Attribution IQ and the new attribution models in Adobe Analytics

Adobe Analytics incorporates a new module that hopes to help you better understand the behaviour of your customers by expanding the number of attribution models available.

Attribution IQ eliminates the existing dependence on the first-touch and last-touch models to allow you to quantify the value of your Marketing actions more precisely and thus improve your ROI (Return on Investment). So, the Adobe Analytics Analysis Workspace has 10 advanced rule-based models, do you know what they are? What is this change? Keep reading to discover all the details.

Attribution IQ

Why Adobe Analytics incorporates new models?

The complexity of the digital environment, with multiple points of contact, complicates the attribution of any conversion. Before buying a jacket, the customer may have been impacted by a publication sponsored on Instagram, have conducted a Google search and opened an email with a discount coupon. To which channel will you assign the credit? There is no correct answer but you do need to consider the implications of each available model to optimise your investment.

Previously, Adobe only applied first-touch or last-touch in the analysis of the value of the different channels, that is, you lost an important part of the customer journey since it did not take into account any other point. With this new module, you will have more flexibility to get unlock insights and answer more specific business questions.

Attribution IQ: What does it offer in the Analysis Workspace?

Attribution IQ has 10 models that can be used with any dimension, metric or event (including Props and eVars), in real time or retroactively. In addition, the solution makes it easy for you to compare as many models as you want, without limits, to allow you to adjust them according to your needs. In this way, you will be able to see the impact of each one of them and the variations caused in your results.

Attribution models are based on a set of rules that describe how to distribute conversions between different hits in a group. And from the retrospective window (lookback window) it is established which sets of hits will be considered to apply each model. This window can be configured as a visitor depending on your needs. It is recommended, for example, as a visitor for long cycles, although, in reality, both options can be customised.

Briefly, here are the 10 models that are now available in Attribution IQ:

  • First touch: 100% of the conversion is assigned to the first interaction. It can be very useful, for example, to assess the impact of awareness campaigns.
  • Last touch: The credit is fully attributed to the last point of contact before the conversion.
  • Linear: The same percentage of the conversion is recognised at all the contact points participating in the process.
  • Time Decay: A percentage of the decreasing conversion is attributed from the last contact point before the conversion to the first.
  • Same Touch: 100% of the credit is assigned to the hit where the conversion occurred.
  • U-Shaped: Merit is distributed as follows: 40% to the first interaction, 40% to the last interaction and 20% divided between any intermediate contact point. If there are only 2 points, 50% and 50% are assigned.
  • J-Shaped: 60% of the conversion is attributed to the last interaction, 20% to the first interaction and the remaining 20% ​​to any intermediate touchpoint. If there are only 2 points of contact, 75% is distributed to the last and 25% to the first.
  • Inverse J: 60% of the credit is allocated to the first interaction, 20% to the last one and, finally, the remaining 20% ​​is divided between any intermediate interaction. As you can see, it works the opposite of the previous model.
  • Participation: 100% of the conversion is recognised at all participating contact points. You must bear in mind that, with this model, the total number of conversions will increase compared to the rest.
  • Custom: Allows you to specify the value you want to assign to each interaction (3 percentages for the first touchpoint, the last and the rest).

In addition, Attribution IQ, as part of the Analysis Workspace , can also benefit from Adobe Sensei-based functionalities that allow you to identify statistical anomalies in your data, contribution factors or differences in segments. If you configure the alerts properly, you will receive a notification when any relevant change occurs.

How to use the new attribution models?

Perhaps one of the most comfortable ways to work with these new models is through the data tables (freeform tables). After adding your Marketing channels and the chosen metric, you will see that you can modify the type of attribution at the column level through the option “Use non-default attribution model”. Next, a window will open with the available models and the two lookback window options.

From this table, you can compare an attribution model with another by dragging the metric to one side to create a new column and then editing it to enter the new model.

In addition, you can use segments to work only with data from new clients or apply breakdowns in order to deepen into a specific Marketing channel. Yes, in this breakdown with the tracking codes for campaigns, you would like to modify the model that is being applied to the display, for example, you could do it without affecting the other channels. Breakdowns are designed to analyse specific aspects in detail.

Attribution IQ also incorporates a new panel with pre-built visualisations that will help you perform faster analysis. You only need to add your marketing channels, the selected metric, the model you want to apply and the lookback window. From here, a set of graphics will be created where different aspects will be compared. For example, you can use the Venn diagram to see how often one channel collaborates with another. This panel will help you explore different routes to conversion and detect trends.

Finally, attribution models are also available in the Calculated Metric Builder, the tool that allows you to generate calculated metrics. When you include your metric, you will see that this option appears in the configuration menu. In this way, you can create metrics that use one or several combined models (hybrids).

If you are interested in this solution, Adobe has created different tutorials on its YouTube channel:

In this regard, we must remember that Google is also working on the launch of a specific attribution product, Attribution 360, which is in the testing phase. We will probably know more details in the coming months.

Have you already tried Attribution IQ? What do you think about this new module in the Analysis Workspace?