A Data Science Central Community
Poor marketing dashboards and enterprise reporting presentations result in indecision. Marketing managers intuitively know when they are dealing with information that is of little value, but is presented as their only solution because of inexperienced practitioners and inflexible enterprise reporting strategies.
Gain incredible insights, lead the charge in a cultural transformation and create the foundation for cross channel campaign optimization in digital and offline efforts with these dashboard strategies, isolating the unique effects of your targeting strategy and offer strategy using readily available information.
It is widely recognized that higher response rates do not guarantee higher ROI, but that does not mean it cannot happen, especially when using techniques that boost response rates and the attractiveness to the offer to the target at the same time, such as nested conjoint optimization .
The metrics presented here represent the unique effects of campaign components by holding other campaign components at a constant. This can be done using the most elementary of statistical methods such as linear regression.
Marketers struggle to understand the underlying dynamics of why one campaign performed better than the other within a channel because of focus on two metrics and how we evolved to process information. Once these strategies are mastered, cross channel optimization is possible. We begin with two common metrics.
ROI is the industry standard for comparing campaign performance, but offers little value for optimization when taken alone. So the only information here with these metrics is that (Campaign A>Campaign B>Campaign C).
Here is an example of the perceptual challenge from these metrics even if ROI is the same across campaigns. [Chart 1]:
So the strategy here in the first installment is to provide indications of drivers of campaign performance using ROI, Response Rate, and the Presentation Quality.
Here we will introduce two new metrics to standardize relationships between campaigns so that the brain is processing information on one critical, and meaning full trend. Perceptual issues aside, these metrics will standardize campaign comparisons and building on these, we can optimize investments across campaign channels and targets in later installments.
The first metric introduced here is Target Efficiency. This single metric uses the same information in the previous chart but the perceptual and practical implications are profound. Here we hold ROI and Presentation Quality at a constant. [Chart 2].
So, all things being equal, targeting optimization does boost ROI by reducing cost, but once we remove unique impacts of cost reduction and efforts to increase the appeal of the offer and presentation, increased response rates are inefficient spend.
The second metric introduced here is Presentation Efficiency. Here we hold target efficiency at a constant. This isolates the unique impact of the offer and how it was communicated. This can be nested in A/B testing of offer and presentation trials. [Chart 3].
So here, we have maximized cost reduction strategies, and the remaining component is to increase the Presentation Efficiency.
From these simple metrics, we can conclude that once ROI is optimized through rigorous predictive analytics and targeting efficiencies, the other component to optimize is Presentation Efficiency. No doubt that there will be diminishing returns as the line moves on to the right with spend on efforts to gain compelling presentations. But the trend between incremental response rate and ROI is linear when using certain ROI techniques that are driven from incremental response rates, it is not linear when using ROI techniques that are driven from direct A/B comparisons not driven by comparing growth rates, but each technique has its pros and cons.
From our perspective, the main difference in ROI approach is dealing with assumptions of the underlying distributions of marketing margin from the targets. This tends to vary from industry to industry, so there is no global assertion as to which ROI method is better.
If an analyst is asked to optimize ROI, she will have to explode the ratio into its primary subjective components, which we will cover later when we engage of methods of constraint based optimization to optimize campaigns across channels.
None the less, this will require a partnership between Marketing and Finance, since financial analysts are better versed in certain optimization techniques than Marketers, and Marketers are better versed in certain optimization techniques than Finance specialists.
We always stress the critical nature of partnerships and cooperation within organizations to promote the general welfare of both the shareholders and those they employ.
Unfortunately, many firms have not even approached the capacity to utilize these metrics, so this is a great opportunity for culture change. Again, please see the online article on how to optimize both of these new metrics at once .