Customer journey analysis and individual conversion attribution have already been discussed several times on twoqubes. While the former describes the path of a customer through different channels, from the first contact with a product up until the purchase, the latter is responsible for the allocation of conversions to different marketing channels. The combination of these two methods allows advertisers to better understand marketing results and to optimize the planning of future budget distribution.
In the best-case scenario you can find out how much each channel contributes to the conversion goal. This is especially useful for those marketing channels that are used particularly often by the target audience or which have shown to be particularly likely to achieve conversions. A better distribution of the advertising budget leads to higher sales and revenue, and therefore to a better cost-revenue ratio. This is one important reason why more attention should be paid to this topic.
However, if this evaluation pattern makes more sense than the standard “last-cookie-wins” principle, and whether it works for every advertiser is not clear. It will require an analysis of real customer journey data. A simple method is the cross-channel analysis. It illustrates how often conversions in one channel are influenced by other channels.
For a better understanding here’s an example of cross-channel analysis: For one of QUISMA’s clients we could evaluate data from a total of 2,218 individual customer journeys in one month. The following figure illustrates the individual conversions per channel. In the analysis the overall result is divided into one-channel and cross-channel conversions.
For SEA brand, for instance, the bars mean that in total 1,109 conversions were analyzed. 616 conversions were carried out by customers, who had only contact with the SEA brand channel. For 493 conversions also other channels were involved in the customer journey. This represents 44 percent of all conversions in the SEA brand channel.
From the 2,218 generated conversions a total of 1,314 conversions were achieved without any involvement of other channels. 904 conversions were a result of cross-channel effects. Therefore, almost 41 percent of all conversions show cross-channel effects.
The share of cross-channel effects on all conversions can serve as guidance either for or against an individual conversion attribution. A general rule does not exist here. However, empirical values show that in most cases an individual conversion attribution pays off once the cross-channel effects reach a value of above 5 percent. In the example above an individual conversion attribution would be worthwhile as it allows budgets to be better distributed.