iCrossing Capabilities Report - Cross-Channel Attribution Modeling in Action Many brands use a last-click attribution model for their marketing efforts online because they do not know that they have other options...

1. by Kaylan Malm, Manager, Advanced Analytics
with Alan Gee, Manager, Business Intelligence
August 2009
iCrossing Capabilities Report:
Cross-Channel Attribution
Modeling in Action
EXECUTIVE SUMMARY
Many brands use a last-click attribution model for their marketing efforts online because they do not
know that they have other options. iCrossing has successfully integrated data from several sources,
created a display visualization dashboard using the iCrossing Marketing Platform that allows clients
to see what their consumers are doing before they convert, and has created a user interface that
provides KPIs in a manner that helps answer questions and allows for data to be downloaded for
further analysis.
TABLE OF CONTENTS
2 Background: Brands are vastly underutilizing an ocean of cross -channel attribution data
Accurate cross-channel attribution models allow marketers to create holistic online strategies
Multi-channel attribution research is actionable
3 Mining a Wealth of Information: Data aggregation and integration
Dataset includes conversion channel, site visits prior to conversion (“assists”) and display impressions
Study focused on one client
3 Making Sense of it All: Data visualization
Data timeframe includes conversions from September 2008 – December 2009
Consumers may find websites through search or display, but will return through a referring or typed in URL
Report shows results from Conversion Funnel, Keyword Funnel, Conversion Mix, Channel Conversion Mix,
Source Conversion Mix and Visit Conversion Mix
10 Conclusion: Cross-channel attribution model dashboards successfully integrate data from several sources
Clients can see what consumers are doing before conversion
The display process methodology allows clients to test models that are most appropriate for their businesses

2. AUGUST 2009Cross-Channel Attribution Modeling in Action
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Background: Brands are Vastly Underutilizing an Ocean of Cross -Channel Attribution Data
The importance of cross-channel tracking in the digital and interactive space is an exhausted topic; what marketers are now
appropriately focusing on is how to implement and analyze cross-channel tracking to correctly attribute conversion credit.
By creating attribution models that more clearly and accurately depict the role of each channel and visit to a site prior to a
conversion, marketers are creating the framework for creating holistic online strategies. The challenge with these models is
not motivating the need, but understanding how to collect and integrate data across channels in a meaningful way that can be
visualized and analyzed. This paper demonstrates how iCrossing’s business intelligence analysts are making this goal a reality
for our clients and the doors that get opened when this type of data set can be gathered.
“To gain efficiency and deeper understanding of campaign effectiveness, marketers must implement attribution measurement
via click-path tracking, data mining, and predictive modeling.” (“Search and Attribution” November 2008). Most marketers
understand the importance of cross-channel tracking, but most don’t even know where to begin to start putting the cross-
channel dataset together. Most companies still use a last-touch conversion model attributing all conversion credit to the site
visit when the conversion takes place, while a small group relies on the first-touch conversion model of attributing all the credit
to the first customer visit to the site regardless of the channel through with the conversion took place. Both of these methods
are flawed and most marketers know it, they just don’t know how to fix it. “Search marketers that assign 100 percent conversion
value to the so-called last click leading to a conversion often unfairly remove much of the brand value in their display ads and
overemphasize the value of keywords that immediately precede a purchase or lead.” (“Search and Attribution” November
2008). While this is true for search, most of the research on this topic is flawed as well by not considering conversions from
referring URLs and direct loads, but rather by focusing only on media channels. “The last-click model is such a problem that
one-fifth of advertisers rely on gut feeling when evaluating the success of brand campaigns online.” (“Transitioning from the
Last-Click Model” July 2008). This is corrected by using a first touch conversion model, but this method also has its challenges
for the same reason of not capturing the entire picture. When data fails to answer the entire question, markets fall back onto
the measurement tool of comfort – their gut. But in an age where we have access to so much data, we just need to learn to use
data in a smarter way.
According to Forrester’s recently released “A Framework for Multicampaign Attribution Measurement” (February 2009), “Of
275 Web site decision-makers surveyed in 2008, a full 52 percent agree that attribution would enable them to spend marketing
dollars more effectively. Yet only 31 percent are actively using attribution today, even though this concept is not new for
marketers, who have long since appropriated credit to marketing endeavors in dubious ways.” Forrester’s research points out
that the 31 percent who say they are currently using attribution today likely have differing definitions of what multi-campaign
attribution is and we suspect most aren’t using it to its full ability. “Cross-channel management allows coordination of all
marketing initiatives: messaging and creative development, media buying, and analytics that allow marketers to measure the
influence of seemingly disparate campaigns on each other.” (“Search and Attribution” November 2008).
The problem is that marketing analytics tools on the market are specialized based on the channel and purpose, often aggregating
information in a way that makes it difficult to match records across systems. According to Juniper Research, a Forrester
Company, “In reality, the technology and benchmarks to achieve accurate attribution are in the early stages.” (July 2008).
Forrester outlines the following problems clients encounter when trying to gather this data:
+ Extended sales cycles mask the impact of first clicks
+ Independent tracking systems result in fuzzy math that doesn’t add up
+ Search looks heroic, but advertising really provides lift
Advertising such as display media is not the only channel getting let down by last-click conversion tracking, but that conversions
credited to referring URLs and direct load traffic will give up partial credit to both media and search channels.
iCrossing’s multi-channel attribution research is not conceptual, it is actionable. Our solution is presented in detail in the following
pages and was built using client data to meet specific objectives. We focused on the process because findings are unique to
every client and therefore should not be generalized. The important task at hand is to identify how to arrive at that solution.

3. AUGUST 2009
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Cross-Channel Attribution Modeling in Action
Mining a Wealth of Information: Data Aggregation and Integration
The most daunting task of multi-channel campaign tracking is gathering the appropriate data set for visualization and analysis.
Using Interest2Action (I2A), a site analytics tool proprietary to iCrossing to collect all of the customer visits data, we kept the
data integration to a minimum. I2A uses a site-side pixel to collect cross-channel visits and stores data for the lifetime of the
cookie, a characteristic that is helpful for clients with longer purchase cycles. The dataset provided by I2A includes: channel,
referring URL, timestamp, keyword searched and engine for all search visits, ad campaign and size for all display media visits,
type of conversion, and revenue. While I2A captures all site visits, for the purpose of this research we looked at the conversion
channel and up to six site visits prior to the conversion which we refer to as “assists.” I2A also collects data on direct loads and
referring URL conversions, two channels that are often ignored by the solutions proposed by media channel tools.
The only data missing from the I2A dataset was display impressions, an important factor when testing the hypothesis that
display media is often under credited when it comes to conversion tracking. Partnering with Atlas, we pulled cookie-level
impression data after passing a unique identifier between I2A and Atlas during the display campaign. Matching this data back
to the I2A conversion file, we added display impressions into the site visits and conversions data, creating a dataset that then
told the entire conversion story. The concepts presented below and the data shown are for one particular client, but the method
of data collection and analysis presented are true of all clients using I2A, and with some hard work and data integration these
could be gathered through many other Web analytics tools. iCrossing’s control over the I2A tool has helped to streamline the
process for clients using our proprietary tools.
Making Sense of it All: Data Visualization
After the cross-channel dataset is collected, we set out to aggregate and visualize the data. The trick to cross-channel
reporting is to only aggregate the data after all the channels are incorporated; aggregating before each channel is added leaves
the story incomplete. The amount of data for most clients is overwhelming, but iCrossing’s business intelligence team and the
iCrossing Marketing Platform are the perfect team to take on the challenge and specialize in data integration and display. Using
the iCrossing Marketing Platform, we created a standard user interface for multi-channel marketing attribution and focused the
UI on helping us answer the following questions:
+ How do we attribute credit to assists?
+ What is the true marketing attribution across channels? How is it different from traditional last-click attribution?
+ Is display media “assisting” other media channels?
+ Is direct load and referring URL traffic taking conversion credit away from media and search channels?
+ Does the search keyword funnel show searchers going from general to more specific brand keywords when they are closer
to converting?
+ Do customers that see display ads more frequently convert on branded keywords?
The iCrossing solution is focused on data integration and visualization to analyze the customer journey and attribution models
that will be unique to each client. We do agree with Forrester that an attribution model should address recency, frequency, and
time on site (“A Framework for Multicampaign Attribution Measurement” February 2009).
The dashboard consists of four data tabs including: Attribution, Conversion Funnel, Keyword Funnel and Conversion Mix.

4. AUGUST 2009Cross-Channel Attribution Modeling in Action
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Attribution (Figure 1)
The Attribution tab of the Cross-Channel Attribution Modeling dashboard (Figure 1) is designed to show the Conversions by
Attribution, as well as the Conversions (+/-) Assists. The reports are described within the dashboard by hovering over the (?) icon.
The Conversions by Attribution is the display of Conversions using the client’s attribution model rather than the commonly-used
Last Click Attribution. In this case, we gave equal credit to any visit to the site prior to the conversion, and then added that credit
up across each conversion to get the new attribution model. For most clients, the model would be much more complicated and
involve a mixture of recency, frequency, time on site and channel weighting, but the important feature is that clients can redesign
the attribution model and display their new attribution, not just last click attribution.
The Conversions (+/-) Assists report shows the difference between the client’s selected attribution model and the traditional last
click model. This shows net change from the last-click to full conversion attribution. In this example, when we give equal credit
to all visits (not weighting based on recency, time on site or channel) and compare that to the model where only the last click
receives full credit, then we see that natural search (2.9 percent), paid search (1.3 percent) and direct load (1 percent) receive more
credit than they are currently receiving with the last click model, while Referring URL lost 5.2 percent of its attribution credit. This
supports the generally accepted idea that consumers may originally find a site through search or display, but will come back to the
site later by either typing the URL or visiting the site through a referring URL when they eventually convert. The Conversion (+/-)
Assists report gives credits to all the other visits leading up to the action. By looking at conversions in this manner, we predict that
most clients will see that their natural search, paid search, and display media channels deserve more credit for conversion than
they are currently receiving using a last click model.
On each dashboard tab you can also select the timeframe. In this case, the time controls the month of the conversion and will
pull all subsequent visits to the site, even if they occurred before the beginning of the month. A filter can be added for clients
who want to look at only at visits within a particular timeframe of the conversion. Also, below each graph the table of raw data is
provided and can be exported to Excel for additional analysis if needed. You will also notice on all the dashboards that there is a
Conclusions section that can be edited by business analysts to provide key findings and insights.
Data Source: Interest2Action, Merchantize; Data Timeframe: Conversions that took place from September 2008-December 2009, adjustable through the
provided drop down menus.

5. AUGUST 2009
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Cross-Channel Attribution Modeling in Action
conversion funnel (Figure 2)
The Conversion Funnel tab provides a more granular view of the journey that customers take before the conversion. The default
page shows the top five most common conversion funnels where the conversion channel is ‘all channels,’ but from the Conversion
Channel drop down, you can choose Natural Search, Paid Search, Direct Load, Display, Referring URL, and Social Media.
Choosing another channel will show only conversion funnels that converted on the chosen channel and are useful to service line
experts. In all cases, the visits’ paths start at the top showing the first visit to the site within the conversion timeframe, and the last
visit that resulted in the conversion is shown at the bottom of the funnel. Using the ‘1st’ Channel as an example, this means that
the most common conversion path for this client was visitors who first came through Direct Load, then later visited the site through
the same channel, Direct Load. They represent 17.5 percent of total conversions during the time frame (775 total), and on average
it took them 7 days to convert between their first visit and their conversion. More interesting are the 2nd and 3rd funnels that show
that Natural Search or Paid Search is the channel visited first, but the conversions actually came through Referring URLs, together
those represent a total of 23.6 percent of total conversions.
At the bottom of the dashboard, you can also choose to see All Conversion Funnels if you want to see more than the top 5, and
also switch the funnels to see the First Touch analysis for clients that use a First Touch attribution model.
Data Source: Interest2Action, Merchantize; Data Timeframe: Conversions that took place from September 2008-December 2009, adjustable through the
provided drop down menus.

6. AUGUST 2009Cross-Channel Attribution Modeling in Action
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The Keyword Funnel tab (Figure 3) is similar to the Conversion Funnel tab except it focuses only on conversions that came
from search. In the drop down menu you can also choose to look at conversions from only Brand or Non-Brand search. The
keywords for both Natural Search and Paid Search were then labeled as brand and non-brand to show keyword cross-over.
For this client there was little cross-over between branded and non-branded search or between search and other channels. The
Percentage of Conversions, Total Conversions, and Average days in funnel metrics are also provided for the Keyword Funnel.
CONVERSION MIX (Figures 4,5,6)
By selecting the Conversion Mix tab, you can see the most granular data provided in this dashboard. In the drop down you can
select the Conversion Type as Channel, Source, or Visit to see three separate reports.
Data Source: Interest2Action, Merchantize; Data Timeframe: Conversions that took place from September 2008-December 2009, adjustable through the
provided drop down menus.
keyword funnel (Figure 3)

7. AUGUST 2009
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Cross-Channel Attribution Modeling in Action
CHANNEL CONVERSION MIX (Figure 4)
Data Source: Interest2Action, Merchantize; Data Timeframe: Conversions that took place from September 2008-December 2009, adjustable through the
provided drop down menus.
The Conversions by Channel (Figure 4) report shows the number of channels used before a conversion. For example, if a user
comes to the site on their first visit from display, then from paid search, and finally converts through a referring URL, that is three
total channels. On the other hand, if a visitor comes three times all through natural search, that is only one channel. In this
example, the fact that one channel represents 85 percent of total conversions shows that consumers for this brand are unlikely
to switch from one channel to another during their journey to an eventual conversion. This same metric is trended over time in
the Conversions by channel timeline and the raw data is provided at the bottom of the KPI panel.

8. AUGUST 2009Cross-Channel Attribution Modeling in Action
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SOURCE CONVERSION MIX (Figure 5)
The Source Conversion Type (Figure 5) report in the Conversion Mix tab will load a report very similar to the Channel selection,
but instead of showing the number of channels, it shows the channel that lead to the conversion. This is the traditional last touch
attribution model and is provided for clients for comparison purposes.
Data Source: Interest2Action, Merchantize; Data Timeframe: Conversions that took place from September 2008-December 2009, adjustable through the
provided drop down menus.

9. AUGUST 2009
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Cross-Channel Attribution Modeling in Action
The last report provided in the iCrossing Cross-Channel Attribution Modeling dashboard is the Visit Conversion Type (Figure 6). This
report shows the number of visits prior to a conversion. For this example, more than 75 percent of conversions happened on the
first visit, but there are one percent of customers that visit the site more than seven times before converting. Using the Conversion
Funnel tab, users can explore these funnels more to determine the channels these frequently visiting consumers are using.
VISIT CONVERSION MIX (Figure 6)
Data Source: Interest2Action, Merchantize; Data Timeframe: Conversions that took place from September 2008-December 2009, adjustable through the
provided drop down menus.

10. AUGUST 2009Cross-Channel Attribution Modeling in Action
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CONTACT
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References
Andrews, Evan. “Search and Attribution: Maximizing ROI in a Tight Economy.” Jupiter Research, a Forrester
Research Company. November 24, 2008.
Lovett, John. “A Framework For Multicampaign Attribution Measurement.” Forrester Research. February 19,
2009.
Riley, Emily. “Attribution: Transitioning from the Last-Click Model.” Jupiter Research, a Forrester Research
Company. July 28, 2008.
Conclusion
By building Cross-Channel Attribution Modeling dashboards for our clients, iCrossing has successfully integrated data from
several sources, created a display visualization dashboard using the iCrossing Marketing Platform, allowing clients to see what
their consumers are doing before they convert, and has created a user interface that provides KPIs in a manner that helps
answer questions and allows for data to be downloaded for further analysis. Our transparency in this process shows the
industry that we are creating actionable solutions to client needs and providing those solutions. We aren’t just talking about the
importance of cross-channel attribution; we are doing it because we agree with Forrester that “Agencies and service providers
must provide increasingly approachable solutions for attribution to become the de facto measurement model.” (“Transitioning
from the Last-Click Model” 2008).
The data integration and display process methodology presented above allows clients to appropriately attribute credit to assists
from other channels and even test several models to determine the one that is most appropriate for their business. Once the
attribution is determined, the models can be compared to the traditional last click model. This can help to explain how display
media is assisting other channels, and to determine how much credit media and search channels are giving up to referring URL
and direct load traffic. Also, by looking at keyword break outs, clients can see how branded and non-branded search terms
fit into the conversion funnel differently, and if seeing display ads causes users to search brand terms more frequently. All of
these questions are addressed in industry research, but clients are now asking for, and deserve to see what their customers are
doing before converting on their site. iCrossing’s approach now makes that possible.