So You Think You Know What Index Means?

It seems all too common among agency teams to rely on rules of thumb, and only cursory understandings of metrics, oftentimes to make critical planning decisions. There are planners and finance leads who cannot explain what net/gross means, and why it’s typically 15%. Analysts routinely use weighted calculations -- handed down like oral histories from generations past -- without any interest in understanding what those calculations truly mean, how to use them in a sentence, or how those insights differ from other numbers.

As the media world evolves, it’s tempting for agencies to hide behind “proprietary processes,” programmatic and automation platforms, and other tools that make media planning less and less of a skill or art form. It’s also becoming more common for “research” to be siloed out, relegated to a select handful responsible for passing insights down for eventual action by a completely different team.

Every team, every client, every plan can benefit if we as media professionals maintain a mindset of curiosity and constantly challenge ourselves to drive for more holistic understanding of the media principles we take for granted.

Here’s one small example, born of a client question: you may already know this, you may have never given it any thought, but in the name of greater curiosity and understanding, I’d like to shine light on one small area.

POP QUIZ!  When we say a TV show has a 130 index for a given target, does that mean 

(a) our target is 30% more likely to watch that show, 

OR (b) viewers of that show are 30% more likely to fall within our target?

Trick question— it’s actually both of the above! This seemed counterintuitive to my team at first too, and being unable to find existing explanations, we crafted our own by developing math proofs to explain and validate this phenomenon. (See Fig.1 below.)

Index reflects two data points, mathematically the same number:

(a) vs. 100, percent more likely for this age group to consume product, 

AND (b) percent more likely for consumers to fall in this age bracket 

DATA EXAMPLE: (See Fig.2 below):

  • Vert Index: (% Age Group represents of Consumers) / (% Age Group represents of Total US [base in this case])

    • 12.4% of Consumers are 13-17, but only 7.7% of Total US (13+) are 13-17 = 62% higher likelihood for a Consumer to be 13-17

  • Horz Index: (% Age Group Consuming) / (% Total US Consuming)

    • 4.2% of 13-17 consumed, but only 2.6% of Total US (13+) consumed = 62% higher likelihood for 13-17 to consume

Was this obvious to you? Did you already know the answer? If you’re a mid- to senior-level media professional, do the juniors on your team understand these principles? What mechanisms does your organization have in place to ensure knowledge-sharing and foster curiosity?

As media (and often also strategy) professionals, it’s our obligation—not only to our clients, but to their end consumers, their brands, their business objectives, and indeed our campaigns themselves—to continually push the boundaries and strive for holistic understanding. 

May the spark of curiosity live on in your organization.

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