Note: this article is only relevant for Explorer Delta
The Tool’s Objective
Attribution in online marketing is the process which credits conversions to the correct marketing activity (or combination of activities). With the rapid increase in the number of channels and platforms available, it has become essential for marketers to be able to correctly evaluate the contribution of each campaign and each online action to determine which combinations of the marketing mix increases conversions/revenue.
The Attribution analysis provides an in-depth analysis of your marketing activities’ performance over a chosen analysis period according to you chosen attribution models.
Custom-built visualisations and innovative analysis customisation features have been added within this analysis’ work environment to enable you to tailor the analysis to your needs.
The attribution analysis is located in Piano Analytics' side menu:
Touchpoint – interaction between a brand’s marketing advertisement and a customer.
Attribution lookback window - the length of time (in days) used to reconstruct the consumer journey prior to the conversion.
Analysis data prerequisites
Ensure you are collecting the correct data in order to have an accurate and fully functioning attribution analysis. The attribution analysis enables you to attribute credit for sale revenue or any of the goal types you have set up. Make sure you are collecting this information via tags in order to have this data available in the analysis.
The attribution analysis can attribute campaign information. Make sure you are collecting this information properly to have an accurate distribution of your sales credits amongst your various marketing activities.
To attribute the correct credit to the various marketing activities we recreate user-journeys for each of the conversions that took place in the analysis window. To do this, we look back to all the interactions that took place between the user and the brand ( the various touchpoints) and stitch them together thanks to two common identifiers : Visitor ID – cookie based identifier and User ID. The in-house methodology we use to combine cookie data and user IDs when they are present enable us to accurately stitch user paths far back into the past as well as cross-device accurately.
The attribution lookback window parameter you set in the analysis will determine how far back the analysis will look to recreate user paths.
First-touch – In a first click model the first touchpoint obtains 100% of the credit for a conversion.
Last-touch – In a last click model the last touchpoint obtains 100% of the credit for a conversion.
Last non-direct touch – In a last non-direct touch model each conversion is attributed to the last non-direct traffic interaction preceding a conversion. If the consumer journey consists solely of direct traffic interactions, the conversion is attributed to direct traffic.
Linear – In a linear (or uniform) model the credit is shared evenly between the various touchpoints.
U-shaped – In a U-shaped model the credit is shared between all touchpoints in the following way:
- 40% for the first touchpoint
- 40% for the last touchpoint
- 20% shared amongst all other touchpoints
Time Decay – In a time decay model, the credit is shared amongst all the touchpoints with weights increasing linearly the closer in time a touchpoint is to the sale.
Shapley Value – The Shapley value model attributes a conversion according to weightings defined by our Shapley value algorithmic model based on each interaction’s contribution.
1 - Site Scope - For each attribution analysis you will need to specify the site or group of sites you wish to analyse. This site selector benefits from useful features such as an integrated search engine to facilitate access when searching for your analysis perimeter.
2 - Calendar - Within the calendar dropdown you will be able to select the period your wish to analyse. The attribution analysis will look at all sales or primary and secondary conversions that took place within this period and attribute their value to the various marketing activities.
1 - Attribution lookback window – with this selector you can choose how many days before a conversion the analysis will look back to reconstruct the consumer journey.
2 - Touchpoint type – with this selector you can select the level of granularity of your analysis. You can choose to attribute overall traffic sources, or attribute all the way down to marketing campaign level.
3 - Conversion type – with this selector you can choose whether you want to attribute Revenue figures or any goal type of your choice. You will find additional information on how to tag a goal type here.
Note: please bear in mind, for data quality reasons, offsite conversion events are not taken into account in the attribution analysis.
4 - Attribution models – with this selector you can choose one or more attribution models to credit conversions to your different marketing activities.
5 - Run button – the run button updates the attribution results based on the parameters you selected above.
The sequences analysis is the first tab in Attribution. Once configured with your attribution parameters, the sequences tab contains top-line KPIs as well as a line graph summarising your performance over the analysis period. The sequences table highlights the top 20 most frequently used paths over the attribution lookback window for the conversions that took place over the analysis period.
The models tab highlights the credit attributed to your traffic sources or campaigns based on the attribution models you chose in the analysis configuration.
The conversions tab organises conversions by number of touchpoints types present in each sequence.
- A conversion with the following sequence: "direct traffic > search engines" will be classified in the column "2"
- A conversion with the following sequence: "direct traffic > direct traffic">"Search Engines" will be classified in the column "3"
The duration tab organises your conversions by the number of days that went by between the first touchpoint and the conversion.
- A conversion where one day went by between the first interaction and the conversion will be sorted in the column "1".
- A conversion where a user first visited the site on the 1st of December and made a purchase on 3rd of December the conversion will be sorted in the column "2".