Marketing is an integral part of any business, whether you are selling a product or providing a service. It’s important to determine whether or not a marketing strategy is effective. If it is, you also need to know the extent of the contribution. This is where attribution modeling comes in. It helps to assign credit to various touch-points, i.e., channels or campaigns. This assignment is supposed to help with budget allocations for marketing mediums among other things. At the end of the day, an attribution model is of value to you if it is actionable.
Without effective attribution, you might end up using the wrong marketing techniques. This ultimately means that you lose out on conversions. While a channel or campaign might be popular, it doesn’t necessarily mean that it’s the best. Your objective as the marketer is to maximize your return of investment (ROI). If you are not doing this then you are not effective. It’s not just about lowering the cost but also maximizing conversions.
For attribution to be effective, your attribution model must be actionable. The question then becomes, “How do you make the model actionable?”
Actionable Attribution Modeling
Simply put, an actionable attribution modeling is one that allows you to interpret the data from attribution. You need to find out how much a certain touch-point contributes to your objective or goal. You also need to ask how much you spend on the particular touch-point. These two factors, contribution and spend – make your model actionable.
For example, how critical is a digital channel in influencing your customer’s journey? How many conversions are yielded from this channel? How much do you spend on this channel in order to get these conversions? The answers would help to determine whether or not to increase the budget on the digital channel and the expected effect on conversions.
Attribution Models and Whether They Are Actionable
The very structure of an attribution model, to a large extent, determines whether or not the model is actionable. For example, fractional attribution models are very basic. They assign a percentage to each channel or campaign in a bid to gauge their contribution in the customer’s journey. This only helps to a certain extent. It will, for example, inform budget allocation and justify any acquisition-based ad campaigns. However, it does not tell you how the specific channel or campaign interacts with others. In this case, you can’t tell the overall effect of the channel on conversions.
To remedy the lack of information on interaction, which is a characteristic of fractional attribution, you can use cohort or multivariate analysis. These two models will allow you to look at the effects of one channel to another, giving you more informed and actionable intel. Another option would be market-mix modeling which is extremely expensive. Unlike cohort or multivariate analysis, it goes a step further and includes variables such as economic conditions and weather patterns.
If you think about simple regression in mathematics, you might find the best way to make attribution models actionable. You can isolate one touch-point by removing it from the customer’s journey. Like simple regression, controlling for a channel or campaign will help to identify its effect on total conversions. It gives you a bigger picture of the customer’s journey. Markov modeling utilizes this concept, making it actionable. You can draw valid conclusions that will do more than just inform your budget allocation.
There are different attribution models that you can use to assign credit to channels or campaigns. While each attribution model informs which channels you can focus on and which ones to avoid, you still need to make decisions using this information. For this to be useful, you need to know which channel or campaign gets the bigger chunk of the budget and how this affects conversions in general after accounting for interaction with other channels. This way, the model is actionable.