Correlation and Causality. Words not often used by the communications industry. Initially because we didn’t need to. Now because we generally don’t want to.
It’s no secret that the communications industry continues to come under increasing pressure to demonstrate that communications efforts are contributing to the organization’s bottom line. This is where practitioners generally roll out a number of counter arguments not to measure.
- The first is that measuring public relations is a bit like catching water with a fork or counting a bucket of eels. I prefer to think of it as challenging but not impossible.
- Counter argument number two, among public practitioners, is that we can’t prove it was exclusively public relations that did what we want so there’s not point in trying. That argument only worked for so long among the consumer packaged goods companies that have figured this out — cracking the causality nut — with something called market mix modeling.
With a few exceptions, measurement in/for/of public relations is really simply about adopting mass communications, sociological, and/or market research methods for our unique needs. The marketing and advertising side of the industry has been doing this for coming up on 100 years.
Consumer packaged goods companies have, for decades, been tracking every sort of communication (I mean this broadly here: advertising, point of purchase, coupons, direct, etc., etc., etc.), and public relations, for a very tense while, was the only holdout. Well, they started to track public relations inputs and outputs as part of their market mix models, and two remarkable things happened:
- They were able to statistically isolate for and ‘prove’ public relations’ unique contribution to the marketing mix, and (more importantly).
- Were able to quantifiably validate a couple of age-old assumptions: Public relations works and it often significantly outperforms other channels.
- Counter argument number three looks a little like this: “OK, so it can be done, but it must cost a fortune.” No argument there. It’s not cheap. But what’s curious is that if we can’t afford Market Mix Modeling (causality), then are we at least demonstrating a correlation (between, for example, quality and quantity of media coverage and public awareness)? Very rarely.
Correlation, NOT causality. PRoxy, NOT PRoof.
With correlation, we’re saying that there is some statistically valid relationship between, say, coverage and awareness. (To be clear, though, we’re not indicating that one was exclusively driving the other.) How do we do it? Well, where market mix modeling involves sophisticated regression analysis and statistical modeling, correlation is a fairly simple — and single — statistical calculation. It’s called Pearson’s Public PRoduct Moment. Wikipedia will have much to say about it, I’m sure.
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Alan Chumley, senior consultant, CARMA International Inc., Global Media Analysts, has twelve years’ experience in the corporate communication / measurement industry, including senior-level, in-house corporate communications roles for leading blue chip organizations such as Bell Canada, as the director of Measurement for Hill & Knowlton, and vice president at Cormex Media Content Analysis. An advocate of driving science into the art of communications, Alan has extensive experience not only in corporate communications strategy and execution but also in the use of research and measurement to inform and influence traditional and social media content analysis. He specializes in interviews, focus groups, surveys, stakeholder relationship measurement, communication and perception audits, reputation research, employee engagement research, traditional and social media content analysis and correlating this data with tangible organization outcomes. Connect with Adam on LinkedIn and on Twitter.
Join Alan along with other members of the PRSA National Capital Chapter (PRSA-NCC)at the PRSA 2010 International Conference: Powering PRogress, October 16–19, in Washington, D.C.!