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Marketing Mix Modeling (MMM) Follow-up January 12, 2007

Posted by metricsman in Return on Investment) ROI.
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Last June I wrote on P&G’s work with Delahaye in marketing mix modeling (Original Post).  There have been a lot of interesting comments (see comments), and I wanted to take a moment to answer a few questions posed by ph hanky in his/her January 10 comment.  Here is the comment:

ph hanky - January 10, 2007[Edit]

who does P&G’s MMM work anyway? Delahaye isn’t a modeling agency.

The problem with companies like P&G and Delahaye making sweeping statements like this is that there is no one to audit or verify the findings. Anytime you have someone doing a regression analysis like MMM, you have to question if the regression analysis was done with the right vigor and make sure enough factors were factored in the analysis.

P&G has been making lots and lots of money and AG Laffley has been talking about their MMM and how they are cutting back on TV in favor of other vehicles. I don’t doubt P&G pulls off some world-class MMM, but I don’t know if they promote stuff like this to put the screws on their ad agencies and TV advertising rates.

If they spent half of what they spend on TV on PR, then they would saturate the airwaves, the web, and print with PR. They don’t address diminishing returns on PR. I would assume you reach saturation point with PR long before you reach saturation on Tide commercials.

First, the easy question.  The company that worked with Delahaye to develop the model is a firm called Communications Consulting Worldwide (www.ccworldwide.com). 

Regarding the audit or verification of findings, my personal view is this is not the right way to think about modeling.  A properly built model should yield a highly correlated approximation of the relationship between public relations results and downstream outcomes, usually sales.  There are certainly some issues that the modeling company may find uncomfortable - co-dependence of variables and reverse correlation to name two.  So while there may be a little leap-of-faith with the model, the rigor is generally much greater than is normally applied with simple media content analysis - and the leap of faith to ROI is much shorter. 

The other issue ph hanky raises is diminishing returns on high levels of PR investment.  In my experience we should be so lucky.  I have never seen a completed model that demonstrated PR investments were on the diminishing returns side of the curve.  On the contrary, every model that I have seen suggests PR investments are well below diminishing returns.  If a company is spending $60 million in advertising and say $1 million in PR (actual numbers from a former client), then the issue of diminishing returns on PR is not applicable.  Moving just $1 million from advertising to PR would show nice leverage in ROI.  I would love to be in a situation where I had to go to a client and recommend we reduce PR spend because we have reached diminishing returns, although I not holding my breath on this one. 

Thanks for reading, DB

Comments»

1. Peter Verrengia - April 6, 2007

Just seeing the reply to the hanky post now, but I’d like to offer a correction. Communications Consulting Worldwide did not create the markeing mix model for P&G. P&G did it in house, working on four brands, and I think Delahaye provided data for at least one of those brands. If you want to see an example of what CCW does do, check out the Feb 12 PR Week case history on how Southwest Airlines measures the business impact of communications. And as for the modleing techniques, it is not entirely clear to us what P&G did in its marketing mix model, but in the work we do at CCW we use causal modeling and we find it is very possible to demonstrate the impact of communications activities on sales, earnings, stock price, or any other business outcome without the problems you describe. Peter Verrengia

2. Don Bartholomew - April 6, 2007

Hi Peter,

Thanks for your comment. This issue was already corrected with this post (http://metricsman.wordpress.com/2007/01/17/damn-got-the-easy-one-wrong/).

Thanks very much for reading. -Don B

3. ahndunk - February 16, 2008

Good post, All information here are newsworthy.