Answering one of marketing most frequently asked questions
One of the
most enduring questions about the resource allocation concerns the proper mix
of online and offline advertising investment. What is the right mix of ad spend
between TV and digital? Answering that question often involves applying a
classic bit of marketing effectiveness analysis known as marketing attribution.
Essentially linking a business outcome to the marketing initiative that drove
it, attribution analysis is not only integral to advertising success but also a
key driver of securing buy-in from the executive boardroom.
Until
very recently, calibrating online and offline advertising investments involved
marketing mix modeling (MMM) or econometrics. This type of high-level,
probabilistic attribution has long been the go-to model for yielding valuable
insights regarding the relative effectiveness different advertising channels
have on consumer behavior. With that knowledge, marketers are able to forecast
future business performance and adjust their budgets to achieve better
outcomes. Two drawbacks of MMM, however, are that it’s typically
‘backward-looking’ and that it takes significant time to execute
The advent
of digital media has brought an onslaught of real-time user and event-level
data that allows marketers to attribute an individual’s behavior to highly
customized marketing levers. Because these insights are immediately after (and
sometimes during) the campaign, marketing channels and tactics can be optimized
to generate maximum value while the campaign is actually running, ensuring the
maximum possible return on investment.
Although
real-time, in-campaign data and optimization offer powerful incentives,
marketers must include Marketing Mix Modelling in their analytical
toolkit. MMM provides a 30,000-foot-view
that cannot be obtained from the event-level insights offered by user-level
analysis. MMM also provides a long-term view of marketing effectiveness the can
illustrate the benefits of brand building, which translates into long-term
brand returns.
The truth
is that the most effective analytic strategies combine a channel-level,
pre/post campaign view with event-level insights revealed by digital data. Below I have detailed four important steps to
creating an analytical toolkit:
1. Build A
Data Infrastructure
Precious
few companies have the data infrastructure needed to sift through the
never-ending stream of digital data, nor the expertise needed to mine for the
golden nuggets. Companies that make an upfront investment in a strong, holistic
data analysis capability will stand to gain immeasurably from the more
effective marketing campaigns they will generate. Remember that user-level data
works in concert with more traditional analysis, not in lieu of it.
2. Ask, “What is the problem we’re trying to
solve?”
This is the
question every marketer should ask before spending a single dollar. Without an
answer, all the data in the world won’t save brands from pursuing costly
endeavors of questionable value. How can success be measured when it hasn’t
been defined? Whether it’s increasing brand health, generating sales, building
long-term value or any other goal, companies need to reach consensus on the key
marketing performance objectives they are attempting to achieve and then
activate their attribution capability to help them build out the right strategy
and tactics.
3. Audit and Optimize Throughout the Marketing
Lifecycle
Applying attribution before, after and during
campaigns helps to inform upstream strategic thinking and enables downstream tactical
optimization. This end-to-end analysis assists marketers in their efforts to
drive improved effectiveness and efficiency for all elements of their media
mix. Every insight along the way will
help marketers optimize their campaigns, identifying which creative is
resonating most, which audiences are most receptive and which channels and
tactics are most effective.
4. Build In Flexibility
To get the
most from attribution clients must also rethink how they go to market. This
line of questioning ensures that marketing programs have the built-in
flexibility to activate recommendations that come out of real-time analytical
insight. This may mean negotiating cross-platform deals that allow for budget
shifts from less effective platforms to more effective ones, or better yet,
deals that allow for wholesale budget cuts with limited penalty. Companies
should also consider holding back opportunistic ‘contingency’ funds that can be
deployed to high-performing channels or tactics as they are uncovered.
So what’s
next for attribution? As more user-level data becomes available for
traditionally offline media channels, and as media buying continues its march
toward a programmatic future, analytics will need to produce answers in an
increasingly complex marketing ecosystem. Pressure will mount to integrate
buying platforms with attribution methods to ensure that analyses are performed
in real time. Additionally, the growing dominance of mobile as a media platform
form is forcing marketers to create new processes to parse data and attribute
credit.
Tomorrow’s
winning marketers will be those who successfully create an integrated, holistic
attribution capability that combines the
high-level strategy of traditional, probabilistic attribution with the
user-level, tactical insights of real-time data, and who work to activate the
outcomes of the analyses in order to realize superior business value.
See This Video To Know More About to the 4 Principles of Marketing Strategy...
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