For every PPC account and display ad campaign, we create a conversion value model for each type of conversion event and (related), select a method for click attribution modeling. When a conversion occurs, the value for that conversion is distributed (“attributed”) up through the sales funnel, with weighting as defined by the click attribution model.
In our conversion value model, what we are after is the gross margin (value) that each conversion action is producing. In the case of a display campaign that advertises products, the conversion value would likely be (sales price-sales tax)*(average gross margin).
For a display campaign advertising a services business (a lead generation campaign), we use a finite planning window, e.g. 1 year. We then calculate the average value of a converted customer over the planning window (e.g. 1 year). The formula Conversion Value = (average value of a converted customer) * (avg. close rate of leads).
Conversion value modeling is important because it allows for calculating the two most important metrics in paid search: return on ad spend, and advertising margin. But more importantly, it provides valuable information back to the automated bidding algorithms, which use machine learning to maximize the performance of the campaign.
For click attribution modeling, we look at the length of the sales conversion process for your market. If there is campaign history in Google Analytics or in the PPC account, we mine that data to fit a click attribution model to the display campaign.
There are articles on this site about the somewhat complex topic of click attribution, a crucial method for driving strong campaign performance, especially for campaigns running with bid automation.