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Here we are looking at what
is called a cohort report.

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A cohort report looks at different
groups or cohorts of our customer base.

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In this example they are separated
out based on the month

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that they first started using our service.

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We call these monthly cohorts.

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Along the y-axis in column A, we can
see the month that they signed up in.

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And in column B, we can see the number
of customers that are in that cohort.

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Then, going along the x-axis, or

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row 3 in our example spreadsheet, we have
the monthly billing point of the service.

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So in our July 2017 cohort, there were 74
customers that started paying us in July.

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The data is showing the average
realized lifetime value of the cohort.

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I'll explain what realized means in
this context in the next video.

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But before that, let's look at
this cohort report some more.

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We see that our first cohort, in
November 2016, we had 75 people sign up.

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On average, each of those people
paid us $1,500 that first month.

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Then the following month on average
each of those 75 people paid

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us $2,471 over the course of those
two months for billing cycles.

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You read the report the same for
all the different cohorts.

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For the cohort in December 2017,

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those 45 new customers on average
paid us $1,544 on the first month.

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By the sixth month,
those 45 on average have paid $4,849.

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So this is showing a cumulative
total of what we've

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collected from the average customer
in that cohort over the time frame.

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When you look at this data,
does anything stand out to you?

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Pause the video and look at it.

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Not for too long, just a minute or two.

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How does it fluctuate by cohort and
over time?

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Okay, welcome back.

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There are lots of things that
might have jumped out to us.

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But the answer I was looking for
is that this business

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doesn't appear to have a set rate cart,
subscription price, or monthly fee.

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Or to put it in different terms,
the ARPU is fluctuating month to month.

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The first month payment is different for
every cohort.

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It also does not scale linearly,
based on a set monthly fee.

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So this suggests that the pricing for

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this product is based on some
component of usage or consumption.

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Maybe there is a satellite card or

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minimum monthly payment with
an additional charge based on usage.

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Or perhaps this is a cohort report for
different tiers of service, and

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we just aggregated all new customers
from a given month into this report.

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Let's contrast the Monthly
tab with the Annual tab.

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On the Annual tab, we can see a clear
linear evolution for each cohort.

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When their contractual obligations
terminate at the end of the year,

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some renew and some don't.

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So for example, we see the different

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realized LTVs in billing cycle 13 here for
the different cohorts.

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The larger the number here,
such as the more renewals there were,

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less churn, higher retention.

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And we can see here for
the January 2017 cohort,

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the realized LTV didn't change at
all from month 12 to month 13,

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suggesting no one was retained and
everyone churned.

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There are a lot of different types of data
you can see presented in cohort reports.

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ARPU, Churn, LTV, Activity,

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Temperature, there's just a lot you can
present with these types of charts.

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Also, you don't always have to
use a time frame on both axes.

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Maybe you want to look at
months across the x-axis,

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but different acquisition
channels along the y.

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So you can compare how your earned
acquisition channels compared to paid.

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In the teachers' notes you will find link
to a few articles on cohort reporting that

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includes some additional
real world examples.

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Let's move on to the next video and
and introduce what realized LTV means.