementioned channels, which are typically used primarily in the final stages of the purchasing process. Because Google assumes that each interaction with the user is reflected in a click, it ignores other user interactions or omits them from its reports.

For example, a user may see a display ad multiple times and learn about the brand, product or service while the ad message stays with them in their subconscious. Later, when deciding to purchase the advertised product or service, they research it online and click on the organic result or a paid search ad. When the sale is made, the entire contribution to the conversion is attributed to the click on the organic hit or search ad, while the display ad receives no credit for the conversion. Obviously, such attribution is misleading, since the display ad first put the user into contact with the product or service and enabled the conversion at a later stage. This means that companies do not have a clear picture of the contribution of different channels, which would allow them to make and justify the most appropriate advertising decisions and investments.

Advanced Attribution Models: Essential for Understanding the Impact of Display Ads and Making Informed Advertising Decisions.

Advanced attribution models, such as multi-touch attribution (MTA) or data-driven attribution (DDA), are required to determine the impact of display ads accurately. These models take into account all interactions between the user and the brand and its advertising, regardless of whether it is a display ad, a search ad, or an organic search result. They paint a more accurate and comprehensive picture of the customer journey and the contributions of individual advertising channels to the final conversion.

To fully understand the impact of display ads, it is important to use advanced attribution models and not rely solely on Google Analytics. These models will give you a more accurate and complete picture of the customer journey and the contributions of individual advertising channels to the final conversion, allowing you to make more informed decisions and effective investments in advertising. Additionally, you can use a private data management platform (iPROM Private DMP) and iPROM Programmatic Platform to create a unified advertising ecosystem that allows you to gather data from all your advertising channels, including those outside of Google’s network. This provides you with a more complete picture of your advertising efforts and gives you a competitive advantage in the market.

Experts Warn of Inaccurate Attribution in Google and Facebook Ad Reports: Lack of Transparency and Weighting of Data May Misrepresent Ad Performance

Experts warn that Google’s attribution reports will give an even greater impression that Google ads played a more important role in user activities than they actually did, as Google gives less weight to advertising outside of its ecosystem. To some extent, this is understandable since Google has more data available for its advertising channels (especially when the Google Analytics and Google Ads accounts are linked together). However, the importance and analysis of other advertising channels and formats are lost at the same time. A similar problem arises when using the Facebook attribution model, which by default assigns all credit for the conversion to its ads if the conversion occurred within seven days of clicking on the Facebook ad or within one day of displaying it. Because each platform wants to assign as much credit for final conversions as possible to its own ads, there is a discrepancy between data in the Google Analytics and Facebook Business Manager services.

The topic of which attribution we trust and make business decisions based on becomes even more important with new machine learning algorithms and data-based attribution models. To model data, data-based attribution models use smart algorithms that are more opaque, making it harder to understand and interpret the attribution of conversions across different channels.

Where does the traffic really come from?

This is where attribution theory and sound methodology come into play. If we want to accurately attribute conversions to different advertising channels, we must consider the characteristics of each channel as well as the different ways in which users interact with ads.

In any business, you need to identify new customers, lead them to conversion and then increase their lifetime value. Consumers may actively engage with a company or brand at any of these stages, but not necessarily by clicking an ad. Subconscious actions are just as important as conscious behavior and will influence conscious decision-making in the final purchasing stages. Therefore, the best attribution model must account for different user activities, such as ad views, time spent watching ads, and the inclusion of any non-digital channels and activities, not just clicks on ads.

Whatever attribution method your business uses, it is important not to rely on a single source and not to rely on it alone when deciding which activities to focus on.


About author

Alena Selimović is an analyst and search marketing specialist who sharpened her skills at various digital agencies. She has been working with digital technologies for more than 5 years and over the past several years, she has been involved in analytics and advertising solution projects as part of the iPROM digital agency.
She successfully integrates her analytical attitude into the development of advanced analytical solutions and implementations, data analysis and the preparation and management of advertising campaigns. The constant desire to learn and grow drives her to search for new, out-of-the-box analytical solutions for the open web.