Discussion: Is Return on Influence the new ROI?
Ouch: “The more I think about this—the more my brain hurts.” Ohmy: “Respectfully, this is complete nonsense.” Jeez: “This goes into my “Are you Kidding me with this crap” Hall of Fame!” This is Hurting: “The only thing more worrying than the content of this article is the fact that people are going to think thatbecauseit’s published on the HBR blog it must be true.” These are only the first few comments on this blog by HBR: “Return on Influence, the New ROI”. Oliver Blanchard is leading the pack of people who are thinking the blogpost made no sense at all. You don’t see this that often, at HBR. The discussion is worth checking out.
So what is al this criticism about (oh, sorry, I just love it when the first comment on a blog just KILLS the blogpost, it’s a tic)? The main point of Amy Jo Martin was that numbers help justify decisions, remove some risk, and limit accountability. And that there’s a distinction to be made (in the measuring of social media influence) between:
- “cold metrics”—reach, frequency, page views, impressions, eyeballs captured.
- “warm metrics”—engagement levels, viral factors, sentiment analysis.
“…I realized that social media provided a way to measure something fan affinity in a way a TV spot never could. Why? Social media communication is two-way. It’s a dialogue versus a monologue. Instead of promotions, it creates conversations, sometimes unprompted conversations that can be listened to, recorded, and measured. No longer did we have to say, “Trust us, our fans really like the team.” Suddenly I had data to show how fans really liked us…. Once you recognize that each entry into the social conversation is creating influence, you track it. A tweet is a transaction. So is a retweet. So is a purchase that results from a retweet. Unlike outdoor and TV advertising, say, marketers can track online behavior from a social channel from the initial marketing message all the way through to purchase.”
According to Oliver Blanchard, Martin is wrong in almost every point she tries to make. If you are in the business of calculating something, metrics are metrics, Blanchard notes. Math is math. Stick to empirical data. And, writes Blanchard: “…what you just did there is attempt to measure the average value of a fan (incorrectly at that). Where was the investment/cost figure in that equation? You only talked about revenue generation.” And he adds this:
“As for “influence” metrics, or even the concept of influence as a measurable phenomenon (cause and effect and/or correlation), when someone comes up with a legitimate unit of measure for it, then we can start talking about a Return on Influence equation. Until then, it’s simply not a plausible discussion.”
What do you think of the discussion and the concept of Return on Influence? Do you think this is the measuring-way-to-go or do yoy think the remarks of Oliver Blanchard and the rest stand ground? Very curious!