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3512 LS Utrecht
The Netherlands
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www.adlantic.nl
[email protected]
Conversion Attribution and Cross Online Media Effects
AdLantic Online Advertising B.V. | Kamer van Koophandel nummer 30225228
BTW nummer NL817861816B01 | ABN-AMRO Bank 24.48.29.756
1
The consumer is changing
It’s time to look ahead. The online advertising experience is changing rapidly, meaning that the communication with
the consumer also needs to
change. The consumer has access
to more information than ever
before, thanks to their
smartphones, tablets, television
and many other devices. This
“super connected” consumer is
asking for a change in the way we
think of online marketing.
Multi Touch point
The market, according to research
agency Forrester, is in need of a
multichannel marketing strategy.
The habit of thinking in separate
marketing channels has to change
into “Multi touch point thinking”.
Based on this, Forrester has
developed the Multi touch point
model, which is depicted in chart
1.
Chart 1
The right message at the right
time
In the Multi Touchpoint-model, the moment of contact with the consumer is central. The consumer anno 2012 is
always connected and consumes information via countless offline and online channels. It is important to show the
right message at the right moment to the right consumer.
Online display and the model
Online display campaigns are an important part of multichannel marketing thinking. Through various touchpoints
display carries messages from the web, mobile and social media.
Measuring is better
AdLantic has developed techniques and tools to set up online display campaigns the right way and make the
necessary measurements. In this document we will focus on these measuring tools, looking beyond CTR and “last
click conversions” per channel.
Conversion attribution
Last click measurements leads to silo approximation
A marketer in the cross medial world uses different online channels to reach his or her goals. SEO, SEA, display and
social media are these days all a part of almost every marketing plan. To measure and weigh the effects of these
channels a “last click” analysis is often done.
The Multi-Touchpoint model makes it is clear that most touchpoints do not result in a conversion. Touchpoints like
discover and search/research contributes to a following touchpoint. They deliver the assist, but are not the last
touchpoint before the conversion.
Marketers cannot judge branding campaigns on their assist value since most analysis tools are not designed for this.
The campaigns therefore mainly gets judged based on “last click conversions”. This could be compared to judging a
central defender on the amount of goals made against his team in a soccer match.
The consequence of this is that campaigns with a discover/search/research goal are judged based on the wrong KPI’s
and therefore eliminated. This irrevocably leads to a situation where only campaigns without any cross media effect
remains; the so called marketing silos.
Sub KPI’s
This is of course not a new problem. Different contact points are also judge based on sub KPI’s (assist values).
Examples of these are; giving contact details or viewing a product page etc. It remains very difficult to estimate the
value of these KPI’s. In soccer you can’t compare one assist to another, because how crucial was an assist really and
did the person making the assist also get an assist?
Conversion attribution – Calculating the value of an assist based on business rules
To emphasize the added value from all channels, AdLantic has developed a conversion attribution tool by the name
of Source Map. This tool measures and weighs all clicks during the purchasing process. Everything is registered, from
the first oriented visit (through e.g. a banner) until the actual purchase (e.g. via Google Paid). With Source Map it is
possible to track the whole journey. Because of that all the different online channels receive a fair value for each
touchpoint.
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Business rules
The division of the “conversion value” is done through linear business rules. A couple of examples of business rules
are:
First interaction conversions: The conversion value is completely accounted to the first point of contact (within a
pre-decided cookie time)
Last interaction conversions: The conversion is completely accounted to the last point of contact.
Proportional distribution: The conversion value is evenly distributed through all contact points prior to the
conversion (and within the cookie time).
Involved conversions: Within how many conversions was a marketing channel involved.
Weighted proportional distribution: The conversion value is distributed over all involved points of contact, but these
are also subsequently weighted. Factors such as page views and relevant webpage’s are also important factors.
First/last interaction: The first and last point of contact is assigned a fixed percentage and the rest is evenly
distributed.
Last X interactions: Only the last X points of contact are assigned a conversion value, according to a fixed division
(e.g. 20% - 30% - 50%)
(Proportional) assisted conversions: Amount of assists caused, possibly weighted against the size of their
contribution.
Chart 2
Analyse all channels
Source Map gives insight to the channels that contributed to a conversion. Additionally it gives insight to how these
contributions looked. In this way you can see per channel what the origin- and destination URL’s were.
In chart 2 you can see all conversions per marketing channel. It is of course also possible to zoom in further to see
per conversion which channels contributed. In chronological order it is shown which touchpoint took place through
which referrer.
Point of Contact per separate conversion
In the example below the points of contact a customer had with a travel organization before he booked a trip to
Turkey (the conversion) are visible. In the example below it becomes clear that Zoover contributed greatly to the
Research and Compare point of contact. The actual sale took place through a Google search. Using this data, the
conversion cannot solely be contributed to Google (last click) but also to e.g. Zoover, which clearly contributed to
various points of contact.
Chart 3
Reporting possibilities
Working with Source Map offers numerous different reporting possibilities. An extract from some of the possibilities
can be seen here below. The various reporting possibilities give insight to the added value of the channels from all
(post click) points of contact to the conversion and beyond.
The data and the options for graphic-rendering are adjustable by the user. In this way every marketer can adjust the
cockpit to his or her wishes.
Involvement
In Source Map it is possible to see how many
percentages of the conversions originated from one
channel. In the example to the right it can be seen
that Google Paid were involved in 8% of all
conversion through a point of contact. Based on this
information it can be seen if Google Paid lives up to
its expectations.
Reoccurring conversion paths
The chart below gives insight to the most reoccurring
conversion paths with the associated time to
conversion.
Chart 4
Chart 5
Time to conversion
In case you want to know where in the Multi-Touchpoint model a given marketing channel belongs, you make use
of the time to conversion reporting.
Chart 6
First versus last click
In chart 2 it was already clear that there are
various algorithms that the input of a
marketing channel can be judge upon. Since
every algoritm gives different values to a
channel, it is handy to be able to be able to
compare these. In the picture to the right
these comparisons are shown over time. The
first click conversions from paid search are
Chart 7
here compared with the conversions based on
last click. In this way you can conclude that
paid search especially has a good score based on a last click basis.
Journey time per day
As a marketer you of course also wants to
gain insight into the average journey time a
visitor takes to convert. This is the period
between the discover-phase until the
purchase-phase. This can of course differ
per product. In the figure to the right the
journey time per day is shown from a
selected group of products.
Chart 8
Turnover per marketing channel
To determine the effectiveness of all
marketing channels, one of the reporting shown below can be used. Here the total obtained turnover per marketing
channel is shown. This gives marketers the possibility to quickly see how the ROI per channel is divided. In the chart
below last interaction conversion (last click attribution) has been used.
Chart 9
Infinite reporting possibilities
Source Map is capable of many other reporting possibilities and the functionalities grow by the day.
Implementation
The implementation of Source Map consists of placing a so called pixel on all page’s where the contact takes place.
This pixel registers the behaviour of the visitors. As soon as the Source Map is installed the results can be viewed and
graphic reports can be downloaded via a “dashboard”.
Cross Online Media Effects (COME)
Is conversion attribution too limited?
Although normal conversion attribution tools such as the Source Map gives a lot of insight in the correlation
between the different marketing channels, the crucial question of a marketer remains unanswered. “What is the
real difference between marketing channels, seen from a Multi-Touch point model and a cross media reality?”
Normal conversion attribution tools use business rules. In this case the algorithm decides how the value of each
marketing channel is calculated.
Post click and post view regression analysis
The positive effect of an integrated marketing strategy manifests itself not only through direct clicks that can be
analyzed through Source Map but contact points can also take place via an impression. Within the Discover-phase it
is for example very possible that a branding impression is sufficient as a contact point.
To measure this post click/view value of the campaign AdLantic has developed “COME” (Cross Online Media Effects).
With COME, marketers can measure the value of the campaigns, in which phase they are used. Additionally
extensive statistical analyses are used. The real added value of a marketing channel is now calculated based on a
regression analysis
COME gives a full overview of your marketing channels performances. Through this you know exactly which channel
contributes more or less and which channels support each other.
Post view effect, cross medial calculations
COME foremost offers an analytic environment, where the post view effect can be measured in the shape of
possible increased conversion ratio’s of all/individual marketing channels.
In this way it is for example possible to judge the effect of the branding display campaign already in the discovery
phase.
Chart 10
The above chart gives another example how high the post view effect of paid search was.
Post view effect, how many extra conversions were achieved thanks to an online display campaign
COME analyses (subsequently) the cross media effect, through a so called test/control group design. With every
analysis the visitors of your website are divided into 2 groups; one group that did see the banner and one group that
did not.
Thanks to the control group you can calculate the expectation of the test group. If the results of the test group
significantly deviate from the control group (chi square test), then the deviation is casual – and therefore caused by
the display campaign. In this way you can exactly calculate how many additional conversions are made due to the
online display campaign.
Chart 11
In this chart it can easily be seen, through the top line, how many additional conversion an online campaign
contributed to.
Why Source Map and COME
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Insight in both the post view and post click value of channels
Analyse all contact points from “discover” to “purchase”
Lose the “Last Click Counts model”
Judge all online marketing channels in a true way