I'm Nicole Blanchett Neheli and this is the second
in a series of videos on analytics for journalists.
Analytics are used by all platforms of news
and help inform decisions on everything
from where content should be placed on a web page
to what types of stories are included in a TV newscast.
There are a lot of different analytics tools used in newsrooms.
For these modules we're going to look at
Google Analytics for the Ryersonian website.
As the interface for Google Analytics itself can change,
and individual newsrooms use a number of different programs,
the goal here isn't to give you
an exact how-to on the software,
but an understanding of how analytics work
and some basic navigation tips.
In this module we're going to look at
how you can find out where your audience is coming
using the Acquisition data.
If you click on the Acquisition heading
you'll see a drop down menu appear
that starts with an Overview.
The overview shows you how your audience is getting to your site.
This pie chart on the top left breaks the information down
into a number of channels:
First up, there's Organic Search -
that's someone arriving at your site
by typing key words into a search engine
and being given a link to one of your stories or your homepage.
Direct traffic comes to your site through a bookmark
or typing in the URL.
But it's also the category that everything gets dumped into
if the code can't determine the actual source -
and this metric can also be thrown off by a big company
or agency where the system is set up so that
all computers share the same IP,
or what you might think of as a computer's address.
For example, thousands of people
working on different computers in a government office
might appear as an individual user.
So keep in mind that Direct Traffic numbers
aren't really refined.
Referrals happen when another site that is not a search engine
provides a link to your site.
Social is where you'll see what social media sites
your traffic is arriving from.
So, for example, if my friend posted a link on Facebook
and I followed it to the Ryersonian site,
my visit would be recorded here.
You'll also notice an Email category
in this timeframe's acquisition report -
that just means someone was directed to your site
through a link they received in an email.
To the right of the pie chart
there's a graph showing sessions per day.
And if you look underneath that,
all of the acquisitions are listed
with the percent of new sessions or users
for each of the channels,
as well as the bounce rates
for pages visited through the categories,
pages per session,
and average session duration.
You'll see on the right hand side of the page
there's a section called Conversions -
that's an option that's not set up on the Ryersonian,
but basically using Google Analytics you can set goals
that are met by users interacting with your site
in specific ways: like a certain amount of time
spent on a page, or the number of pages visited,
or you can set goals for events.
Events include things like downloading a video.
If you had one of those goals set,
each time it was met
it would be counted as a conversion.
If you click on the individual channel
you can get some really detailed information.
This is the Organic Channel.
And just below the graph and above the chart below
you'll see some words in black, some highlighted in blue.
Right now Keyword is in black
and that's the data you're looking at -
the keywords people typed in to find the Ryersonian.
If I select Source, it shows me where they came from -
in this case most did a Google search.
If I select Landing Page it shows me where they ended up -
or what story they “landed” on.
The “Other” option just takes you to a
different category so we're just going to skip past that.
You'll notice during this timeframe on the Ryersonian
that the Organic searches were quite high.
It turns out the search term people were using
was 'youtube sex' - which linked them to a Ryersonian story
on a YouTube sex educator.
I'm going to go out on a limb and say
that's probably not what they were looking for,
but it did bring a lot of people to the site.
However, they didn't stay -
as you can see from the bounce rate.
They must have left to find some, uh,
let's just say a different type of content.
You can see what an impact
social media referrals can make on your website
if you look at these Ryersonian stats
from March 11th to April 11th -
Reddit pushed a story about white students being banned
from a student union funded event
and that really boosted traffic to the site.
But again, the bounce rate was pretty high,
meaning once readers checked out that story,
they didn't stick around.
Another note, some of the options on Google Analytics
give you pretty much the same info but in a different format.
And, seriously, I think someone at Google
needs to come up with a few more original headings
because although a Referral usually refers to a channel,
in this case where another site is linking to yours,
the referrals in the Acquisition drop down menu
is different and also includes social referrals.
We're not going to worry about that
for the purpose of what we're doing.
I just wanted to acknowledge that navigating through
these types of sites can be a bit confusing.
Which brings me to our next sub heading
that is also a channel!
Social. Not all of these areas
are fully used by the Ryersonian
but we'll just touch on a few.
Network referrals tells you
from which social media site
you're getting the most hits.
And clearly Facebook leads this category.
If you go into Landing Pages you can see where social referrals,
which are just links from Twitter or Facebook, for example,
are taking your readers.
Trackbacks shows you which sites are linking to yours
and from where the reader was linked.
Users Flow is particularly useful in terms of looking at engagement
because you can see how readers are making their way
through your site.
Here, as we\'ve already seen,
the biggest percentage is coming from Facebook,
going to the homepage,
and then some of those readers visit that story
about the students being banned from the event.
And Users Flow gives you a different visual
to show how those Reddit readers
we talked about in the first video dropped off
the site after checking out that one story.
You can also see how some people enter the site via a particular story,
then head to the homepage and find more stories of interest.
Now, we could go even more in depth with the data here,
but, again, the idea is just to get you familiar
with navigating through analytics data,
thinking about the way your readers find you,
how that might impact how you reach out to them -
or, even shape your content.
And that wraps up this module on Acquisitions data.
In the next we'll tackle the Behaviour metric.
Now that you've finished this module you should be able to:
Demonstrate an understanding of web analytics
as a function of editorial decision-making.
and be able to navigate through Google Analytics