some context to the analysis metrics, it is important to understand the context
of the demo data.
hypothetical company, Panoply Technologies, is a vendor of time and event
management software. To boost sales they have decided to run an event in New
York, and have built a marketing campaign to deliver this. One of the key
elements of this is an email marketing campaign. An initial target list was
developed from a segmented group
created in CRM (screenshot below). Given that the event is being held in New
York, the event organiser was able to create a group in CRM based on prospects
whose companies are in the NY area (Territory: US East), thereby increasing the
likelihood of them attending.
the "E-marketing Wave Activity Analysis" tab (screenshot below) you will see a
range of metrics you can use to assess how this campaign performed. Each link
brings up its own list of data which can then be used to create new groups
(instant segmentation). This data can also be exported to either excel or PDF
format for further analysis.
starting point for your analysis is the "E-marketing Results Summary" line
which gives you an instant overview. Of the 36 people on the initial target
list, 34 mails were submitted, 31 sent and 5 bounced. There were 27 unique
opens and 34 unique clicks, with 68 clicks in total. Let's take a look at some metrics.
Opens & Clicks
& clicks" are the first major indicator of campaign performance (see
screenshot below). This report provides you with details about how your email
recipients interacted with your email and gives you unique insight into your
customers' behaviour and interest.
The use case
for this metric starts with looking at the relationship between the opens and
volume of opens/Low volume of clicks - a
repeated number of opens suggests that there is an interest in the email
content, and that your subject line appears to be successful. However the low
number of clicks would suggest that the next step in the process - that of
driving behaviour by bringing the customer from the email to the company's own
platform - isn't as successful. Check your links and decide if you need to
"hold back" some information from the email core content to produce the desired
volume of opens/High volume of clicks - this is
an engaged reader who could now be termed a prospect. Follow up/retention
emails are essential now to keep this person's attention and bring them to a
further step in the process - "consideration" of your offer.
volume of opens/High volume of clicks - this
recipient may be a typical email "scanner" who is pressed for time. The subject
line is bringing the person to the core content, but he/she is not coming back
to the mail more than once or twice. Given the high number of clicks, this
individual may become a prospect; however specific segmentation based on the
first email's content will be required to engage this person further.
volume of opens/low volume of clicks - the fact
that this person has opened the mail at least once points to some level of
interest (and therefore you could have a good subject line). However on
opening, this person may realise the content isn't that interesting or
relevant. You should try a further segmented mail to see if this behaviour
changes - if they move to the "unopened" metric, then it may be time to clear
them off your list.
action is to "create new group" based on the various profiles above. Use the
filtering button on the right to define your open/click ratio before creating
Opens by time and unique opens by time
metrics are related, however have been separated out to improve the usability
of the reporting feature.
The opens by time screen (below) lists each individual time that a user
has opened your mail. So if the person has opened it 5 times, you will see 5
listings for that email address with the time recorded beside it. This is
extremely useful for segmenting your data and building groups based on different
time-zones or behaviour at different times of the day and week (remember -
weekends are generally better for B2C, Tuesday - Thursday working hours in
The unique opens by time metric is essentially a summary of the above
metric. Instead of having the addresses listed multiple times, there is a
number beside the address. The time listed in the left column is when the email
was first opened.
A sample use case for this combined set of
metrics is as follows:
Click on the unique opens by time metric first and filter by "opens" to list the
recipients that appear to show most interest.
This is a first opportunity to
segment. Noting the "local time" in the left column for a selection of
recipients, revert now to the opens by
Pick a number of sample addresses that
were good prospects from the first metric. You will note that every time the
email was opened is listed on the left hand side. Look at this data for
patterns in the open times.
Consider the following questions:
What time was the first mail opened?
What time were the second and
subsequent mails opened?
How frequently were they opened?
Were they opened at the same times
roughly on particular days?
Are the repeat opens clustered, for
example, around weekends?
In the next
blog we will look at "Opens by email and
unique opens by email" and the "Clicks
by link, unique clicks by link, unique clicks by email" metrics.
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