- [Instructor] One feature that you're likely to see
on almost every report on Google Analytics
is the main data over time chart.
This is the chart you'll see here
where we've got data graphed over time,
and this is great it gives us a 10,000 foot view
but to really utilize it,
we can configure it to show much more.
For example, let's take a look at the audience report
that shows website traffic by device category.
This can be found under audience,
then we'll scroll down to mobile,
and we can look at the overview here.
And this overview report can be useful
to compare the traffic coming from mobile devices,
desktop, and even tablets.
I've adjusted the time period for this particular report
up here in the top right corner.
I'm also viewing this data in terms of days
which I've set here, although I could set this
in terms of weeks or even months.
And if you see that I do that
the visual representation of this here
is gonna change quite drastically here.
For now I'm gonna go with the most granular one
of a day because I've only got a couple of months here,
three months, and so I want to be able
to see individual days,
but if we had a much longer time period,
or if we just wanted to see large trends
it might make sense to use one of the other two options.
Even though this is a really simple report
we can get some insights out of this.
For example, one of the things we can see here
if we scroll down, is that the number of users
seems to fall off quite a bit over the weekend.
So Saturday and Sunday, Saturday and Sunday,
and then rises again on the week.
So we see a very consistent repeatable pattern here
just with a brief look.
So right now this graph is set to users,
which we can change with this drop down here,
and what we're going to see are these drop downs,
these are grouped the same way that these tabs
up here are grouped, so we have ecommerce,
goal set 1, site usage, and summary.
So inside of these are going to be different metrics
that are gonna correspond to those.
So in the site usage we talk about sessions,
and bounce rates, and users.
In the ecommerce section up here
we would talk more about things around commerce,
like average order value and revenue,
transactions, things like that.
So, speaking of ecommerce, let's go ahead here
and grab revenue and put the graph to revenue over time.
Now what's interesting, we see some spikes here,
the most basic kind of analysis I want to rule out
is whether there were simply more users
on the days that had higher revenue.
So I could try to think back to that users one
or I could actually put that right on top of it,
I can go here to select a metric,
come down to site usage, and I could grab users
in this case what I really wanna see is sessions.
If I'm getting more sessions
I would assume I'm getting more transactions
and so I can overlay those.
You see the light blue here are the number of sessions
and our existing dark blue is of revenue.
So on this spike, we do indeed see that there are
a high number of session on that day,
but there are also a high number of sessions on the next day
and our revenue drops dramatically.
So it's not always that the two are directly correlated.
So this ability to change this graph
and even put two different metrics on at the same time
is something that's quite an underutilized feature
most people look right past it.
Now another thing we can do,
instead of comparing two different metrics,
we can also compare two different time periods
with a single metric.
So I'm gonna hit the X here,
that's gonna clear out the sessions,
I'm gonna bring back my drop down,
and I'm gonna say compare to previous period.
Then it's automatically going to set it to same time period,
but a previous one, and if I say okay
it's gonna overlay these on top of each other.
It's gonna be that same metric, revenue,
but for the different time period.
So in blue I see the one I originally had selected
April 15th through June 15th,
and in orange we have February 12th through April 14th,
right up to that time period.
This could be really useful for month over month,
year over year, those kinds of
type of analysis where we're trying to compare
one time period against another for the same metric.
Okay taking away the compare time period one,
another thing we can add to this
is the ability to plot individual rows
in addition to the overview.
So for example I could come down here and I can select
desktop and I can select mobile, and I can plot those rows.
And what we see, immediately,
is that there is almost no revenue coming from mobile.
That green line is skidding down here along the bottom,
barely skimming along and almost all of the revenue overall
is led by desktop, in fact those two
are almost an exact match,
the only time I see here where they're not,
is on May 5th where we had a slight increase in mobile
and therefore the desktop didn't entirely match
the overall revenue, but everywhere else
we can see that mobile is not really making a dent.
Certainly something we want to analyze more closely,
figure out why that might be,
but this graph immediately shows us that insight.
Okay so the data over time graph
is a staple of Google Analytics,
it allows us to visual our data quickly,
and effectively, and the customization options
make it a more versatile tool than most people realize.