1.
Toward a Revolution and Reinvention of Marketing ROI Measurement
What is the State of affairs for Marketing ROI Measurement?
About 6 months ago, I wrote an article entitled “The Death of Marketing-Mix Modeling, as we
know it”. In this article, I raised an issue about the present use and success of marketing-mix
modeling, which has traditionally been considered the gold-standard of marketing ROI
measurement. The key focus of this article put into question whether this statement is true
anymore; and even suggested that marketing-mix modeling is broken, because it has not kept
pace with the fast changing and complex marketing landscape.
Since then, and little to my surprise, more than a few advertisers that I have spoken with in
recent months have told me that they have either discontinued their marketing-mix model
projects altogether, have postponed them for the current business year or are seriously
considering one of these two options. This is a little alarming, but not totally unexpected. In
addition, I am hearing considerable criticism of traditional marketing-mix modeling in terms of
the answers it has given for digital marketing ROI measurement. To this end, many advertisers
have now abandoned marketing-mix models for any digital measurement and now rely on
digital attribution models. Traditional marketing-mix models, I am told, simply do not agree or
align with these new digital analytic tools.
I am hoping that, with this article, that I get many responses as to whether the state of affairs,
as I have described, is an accurate assessment. I certainly have no restrictions on who I would
like to respond to this, but I am particularly interested in hearing from users or corporate
advertisers.

2.
Manifesto For Change
My first encounter and thinking about the need for change in marketing-mix modeling came
from an experience I had about a year ago. Back in my early career days at Kraft Foods in the
early nineties, commercial marketing-mix modeling was in its infancy. When I compare the
presentation decks from back then to about a half dozen vendors of the present, I saw little, if
no change in the issues addressed or how the answers were derived. This led me to believe
that there really has been little, if any, important changes in marketing-mix modeling over this
period of time. Yet, our market place has exponentially changed. It has become significantly
more complex. Channels and products have grown significantly. Much more advertising is
being produced and the digital revolution has enveloped the entire discipline of marketing.
Nevertheless, it is not that marketing-mix modeling has been totally stagnant. Indeed, more
advanced methodologies such as Bayesian modeling, Vector Auto-regression and agent-based
modeling have come on the scene. However, these developments have only addressed the
issue of “doing things right”, rather than “doing the right things”. Marketing-mix modeling is
still, for the most part, addressing only short-term sales response and ignoring discussion of
long-term brand equity issues. It is also focused almost exclusively on marketing effectiveness
and efficiencies across channels; and tends to ignore measuring the creative element of
advertising messaging. The issues are many.
The real need, here and the call-to-action, is that marketing-mix modeling needs to be
reinvented. It needs to change in more than just how it is done (doing things right), but rather
what it is measuring and the questions it is answering (doing the right things). Fundamentally,
marketing-mix modeling has lost much of its luster because it simply is not answering the right
questions and issues.
While completely new approaches, like digital attribution models, have crowded into the
marketing measurement space, these have no chance in displacing the “holistic view” of
marketing-mix models, which “can” cover both the digital and traditional media domains. The
marketing world clearly needs holistic and integrated tools, which will address marketing
decisions across both digital and traditional channels. The time for change could not be more
urgent!
Reinventing the Wheel of Marketing-Mix Models and ROI Measurement
The issue with marketing-mix models, I believe, is focused more on short-falls with respect to
“doing the right things”. This is a topic that generally goes beyond discussions and arguments
about methodology and having the right data, all of which are important, but we are much
beyond that. To fully transform the world of marketing ROI measurement, the following are
things that need to be done. This is a manifesto for change.

3.
1. The need for models to measure the “long-term impact” of advertising and
marketing is absolutely critical. This must be measured for every brand. No more
cop-outs with “the Adworks Rule-of-Thumb”. Including a 2X factor by judgment
into the exericise is not only a cop-out, but is dangerously erroneous, especially
when my 20 years of experience tell me that the range of long-term ad effects are
between “Zero and 15X the short-term ad lifts”. The absolute necessity of including
these long-term effects in a model is based on the fact that, in their absence, most
short-term ad effects from today’s marketing-mix models yield negative financial
returns.1 This perspective, therefore, frequently leads to bad investment decisions.
Adding long-term effects thus often change the financial returns of advertising from
a loss to a positive profit. So, if marketing-mix modeling is to survive, it simply must
emerge from the total short-term focus of its past.
2. Models need to break out of their silos and account for the cross-channel
synergistic effects of marketing. From my own recent modeling experience, I have
found a consistent pattern of synergistic marketing effects between traditional
mass-media and digital media. What this means is that the net impact of these two
media forms, when executed together, is usually substantially greater than the sum
of the independent effects of each run separately. This concept of “marketing
synergy” really forms the foundation of what integrated marketing is all about; and
really needs to be a part of the measurement exercise. Unfortunately, the single
equation econometric models still used by many vendors are based on the principle
of the “independence of variables”; and by itself, this greatly inhibits marketing-mix
models from recognizing and measuring these “marketing syenrgies”.
3. Marketing-Mix models need to include “the voice-of-the-customer” inside of each
modeling exercise. There are perhaps other ways of doing this, but I have done this
by transforming “textual brand experience comments” from social media into a
metric, as a part of the modeling solution. By doing this, in the required detail, you
get a picture of the importance of every day customer experiences with your brand,
and their likes and dislikes. Interestingly, this VOC metric, when quantified, tends to
be as large and important as the sum of all advertising and promotion. Putting this
into a model sheds light on the importance of being “customer-centric” and truly
brings the customer’s brand experience to the level of importance that it deserves,
when expressed in dollars-and-cents value.
4. Models also need to go beyond the measurement of channel alone and develop
ways of measuring the advertising message and creative content. The entire
discipline of marketing has always been about communication and developing the
best communication strategy to drive brand performance. I have recently
discovered a way of incorporating advertising copy tests into models that permits

4.
the monetization of ad creative. There are probably other approaches to this that
also work, but marketing-mix modeling needs to be able to measure the
effectiveness of ad message. This is not only important for getting a seat on the
brand strategy table; but also for getting ad agency partners fully engaged in and
supportive of the modeling process.
5. Marketing-Mix Models need to break through the “digital divide” and more
accurately measure digital attribution. This is an area that has generated the most
criticism as of late, in that traditional single-equation marketing-mix models come
up woefully short in accurately attributing the correct “path-to-purchase”
contribution of digital media channels. Just as important, these traditional models
also fail to fully measure the important interactions and synergies across mass
media and digital channels. With new multiple equation approaches to modeling,
however, I have found that these models reveal different and more balanced
attributions than the traditional models. There is hope for a solution here.
6. All marketing models must “come alive” and change their focus from a one or two
times a year exercise, to one which is continuous, always-on and linked directly to
a brand and company’s shipments and financials. This means that modeling output
needs to be translated into a forecasting and simulation tool, which plugs directly
into brand planning and forecasting of the enterprise. This means an “always on
tool” or capability to effectively determine the revenue and financial implications of
all planning and marketing scenarios; and where the official plan is in fact linked
directly to the tool. For marketing-mix models to be totally relevant to the
enterprise, the challenge is that they must always be current and directly linked to
internal operations and business plans.
The task ahead
It is one thing to talk about “data-driven marketing” and it is another thing to live it and
breathe its air. Is marketing-mix modeling, as we know it, on its way out? It appears
that it is headed in that direction. That is not necessarily a bad thing, if it is reinvented
and it addresses “doing the right things”. The fact that a number of “in defense of…….”
articles have popped up lately might suggest that this problem could be broader and
deeper than we think.
Everything here, of course is an opinion. There still might be some out there who think
all is well; but I would argue that marketing-mix modeling has never achieved the
position of being “indispensable” to the business planning of the enterprise. By doing
“the right thing”, I believe it has the potential to reach that lofty status.

5.
The good news here is that, of the six things listed above, the means and methods
currently exist to solving this dilemma. In my opinion, the time for defending the status
quo has passed. Each buyer of marketing-mix modeling needs to have a serious talk with
their vendors to see if they are on the same page regarding the changes that need to
occur. If they align, then put a plan for change in place. If they do not, then it might be
a good idea to look for another vendor. I don’t claim that my answers to the six-points
above are the only ones; but there are real solutions that can be pursued; and now is
the time to pursue them.
mjw@bottomlineanalytics.com
1 See my LinkedIn article “Considering the ROI of Advertising”, 10-6-2016