Marketing Measurement: Definitive vs Directional Metrics

Multi-touch attribution tools are all the rage in marketing these days. Tools like HockeyStack and Dreamdata seem to be everywhere across client conversations, LinkedIn posts, and community feedback threads.

However, a word of caution when using these tools: don’t sum up your leads or customer data across channels.

For example, let’s say your linear attribution model for last month is providing the below breakdown of leads by channel:

• Paid Search - 50

• LinkedIn Ads - 20

• LinkedIn Organic - 30

• Organic Search - 65

• Email - 25

• Webinar - 15

• Total - 205

At first glance, you might think that it’s fantastic how you can see the weighted impact of each channel!

When looking deeper, you might discover that the business only actually generated 150 leads in total. If you send a report to finance and leadership about how effective marketing was, they’ll have some immediate questions. There’s often overlap in how MTAs tool count and report on metrics across touchpoints.

This is why I find it to be helpful to break down performance metrics in definitive and directional categories.

Definitive data like lead volume, pipeline, customers and revenue should come directly from your CRM (based on my experience). This data will most accurately reflect what the finance team is seeing, and it’s often how the business will set goals and measure progress against them.

On the other hand, directional data can actually be the same set of metrics, but come from another source. This is where MTA tools or lift tests can be useful. Similar to what I called out above, these measurement models can be great for evaluating the directional impact of individual channels (or even campaigns).

The reason why this data is directional is that it’s borderline impossible to understand the exact contribution from every single marketing touchpoint, and how that boils down into an ROI model. There are too many untrackable human variables involved to accomplish this.

The big value in directional channel level measurement is that it can help you answer questions like:

• Where should we spend our next dollar?

• Where should we pull back, or reallocate budget from?

By comparing the directional impact of each channel, a marketing team can adjust their media mix and how they allocate resources. If done correctly, the definitive data in the CRM should show a positive improvement.

Marketing measurement can be tough, so aligning on an approach across stakeholders can still be important here.

Have questions, considerations, or critiques? I’d love to hear them, just comment on this post!

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