Corporate Executive
Board
Marketing Leadership Council
Allocating Marketing Communications Resources in
a Chaotic Consumer and Media Landscape
Corporate Executive Board – Marketing Leadership
Council
Doug Hutton:
Good morning everyone. Thanks for taking an hour out of
your mornings, or afternoons, to join us here today, at the
MLC.
We’re certainly excited about today’s teleconference,
although the title of today’s title conference may be a little
bit verbose. I’m excited to have several guests with us, on
the teleconference today, from 2 companies, MTV Networks,
as well as Marketing Evolution. It’s a case study that we’ve
been working closely with both of them on and I’m really
excited to share it with you today.
But before I go any further, let me do a couple of brief
introductions, as to who we have on the call today. As
Regina said, I’m Doug Hutton, I’m an Executive Advisor here
with the Council, but also joining me today we have Todd
Cunningham, the Vice President of Consumer Insights for
MTV Networks; and we also have Damon Burrell, Vice
President of Marketing for MTV, as well. Last, but not least,
we have Rex Briggs, who is the CEO of Marketing Evolution,
a vendor that you’ll hear a little bit about as we go through
the case study as well.
Todd, Damon, and Rex will be contributing to the
conversation as we go, and I hope you take advantage of
the knowledge that they bring to the table today with some
good Q&A as we go forward, but let’s move beyond the
slightly verbose title, if you will, and get into really, the key
challenges that brought us to this case study here today.
And you sort of see those challenges called out in the top
part of this page, “New Challenges Call for New Tools.”
I don’t think anyone on the line today would argue with the
fact that today’s Marcom and media environment is getting
more fragmented, is more splintered, and has more touch
points than ever before; and frankly, for many of our
members here at the Council, that is becoming, in part for
some, an intractable challenge. And you see some of the
trends in consumer media behavior that’s driving those
challenges, on top of the page; splintering media
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consumption, certainly to the rise of multitasking, and
smartphones. It’s getting more and more difficult for us, as
marketers, to understand the media consumption behavior
of consumers.
And number 3, the explosion of data trails. There’s so much
data. It’s not that all this new stuff is not measurable, it’s just
that we may not have the time, in terms of overload, to do
this and actually squeeze insight from the information that
consumers are giving us. And so what we found, and this is
not just unique to MTV Networks, but the problem
statements that you see on the bottom of the page are
cheatedly here for many of our members.
Problem number 1 is that we have more products, more
channels, more geographies, to allocate resources to, but as
a result that process becomes more and more complicated
by the hour. The second major problem is then even if we
determined what products we are going to market, our
media planning doesn’t really work either because
historically, it’s been optimized to the efficiency of each
channel, rather than the overall effectiveness of the
objectives we’re trying to achieve.
And so, why we’re excited to bring today’s case study to you
from MTV Networks and their partnership with Marketing
Evolution, is because of the 2 solutions that they’ve brought
to those challenges that may seem right now, a bit
intractable.
We’ll talk first about the solution on the lower left,
“Assumption Driven Portfolio Allocations,” and you can
essentially jot this down as, “How do we decide what to
market?” And on the right-hand side, we’ll then talk about
the solution of “Objective-Based Media Optimization” which
is essentially, if you want to jot it down, how to market it.
But let’s dive in first to that first solution, “Assumption Driven
Portfolio Allocation” on the left and take a look at the next
page.
What we’re seeing, with our member, is a little bit more
blown out here, as the title would suggest. A research
allocation Rubik’s cube, if you will, and we see there the
proliferation of number of products that any given one of us
is trying to sell, the number of Marcom channels we have
available to us, and the number of geographies that we’re
trying to get into as well.
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Not only that complicating the process; we also probably
have more stakeholders involved in the process than we’ve
ever had before. I’m sure you’ve probably been sitting in a
meeting where you’ve heard one or more of the quotes from
each of the individuals that you see around that Rubik’s
cube. Some folks have a short-term focus, some folks have a
long-term focus, some folks have a budget focus; some folks
want to spend all the money in the world.
Obviously, new products versus existing products; there’s
just so many tensions within this Rubik’s cube, and
ultimately, we come to a point where it’s just unproductive.
You have these folks in a room that are trying to make
research allocation decisions, and it’s just incredibly difficult if
you don’t have the framework to do it.
So, what happens - take a look down at the bottom of the
page. This is what our members tell us all the time, is that
the organization simply settles for the marketing allocation
that they’ve done in the past. At best, they’re allocating it
based on what they did last year; at worst, it’s the gut feeling
as to what’s going to change going forward. Either way, all
of those stakeholders around the Rubik’s cube at the top of
the page, have very low confidence that the outcome that
they’ve achieved during this process is actually optimal.
Certainly, as it gets worse, in terms of the media splintering,
we’re always reminded of the quote as it comes to
advertising. We don’t know which half of our advertising is
effective, and I think that key quote down at the lower lefthand side of your page is indicative of that as well. When
the budget axe falls, maybe your cuts get made arbitrarily
because they don’t have a clear rationale for why we
invested where we did. No one ends up happy.
So, that’s the preface, if you will. Before we get into the
actual case study, I did want to turn it over just for a couple
of minutes to Damon Burrell, at MTV Networks, and Damon,
thanks very much for joining us. Before we dive in, I’d love
to just get your take on that challenge and how that
challenge led you at MTV, to really dive into the process that
we’re going to talk about today.
Damon Burrell:
Sure, I mean to be honest, I think you did an amazing job at
setting it up and really talking about those challenges, but
just provide a little bit more color. Before we started on this
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project, I saw and I think all of my colleagues would agree
that more and more marketing executives were and still are,
being asked to show and prove how they are making
decisions regarding how and where they’re spending their
overall marketing budget. So for me specifically, I was in a
place where I had an infinite number of priorities or shows,
for that matter, to promote, but with a finite amount of
money and budget; and that amount of money was actually
decreasing, in some cases.
In addition to that because of the declining market and also
just the nature of our business – our business measures were
declining. Whether it’s, you know, revenue or earnings per
share, or stock price, etc. [During those times you also start
to receive those requests from the CFO’s of the organization,
and the CEO’s of the organization to really provide,
perspective on what is the return on investment for
everything that you’re doing.]
So, because of that – because of those forces of nature all
coming together at one bit in time, we reached out to
Marketing Evolution to help us develop a set of tools that
could help us decide, out of all of the portfolio of shows that
we had, where was the big upside. If we were to place our
bets and send our money: And then once we figured that
piece out, how do we allocate the amount of money that we
do have in a way that’s going to give ups the biggest upside
against our objective – Objectives being increasing
awareness or increasing intent to view and then the ultimate
goal, increasing ratings overall.
A lot of external factors basically pushed us to start to figure
out internal solutions on how we can be smarter and more
strategic on how we’re making decisions on where we’re
putting our money. And then once we do get that money
to spend, what’s the best way to allocate it, in order to
achieve our objectives. The ultimate objective being tune in.
Doug Hutton:
Sure, fantastic. Thanks Damon. That’s actually a great leadin to the next page that we’ll put up on the screen for you to
talk about the first tool that MTV Networks developed in
partnership with Marketing Evolution. And you heard
Damon just, sort of, overview it a little bit and let me just give
you a little bit more color.
If we think about the Rubik’s cube that we just saw on the
same page, and stakeholders being pulled in different
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directions, and not really having the same decision criteria, if
you will, step 1 in this process is getting folks actually, to
agree on what the decision criteria are when determining
where they’re going to place their bets.
So, again, we’re talking about MTV Networks here. So the
bubbles that you see in the chart each represent a specific
television program against which MTV could place
marketing dollars, and what MTV wanted to do and you see
the “X” and “Y” axis here; is through a substantive
interviewing process with stakeholders, trying to arrive at the
short list of decision factors that will help determine which
shows are going to get the dollars and which won’t.
And take a first look at your “Y” axis - and I know it’s written
horizontally, but the “Y” axis there is “Opportunity Strengths:
How strong is our opportunity for these TV programs?” You
see metrics like “content strength,” “talk-ability,” “ratings
potential.”
Similarly, for those council members who have been around
with us a while, you’ve seen opportunities fit matrixes like
these before, and you see down on the bottom, the decision
factors for fit. Things like “Does it fit with our brand image?”
“Does it fit with the audience we’re going after?” and “IP
Ownership,” and the “Association of Talent”.
We’re in a much better place if we add that size of the
bubble that you see on the right-hand side. Where the
bubble size is, as Damon was just talking about is essentially,
how much upside is there for marking to spend on this
program versus another? And what we mean by that is
essentially, ”what is the potential contribution of that
program to those metrics that Damon was just talking
about?”
How much value would the money that we invest create on
the back-end? And so, this matrix channel will take you to
the actual tool here shortly, which can actually help with
this, but develop a few key takeaways developed by
stakeholder interviews to help capture that list of decision
factors. Those factors are then filtered so that we’re getting
to the right factors for opportunity-fit, strength, and
marketing upside; and ultimately, the stakeholders together
review the framework and then collectively sign-off
individual brand teams on it as they go forward.
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One thing I know - and feel free, Todd, Damon, or Rex, to
hop in here - that I know our members are interested in, as
I’ve been talking to them about this case study, is, “How did
you arrive at the consensus with those key stakeholders
during that interview process?” Obviously, we saw, on the
previous page, they’re often in many different directions.
How are you guys able to get to a very tight list of factors
that folks could agree on? What did that look like in your
organization?
Todd Cunningham:
Well, this is Todd Cunningham. So being the facilitator for
the initiative itself, coming through research is really critical
because it’s exterior are lots of more - and a growing list of
measures and ways of measuring and things like that are
actually becoming more and more valuable, and the great
thing about this tool is that it allowed us to have a
framework to allow lots of voices around the table, to be
heard, and so it was up to each. So, we did this across 6 of
our brands here. MTV was one of the first ones to actually –
to kick it off. So, Damon – Damon and his counterparts
determined, who were critical to the mix and so different –
different channels have different voices that are important to
the mix. The way that we did it basically, was in working,
with Marketing Evolution, to have a process of, like these are
the - kind of questions we will be asking. Give them time to
answer them. Come back. Like, debate them. Submit them
back to Rex and his team. They go off and do their bits,
which we’ll talk about in a few minutes and then, come back
and share that with the team.
There are lots of checks and balances, of course, making sure
that the marketing lead is the person navigating the effort at
large, but really it was about like, setting up a framework to
have the conversation. Just to have the kind of conversation
that everyone wanted to have, or that was happening in a
very informal unstructured way. To just put more rigor and
discipline around it.
Doug Hutton:
Absolutely. Let’s just list the next stage. Show folks a bit of a
screen capture from that tool and a couple of good things.
For those of our members on the phone, just to add some
additional credibility to what is already a great tool, members
of ours in our corporate strategy board are actually using
similar tools like this to get stakeholder buy-in, to corporate
strategies at large.
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So, what marketing is doing here is actually a little bit ahead
of the curve, in terms of what corporations are doing at large
from a strategy perspective. What what you see here in this
screen capture, you see those factors captured down the lefthand side of your page. So, as we were talking about things
like the show’s content strength, its ratings potential, etc. As
you move from left to right, first – in the first column, the
different weight assigned to each of those factors. Obviously,
some are more important than others and then, as you
continue to move left to right, you see how those ratings
would play out for each of the different shows, within that
brand’s portfolio.
I have to say I was very much looking forward to today’s
teleconference because it gave me an excuse to talk about
“Jersey Shore” in an actual marketing context which is
fantastic, but as you look at the screen capture there, and at
the callout box, particularly on the top right-hand side of
your page. At the beginning of these processes every
stakeholder, once they bought into the actual factors
themselves, can provide their ratings for each of the shows
as to where they see that show performing on that given
factor.
Ultimately, leading up to the front screen capture where you
can see the composite scores. The really cool part about this,
and Rex, I love to toss it to you here in a second for a little bit
more color, but the cool part of this from our perspective
here at the Council is this is all dynamics. So, none of this is
really hidden.
So, if somebody wants to change a score, or folks want to do
some scenario planning, which I’ll show a little bit more on
the next page shortly, you can move the numbers around to
see what would that look like. What would that change in
allocation look like, if we were to let’s say, change the weight
for a given factor? If we were to change the score for a
given program, what does that look like? And that scenario
planning, that forward-looking assumption, is much more
powerful than that backward-looking media planning we
talked about earlier.
Rex, while we’ve got you on the line, I’d love to hear a little
bit more from you about the tool and in particular, sort of,
the thinking behind it.
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Rex Briggs:
Thank you – the tool really is designed to both take the
executive judgment that comes in to these decisions, as well
as data screen. So, one of the things that also plugs into
these tools is for example, the second item down, “How
buzz-worthy a show is.” So if that’s something that you have
quantitative measurement for, that can directly feed into the
tool with a score already pre-populated and locked in.
So, you begin to focus people’s attention on where there
truly is marketer’s judgment that’s going in, and you’re
beginning to connect together the data that you have across
the enterprise to help make those decisions more fact-based.
So it really is that blend of the art and the science that we
know goes into portfolio decision making, and it puts it in a
place that’s very transparent and easy for people to see. A
and as you mentioned, if there are disagreements between
how different people see a certain score, you can very
quickly see well, does it matter? I mean does it really, that
one score that we disagree upon, does that change the
decision that we make and if so, then let’s really have a deepdive discussion. If not, then okay you know, you give it a 4, I
give it a 5. It doesn’t change the fact that we’re – that its a
second tier priority, or first tier priority, or whatever, and that
– that is something that we really wanted to help Damon
and the other teams, within MTV Networks, be able to do
much more efficiently and much more transparently in their
process.
Doug Hutton:
Sure, fantastic, thanks, Rex. And as you look at the next page
that we’re going to put up on the screen here, a couple of
additional screen captures from the tool that I think illustrate
exactly the point that Rex was just talking about. I’ve made
that scenario capability point on the top right-hand side, but
as you can see, even for this particular example on the page,
if let’s say, folks were arguing a little bit about the given
score, the given attribute, they could determine if that would
make a difference.
You see the portfolio bubble chart, which looks exactly as
strengths, fit, and again, the size of the bubble is the upside.
Even as you move from the top left graphic to the top right
graphic, you can see that that doesn’t really change overall,
even with that one small change, how that actually would
play out from a marketing allocation perspective.
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The output of all of this though, is that – which I think is
equally as important. As you see the graphic in the lower
right-hand side of your page in terms of the sample output,
you see the “strength factors,” “SF,” and the “fit factors,” “FF,”
and then the optimal spend that should be allocated across
those. Obviously, there’s sort of a set pot of money to go,
but as I mentioned a little bit earlier, if you’re mid-way
through a year and have to make a tough budget decision
as to where those dollars move, this is actually a pretty quick
way to move through those capabilities, and through those
different scenario plans, to determine where we could
reallocate that money throughout our program portfolio.
Damon, I’d love to bring you back into the conversation
here, for a quick second. You were sort of, one of the guinea
pigs, I believe for the process. I’d love to just hear how this
tool, for you guys at this stage potentially changed or helped
you have better conversations with the stakeholders
involved in the planning process.
Damon Burrell:
Well, it definitely adds - and I think, Rex said that it definitely
adds a – a certain level of transparency around the decision
making process that I, the people on my team, and my peers,
go through when making these decisions. This is one of
those situations where every marketer already does the
majority of this already, but it’s done either in a vacuum, or
it’s done within someone’s own kind of mental capacity, and
what we’ve seen and what we’ve been able to showcase is
that unless you are a master at 3 dimensional chess, it’s
basically impossible to factor so many different variables at
any given time and come to a kind of strategic conclusion on
the best way to do it, unless - unless you can model it out
with a tool in this way.
So once we got past that hurdle and that understanding, I
think everyone saw the value at being able to utilize this tool,
and then it makes the conversations a lot easier from there
it’s really, well, what does – what does the tool say?
Everyone believes in it. Everyone understands the way that
it works. Everyone sees the value, so then it actually makes
our jobs a lot easier. So when we do come to the table and
say, in 2011, we’re going to be placing our dollars in our
overall budget then there’s less time spent on “Well, how did
you come up with that decision?”
Because everyone was actually involved and there’s
transparency on how the decisions are made.
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Doug Hutton:
Yep, fantastic. And I think one of the key things that we like
here at the – at the Council about the tool, and about this
process in general, is what you see here on this page, the
iterative of the nature of the tool, particularly as Rex and I
can – sum of the factors because they are fed by data. It is
quite easy to see within the tool, if some of the assumptions
that were made are not panning out, either positively or
negatively. And so, what you’re seeing, in the graphic here
on the page is just one of those variables on the “Y” axis talkability, sort of that word of mouth, and you can see each of
the letters across the bottom of the page representing a
given television program.
Each “X” corresponding to what was the assumed talk-ability
about that program, but you see, under the reality shows the
possibility that when the data comes back there’s a much
different actual performance than there is under the
planning – than was under the plan performance. And so,
as a result, this can get – quickly dates right back into the
tool, and as Damon mentioned, the trust that is built as a
result, and this goes back into the tool of changes, the
planning assumptions, a little bit, and as a result, it can
change where that allocation goes, throughout the
portfolio. And so, that assessment of actual performance
versus planned performance can constantly contribute to
the iterative nature of the tool.
Todd and Damon, one of my members asked me this
question, and I’d love to just get your take on it, “How often
have you guys, sort of, gone back to the tool, now that
you’ve, sort of, been through it once, maybe twice?” “If
something like this were to occur, what is – what sort of
steps have you guys taken internally, to ensure that it does
get back into the tool, and then it gets updated in terms of
where our research allocation goes?”
Todd Cunningham:
Sure, I’m definitely willing to answer that because basically,
what we did in our corporate role was to help facilitate a
unified approach, just a framework that each of the teams
could then take and kind of, mold to their needs. Some
brand’s had a long list of inputs, and some had shorter ones.
We have a number of different data strings which, of course,
come in on a very frequent basis.
Some brands need that on a weekly or more frequent basis.
Some look at it in more like, a month rollup kind of thing.
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So, in terms of the frequency of updating, I’ll let Damon
throw to that but we have not – it’s basically their tool. It’s
theirs to act on.
Doug Hutton:
Sure.
Damon Burrell:
Sure, so I’ll respond by saying that we – we’ve utilized this
tool on a number of occasions. Our planning process is
definitely fluid. We have new priorities and new shows that
are coming in and out of our slate. At any given times, there
is a constant need to have to readjust and reassign priorities;
but getting at the heart of the question, we’re always going
back and readjusting.
Marketing is a mix of both art and science. This tool
definitely brings a lot of the science into it, but then at the
same time, it’s up to the art of a marketer and their own kind
of subjective experience to be able to make the decisions
based off the data and the information that they have, and
the direction that they are getting from their utilizing the tool
like this.
So, we are constantly adjusting. We’re looking at the results
that come from the tool and then, kind of, readjusting and
putting information back in before we can make a final
decision, but I think you know the key answer to the
question that – there’s always going to be a mix of both art
and science.
Doug Hutton:
Yeah, absolutely, and I think the interesting thing that you
said Damon, that I don’t believe is always the case for some
of our members, is the fact that it - sort of, - always going
back and re-evaluating. I think often times, for some of our
members, planning becomes sort of, the once a year, once
every 6 months process, but the iterative nature of it and the
constant desire to go back and re-evaluate, I think is a pretty
key take-away.
Todd Cunningham:
But also – this is Todd. I would just say that from a consumer
advocacy position, it’s like we can no longer afford to look at
– to not be continuous about all this kind of stuff, right? I
mean, it’s not just because the data is there, but because the
dynamic is changing so much, and the dynamic is changing
in terms of, like, you know, important – in important ways for
marketers to be responsive, and to be, kind of, open to
understanding what the data means. That’s a new, kind of,
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role for research to be playing, is also help our marketing – in
marketing plans, but it’s to understand how and why the
data changes the way it does. Not just report on it, but to
also be able to make course directions in real time.
Doug Hutton:
Yep.
Rex Briggs:
I could just insert a quick anecdote to fill in - feedback for that
example. I am going to share one where a person had built
a plan and then they did it based upon a feeling that the
product was going to be of a certain quality. A show was
going to test really well and then it didn’t, but you know,
they didn’t get that score till like, the week before they were
supposed to start spending their marketing money, and I’m
sure that there are some people on the phone that probably
can relate to that situation. You build a plan months in
advance based upon certain assumptions. As the facts come
in, the facts picture looks different. What the tool allows you
to do very easily is to change that score and see if that
actually leads you to change your course of action.
And I think that’s just a really powerful – Todd and Damon’s
point. I mean that’s just the way business needs to work
these days. You can’t just sort of lock yourself into a plan
that says that “We decided to spend this money a year ago,
it’s a way to spend – you know, throw good money after
bad,” if you see the fact that your –changed, this makes it
really easy to see why you need to reallocate and speak to
those new priorities.
Doug Hutton:
Absolutely, and I think that’s a – a good transition here, as
we look at the page on the screen right now, in terms of
before and after. What does this enable us to shift to and I
think these are – regardless of whether or not you use a tool
exactly like the one that MTV Networks is using here, I think
the principles you see here are ones that we here at the
Council, will certainly advocate for in moving from the
incremental approach, to allocating our dollars on the lefthand side which yields the low stakeholder confidence that
we saw at the beginning of the case, to this assumptiondriven allocation on the right-hand side, which is forward
looking, which is fact-based, and as you heard Rex say, in as
many cases as possible, fed by real data, which gives us the
high stakeholder confidence in the decisions that we are
making. And, as you heard Damon say, a lot of buy-in from
the internal folks, knowing that we’ve held hands on this,
that there’s god data feeding into it, and we have to move
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quickly to ensure that the changes in consumer habits that
we see every day are baked-in to the planning processes that
we have.
But, if that’s step 1 of the process, in terms of looking on the
left-hand side of this page, problem number 1, as we just
went through. We have to allocate our dollars based on
forward-looking assumptions. There’s still the second
problem, which is okay, we’ve picked which - in this instance
which programs we are going to action against, but we still
need to figure out what does the media planning approach
look like?
Because our typical media planning optimizes to efficiency,
not effectiveness, and so here, we’re looking at what we call,
“Objective-based Media Optimization,” and before I get too
far into that though, and again, bring Rex into the
conversation again, just a little bit more detail on what we’ve
seen from our members in terms of optimizing for efficiency,
rather than effectiveness.
Don’t get me wrong, efficiency is still a good thing and
especially over the past couple of years as our members have
been certainly strapped for dollars, and strapped for more
dollars than they otherwise would.
Don’t get me wrong that efficiency is something you don’t
want to care about, but that said; our traditional media mix
modeling that you see sort of in the methodology box, at the
bottom of the page, is just that.
It’s a mathematical optimization of impressions delivered
against our target audience and again, constrained by our
budget which naturally – which gives us the false, we
believe, assumption that you see in the blue box at the very
bottom of the page which is that all touch points deliver
equivalent effectiveness, regardless of marketing objectives.
Now, I’m sure most of the folks on the phone today probably
dialed in because in some sense that they know that
assumption is false and they’re trying to change the way the
organization thinks about that assumption, so that we don’t
just get an efficiency output, as you see in the top right-hand
box on your page, but we move from efficiency to
effectiveness, so that we can really determine are we getting
to the right marketing objectives, and do we have the right
marketing communication mix to make that a reality?
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So, if that’s the case, if we want to move from efficiency to
effectiveness, here’s how Marketing Evolution and MTV
Networks have come together to do this, in fact. A couple of
things; obviously, this needs a substantial amount of inputs
and you see those two inputs on the left-hand side of your
page.
A database is in market, Marcom Performance, as well as
ongoing tests. For those of you on the calls that have been
tracking our marketing communications work, and also our
social media work over the past year, year and a half, you
know that we are huge believers here at the Council, of test
and learn and that’s exactly what’s happening here on the
lower left-hand side of the page.
Putting those two things together enables us to figure out
what different – for each given touch point - and you see
“TV,” called out in the 3 graphics on the right-hand side.
What are the different levels of effectiveness against different
objectives?
The TV may be great, let’s say, at aided awareness, but it may
not be quite as great as it is for brand prestige, the top one
on the page. You could similarly make charts like you see on
the right-hand side impact on the “Y’s” than on the “X,” for
any given touch point if you’ve got the data.
Now, obviously, this does require a little bit of database
building, but Rex, I’d love to hear from you in particular, a
little bit of the in’s and out’s here. I know for some of our
members, this may be a bit of a new concept. I know we’ve
worked with – I know we’ve worked with you and Ford
before, on how they’ve leveraged this process, but I’d love to
just hear from you as to how, sort of, this database of inmarket performance and these ongoing tests enable us to
track different touch points against these different objectives.
Rex Briggs:
Sure, and as you pointed out, the Ford case study is another
good one in a totally different industry that helps to illustrate
some of these points, but the most important point, I think,
that you made, that is a ground-setting point, is that
marketers know in their hearts. They know in their minds
that different – that there are different types of objectives
that they have to deal with and those require different types
of media mixes, to be very specific in entertainment and then
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to make it a little bit more general for MTV Network, or any
other entertainment brand.
Really, we know that there’s a very distinct different pattern
between launching a new show, where you’re going after –
trying to build new customers versus marketing a returning
series, where you’re really trying to market to your existing
customers. And to make that more general that pattern that
you see in CPT and a lot of other categories as well, which is
that the dynamics of marketing to new customers is different
than the dynamics of marketing to an existing customer.
A lot of that, to make the next step forward, is - the reason
why those dynamics are different is because in going to a
new customer, you have to build awareness and interest in
connecting at a certain point that your brand is relevant and
set up certain cues so that people think about that brand
when they’re in that buying behavior pattern, and that’s a
little bit different than what you need to do for marketing to
an existing customer, where you just really have to re-cue
them to remember what they love about your brand and get
them to buy you again.
And that’s very similar in television where, as you begin to
look at the media mix that does a really good job at building
awareness and relevance, for a new customer that’s a
different set of media mix than the media that is good at
reinforcing and driving conversion among existing
customers. So, you know that’s just one example of how
your different objectives, whether it’s going after new
customers or existing customers, lead to different media
mixes, because we know different media perform differently
in achieving the different type of communication objectives.
So, what we’ve done is we’ve measured literally billions of
dollars of marketing campaigns and surveyed millions of
consumers and ran modeling on sales behavior and ratings,
and so on, in hundreds of campaigns and we’ve developed a
normative database that allows marketers to get a quick start
in their category at what those patterns should look like,
depending on their objectives and goals.
Doug Hutton:
Uh-huh.
Rex Briggs:
And that’s what MTV used to get started and they’re now
looking at whether or not they should conduct their own
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proprietary research to fuel that data, but the fact that
there’s a lot of normative data, a lot of people to get over
that hurdle of, “Gosh, I don’t have the data,” or “I don’t have
the – the time or the money to do the big analysis.” You can
get started at least with normative information in a pretty
quick manor.
Doug Hutton:
Yep, and Rex, you made a great point there at the end and I
know probably some of our members have been thinking
about this throughout the call, as to what is the price tag of
all this going to cost me; and don’t worry folks, I’ve got a little
bit of an answer for you at the back of our presentation here,
so stay tuned for that in particular.
But similar to the portfolio allocation that we were talking
about a little bit earlier. I’ve just pulled up on your screen, a
screen shot of the media optimization tool that Rex was just
giving us a little bit of background on, on the screen in front
of you. And just to go through the canned call-out boxes
that you see down the right-hand side of your page, there’s
certainly, again, the ability to make adjustments and the
ability to plan for different scenarios so that you can get that
holistic assessment of marketing communications.
Also, as you see in the second tan call-out box, probably
important for a lot of marketers; obviously, there’s certainly a
lot of statistical analysis that’s going in here, but the good
part about the tool is that marketers in your organization
don’t necessarily have to have the statistical background to
do that.
Can you see where that arrow is pointing to those external
factors? Things like competitive activity, innovation, etc.
We’re not using, statistical numbers there; we’re trying to get
that sort of - we call it ordinal scoring, if you will, but using
words, which is often a little bit easier. But then again,
flexibility in planning to optimize the media mix is what you
see in that third call-out box.
As Rex was just talking about what are the different metrics
that we are trying to achieve? The different objectives - and
you’ll see the objective there - “Intent to Tune In” that’s going
to be different than the objective of “Brand Awareness” and
it’s going to be different than the objective of you know,
“Returning Users” as Rex was just talking about.
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But again, I don’t want to dwell on the precise you know, ins
and outs of the tool here, but again the over -arching point make it simple for folks to make allocation decisions that’s
smart and sort of, the normative basis that Rex was just
referring to and then also, what’s the best allocation for a
particular objective? You know, “How should I allocate the
money that I have to get me the best result?” as you go
through.
You see down at the bottom, the very bottom, the tool.
There’s no call-out box to it, but you see the media and
recommendation allocation down at the bottom, and then
also, you see in the red highlighted area towards the lower
right of your page, the actual results that would come
through. So, again, much like with the portfolio-driven
research allocation up front, we can determine by getting
real data on the back end, what is the impact of the media
mix that we are putting out into the market place?
The goal of all this though, is simplicity. There’s a lot of good
statistical stuff going on behind us, but the simpler we can
make it for the marketers using it is going to increase uptake
and I know Todd, we’ve quoted you here on the lower lefthand side of the page towards that point, boiling it down to
simple things that marketers and market researchers can use
in the planning process.
Todd Cunningham:
You know, the tricky thing is we’ve been talking about all of
the sunshiny things about this whole process and how
exciting it is. There are challenges along the way and I’m
sure people are probably asking themselves like, “Mm, what
– what’s the downside because it can’t all be so perfect.” I
would say that keeping your eye focused on simplicity is,
probably the hardest thing. You can keep it focused there,
but it’s because there’s so many factors that have just, you
know, that come in at any given moment; to be important,
to factor in to the mix, is like, you just have to be – I think it’s
really just around being kind of consistent and having those
open conversations as frequently as possible. And then,
through that it allows you to get to the point of - because
they didn’t like start to learn what matters and learn to
measure what matters most.
There is the inverse relationship thing of like, the more data
you put in, the less simple this is, and the meaning – the
more confusing it possibly could be to someone across the
table from you. So, striving toward simplicity is critical.
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Doug Hutton:
Absolutely. A couple more points I wanted to make here,
and we’ve pulled up the slide on the screen, “Course
Correcting.” Obviously, the goal of all of this much like with
the earlier research allocation in terms of what to market, is
obviously to change our mix as we continue to go forward,
and I think typically here, we see members with what we call
the “launch and leave approach.” It’s, here’s what we
planned, let’s do it, and see how it goes.
Actual though, in terms of this model, is how can we change
this in the moment? So you see the graphic on the page in –
again against each objective a given target audience and
then with the data stream starting to develop some of these
curves in terms you know, what’s the incremental progress
towards our objective on the “Y” axis? Again here, “Intent to
Tune In” against how much we’re going to spend; and
again, how much can we optimize against any one of those?
You see the 2 blue boxes on the bottom which I think are
critical points? The whole point here is “test and learn.”
Rapid learning loops, discovering what these performance
curves actually look like, and then the one on the right-hand
side. Combining the data from different touch points
certainly enables us to make those shifts that we need, that
we’ve talked about.
The goal, though, particularly in today’s media environment
again, if you’ve been with us here at the Council for a while,
you know that even in just the past 18 months, where we’ve
produced so much social media research, the number of
tools and platforms that are out there from a social media
perspective, have changed vastly. And with the efficiencybased media planning on the left-hand side of this page, it
doesn’t let us get into some of those new channels because
they are unproven and we don’t know how to use them
properly.
But here, as we move to the right-hand side of having an
objective-based media optimization approach, it can let us
take advantage of some of these newer models because we
can quickly see how they’re impacting our math – our mix,
excuse me.
If you take a look though, one of the points that is not right
on the page if you will, but is in the last bullet point down on
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the left-hand column, which is just interesting for us here at
the Council.
There are a couple of additional benefits here. Again, not to
sound too rosy about stuff, but I think these are important.
You can use this as an alternative view to really horse-race
against the media plans that your agencies are producing.
So, how are - are they kind of getting the message as well
and are they starting to line up with what’s working in your
organization?
Similarly, the second bullet point, “Global Visibility Into Media
Buys.” We can start to see some best practice sharing across
geographies. As we think about the Rubik’s cube where we
started here in our conversation this morning, it’s not just
about products and channels, but it’s about a global reach as
well and how can we weave that in here too?
Ultimately, we get to the bolded statement down on the
bottom of the page. Some back testing that MTV’s been able
to do across their historical campaign, suggested they’ve got
15% to 25% increases in effectiveness based on this method
of media planning. Now, that’s just amazing stuff. And if we
flip through the next page; I did promise folks that I would
talk a little bit about costs because I’m sure it’s in the back of
everybody’s mind these days.
But we do see a huge cost benefit, looking at that 15% to
25%. Now, you see the costs here on the left-hand side of
the page; we don’t want to hide the ball here, from you, but
as you look at that break-even point, we know we’ve got
some very large companies in our membership, and in that
blue box, we believe based on some of the back of the
envelope calculations, that brands that spend more than
$5,000,000 annually on media could expect to boost
effectiveness by that $500,000 which clearly offsets the cost
of that implementation.
So, from our perspective certainly; again, don’t want to hide
the ball on the cost, but even just achieving that benefit of
10% lift in effectiveness and media spend, is pretty good, and
MTV saw 15% to 25%. Certainly some implementation
guidance at the bottom of the page, in terms of having a
reasonably large number of Marcom initiatives, having a
significant sample size your target audience. Certainly,
having that high quality and variety of consumer data
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sources that are not currently being factored into key
decisions I think, are appropriate as well.
But you know, at this point you know, at this point, you
know, we’re sort of nearing the end of – nearing the end of
the material here, but I wanted to sort of get some final
thoughts from – from the 3 folks on the phone. We’ll maybe
start with Rex, and then Todd, and then Damon. Damon,
you can finish us off, but anything that we haven’t
necessarily called out specifically, as we’ve gone through
today that you’d, sort of, like to leave our member
participants with while we’re on the call?
Rex Briggs:
Don’t be intimated to dive in and get started. I mean, one of
the things that I was really impressed with working with
Damon was that he approached us and said, “Look, you
know, we have some areas that we want to improve around
marketing cuts around the customer – around improving
while we’re building plans and we want a more you know,
fact-based way of doing it you know, how do we get
started?” And, really, within a few weeks there was progress
made and answers – just getting people organized around
the ideas, and what data facts they had, and you can make
progress very quickly if you just dive in.
Doug Hutton:
Good, Todd, any final thoughts from you?
Todd Cunningham:
Yeah, I think it’s probably no secret to anyone that for many,
many years, it’s like the relationship between marketing and
research has not always been, you know, they aren’t BFF’s.
Mostly because it’s like there wasn’t a desire to measure
creativity and certainly didn’t want to be negotiating around
those kinds of things, but now that pretty much everything
can be measured, as Damon said earlier, it’s like so critical to
– for both sides to understand how they can meet in the
middle. Where art and science can actually work for good,
and this framework is a terrific way of being able to help that
actually happen.
Doug Hutton:
Damon, you get our last word.
Damon Burrell:
Sure, and I think – I think you know, my colleagues definitely
covered the main points and just to – just to echo that. It’s
not a – it’s not a marketing exercise. It’s actually a corporate
exercise. If there’s anyone who tries to go down this road
and do this process with the marketing department alone, I
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don’t think it will be successful. It definitely takes, you know,
- and it requires a lot of, kind of, collaboration and input from
multiple departments so that there is buy-in from a corporate
level. I would just say that while you know, it is a – it is a – it
is a marketing a tool and it allows for you to you know,
provide value to, kind of, key business measures, the exercise
in itself to make it happen is a corporate issue.
Doug Hutton:
Fantastic. But in wrapping us up, I want to extend just a
huge thank you to Damon and Todd, from MTV; and Rex
from Marketing Evolution, for joining us here on the call
today.
I think your thoughts were quite valuable to our members
on the phone. I know it gave a lot of additional context to
the graphics that we had put on the page. So, thank you
very much for that.
For our members on the phone here today, if there’s
additional follow-up that you’d like from today’s session, in
terms of learning a little bit more about the specific tool that
MTV Networks used, learning a little bit more about the ins
and outs of the case study, do feel free to contact your
account manager or executive advisor. I’m more than happy
to provide you with those additional details, and the case
study itself, can be found on the MLC web site, as well.
So, again, in closing, thank you all on the phone today for
joining us here this morning, and Damon, Todd, Rex, thank
you again for your participation and hopefully we’ll get a
chance to continue to work together here in the future.
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