Do you recommend we invest in additional lead generation or shift our marketing mix towards brand awareness spend?  In just the last week, I heard or participated in this discussion at least 5-6 times within my team as we put together our marketing plans and budgets for 2015.  Although our operationally-focused company has a conceptual belief in building name recognition, our willingness to do things that build awareness, particularly things that cost money, is limited.  One of our company strengths is that we invest in marketing (and other programs) and focus on measuring their success with a laser-like focus.  The good…It brings an attention to execution excellence that is outstanding.  The downside, it often brings a lack of focus on long-term choices which cannot be simply measured.  The implication of this is those long-term choices often get put on the back burner in our plan recommendations.

It takes me back to my days as a P&G junior marketer, and the introduction of marketing mix modeling (MMM).  I don’t know when this process first took hold at P&G, but my first exposure to them was in 2003 when we were trying to effectively plan our multimillion dollar marketing budget and identify the right balance between advertising and trade spend.  At the time, retailer influence was growing dramatically, and the only way to afford the trade spend and price promotions being requested was to cut our television and print spend.  Was this the right plan?  If you looked at the traditional media metrics of reach, frequency, GRPs and TRPs there was no way to spread our message more efficiently than with these marketing choices.  As brand managers had a fundamental belief that investing in this media helped drive the effectiveness of our customer promotions (price promotions, coupons, displays at retail, etc.).  Our sales partners, and our retail buyers didn’t necessarily share this belief.  The beginning of MMM was an attempt to not only guide our decisions, but reinforce to these other important constituents how all of these pieces worked together to drive revenue.

As with anything, the results of this effort were only as good as the information and effort that was put into the tool, as well as how effectively we interpreted the outputs.  I don’t know if we ever reached the goal of driving cross-functional alignment to our marketing choices, but we did learn a lot.  At the core, we learned that all of our marketing choices helped make the others more effective….that in a perfect world we would run in all parts of our marketing mix simultaneously as this created the best revenue results.

Since then, the progress in both the modeling and the marketing analytics industries has been substantial, as has the shift to digital media.  About a year ago, the Council for Research Effectiveness published a whitepaper regarding the state of MMM.  Don’t read this one unless you are ready to geek out.  As I think about the conclusions in this analysis, one particular thing comes to mind:  no modeling, no analytics, no measurement of return-on-investment works without applying our human instinct to interpret the analysis.  We are often stuck believing that the “data will tell us something.” My experience is that although true, the data will tell you something, applying experienced-based reason and intuition is the critical step to turning data into something that drives the business.

This brings us back to the fundamental question for our marketing plan next year…should we invest in additional brand awareness spend (media and content) as a part of our marketing mix?  Smaller companies, like CHG Healthcare, don’t have the budgets to invest in sophisticated models such as those P&G put together, yet we still need to to make decisions regarding our budget and marketing plan choices.  So, my recommendation as we work to put together our recommendations for next year is spend time in the modeling, in the data and analytics, but to more importantly apply your reason and intuition and recommend what you believe to be the best plan to grow our business.