This document discusses marketing attribution tools Marketo and Bizible. It provides an overview of how attribution tools work by capturing marketing efforts, audience engagement, and performance outcomes. It then compares how Marketo and Bizible handle key functions like data capture, data modeling, and data reporting/visualization. For data capture, Bizible has simpler tracking than Marketo. For data modeling, Bizible groups interactions into touchpoints while Marketo uses programs. For reporting, Bizible offers more flexibility and attribution models than Marketo. The document aims to help choose the right attribution tool based on needs and capabilities.

1. THE ART AND SCIENCE
OF MARKETING ATTRIBUTION
Exploring the philosophies and technical aspects of attribution: how it works
and how to choose a model to meet your business objectives

2. >The Science: How Attribution Tools Work
>Data Capture
The process with Marketo
The process with Bizible
A Functional Comparison
>Data Modelling
The process with Marketo
Create separate programs for offers
and channels
Create a program for every offer +
channel combo
Copy UTM values to the campaign
member
The process with Bizible
A Functional Comparison
>Data Reporting and Visualization
The process in Marketo
The process in Bizible
A Functional Comparison
>The Art of Attribution:
Philosophies Behind the Models
>Models
>Final Thoughts
02
TABLE OF
CONTENTS
06
09
10
10
11
12
13
14
15
16
17
19
20
21
21
22
25
27
36

3. Both raise questions about observation and
perception. The marketing answer, however,
depends on your approach to attribution.
03
PHILOSOPHICAL
LIFE QUESTION
“If a tree falls in a forest and no one is
around to hear it, does it make a sound?”
PHILOSOPHICAL
MARKETING QUESTION
“If a marketing campaign dropped but didn’t
generate a sale, did it have an impact?”

4. 04
According to the 2016 State of Pipeline Marketing Report, only
20% of CMOs believe they are using the right attribution model.
Their uncertainty is understandable. Marketing attribution has never been more
complicated; the explosion of marketing channels and devices has added complexity
and connecting sales to touchpoint interactions has marketing operations teams
working overtime. This guide will examine the science of marketing
attribution—Marketo’s tools, features and benefits, as well as explore the art of
attribution—commonly used attribution models and why you might choose one
model over another.

5. THE BIG QUESTION:
DID MY CAMPAIGN WORK?
05
Nothing is more frustrating than spending countless
hours and dollars rolling out a multi-channel marketing
campaign and not knowing which of your efforts had
the most impact. Sound all-too familiar? You are not
alone. In fact, 54% of marketing professionals cite the
inability to measure impact across channels and
campaigns as their biggest challenge. (Marketing
Measurement and Attribution Survey Report, Demand
Gen Report, 2017) Consequently, spending on marketing
analytics is also projected to rise 198% over the next
three years. (The CMO Survey, February 2018) A natural
progression—analytical tools provide critical insight into
the performance of each campaign. But having the
appropriate tools is only part of the solution. Equally
essential is understanding how the tools work, the data
they generate, and selecting an appropriate attribution
model for your unique sales cycle.

6. 06
THE SCIENCE:
HOW ATTRIBUTION TOOLS WORK
Simply stated, marketing attribution is the process of determining which of your marketing
efforts is driving revenue. As a byproduct, attribution tools also enable you to optimize marketing
campaigns, resource allocations, and your marketing budget.
How do they work?
Technology aside, all attribution systems examine the intersection of three related datasets:
1. Marketing Efforts: the marketing campaigns you launched.
2. Audience Engagement: the people (prospects, customers, etc.) who engaged with
your efforts.
3. Performance Outcomes: the results of your efforts. Usually this is revenue or pipeline value
but could also be a metric like MQLs.

7. 07
In order to tie the three datasets together in a meaningful
way, three primary functions must take place:
Data Capture: tracking all three
datasets—your efforts, engagement and
outcomes.
Data Modelling: storing data captured
in such a way so as to provide flexible
and meaningful reporting.
Data Visualization and Reporting: just as it
sounds, reporting on your results.
When people engage with your marketing efforts then take a
desired action, such as buying your product, attribution tools apply credit to the appropriate
marketing effort with which they interacted. As to which effort and how much credit depends
on your attribution model—the methodology can be simple or complex, but all are based on
this underlying principle.
MARKETING
EFFORTS
AUDIENCE
ENGAGEMENT
PERFORMANCE
OUTCOMES

8. 08
REPORTING AND ATTRIBUTION IN MARKETO:
COMPARING YOUR OPTIONS
If you’re accustomed to tracking attribution using
Marketo and Revenue Explorer, then transitioning
to Bizible, the newest member of the Marketo
family, will be significantly different. How does
Bizible impact your marketing operations? In this
section, we’ll delve into the tool variances by
primary function—data capture, data modelling
and data visualizing/reporting—and compare the
implementation process for common reporting
scenarios.

9. 09
DATA CAPTURE
Let’s say you want to track what marketing initiatives are
bringing people into your database, or in other words,
you want to know the “Lead Source”. How do you
set this up?

10. 10
The process with Marketo: Most marketers
can track an offer (ex: a content asset) in
Marketo fairly easily using a combination of
the form and/or landing page. However,
tracking a channel (ex: paid search, SEO,
social media, etc) is much harder, especially
when it involves digital channels.
To obtain channel information in Marketo,
your team will need to create UTM parame-
ters on your landing page with web referrer
data to deduce organic channels. To get this
data into Marketo, your team must also im-
plement custom tracking script to capture
the data, convert it to cookies that persist as
the visitor jumps from page to page, ensure
all forms have hidden fields to capture UTM
and referrer values and finally, pass these
values to fields on the person object, which
can then trigger adding the person to an ap-
propriate tracking program. It’s a significant
amount of work. Moreover, scripts must be
flawlessly written, to avoid failure in certain
browsers or Marketo logic fails. Many mar-
keting organizations use these methods
very successfully, but there is, nevertheless,
complexity and potential for error with this
approach.
The process with Bizible: There is little con-
figuration to start capturing data with
Bizible. Since Bizible has its own tracking
script, tracking is simplified, especially for
digital activity. High fives for your operations
team!
What’s happening behind the scenes: when
someone fills out a form, Bizible detects and
logs the URL of the form completion page
from which you would deduce the offer.
Where Bizible excels is in tracking channels.
Bizible automatically detects and stores the
UTMs and web referrer data associated with
the session, without having to set custom
cookies or modify your forms. Finally, be-
cause Bizible has direct API connections
with ad platforms like Adwords, Bing, and
Facebook ads, it automatically pulls ad and
cost detail from these platforms, without
any manual tagging required on your part.

11. 11
A FUNCTIONAL COMPARISON
MARKETO
OVERALL
OFFERS
CHANNELS
BIZIBLE
Munchkin tracking script captures web
activity. Marketo also logs form fills and
email interactions. Referrer/UTM data
stored but only in activity log. Custom
script required to make this data
accessible at the field level.
Easy to track; typically uses a
combination of a form plus landing
page to identify offer, which can trigger
the addition of a person to the
corresponding program.
Harder to track, especially digital;
requires custom script to convert
UTM/referrer data to cookies and form
management to ensure data is mapped
to fields on the person record in
Marketo.
Bizible tracking script tracks web
activity and form fills as well as referrer
and UTM data, which is associated with
touchpoints for easy reporting. Tracks
full clickstream data via Bizible Data
Warehouse product, giving it the detail
of a full-featured web analytics solution.
Detects and logs the URL of the form
completed; offer is deduced based on
URL.
Automatically detects and stores UTM
parameters and web referrer data,
without creating custom cookies or
modifying forms. Direct API
connections with ad platforms capture
ad and cost data without manual
tagging. Platforms currently supported:
Adwords, Bing, Facebook Ads.

12. DATA MODELLING
For this example, let’s say you’re launching a multi-
faceted marketing campaign consisting of many offers
(blog posts, webinars, eBooks, etc.) across numerous
channels and at the conclusion of your campaign, you
want a report showing which channels are driving the
most engagement with particular offers.
12

13. 13
Marketo’s unit of attribution revolves
around the program, which represents a
single marketing initiative you want to
track. Multiple programs can be created,
and stages indicate the level of interaction
with each program and if that interaction
was successful. Programs correspond to a
Salesforce campaign (if you track this in
Salesforce). Capturing the relationship
between offers and channels, though, is
much harder and your options not ideal.
In other words, additional set-up is required:
THE PROCESS
WITH MARKETO


14. 14
Create separate programs for offers and
channels: This allows you to capture each
marketing asset and traffic source the
person engages with, but there is no
connection between them. Also, if someone
engages with the same channel (e.g., organ-
ic Twitter) twice, you can’t track the second
interaction, because a person can only be a
member of a program once.
1

15. 15
Create a program for every offer + channel
combo: Ex: ABC Ebook + social; ABC Ebook +
paid search…and the list goes on. Prepare
yourself for a mountain of work and huge
task list to maintain.
2

16. 16
Copy UTM values to the campaign member:
which also moves reporting to Salesforce (as
you cannot store this additional metadata
related to a specific program status in
Marketo). This option gives you a more flexi-
ble model but requires extra configuration
and custom code in Salesforce. Additionally,
there are some challenges to tracking costs
for ROI and reporting by channels with this
method, as you no longer have a distinct
campaign to represent the channel.
3

17. 17
THE PROCESS
WITH BIZIBLE
Bizible uses “touchpoints” (or the marketing
interaction between a person, offer, and
channel) as the unit of attribution and cap-
tures every web visit, form fill, and offline
touchpoint, grouping them into channels or
subchannels that you create. Theoretically,
unlimited touchpoints are possible.
The process is straightforward as Bizible cre-
ates touchpoints automatically with little to
set-up or maintain. Additionally, all interac-
tion data, both offer and channel, are stored
on the same record. As a result, there is
greater flexibility in reporting options,
including changing channel groupings
midstream and reprocessing of all data
without information loss.
The downside? You’ll have less rich metada-
ta about offers, because the form URL isn’t
as precise as the metadata associated with
Marketo programs. For this reason, it’s rec-
ommend that you maintain offer programs
in tandem in Marketo, which you would
likely need anyway to send fulfillment
emails, etc.

18. 18
CHANNEL
DATA
OFFER
DATA

19. 19
A FUNCTIONAL COMPARISON
MARKETO
UNIT OF
ATTRIBUTION
DATA
MODEL
METADATA
BIZIBLE
Unit of attribution is the program, a single
marketing initiative which corresponds
conceptually to a Salesforce Campaign.
One person can be a member of many
programs, but only once per program or
campaign. Stages indicate the level of
interaction with the program and whether
that interaction was successful. Program
structure can be as granular as you want,
but this becomes hard to manage when
tracking offer + channel combinations.
A program can have various types of
metadata to add additional dimensions, ex:
region, product line, type of marketing
initiative, etc. but program tags are limited
to a fixed set of values, limiting their
usefulness.
Unit of attribution is the Touchpoint, a
single marketing interaction between a
person, an offer, and channel, stored in a
single record.
Touchpoints are unlimited; touchpoints are
captured for every web visit and logged in
CRM for a person’s first anonymous visit,
every subsequent form fill, and for offline
touchpoints when synced from a campaign,
even when repeat interactions with the
same offer and channel occur. Channels are
assigned to touchpoints dynamically based
on business rules, eliminating the need to
maintain a set of pre-existing campaigns for
tracking purposes.
Touchpoint data is set based on UTM
parameters, providing more flexibility to
describe channels according to your
preferred taxonomy. Channel and
subchannels group touchpoints according
to your configuration, which can be altered
and data reprocessed. Metadata about offers
is limited, as only the form URL is captured.

20. 20
DATA REPORTING
AND VISUALIZATION
Your marketing campaign has completed and now
it’s time for the fun part—analyzing the results. You’re
excited to see how each effort performed and eager to
know which was the most profitable; you ask your
team for a report showing ROI.

21. 21
The process in Marketo: To run the requested
reports and provide revenue attribution
metrics, you must have Revenue Explorer or
the newer Marketo Performance Insights
(MPI) product. Both apply a multi-touch,
even-split model to attribution with slight
variances between the tools. With RE,
reporting visualization is pivot table style
with some ability to create calculated fields
and add custom dimensions; however,
flexibility is limited, and the calculated data
is in a silo that can’t be connected to other
sources. The MPI reporting dashboard is
more visually appealing, but customization
is very limited and not designed for ad-hoc
data exploration. Overall, if multi-touch,
even-split attribution is not the model you
want, then Marketo-based attribution does
not meet your needs.
The process in Bizible: Bizible offers an array
of choices for users accustomed to RE
or MPI, including multiple attribution
models ranging from traditional to complex
plus a newer machine learning model.
Determining which of your marketing
efforts are most profitable is easier in Bizible,
as it allows for more flexibility in manipulat-
ing and combining data with other objects
and systems. Moreover, because attribution
calculations are stored in fields on CRM
objects, you have full access to the native
reporting capabilities of your CRM. The data
is also accessible via API, can be added to
other systems or exported to a data ware-
house. Marketers will also appreciate
Bizible’s Discover UI, which is similar to MPI,
for a familiar and aesthetically appealing
view.

22. 22
A FUNCTIONAL COMPARISON
REVENUE
EXPLORER
PERFORMANCE
INSIGHTS
REPORTING
TYPES
MULTI-TOUCH
ATTRIBUTION
MODELS
SUPPORTED
CUSTOMIZABILITY
BIZIBLE
Pivot table style ad-hoc
analysis as well as charts.
Visually appealing
dashboard but limited
customization.
Inherits all the benefits of
your CRM reporting
engine; fully flexible to
manipulate data and
combine with data from
other objects.
Even split model is the
only multi-touch option.
Even split model is the
only multi-touch option.
Multiple attribution
models: u-shape, w-shape,
full-path, custom,
machine-learning, to name
a few.
Limited flexibility: analysis
areas are fixed. Some
ability to create calculated
measures and add custom
dimensions.
Analysis areas are fixed,
cannot create custom
measures. Not designed
for ad-hoc data
exploration.
Very flexible: attribution
calculations are stored in
fields on CRM objects and
can easily be combined
with custom fields and
objects or custom
calculations in code, etc.

23. 23
A FUNCTIONAL COMPARISON (continued)
REVENUE
EXPLORER
PERFORMANCE
INSIGHTS
DATA
PORTABILITY
PERFORMANCE
BIZIBLE
Attribution data is locked
and cannot be
manipulated in other
systems.
Attribution data is locked
and cannot be
manipulated in other
systems.
Data is accessible via API,
can be added to other
systems or exported to a
data warehouse.
Reporting engine runs
very slow.
Too soon to tell. CRM reporting engine is
typically more performant
than RE.

24. WHICH ATTRIBUTION TOOL
IS RIGHT FOR YOU?
24
Let’s face it, marketing isn’t getting any simpler. Rather, we’re working with more channels, more
offers, and a non-linear customer journey. Marketo and Revenue Explorer track the offer and do
simple attribution reporting reasonably well, but quickly become labor-intensive and extremely
limited when attempting more complex analysis. In contrast, Bizible offers easier tracking out of
the box, less maintenance and work for marketing operations teams and more flexibility for
higher level reporting and analysis. And for those who want it all, Bizible is an easy stepping stone
in your journey towards a full data warehouse.
Now that we’ve covered how attribution works and your attribution tool options in Marketo, now
we shift our focus to the art of attribution and selecting your attribution model.

25. 25
THE ART OF ATTRIBUTION:
PHILOSOPHIES BEHIND THE MODELS
The topic of marketing attribution isn’t new,
but the conversation is evolving. Of course,
ask a marketer which attribution model he
or she prefers, and you’ll get an assortment
of responses. From single-touch to complex
regression-based analysis, some marketers
are passionate about a particular method
while others are still contemplating which is
the best option. The topic generates
interesting conversation, to say the least.
As we explore your options, keep in mind all
models are simplified approximations of
an infinitely complex reality, and, no
attribution model is perfect. Attribution
models attempt to estimate the influence of
your various marketing campaigns on
human behavior that is unpredictable,
irrational and fluid in nature. There’s no way
of actually knowing that your white paper or
webinar was responsible for 33% of the
purchasing decision and therefore should
receive a third of the credit. But, even with
the flaws of attribution, applying the
appropriate model, understanding the data
it’s generating, and applying the directional
insights will help you make better
marketing decisions.

26. 26
GETTING STARTED
WITH ATTRIBUTION
Before settling in on a particular attribution model, be realistic about what you want
to accomplish and what you can actually handle. Start by taking an inventory of your needs; the
answers to each of these areas will help guide which model you choose.
>What questions are you trying to answer? Contribution to revenue, pipeline value,
understanding your sales cycle from the first touch to deal closed, which efforts are most
impactful, why leads aren’t converting to sales—what do you need answered to sharpen your
marketing plan and align reporting with your organization’s objectives?
>Is your sales cycle simple or complex? Do you have a lot of marketing efforts or only a few?
>What’s attainable for your organization? Do you have the appropriate tools in place? Are you
just starting with attribution or are you more experienced?
Once you know what you want to achieve, then you can select a model that’s appropriate for
you.
All models discussed in the sections that follow are as defined within Bizible’s platform, unless
otherwise stated.

27. 27
FIRST-TOUCH
MODEL
Stemming from the philosophy that a sale
cannot happen if a customer doesn’t know
you exist, a first-touch model applies 100% of
attribution credit to the first tracked market-
ing interaction, which may occur before the
person even enters your marketing data-
base. The model itself is simple, and data
analysis is less complicated. In a simple sales
cycle with a quick or transactional sale, it’s
very easy to see marketing effectiveness and
contribution to revenue. The challenge with
a first-touch model is data collection,
because you need a way to capture and
store the anonymous first touch and then
associate it with the person when they even-
tually enter your lead database. You can
solve for this challenge with custom track-
ing script and Bizible tracks this out of the
box.
In more complex sales cycles, first-touch
attribution acknowledges the brand
awareness stage, highlighting which of your
early marketing efforts were most successful
at attracting new customers to your product
or service. If you seek to gain insight into
top-of-funnel activity, then a first-touch
model can be useful in providing answers. If
you want to know marketing influence in
later stages of your sales cycle, a first-touch
model falls short as it only tells part of the
story by overvaluing early-stage efforts and
ignoring subsequent campaigns.

28. 28
LEAD CREATION
MODEL
Going beyond brand awareness, a lead
creation model attributes 100% credit at the
point a customer is interested enough to
provide contact information and essentially,
becomes a “lead.” For example, if a customer
visits your website three times and on the
fourth occasion, completes a form for more
information, the marketing effort that drove
the fourth visit would receive 100% of
revenue credit. The philosophy here is the
campaign that converted a prospect to a
lead is the most significant. Many organiza-
tions often start with a lead creation model
because it provides an excellent introduc-
tion to attribution and the set-up is relatively
straightforward.
Like first-touch, this single touch, simple
model does not provide a good representa-
tion of longer and more complex sales
cycles; for that, you need a multi-touch
model.

29. 29
EVENLY-SPLIT/LINEAR
MODEL
A Linear or Evenly-Split model gives equal
weight to every touchpoint with the ratio-
nale that every marketing effort is essential
to moving a prospect through the sales
pipeline. The challenge with this model is it
oversimplifies the marketing process and
fails to take into account the context of
when the interaction occurred when giving
credit.
For example, let’s say a person enters your
database, consumes a few blog posts and
then - a few months later - attends a VIP
dinner and soon after is added to a new
opportunity. With an evenly-split model, the
casual content consumption that did not
occur in proximity to any meaningful funnel
event would get the same amount of credit
as the high-touch dinner that likely made a
much bigger impact on the sale. If you relied
on this model exclusively, you might easily
draw some inaccurate conclusions about
relative channel importance.
Nevertheless, a Linear model can still
provide some insight into which marketing
programs are impactful. If you are tracking
attribution using Marketo and Revenue
Explorer, this is the only multi-touch option
available.

30. 30
U-SHAPED
MODEL
U-Shape is a simple multi-touch model that
distributes credit between the early-stage
touches to provide a more balanced view of
which channels are generating new names
in your database. In this multi-touch model,
50% of the weight is assigned to the first
touch and 50% to the lead creation touch.
The philosophy behind it is to emphasize
lead generation while also sharing credit
between the various touches required to
grow your database. For this reason, many
marketers prefer it over either a First-Touch
or Lead Creation single-touch model for
evaluating lead generation activities.

31. 31
W-SHAPED
MODEL
A W-shaped model is very similar to a
U-shaped model except it acknowledges a
third milestone, opportunity creation. Each
primary stage of the sales cycle, first touch,
lead creation and opportunity creation, is
attributed with 30% of revenue and the
remaining 10% is split between the other
touchpoints. A W-shaped model is one of
the most popular attribution models as it
gives marketers a well-rounded view of the
marketing campaigns leading up to the
opportunity creation stage.
What’s missing in a W-Shaped model is
insight into any activities that occur after the
opportunity is created. For example, let’s say
you organize a special event for customers
and later stage prospects and then several
opportunities close soon after. With a
W-Shaped model, the significant invest-
ment in this event wouldn’t receive any
credit.

32. 32
FULL-PATH
MODEL
Similar to the W-shaped model, a full-path
model also acknowledges major milestones
in the sales cycle, now extending all the way
through the revenue stage. Each significant
stage receives 22.5% of the credit with the
remaining 10% spread across touchpoints in
between. The Full-Path model is obviously
more complete than the W-Shaped model
and is arguably more sensibly-weighted
than an evenly-split / linear model, as the
touchpoints that occurred in nearest
proximity to important funnel events get a
much higher percentage of credit. This can
produce reports that better reflect the
“actual” impact of these important activities
while still giving credit to everything. For
businesses with a complex sales cycle who
want full visibility, a Full-Path model is a
smart choice and remains easy and simple
to implement.

33. 33
CUSTOM
MODEL
A more advanced multi-touch option within
Bizible is the Custom model. With this
model, you can define custom stages in the
sales cycle in addition to those included in
the Full-Path model—a common one to add
is an “MQL” stage. You can then define your
own percentage weightings for each stage
based on your unique business model.
This model offers more flexibility and
requires some extra configuration. Its
relative freedom also brings a certain level of
risk, as the marketer might have inaccurate
assumptions about the relative weightings
that the different stages should receive and
thereby create misleading distortions in the
model.
Companies may want to run a Full-Path
model first, then as knowledge of their
unique sales process deepens, transition to a
Custom model to achieve a more tailored
approach.

34. 34
MACHINE-LEARNING
MODEL
This model uses the same stages as the
Custom model, but in this case, the machine
makes recommendations for weighting
credit between the various stages,
representing the relative importance to
winning a deal based on three criteria:
>Predictiveness: the correlation between
stage progression and whether the deal
will close
>Ease/Difficulty: high conversion rate
implies less importance in the customer
journey
>Uniqueness: if a touchpoint is shared with
multiple stages, the credit is shared, too
The algorithm is not random—Bizible based
it on millions of touchpoints and buyer
journeys. Notice in our example the product
demo stage is now receiving 10% credit,
demonstrating the significance of this event
in the sales cycle. You can use the insights
from the Machine-Learning model to refine
and alter your Custom model, ultimately
producing a machine-learning influenced
model that incorporates human insights
specific to your organization.

35. 35
TACTIC-WEIGHTED
MODEL
In a Tactic-Weighted model, credit is allocated
based on the importance of the specific
marketing tactics involved. For example,
attending a webinar may get more credit
than downloading an e-book, and attending
a prospect VIP dinner may get even more.
This type of model—or one that blends
it with a position-based model defined
above—makes a lot of sense to many
marketers and is popular with those who
believe spending four hours at a high-touch
event naturally carries more weight than
casually perusing web content.
The Tactic-Weighted model is an advanced
model that is not available out of the box,
but it is something an analytically-mature
organization could engineer within a BI tool.

36. 36
As you embark on your attribution journey, remember:
Take an inventory of your needs and start with what’s
attainable. You can always transition to a new model as your
knowledge and understanding grows.
No tool or model is perfect. The benefits far outweigh the
drawbacks and the insights gained will be appreciated across
your organization.
FINAL
THOUGHTS

37. Perkuto is here to help. From getting you up and running
with Bizible to fine tuning your attribution model, our team of
Marketo Certified Solution Architects is ready to consult with
you, talk through your options and implement custom
solutions.
Attribution is both a science and an art—but more importantly,
attribution empowers marketers to make better business
decisions.
JENN STEELE,
VP of Product Marketing, Bizible
If you’re confident in your ability to measure effectiveness,
you’re empowered to test new ideas and innovate.”
“

38. Perkuto helps leading brands orchestrate memorable customer experiences through
flawless marketing operations. Our team of Marketo experts assists in eliminating
infrastructure uncertainties, safeguarding against campaign errors, improving
marketing performance, and executing high-volume campaigns. Perkuto is a certified
service partner for Marketo Engage, Adobe, Bizible, and Microsoft.
Learn more at perkuto.com.
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