Learn how to improve your customer performance measurement into the future in this eBook.

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Table of Contents
Introduction
1. Stop relying on basic single-touch attribution models alone
2. Evaluate the entire customer journey—not just marketing touchpoints
3. Go beyond optimizing to initial conversion
4. Ensure rich data dimensionality so you can diagnose what works and why
The key to trusted insights is trusted data
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INTRODUCTION
Marketers will tell you they need a lot of things in
order to do their jobs well, but the truth comes down
to three very “simple” things. The most fundamental
questions to which marketers need answers are:
1. What is working?
2. What isn’t working?
3. Why?
Obviously, there are many other important details
and nuances when seeking for the answers; but the
reality is that in today’s marketing landscape—where
decisions need to be made quickly and strategy
needs to be adaptable—it is essential that marketers
trust their data in order to have the confidence to
take actions that will drive their businesses forward.
This is why you’ll find dozens (if not hundreds) of
services and technologies aimed at “solving the data
problem.” Yet it’s difficult to find a solution on the
market today that actually answers the three afore-
mentioned questions across all investments an orga-
nization is making around their customer experiences.
There are 4 reasons why marketing insights of the
future are going to look drastically different than the
past; and if your team isn’t on board with them, you
will be left behind. And given the astronomical rate
at which data is being created every single day, if you
have to play catch up, your organization will be at a
measurable disadvantage.
Those three questions presented in the introduction
led marketers to the concept—and eventually the
technical capability—of attribution. It’s the process of
giving credit where credit is due, and is essential to
understanding which specific brand touchpoints (both
channel and content) are most effective in driving key
business metrics.
There are a lot of attribution models out there, from ba-
sic rules-based models to more complex machine-led
algorithms. All models give you a different view of “what
happened” and can assist in determining your organi-
zation’s performance, but they are not created equal.

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1. Stop relying on basic
single-touch attribution
models alone
Despite the access to more sophisticated models that
can remove guesswork, most marketers and analysts
still use basic single-touch models. According to recent
research released from Strala by ObservePoint, 72% of
marketers are still using last-touch attribution.
Unsurprisingly, the majority of those who report using
those particular models are unhappy with them. Not
because they’re using a “wrong” model, but because
they’re using a model that can only show them a sliver
of the complete picture.
While a single-touch model may be sufficient for cer-
tain tactics within a smaller or newer business, eventu-
ally growth must be matched by sophistication, espe-
cially in measurement and reporting. For an enterprise
business, this means still using single-touch models
where appropriate, but also adding in heuristic and
machine-driven multi-touch models to the measure-
ment and reporting mix. The world’s largest and most
successful companies are already doing this. Others
who wish to compete must begin doing the same.
Let’s take a look at that next.
A word of caution: even the most sophisticated
model is only as good as the data it’s fed. Just as
a sports car needs the right type of fuel to per-
form at the optimal level, attribution models
also need the right quality of data to produce
the insights needed for business optimization.

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2. Evaluate the entire customer
journey—not just marketing
touchpoints
When a company is analyzing tactics, hoping to either
scale successful efforts or quickly re-strategize when
certain efforts prove less promising, the full customer
journey is critical. Although we introduced more sophis-
ticated attribution models as our first reason market-
ing insights are going to look drastically different in the
days ahead, the fuel that drives those models across
the line to success is the data itself.
Forward-thinking marketers are already evaluating the
entire brand experience, attempting to collect and uni-
fy data spanning the complete end-to-end customer
journey. Nearly every solution on the market attempts
to do this after the data has been collected, resulting
in misaligned data and data sets that are enormously
complicated (often entirely impossible) to unify.
Think of the data as food for an attri-
bution model. While calorically, one
can technically exist on donuts, peak
performance can only be achieved with
the right type—and mix—of nutrients.
Complete, consistent, and unified data
are the nutritional inputs attribution
models—and your entire marketing
measurement practice—need to thrive.
Why?
Most media measurement and attribution platforms
take a myopic approach: they only consider paid chan-
nels, and often only paid digital channels, because dig-
ital is a whole lot easier to track and programmatically
manage. This results in silos, from the way the work is
done to how it’s measured. Siloed channels lead to a
significant roadblock for any organization attempting
to accurately measure performance: siloed data.
Unfortunately, most organizations are forced to use
siloed data when looking at performance because it’s
how their marketing efforts are structured.
The organizations attempting to unify data beyond
paid media for the sake of more accurate attribution
do so by actively gathering data from all paid, owned,
and earned marketing channels—and hopefully con-
sidering both online or offline touchpoints. They also
begin to look beyond the “channel lens” and collect
data highlighting performance tied directly to content

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(creative assets, promotions, etc.). It’s only through
breaking down these data silos that brands can truly
move toward a more complete view of the entire cus-
tomer experience.
Taking this a step further, leading measurement
professionals know that truly holistic performance
measurement requires incorporating data that ex-
ists outside the walls of marketing. For example:
Sales
Services
CX/VoC
In-product experiences
All these areas have unique and valuable data sets
that provide powerful insights into the end-to-end
customer journey, and can help you more completely
and accurately measure not only transactional attri-
bution, but also full customer lifetime value.
It can feel daunting, but holistic data collection and
unification is the only way to produce accurate in-
sights that can be trusted. After all, many solutions
already deliver some insights, but as reported in the
2019 Marketing Benchmark Report,
89% of marketing leaders have
stated that just because the insights
exist doesn’t mean the insights are
actually trusted enough to lead to
confident actions.

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3. Go beyond optimizing
to initial conversation
Once all marketing channels and brand touchpoints
are measured holistically, the metrics marketers em-
ploy will begin to shift. Obviously sign-ups, leads, book-
ings, orders, and other primary conversion events are
relevant KPIs to be tracked for most organizations; but
as the acronym implies, these are simply indicators of
business success.
Marketers need to become financially literate—and
communicate in the language of the broader busi-
ness—tying program performance to broader busi-
ness outcomes. Learning to connect function-spe-
cific KPIs to concrete enterprise metrics like top-line
growth and bottom-line profitability help to strengthen
marketing’s position and prove the value of both effort
and money spent.
One buzz term attempting to lay claim to this shift in
perspective is the designation of “data-driven mar-
keter.” However, it is not simply the use of data, but
also which data a marketer focuses on that is import-
ant. We’d argue that the better designation is being a
“bottom-line marketer.”
And the only way to get an accurate view of market-
ing’s contribution to the bottom line is by measuring
and running attribution on every single interaction
each customer has with your business. This includes
everything from initial brand awareness to post-pur-
chase experiences in the ongoing customer journey.
Additionally, this will help you measure and optimize
customer lifetime value, which moves measurement
beyond the narrow view of “transactional attribution”
to more holistically measuring and placing value on the
ongoing customer relationship.
Customer centricity is clearly becoming a significant
focus for many businesses, and the most advanced
companies are discovering unique and meaningful
ways to incorporate customer experience data into
their performance measurement practice.
According to Peter Fader, Professor of Marketing at
Wharton University,
“Customer centricity is a strategy that aligns a
company’s development and delivery of its products
and services with the current and future needs of a
select set of customers in order to maximize their
long-term financial value to the firm.”
To fall behind on such a critical metric will be problem-
atic for any company hoping to keep pace.
bot•tom line mar•ket•er
“Bottom-line marketers” maintain an avid focus on
the core economic drivers of your organization’s
short- and long-term profitability and growth.
/’bädәm ‘ ,līn/ märkәdәr/

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Quick Recap
1. Basic attribution models are too limited by themselves for an enterprise business
to measure channel and content success.
2. The entire customer experience—not just marketing touchpoints—must be evaluated
when trying to gain an understanding of an organization’s performance.
3. In order to prove marketing’s impact on the broader business, marketers must
learn to measure and communicate using financial metrics, not just functional KPIs.
These principles ensure that marketers and analysts are holistically measuring and attributing credit to all touchpoints
across all channels a customer may interact with during their relationship with a brand. They also ensure that success
(and failure) is framed using broader economic performance metrics relevant to the entire business’ bottom-line.
With these holistic insights, you can be confident that the data you apply to your attribution models and the
resulting performance calculations (such as ROI) are complete, consistent, accurate, and what you need in order
to move ahead of your competition.
So let’s talk about how to answer the final question: why are these things working, or why are they not working?

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There are some important questions every marketer
desperately wants to be able to answer, and frustrat-
ingly often can’t.
• Why is my email program outperforming my pro-
grammatic display campaigns?
• Why does my annual customer conference produce
such a high ROI, while other events don’t?
• Why do certain types of content lead to more book-
ings than other types of content?
The most successful marketers who add significant
value to an organization are relentlessly curious about
why certain actions get results while others don’t. Yet
despite ongoing technological advances in analytics,
marketing automation, programmatic advertising, and
other digital marketing disciplines, the ability to con-
sistently answer these questions hasn’t necessarily
kept pace. Analysts and marketers need to look deep-
er than the typically limited, out-of-the-box dimen-
sions and attributes most ad and martech solutions
provide.
It’s not that simplistic measurements like UTM param-
eters don’t have a place in a marketer’s toolkit, but
UTM parameters alone only provide a limited amount
of data and are subject to significant pitfalls such
as human error. Eventually, an enterprise company
needs to justify its enterprise-level marketing budget,
and doing so requires precision in reporting (some-
thing UTM parameters simply aren’t built to do), partic-
ularly when it comes to return-on-ad spend.
The “why” partly lies within a rich and consistent meta-
data layer that marketing analysts require in order to
answer key business questions. Don’t misinterpret this
to mean every little data piece that could ever possibly
be collected should be. There are certain levels of data
that may not be pertinent to your organization, and
it’s important to audit what that looks like when imple-
menting a more robust metadata layer to enrich your
attribution and performance measurement.
However, very few organizations today capture a con-
sistent enough layer of data to accurately pinpoint the
“why” of their marketing efforts’ successes and failures.
And even more rarely are measurement standards ap-
plied consistently across all the relevant touchpoints
in the customer experience, unifying once-siloed data
sets.
A great example is how certain brand campaigns are
both defined and measured across numerous chan-
nels, especially campaigns that include social, digital,
and offline components. One campaign alone can have
a staggering number of platform- or publisher-specific
data sets that should in fact only be one unified data
set. Yet so few organizations take the time to predefine
the data in such a way that each channel can use a
holistic, common taxonomy that provides dimensional
4. Ensure rich data
dimensionality so you can
diagnose what works and why

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Some may argue that A/B testing accomplishes this
without needing to expand the channel and content
attributes included in your enterprise taxonomy,
but today’s marketing environment is extraordinari-
ly complex. It isn’t enough to simply test subject line
length. Even things as seemingly uninspiring as font
size, image location, or playback speed can have sig-
nificant impact on performance. Quite simply, there
just aren’t enough letters in the alphabet to account
for how many variables must be measured against
each other (and in which optimal combinations).
analysis along any performance-influencing attri-
butes. Not only can each tactic not be compared
apples-to-apples to all others in the campaign,
but performance insights cannot be shared across
channels to benefit the entire effort.
Certain channels can be really consistent and detailed
regarding channel attributes, and therefore have more
consistent and detailed data to analyze performance.
Paid search does well in this regard; email is a bit less
standardized; and website or in-app metadata struc-
tures can vary wildly from company to company. Unify-
ing measurement attributes in an enterprise-wide stan-
dard enables meaningful and consistent insights across
all channels and content, regardless of where or how
consumers interact with them.
Overcome content attribution challenges
Nowhere is this felt more acutely than by content mar-
keting and creation professionals. These teams and in-
dividuals assist both sales and marketing departments
to generate the messages and assets delivered across
a myriad of channels. Yet for years the measurement
available to prove the value of their contribution to
customer experiences has been relegated to a single
UTM parameter, or at best half a dozen classification
columns in an analytics implementation.
Yet leading marketers know these are false constraints,
and that there are dozens (if not hundreds) of dimen-
sions along which content performance can and should
be measured. No longer are they stuck assuming case
studies will always perform better than an infographic.
Or that a direct “Buy Now” call to action will consistently
outperform the more subtle “Learn More” prompt. It
is indeed possible to know which messaging resonates
most, if a video truly does engage more than the image,
and how to better structure a pitch for the next sales
sequence send.

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Every additional variable accounted for and then ap-
plied to a measurement program enables deeper inqui-
ry into business performance. This empowers analysts
and marketers to finally know not only what happened,
but why it happened. And perhaps equally as important,
how they can share those insights across channels to
“raise all ships.”
Sample of Recommended Channel
& Content Attributes
Channel (Medium)*
Channel Type
Publisher (Source)*
Campaign Name*
Campaign Theme
Campaign Owner
Campaign Budget
Media Cost Model
Placement
Audience
Device
Keyword (Term)*
Geo Country
Geo State/Province
Geo City
Language
Target Life Cycle Stage
Target Customer Persona
Target Industry
Promoted Product Name
Promoted Product Category
Promoted Product Description
Promoted Product SKU
Content Title*
Content Type
Content Description
Content Promotion
Content Call to Action
Promoted Asset Type
Promoted Asset Name
Promoted Asset Description
Asset ID
Asset Owner
Touchpoint URL (external)
Landing Page URL
Landing Page Title
Landing Page Description
*traditional UTM parameters

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All of the resulting insights give data professionals the
confidence to know precisely what their next move
should be. That sort of trust in the data is hard to come
by, but as more marketers tear down the false con-
straints of their dimensional measurement—especial-
ly in the realm of content analysis—this approach will
quickly move from “best practice” to “standard prac-
tice.” Those who begin this process now will be expo-
nentially ahead of the curve, particularly in crowded
fields where even a small increase in return has a sig-
nificant impact on the bottom line.
There are marketers and analysts today who are al-
ready reaping the benefits of these sophisticated, ho-
listic attribution models, who take into account the en-
tire customer experience, who measure beyond basic
metrics and KPIs. They have already broadened and
deepened the dimensions and attributions necessary
to capture the entire performance picture, and as a
result, they are winning.
Schedule Demo
The key to trusted insights
is trusted data
They aren’t winning because they have more data
than anyone else—they’re winning because the infor-
mation they do have gives them the confidence they
need to reinvest dollars, cut losses, and account for
all efforts across every customer touchpoint.
This foundation of trusted data and insights enables:
Accurate forecasting
Budget optimization
Experience personalization
Increased ROI
Stronger, longer customer loyalty
Your peers who have implemented these key prin-
ciples already know how to optimize their programs
for superior ROI. The good news for most marketers
is there’s still an opportunity to be an early adopter
and reap the benefits of outpacing competition.
Schedule a demo to see how Strala by ObservePoint
ensures complete, unified marketing and experience
data for actionable insights you can trust.