Nowadays, marketing channels no longer map easily to a single objective. Display continues to evolve on all fronts, covering everything from premium inventory to highly-focused retargeting ads.
With the addition of custom audiences and FBX, Facebook is becoming viable for direct response in addition to awareness and advocacy. Now even paid search, the quintessential direct response channel, is making moves up the funnel.
Fragmentation of digital marketing has been occurring for some time and is talked about extensively. Today, a different type of complexity is emerging in parallel with fragmentation: digital media and platforms are maturing and expanding out of their core offerings, vying to obtain a larger piece of the customer journey pie.
With diversification in funnel position and customer touch points for any given channel, a single key performance indicator (KPI) is increasingly inadequate to capture the complete marketing results. Multiple funnel positions necessitate multiple objectives, which require additional metrics to measure.
The Problem With Having Multiple KPIs
However, this additional complexity causes problems with reporting. For example, let’s say you have two KPIs for your campaign: registrations and conversions. If both KPIs increase, you are doing a fantastic job; if both go down, you are in trouble.
But what if one improves, while the other declines? This happens very often; with two objectives there are inevitably tradeoffs on optimization between one vs. the other. How do you quantify whether the result was a success or failure? This is fine (or even interesting) for analysis, since you can drill down, find the root cause, and uncover insights. But for reporting, the situation is sub-optimal.
I have seen some take advantage of this type of situation by showcasing only those KPIs that improved, while glossing over those that did not. Whenever there are two numbers on the same page that have no strict order of priority, “performance” suddenly becomes a lot more subjective. The greater the number of KPIs on the report, the more prevalent this problem becomes.
To avoid this type of ambiguity, you should ideally have one uber-KPI to rule them all, to give the definitive verdict on whether performance has gone up or down. This creates the need for compound KPIs.
Multiple Objectives & Compound Metrics
So what do compound metrics look like? Let’s look at a few examples:
Facebook Engagement Score = 1 x Likes + 3 x Clicks + 5 x Comments + 10 x Shares
Performance Score = Conversions + New Registrations x 2
The concept is simple enough: take several metrics, weigh them, and add them together. (There exist more complex compound metrics that involve more operations, but I will not cover them here.)
The tricky part is in how to choose those weights. If there was only a single objective, it sometimes possible to use controlled testing, or apply modeling to calculate the relative impact of each metric. But having multiple objectives call for a structured framework for determining the appropriate weighting.
This can be done in five steps:
Five Steps For Defining A Compound KPI
Define the strategic objectives of the marketing campaign/channel
Define a KPI or combination of metrics for each of the objectives
Calculate the baseline volume (e.g., average daily value) of each objective-specific KPI during a historical reference period
Determine the percentage focus on each objective
Weigh and aggregate the objective-specific KPIs to define the uber-KPI:
(It’s not as complicated as it looks, I promise!)
A Simple Example
Let’s look at an example of how these steps can be applied.
Scenario: As a paid search marketer, you’ve always used revenue (tracked) as your primary KPI. However, with recent studies showing branding effects of paid search, your stakeholders become interested in incorporating brand awareness into performance reports.
You need to incorporate brand awareness along with direct response as objectives for your paid search program.
You define the following KPIs to use for the objectives: – Direct Response KPI: Tracked revenue (same as before) – Brand Awareness KPI: Clicks with time on site > 30 seconds (“CTOS30”)
You calculate that during the previous reference period (last quarter), the average daily revenue was $20,000, and the average daily number of CTOS30 was 3,000.
After some internal discussion, your team decides that the objective of the paid search program should be focused 90% on direct response, and 10% on brand awareness.
You weigh the metrics to come up with the following uber-KPI: Performance Index = 0.9 * (Tracked Revenue) / 20,000 + 0.1 * (CTOS30) / 3,000
There it is: your uber-KPI that encompasses both direct response and branding objectives. Though this is a relatively simple example, the same framework can be applied to more complex cases such as social media engagement.
Conclusion & Notes
Compound metrics are chimera-like mashups of numbers that do not represent anything concrete. But if compound KPIs have shortcomings, so does having too many KPIs. The increasing complexity of the digital marketing landscape requires new ways of aggregating data into digestible sizes.
As with any framework, the compound uber-KPI are calculated above is suited for some uses and not for others. When considering adoption, please pay attention to the points below.
What this framework helps with:
Defining a single, unambiguous metric for aggregate performance
Aligning performance measurement and reporting to your marketing objectives
What this framework does NOT help with:
Analytics (compound metrics are for reporting, not analysis!)
Determining the relative economic value of each metric
Defining goals for each objective (objectives should still have independent targets; the uber-KPI just serves as the reference point on overall performance)
Points of note when creating compound KPIs:
A compound KPI is only as good as the sum of its parts. Be sure to choose the correct metrics for each strategic objective, or you may end up with misleading results.
The baseline volume calculated in step 4 will need to be adjusted regularly, when the reference period changes.
When KPIs are ratios e.g. ROI, sum before dividing when calculating the uber-KPI
Do not try to aggregate KPIs with opposing performance direction, e.g., CPA where lower = better, with ROI where higher = better.
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