Who knew understanding behaviors is as easy as 1, 2, Cohort Analysis? Our search rock stars did! In this POV, Matthew Howell and Jessica Kichline explain what the Cohort Analysis report Google added means to understanding data and behaviors and how it will ultimately help search campaigns

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POINT OF
VIEW
Data drives decision making, and in 2015 this
has never been more true. As more innovative
marketing tactics and technology come to
fruition, a more complex way to track user
experience and user behavior has become
increasingly necessary. Google has begun to
address the need for enhanced user behavioral
analysis through the introduction of two new
reports to its analytics suite. The new features
include an “Active Users” report, as well as a
“Cohort Analysis” report. Cohort Analysis is a
way to look at groups of users over time in
order to assess how and why their behaviors
differ.
Cohort Analysis will be a quintessential assessment
tool moving forward as it can help drill down to
Turning Data into Conversions: A Primer
on New Developments in Behavioral
Analysis
March 2015
Discovering Micro Trends
Cohort Analysis report in Google Analytics
pinpoint the differences in acquisition,
engagement, retention, and response to marketing
efforts.
This report tracks a user’s behavior from their
“acquisition date,” with acquisition date
interpreted as their first interaction with your
website. From there you are able to measure
trends in retention over periods of time, as well as
the different interactions a user has with your
brand over a day, week, month, etc. This can help
to uncover how frequently users are returning to
your websites and the reason why as it relates to
your advertisements and marketing efforts.
For a display campaign running different creative
executions you’d use this report to analyze
behavioral trends amongst users once they’ve
arrived on your site via a display ad.

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This report will allow you to view the points at
which users who saw your creative re-engage
with your website, and then segment them
based upon patterns you discover. If you
observe a trend of users who saw the branded
creative on a Monday, and then return to your
website on Thursday but typically never return
again, this is an actionable insight. You could
use this insight to identify the best points for re-
engagement, or dive deeper into why site
visitors who view this execution only return to
your site once. Could it be the content or user
experience is not optimized to their needs?
These are all questions that Cohort Analysis will
help you better understand and hopefully
answer.
Likewise, if you observe that typically users who
viewed your unbranded creative on a Monday,
returned Tuesday, and then came back to
convert on Friday, you can use this insight to
improve the efficiency of your campaign.
Perhaps you allocate more impressions toward
unbranded executions due to them leading to
more conversions. Or maybe your display
rotations on Mondays skew more toward
unbranded because you know that users
who’ve viewed ads on a Monday typically
convert the following Friday. These more
advanced optimizations are all possibilities
through micro trends that are more evident
through Cohort Analysis. The options are
limitless; there will soon be more ways to
segment your users and their behavior than
there is time in the day for the assessment of
them.
Engagement metrics are transitioning toward a
model that is much deeper than bounce rate,
time on site, and pages per session. Micro
trends observed can help you hyper optimize
your campaigns, but another great feature of
the Cohort Analysis report is the enhanced
understanding available of user retention.
Getting users to your site at efficient rates is a
staple of any good paid marketing campaign.
The next measure of campaign efficiency is that
those users who you’ve efficiently driven to
your site are engaging with your content.
“Engagement metrics are
transitioning toward a
model that is much deeper
than bounce rate, time on
site, and pages per session.”
The evolution of behavioral analysis will soon
allow marketers to see that a one-time engaged
visitor is not necessarily a success. Brands want
loyalists, and must begin to devote more time
to measuring the affinity of those who become
aware of their brand through marketing efforts.
It ultimately will be more productive to market
to users who frequent your site once a week, or
once a month, over those that are engaged for
a single visit.
Engaging Users vs. Retaining Users

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The retention aspect of Cohort Analysis will
provide a day by day, week by week, or month
by month view of when users are disengaging
from your website. This information is critical to
knowing how to address the ebbs and flows of
visitors entering and exiting your brand site.
“Search behavior is
ultimately different in
terms of branded vs.
unbranded search.”
Active Users Report in Google Analytics
Enhanced Paid Optimizations
From a Paid Search perspective, Cohort Analysis
will be particularly beneficial in optimization
and persona creation within the campaigns. We
will be able to track behaviors on both a
monthly and weekly basis and identify patterns
in search behavior. This will allow us to identify
the relationships between the content and the
behavior for both branded and unbranded
campaigns. Many marketing campaigns are
deemed successful based upon topline metrics
that do not tell the story of what a user does on
site. A CTR of 3% may give the impression of a
success, however these new additions currently
in BETA brought to you by Google offer an
opportunity to dive deeper.
Search behavior is ultimately different in terms
of branded vs. unbranded search.
For branded terms the user is pre-qualified as
they’re either already a customer or at the very
least familiar with the brand. Unbranded is a bit
more open ended and allows the advertiser to
win over the user with key actionable insights
and unique value propositions. Using Cohort
Analysis, we would be able to develop a
strategy not only based on user retention for
time of day or day of week, but also use our
previous knowledge of user behavior based on
the type of campaign for another layer of
granularity within the analysis.

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Matt Howell
Senior Search Analyst
Communications Media, Inc.
Jess Kichline
Senior Search Analyst
Communications Media, Inc.
Analysts:
• Observe the quickest paths to conversion
based upon multiple engagements.
• If we were to A/B test landing pages
on any given campaign, we could
identify with this new Beta if one
page garnishes a quicker conversion
than another and how content assists
with conversion funnel. This will also
allow us to bid differently, reallocate
budgets effectively, and even
potentially rework messaging to
accommodate these changes in the
campaign.
Most importantly, this new analysis tool will
allow for a more general understanding of the
HCP and consumer search habits, and opens the
door for more proactive, intuitive account
structure in the future. The engaged user is of
the utmost importance to all brands, and how
we measure engagement is beginning to evolve
across display, paid and organic search. A much
more robust way of conducting behavioral
analysis of website visitors is coming soon, and
layering in this data with current campaigns is
the next step in brands separating themselves
from the competition.
Cohort Analysis will ultimately help the search
campaigns within the following areas:
• View specific acquisition dates to measure
whether receiving a click on a certain day
promotes more continuous engagement when
compared to other days.
• Optimize more thoroughly on a CTR and CPC
basis, especially if there’s data that shows
returning visits before converting (which will
ultimately skew the goals of the account).
• If data shows that a user engages with
the site 3 times before converting at an
average CPC of $1.25, this analysis
would help evaluate what an
appropriate goal would be in terms of
CPC/CTR as such. Would it be more
beneficial to make the goal $3.75
instead? Maybe. It depends on the
profitability of that user.
• Measure CPCs based upon user retention.
• If we’re able to establish that certain
keywords result in continued
engagements over longer periods of
time, then we’ll be able to provide a
different baseline in terms of what is
acceptable to pay per click for that term.
• If “keyword A” has a CPC of $5 and once
a user visits the site they never visit
again, is that better than paying $17 for
“keyword B” if we know that this user
typically returns 4 times from other
unpaid mediums?