A critical guide to selecting metrics to define a data-driven customer success strategy. Here is the table of contents: - Metrics are for Decisions - The Nature of Metrics - Metrics Can Be Difficult - Customer Success Metrics Customer Lifetime Value (CLV) Customer Churn Rate Net Promoter Score (NPS) Customer Health Score Support Ticket Volume Customer Log-in Counts Customer Acquisition Cost (CAC) Product Activity Score CSM Subjective Score Customer Newsletter CTR Background Signals

1. THE CUSTOMER SUCCESS
METRICS THAT MATTER
A guide to selecting the metrics that drive
your data-driven customer success strategy
eBook
August 15, 2014

2. Table of Contents
Metrics are for Decisions
The Nature of Metrics
Metrics Can Be Difficult
Build Your Metrics Map
Customer Lifetime Value (CLV)
Customer Churn Rate
Net Promoter Score (NPS)
Customer Health Score
Support Ticket Volume
Customer Log-in Counts
Customer Acquisition Cost (CAC)
Product Activity Score
CSM Subjective Score
Customer Newsletter CTR
Background Signals
DISCUSSIONS METRICS

3. Metrics Are For Decisions
For each metric in this eBook, these icons
describe the types of decisions the metric informs.
Strategic Metrics
• Metrics that are measured/reviewed over a longer time frame
• Inform top level measures your execs and Board care about
Performance Metrics
• Monthly or weekly metrics that tell you if you’re on pace
Tactical Metrics
• Give insight into whether the piece parts are all working well
TacticalStrategic Performance

4. The Nature of Metrics
For each metric, this key describes what the
metrics actually are.
Predictive Metrics
• Tell what’s about to happen so you can take preemptive action
Descriptive Metrics
• Provide you with context about what is happening and trends
Signal Metrics
• These are an input/subset of predictive/descriptive metrics
Predictive SignalDescriptive

5. Metrics Can Be Difficult
2+2
Easy
E=MC
Hard
2
X
Kinda Hard
In this eBook, this key describes how difficult it is it
to measure each metric.
Metrics may be rated as “Hard” for a number of reasons:
• You need special software or code to capture the raw data
• You have to account for a lot of assumptions
• How you calculate some metrics may differ as you apply them
across products, segments, plan types, etc.

6. E=MC
Hard
2
Strategic
Customer Lifetime Value (CLV)
CALCULATION
CLV = Margin % * Average MRR / Monthly Churn %
WHY WE “RECOMMEND” IT
It’s the foundation of your strategic decisions such as how
much you can profitably spend on customer acquisition.
DOWNSIDE
It can get complicated:
• You first need to calculate churn, MRR and margin %
• Likely varies by product, acquisition channel, etc.
• Outside variables can affect it (e.g., will margin and churn
% change over time?), so you’ll need to make
assumptions – or risk high complexity
Descriptive
Recommended
LEARN MORE

7. Customer Churn Rate
CALCULATION
WHY WE “RECOMMED” IT
You have to measure churn. Most already do but there’s not
always internal alignment on the “right” churn calculation.
DOWNSIDE
Like CLV, churn rate gets complex when you start splitting by
product, monthly vs. annual plans, etc. There are several
ways to calculate churn depending on your business model.
Descriptive
Recommended
X
Kinda Hard
$50,000 Revenue Lost
$500,000 Total Revenue at Start of Period
= 10% Churn
Strategic
LEARN MORE

8. Net Promoter Score (NPS)
CALCULATION
WHY WE THINK IT’S A “GOOD IDEA”
Definitely measure NPS and monitor the trend on this metric
over time to see if you’re “moving the needle”.
DOWNSIDE
NPS is kind of a victim of its own success. It’s truly great for
what it is, but if you try and apply NPS for purposes other
than what was intended (i.e., to determine if a customer
would recommend you) you may find unexpected results.
Descriptive
Good Idea
2+2
Easy
Performance
# Promoters (9-10)
# Total Responders
= NPS-
# Detractors (0-6)
# Total Responders
LEARN MORE

9. E=MC
Hard
2
Customer Health Score
CALCULATION
Calculation typically executed by software from a
sophisticated roll-up and analysis of many signals
WHY WE “RECOMMEND” IT
The toughest metric you’ll ever love. Done properly, a data-
driven customer health score can be the best predictor of
churn risk, up-sell potential and conversion to purchase.
DOWNSIDE
Collecting and analyzing all the data needed to make
predictions is no small matter. And not all health scores are
created equal. Lighter weight ones are just “Descriptive”
while more robust analysis yields a “Predictive” health score.
Recommended
Performance
Predictive

10. E=MC
Hard
2
Support Ticket Volume
CALCULATION
Add up the volume of tickets for a given period.
WHY WE THINK IT’S A “GOOD IDEA”
Support ticket volume provides interesting context for how
your customer is interacting with your product. You should
always know how often customers are reaching out.
DOWNSIDE
Support ticket volume is typically not a consistent indicator of
customer health. High ticket volume may mean a customer is
struggling, or it could mean the customer is so engaged they
are continually pushing into new areas of the product – how
do you know?
Good Idea
Tactical
Signal

11. Customer Log-in Counts
CALCULATION
Typically performed by software that pulls from log files or by
firing a script upon successful log-in.
WHY WE THINK IT’S A “BAD IDEA”
Counting customer log-ins is a good first step to measure
customer engagement. But by itself it’s of limited value
because there’s no visibility into what’s happening within your
app, what the background signals look like, etc.
DOWNSIDE
A rules-based approach to determine how many log-ins
constitute good or bad health can inject uncertainty into an
already troublesome metric.
Bad Idea
2+2
Easy
Signal
Performance
LEARN MORE

12. Customer Acquisition Cost (CAC)
CALCULATION
WHY WE “RECOMMEND” CAC
With so many voices in the market, it can be expensive to
stand out from the noise. CAC helps you stay focused on
acquiring customers at a sustainable cost.
DOWNSIDE
Customer Acquisition Cost can be a little confusing if you
don’t define it clearly. Be sure everyone knows the exact
sales and marketing expenses you are including.
Descriptive
Sum of all Sales & Marketing Expenses
# of New Customers Added
= CAC
Recommended
X
Kinda Hard
Strategic

13. Product Activity Score
CALCULATION
Roll-up all customer activity in your product. Typically
executed by software monitoring customer activity.
WHY WE “RECOMMEND” IT
It’s similar to Customer Health Score, just more focused and
perhaps a bit easier to understand. And it’s predictive which
means we love it.
DOWNSIDE
As with Customer Health Score, collecting and analyzing
product activity data is no small matter. Be sure to look at the
data on an individual customer basis as you likely have many
levels of different activity across customer use cases.
Recommended
E=MC
Hard
2
Performance
Predictive

14. CSM Subjective Score
CALCULATION
Have your customer success managers review each account
and assign a score (e.g., 1-5) based on “how healthy” they
think they are.
WHY WE THINK IT’S A “GOOD IDEA”
Having CSMs critically evaluate each account forces them to
think critically about each account. It also provides a counter-
balance to objective measures so you can identify and
discuss any discrepancies.
DOWNSIDE
It’s totally subjective (of course).
Descriptive
Good Idea
2+2
Easy
Performance

15. Customer Newsletter CTR
CALCULATION
Any email or marketing automation platform that you use
should be able to tell you the Click Through Rate (CTR).
WHY WE “RECOMMEND” IT
Monitoring Click Through Rate of customer emails is a first
step in measuring customer engagement outside of your app.
Don’t underestimate the importance of the monthly customer
newsletter in building brand loyalty.
DOWNSIDE
It can be impacted by external factors such as day the email
was sent, its design, subject line, etc. Monitor CTR over the
long-term and experiment to see what customers like best.
Descriptive
Recommended
2+2
Easy
Tactical
LEARN MORE

16. E=MC
Hard
2
Background Signals
CALCULATION
Background signals measure the activity of your customer’s
customers. If you sell an email platform, background signals
are the response activity (e.g., open rates, click-thrus) of the
emails your customer sends.
WHY WE “RECOMMEND” IT
Background signals are an ideal complement to activity
scores and health score. All three are predictive, and
together pack a potent predictive punch.
DOWNSIDE
It’s somewhat complex to gather and analyze on your own.
So, you’ll likely need special software.
Recommended
Performance
Predictive

17. Build Your Metrics Map
Tactical
Strategic
Performance
CLV Churn Rate
Customer
Newsletter
CTR
Customer
Health
Score
Customer
Acquisition
Cost
Net
Promoter
Score
Focus is an essential ingredient to a data-driven customer success
strategy. Select the essential metrics that matter and craft a plan to move
the needle on each. Below is a simple framework for a metrics map.
Product
Activity
Score
Support
Ticket
Volume
Background
Signals