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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
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
Customer Health Score 1.0 Analysis - Takeaways
17
Hits (churn)
81%
18%
1%
CHS on week of Churn
Poor Average Good
Customer Health Score 1.0 Analysis - Takeaways
18
Hits (churn)
81%
18%
1%
CHS on week of Churn
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
Customer Health Score 1.0 Analysis - Takeaways
19
Hits (churn)
81%
18%
1%
CHS on week of Churn
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
Automation
53%
30%
9% 8%
CSM Sentiment (manual)
Low Utilization
(auto)
Low NPS (auto)
Active Days (auto)
Main Reason(s) for Poor CHS
Customer Health Score 1.0 Analysis - Takeaways
20
Hits (churn)
81%
18%
1%
CHS on week of Churn
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
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
Customer Health Score 2.0
CHS Cycle
22
Defining Customers’ Segments
The Multiplication
Model - Defining CHS metrics
Create Follow-up Items
Retrospection
Defining Customers’ Segments
Defining customers’ segments
24
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
The Multiplication Model – Key Metrics
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?)
The Multiplication Model – Key Metrics
Awareness Relationship
28
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?)
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?)
The Multiplication Model – Key Metrics
Awareness Relationship Usage of Scale (Depth)
29
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?)
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?)
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?)
The Multiplication Model – Key Metrics
Awareness Relationship Usage of Scale (Depth)
Usage of Scope
(Width)
30
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?)
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?)
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?)
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?)
The Multiplication Model – Key Metrics
Awareness Relationship Usage of Scale (Depth)
Usage of Scope
(Width)
31
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?)
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?)
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?)
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
Create Follow-up Items
Create Follow-up Items
34
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:
Create Follow-up Items
35
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:
• Poor Health due to Low NPS – SuccessPlay ‘Contact the Customer’
Create Follow-up Items
36
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:
• 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’
Create Follow-up Items
37
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:
• 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’ • Average Health due to Usage of Scope – Campaign ‘How-to use Non-Competitive’
Create Follow-up Items
38
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:
• 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’ • 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
41
Define metrics that will help us analyze the CHS effectiveness. KPIs (to be achieved in 180 days):
Goals
CHS Effectiveness Metrics
42
Define metrics that will help us analyze the CHS effectiveness. KPIs (to be achieved in 180 days):
At least 90% of customers that
churned will be in Poor CHS
Goals
CHS at week of Churn (did we predict the churn?)
CHS Effectiveness Metrics
43
Define metrics that will help us analyze the CHS effectiveness. KPIs (to be achieved in 180 days):
At least 90% of customers that
churned will be in Poor CHS
Poor CHS will be no more than 20% from
customers that renewed
Goals
CHS at week of Churn (did we predict the churn?)
% of False Alarms (how many customers renew on Poor health?)
CHS Effectiveness Metrics
44
Define metrics that will help us analyze the CHS effectiveness. KPIs (to be achieved in 180 days):
At least 90% of customers that
churned will be in Poor CHS
Poor CHS will be no more than 20% from
customers that renewed
At least 70% of churn will be
identified 4 weeks ahead of churn
Goals
CHS at week of Churn (did we predict the churn?)
% of False Alarms (how many customers renew on Poor health?)
# of weeks from Poor CHS to Churn (how long in advance could we identify the churn?)
CHS Effectiveness Metrics
45
Define metrics that will help us analyze the CHS effectiveness. KPIs (to be achieved in 180 days):
At least 90% of customers that
churned will be in Poor CHS
Poor CHS will be no more than 20% from
customers that renewed
At least 70% of churn will be
identified 4 weeks ahead of churn
at least 60% of churn will be identified
through automated early signals
Goals
CHS at week of Churn (did we predict the churn?)
% of False Alarms (how many customers renew on Poor health?)
# of weeks from Poor CHS to Churn (how long in advance could we identify the churn?)
% of Poor CHS due to Subjective Risk Rating (Man vs. Machine - how well are our automation alerts working?)
CHS Effectiveness Metrics
46
Define metrics that will help us analyze the CHS effectiveness. KPIs (to be achieved in 180 days):
At least 90% of customers that
churned will be in Poor CHS
Poor CHS will be no more than 20% from
customers that renewed
At least 70% of churn will be
identified 4 weeks ahead of churn
at least 60% of churn will be identified
through automated early signals
100% 24% 86% 63%
Goals
CHS at week of Churn (did we predict the churn?)
% of False Alarms (how many customers renew on Poor health?)
# of weeks from Poor CHS to Churn (how long in advance could we identify the churn?)
% 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
Jill Rubin Chief Marketing Officer
Shachar Avrahami Customer Success Operations
www.feedvisor.com @feedvisor