The Attribution Analysis section is the place in Roivenue which gives users the ability to compare available attribution models and modify the main model of attribution which will be used to recalculate data in the Performance Monitor.
To define the displayed graphic, you can use the following functionalities:
- Metric : select metric which will be recalculated for each model. Please note that unpaid channels will not be displayed for ROMI, MIR, mROMI, mMIR.
- Attribution models : check the models you would like to display, up to six models can be selected.
There are three tabs for making comparisons between the selected models. These are:
1. Attributable [metric] - displays selected metric by channel for selected models on a horizontal column graph. This can be seen on the picture below. Each of the models have corresponding color and the displayed models are selected from attribution models dropdown menu.
3. Explore the numbers - compares values for each channel in a matrix. Each column is assigned to an attribution model and cells in this column are conditionally formatted based on their value compared against last touch - less than last touch is red, more is green.
*Sorting can be applied via dropdown menu on the top right corner of the screen. All results can be filtered by channel and date on the right hand side of the screen.
The final step of this analysis is the selection of an attribution model. Roivenue offers three data driven attribution models: Shapley Value, Markov 1st and Markov 2nd order. The question is which model suits your situation better, as each has a different logic and thus different strengths.
The Shapley value evolved from attempts to optimize formation selection by ice hockey coaches. The calculation simply compares paths which resulted in conversions with the paths which did not, for each channel. The higher Shapley value is, the higher the ratio of successful participation to unsuccessful. Therefore, this model tells us whether the contribution of a single channel to the whole marketing mix is positive or negative, but it does not take into account a place on which the channel stood in the conversion path. For this reason, it is usually used as a supporting model to Markov chain models.
Markov models are probability models, which are based on calculation of likelihood of each possible transition from a touchpoint. This is calculated for for every channel. Markov models can be calculated on several orders, with each order signifying how many jumps over touchpoints are taken into account. In Roivenue, we work with order 1st and 2nd. As their mechanics are very similar, we can explain them on Markov 1st as it is a bit easier to comprehend.
The diagram below proposes an example schema of Markov 1st order. It provides a scenario of channel A and its evaluation according to this model. There are several options for advancement from the current state to the next state. This advancement means the next action the customer will take. B, C, D, and E represent other marketing channels, the checkmark represents a conversion and the X represents no action. Each of these steps have a certain probability, so for example the probability that a customer will touch channel C after touching channel A is 20%.
The higher is the order of the calculation, the more transitions are taken into account. For example, Markov 3rd order takes into account three transitions, so one group of transitions would be Channel A - Channel B - Channel C - Conversion. Higher orders decrease probability for each transition and therefore decreases statistical strength of the calculation. That is why we work with Markov order chains up to 2nd order in Roivenue attribution modelling.
So, for the big question - which model is the best for you?
Attribution coefficients are recalculated on a weekly basis. So at the beginning of each week, Roivenue collects all conversion paths from the last complete week, calculates models and sets conversion coefficients. These will be updated each week. You only need to select your model once, Roivenue will use it for the selected business unit until further changes are applied. Please note that the selected model changes conversion distribution for the whole account, so your selection will impact data displayed to all users who have access to this account. Therefore, it is better to properly manage your user rights - limit administrator and operator access only to core members of your team.