When Adobe Systems launched a new digital
marketing campaign for Adobe Marketing Cloud, a
collection of integrated online marketing and Web analytics solutions,
it used conversion rate as a key metric to measure success. Conversion rate is
“the ratio of conversions over a relevant denominator” (WVU, 2015). A
conversion happens when a visitor to a website takes an action the digital
marketer wants them to take, whether it’s making a purchase or downloading a
white paper (Qualaroo, n.d.).
The goal for Adobe’s Marketing Cloud campaign
was to convert more visitors to its website into solid leads. Since the campaign
launched, Adobe has seen a higher number of inquiries over
pre-campaign averages (Adobe
Systems Incorporated, n.d.). Perhaps Adobe’s conversion rate is based on the
number of visitors that submitted a form to request more information. Company leadership may have decided that in
order for this digital campaign to be successful, the conversion rate of this
form needed to increase by 10% over pre-campaign averages.
The key performance indicator (KPI) set by
the leadership is being reported at the aggregate conversion rate as a 10%
increase on form submissions for the site’s entire universe. Adobe also needs
to apply conversion rate to a segmented universe as well. A segmented universe
is a subset of traffic defined by some period of time, campaign (i.e., banner
ad), referrer, etc. Company leadership may measure success by this KPI;
however, the digital marketer needs to dive deeper than just the aggregate
conversion rate (WVU, 2015).
For example, part of Adobe’s new digital
marketing campaign may have included a series of banner ads. Adobe’s digital
marketing team would need to know which of the banner ads it is running,
converted to the most and least visitors. Adobe may find a banner ad on
PCWorld.com converts fewer visitors than a banner ad on CIO.com. Why? Perhaps
CIO.com is the better target audience for Adobe Marketing Cloud. Whatever the
underlying reason, with limited budgetary resources, a digital market has to be
able to spend limited resources wisely. As a result, Adobe may decide to stop
advertising with PCWorld.com based on data and not a gut reaction. This money
could then be reallocated elsewhere.
To determine the conversion rate for these
individual banner ads, a unique URL can be created for each one using tools
such as Google’s URL builder (https://support.google.com/analytics/answer/1033867?hl=en).
This tool adds custom campaign parameters to your URLs (Google, n.d.). Goal
funnels can then be up in an analytics program to report the conversion rate on
these URLs (banner ads). Adobe would then be able to see out of the referring
banners, identified by their unique URLs, which one had the most and least
users submitting the request more information form.
If Adobe is looking to increase or optimize
its conversion rate, it can identify trouble spots by looking at and analyzing other
key metrics such as bounce rate, exit rate, average time, and average page
views. Understanding what’s going on behind these numbers is the first step in
devising a plan to improve conversion rate. A high bounce rate means people
aren’t finding what they’re looking for; so, they’re leaving immediately. Exit
rate is the percentage of people who leave after viewing the page. Therefore, a
page with high exit should be a red flag. If average time on site is low,
visitors aren’t sticking around long enough to convert. When it comes to
average page views, while more page views may mean more engagement, it can also
mean a lack of clarity in your conversion funnel if there’s no conversion. By
improving upon these metrics, conversion rates will increase (Qualaroo, n.d.).
References
Adobe Systems Incorporated. (n.d.). It’s the ultimate case study: Ourselves.
Retrieved from http://success.adobe.com/en/na/programs/ultimatecasestudy.html
Google. (n.d.). URL builder. Retrieved from
https://support.google.com/analytics/answer/1033867?hl=en
Qualaroo. (n.d.). What is conversion rate optimization? Retrieved from https://qualaroo.com/beginners-guide-to-cro/what-is-conversion-rate-optimization/
WVU. (2015). Lesson 2: Basic web analytics. Retrieved from
https://ecampus.wvu.edu/webapps/blackboard/execute/displayLearningUnit?course_id=_29082_1&content_id=_1454153_1&framesetWrapped=true
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