measuring the effectiveness of customer health model

How to Measure the Effectiveness of a Customer

Health Model

Part 2

Today’s Speakers

Jill Rubin Chief Marketing Officer Totango

Shachar Avrahami Customer Success Operations Feedvisor

Reminder: What is a customer health model?

A customer health model is a framework to identify the status of your customers – are they in good, average, or poor health – in order to determine who needs attention, why and the proper course of action. It is comprised of health scores and health profiles.

Health Webinar Part 1: http://v.alue.co/part1-health

Best practices for a Health Score

•  Combine several KPIs and metrics into one comprehensive score

•  It should represent the complexity of

customer operations but represent it in a simplified manner

•  Needs to be credible

•  Needs be actionable and indicate the reasons for the change in health

•  Should be automated and reflect customers’ real-time health status

Best practices for a Health Score

Best practices for a Health Profile

•  Combine several KPIs and metrics into one comprehensive metric

•  It should represent the complexity of

customer operations but represent it in a simplified manner

•  Needs to be credible

•  Needs be actionable and indicate the reasons for the change in health

•  Should be automated and reflect customers’ real-time health status

•  Segment customers based on similar characteristics with different behavior

•  Each segment should have its own health definition and score

•  Each customer should qualify for only one segment at a time

•  Should allow you to roll up health of all accounts into one health score for the entire portfolio

Creating a customer health model is NOT

a set-and-leave-it project.

Important!

Now that you have a health model…

What are you doing with it?

How can you tell if it’s working?

When should you modify it?

Five ways to leverage a health model

1.  Build an early warning system on it (alerts & notifications)

2.  Use it to forecast churn, renewal, and upsell revenue

3.  Create trigger-based emails to nurture accounts back to good health

4.  Make it visible to everyone in the company, including the board

5.  Compensate CSMs for customers in good health

Measuring the effectiveness of a health model •  Compare CSM sentiment to health scores weekly

•  Conduct a churn analysis every month •  What was health at time of cancellation? •  How does their health score compare to their product

usage? •  How does their health score compare to customers in the

same health segment?

•  Track what’s working – are there commonalities between the renewals and upsells? •  Look for sticky features and incorporate that into health

Approaches to fixing a health model

•  You need to continuously tweak your health model (think agile, make iterations)

•  If the health definition of a segment doesn’t seem accurate, add additional segments

•  By creating more segments (or sub-segments), you can be more granular and test new health definitions for accuracy

•  Give each segment at least 30 days for analysis

Default (all customers)

Onboarding Established

Totango customer built a 4-stage approach to building an effective health model

Real life example

Measuring the Effectiveness!of a Customer Health Model

Presentation by Shachar Avrahami

Feedvisor - Who are we and what we do?

13

Feedvisor’s Algorithmic Repricing and Revenue Intelligence solutions power millions of pricing decisions daily; providing retailers with actionable insights to maximize profitability and drive their business growth.

0

10

20

30

40

2013 2014 2015 2016 2017

# of CS workers, over time

Tel Aviv New York Seattle

The Customer Success group is the owner of existing customers’ revenue – renewal & upsells

The CS team includes CSMs, Support, Education, Professional Services, Analysts, SMEs and Operations

Massive growth in the last 2 years

Multi locations

Customer Health Score 1.0


15

6-7 Criteria per Profile Revisions & Updates

Based on estimations to where we

want our customers to

be

Onboarding, Ongoing

Few fixes after new use-case release / processes

2 Health Profiles

After 8 months, we thought it’s the right time to review the model and to adjust it. !We started analyzing the results of the Customer Health Model

Customer Health Score 1.0 Analysis - Takeaways

16


17

Hits (churn)

81%

18%

1%

CHS on week of Churn

Poor Average Good


18

Hits (churn)

81%

18%

1%


Poor Average Good

Early Signal

19% 26%

12%

43%

Not Poor 1-3 weeks 4-6 weeks 7 and above

# of Weeks from Poor to Churn


19

Hits (churn)

81%

18%

1%


Poor Average Good

Early Signal

19% 26%

12%

43%



Automation

53%

30%

9% 8%

CSM Sentiment (manual)

Low Utilization

(auto)

Low NPS (auto)

Active Days (auto)

Main Reason(s) for Poor CHS


20

Hits (churn)

81%

18%

1%


Poor Average Good

Early Signal

19% 26%

12%

43%



Automation

53%

30%

9% 8%

Churn Probability (manual)

Low MPSR (auto)

Low NPS (auto)

Active Days (auto)

Main Reason(s) for Poor CHS

False Alarms (renewal)

36%

5%

59%

CHS on week of Renewal

Poor Average Good

CHS Cycle

22

Defining Customers’ Segments

The Multiplication

Model - Defining CHS metrics

Create Follow-up Items

Retrospection

Defining Customers’ Segments

Defining customers’ segments

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Split your customers into groups that behave differently, based on: •  Size / Plan •  Customer Journey Phase •  Products •  …

Each customer should be qualified for one segment at a time - make sure the segments are not overlapping.

Customer Journey Phase

Onboarding Ongoing

SMB Strategic

The Multiplication Model - Defining CHS metrics

The Multiplication Model – Key Metrics

26


Awareness

27

The ability to understand the

customer status.

(When was the last time we spoke with the customer? Is the

customer responding? Did we follow-up on the last NPS score?)


Awareness Relationship

28


customer status.



The results of our relationship with the

customer

(Did we show good ROI? What is the Churn

Probability? How many aging support tickets are

opened?)


Awareness Relationship Usage of Scale (Depth)

29


customer status.




customer



opened?)

How deep is the customer invested with our product

(Product stickiness - What is the frequency of usage? How many licenses are in

use? Advanced integrations?)



Usage of Scope

(Width)

30


customer status.




customer



opened?)




How wide is the customer’s

dependencies in different use-cases

(Product stickiness - How many different use-cases are there? How many different needs our product helps the customer?)



Usage of Scope

(Width)

31


customer status.




customer



opened?)




How wide is the customer’s

dependencies in different use-cases

(Product stickiness - How many different use-cases are there? How many different needs our product helps the customer?)

= CHS × × ×

Just like a simple mathematical multiplication calculation - when one of the parts in the equation is zero, the entire equation equals zero (meaning – you must have them all in order to be successful):

The Multiplication Model - Detailed Metrics (example)

32 The metrics should be a combination of auto-

alerts and subjective CSM risk rating


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Based on the CHS criteria, you can create follow-up items for the CSMs that will focus them on the right way to address the customer:


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•  Poor Health due to Low NPS – SuccessPlay ‘Contact the Customer’


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•  Poor Health due to Low NPS – SuccessPlay ‘Contact the Customer’ •  Poor Health due to Usage of Scale – Campaign ‘customers that didn’t login over 30

days’


37



days’ •  Average Health due to Usage of Scope – Campaign ‘How-to use Non-Competitive’


38



days’ •  Average Health due to Usage of Scope – Campaign ‘How-to use Non-Competitive’ •  Good Health based on good ROI field – SuccessPlay ‘Upsell opportunity’

Retrospection

CHS Retrospection

40

CHS 2.0

Micro-Level Analysis: investigation on every renewal/churn/upsell/downgrade case

understand what impacts the prediction. Do not ‘set it

and forget it’. (3-6 months, OR once you feel you have enough data)

CHS 3.0 Adjust the segments, metrics and action items

M a c r o - L e v e l A n a l y s i s

CSMs Feedback

E f f e c t i v e n e s s Metrics Analysis

CHS Effectiveness Metrics

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Define metrics that will help us analyze the CHS effectiveness. KPIs (to be achieved in 180 days):

Goals


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At least 90% of customers that

churned will be in Poor CHS

Goals

CHS at week of Churn (did we predict the churn?)


43




Poor CHS will be no more than 20% from

customers that renewed

Goals


% of False Alarms (how many customers renew on Poor health?)


44






At least 70% of churn will be

identified 4 weeks ahead of churn

Goals



# of weeks from Poor CHS to Churn (how long in advance could we identify the churn?)


45








at least 60% of churn will be identified

through automated early signals

Goals




% of Poor CHS due to Subjective Risk Rating (Man vs. Machine - how well are our automation alerts working?)


46








at least 60% of churn will be identified

through automated early signals

100% 24% 86% 63%

Goals




% of Poor CHS due to Subjective Risk Rating (Man vs. Machine - how well are our automation alerts working?)

Take-aways

Takeaways

48

Building a Customer Health Model is not a one-time job

Ongoing learning process – constantly analyze your churn and renewals as they occur

Measure your health model in an empiric data-driven method

Once you prove good correlation and predictions – the team will trust your model

Questions?

www.totango.com @totango

[email protected]

Jill Rubin Chief Marketing Officer

Shachar Avrahami Customer Success Operations

www.feedvisor.com @feedvisor

[email protected]

measuring the effectiveness of customer health model

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