Customer Churn Management For Profit Maximization PowerPoint Presentation Slides

Customer Churn Management
for Profit Maximization

Agenda for Churn Management
2
Company needs to prevent customers from reducing
their purchases of products and services
Discussing about various ways through which firm can
manage the customer churn
Discussing about churn propensity model
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Table of Content for Churn Management
3
Churn Propensity Model
• Various Customer Attributes to Look For
• Preventing Churn through Predictive Analytics
• Machine Learning Process
o Problem Understanding
o Data Collection, Preparation and Pre-processing
o Modelling and Testing
• Predicting Customer Churn
• Customer Journey Analytics
Dashboard
• Customer Purchase Tracking
Impact of Successful Implementation of
Churn Management
Various Types of Customer Churn
Introduction
• Key Statistics Associated to Customer Churn
• Present Churn Situation in Firm
• Current Customers Attrition in Firm
• Customer Churn Rate on Monthly Basis
How to Handle Customer Attrition?
• Four Stages of Churn Management
o Segmentation on Basis of Customer Spending
o Acquisition Strategy for Churned Customer
o Delighting Customers to Improve Loyalty
o How to Prevent Customer Churn?
o Several Anti – Churn Campaigns
• Customer Treatment Framework

4
Dashboard
Churn Management
Introduction

Key Statistics Associated to Customer Churn
5
Customer churn is a serious issue which affects firm’s overall performance. Due this, firms incur heavy losses in terms of abandon purchases and lower revenues. Retaining
existing customer is more profitable than acquiring new customers.
Costs 5x more to acquire new customers
than keeping existing ones
16x more to bring new customers to the
same level of current ones
Companies are losing $85 billion each
year due to customer churn and
abandoned purchases
Probability of selling to existing customer
65 - 75%
Probability of selling to new customer
5 - 15%
90% of firm’s future revenues derive from
30% of existing customers
5% increase in customer retention
leads to 30% - 90% increase in profits
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Present Churn Situation in Firm
6
This slide depicts the current scenario of churners compared to customers over the years. It also provides information regarding annual churn rate of the customers.
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40
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120
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2015 2016 2017 2018 2019 2020
Millions
Chumers Subscribers
Key Takeaways
• There is increase in churners with increase in customer base from 2015 to 2020
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Customers and Churners
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20
40
60
2015 2016 2017 2018 2019 2020
Percentage
Key Takeaways
• There is a rise in customer attrition rate in past years
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Annual Churn Rate of Customers
This graph/ chart is linked to excel and changes automatically based on data. Just left click on it and select “Edit Data”.

Current Customers Attrition in Firm
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This slide provides information about current customers, number of churners with churn rate for last three months.
August September October
Current Customers 10,000 14,375 18,531
Number of Churners -500 -719 -927
New Customers 5,000 5,000 5,000
New Churn -125 -125 -125
Total Customers 14,375 18,531 22,479
Adjusted Churn Rate 5.13% 5.13% 5.13%
Quarterly Churn Rate 5.17% 5.17% 5.13%

Customer Churn Rate on Monthly Basis
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Firm has tracked customer churn rate on monthly basis. It has been seen that firm has faced highest churn rate in last month.
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2%
4%
6%
8%
10%
Jan-18 Feb-18 Mar-18 Apr-18 May-18 Jun-18 Jul-18 Aug-18 Sep-18 Oct-18 Nov-18 Dec-18 Jan-19 Feb-19 Mar-19 Apr-19 May-19 Jun-19 Jul-19 Aug-19 Sep-19 Oct-19 Nov-19 Dec-19 Jan-20
01/07/2018 01/06/2020Customer Churn
Key Takeaways
• There is steady increase in customer churn from 2018 to 2020
• But in Dec 2019, firm has encountered the highest customer churn rate
• Reasons for high churn rate –
o Poor client experience
o Bad onboarding experience
o Lost value perception
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9
Dashboard
Churn Management
Introduction

10
This slide provides information about several ways in which firm can experience customer churn such as – when customer stops spending, churn due to product quality, etc.
and the reasons behind them.
• Decrease in overall spend with firm
• Purchasing in less volume and
ordering less frequently
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• Products become unattractive for
various reasons –
o Failure in meeting customer
expectations
o Failure in providing value to
customers as compared to
competitor’s offering
o Degrading in quality and
shortening shelf life
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• Reasons for customer leaving
business entirely
o Failure in delivering promises
made
o Not finding product useful
o Bad customer service
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Account Declining
in Spending
Product
Churn
Complete Customer
Account Loss

11
Dashboard
Churn Management
Introduction

Four Stages of Churn Management
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The firm is need of managing its customer churn and it will achieve this in four stages such as – acquiring churned customer, delighting customer, preventing customer
attrition and saving customers through various campaigns.
Acquire
Delight
Prevent
Retain
› Customer segmentation
› Acquiring customers through
different strategies
› Preventing customers from
attrition through analyzing
various churn signals and
triggers
› Delighting customers in order to
increase customer loyalty as
compared to competitors
› Focus on saving customers
from leaving the firm through
several campaigns

Segmentation on Basis of Customer Spending
13
The firm will bifurcate its customers based on their spending pattern.
Customer Spending Range Segment
From To
$0.00 $25.00 Low
$25.1 $50.00 Medium
$50.1 $75.00 High
$75.01 $100.00 Silver
$100.01 $150.00 Gold
#150.1 $1,000.00 Platinum

Acquisition Strategy for Churned Customer
14
The firm is looking for acquiring its churned customer as it is costlier in acquiring new customers than retaining the existing ones. The customers will be categorized into
segments such as deal seekers, tariff optimizers, etc. and strategies will be implemented according to the categorization.
Category Strategy Frequency
• Deal Seekers • Short term promotions • Quarterly
• Tariff Optimizers • Add text here • Add text here
• Apathetics • Add text here • Add text here
• Loyalists
• Increasing benefits over time
o Providing free and easy to access to cloud storage
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0
2
4
6
Average lifetime indexed to deal seekers Average CLV indexed to deal seekers
0%
20%
40%
60%
80%
100%
Total market Acquisition market
Deal seekers
Tariff optimizers
Apathetics
Loyalists
Customer Segment Mix of segment per universe
Lifetime Customer Lifetime Value Availability in % of market
Alteringmixofacquisition

Delighting Customers to Improve Loyalty
15
The firm is looking for different parameters in order to delight its customers. This slide portrays various strategies that firm will implement to enhance customer loyalty and
the benefits that it will incur.
Parameter Strategies Benefit Comments
Improved Customer
Interactions
• Loyalty program
• Interactable and intuitive system
• Customized email responses
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• Enhanced customer engagement • Add text here
Treating Customers
• Small gifts
• Thanking customers through
handwritten notes on invoices
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• Loyalty building • Add text here
Follow Up
• Sale follow up
• Satisfaction/ complaint feedback
survey Add text here
• Enhanced customer service
experience
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Churn Triggers Description Preventive Measures
Pending or unresolved incident No action taken on complaint call
Increased complaints
4 - 5 complaints related to
• Invoice
• Orders
• Product quality
How to Prevent Customer Churn
16
This slide depicts information about how firm can prevent the customer churn. The firm can proactively handle the churn issue by detecting the churn signals and triggers
from customers.
Churn Signals Description Preventive Measures
End of commitment
Customer inquires about the commitment
period duration and status
Your text here
Communicating with competitors
Interacting with competitor’s tele sales
department thrice in last two months

Several Anti - Churn Campaigns
17
This slide portrays information about various marketing campaigns in order to retain its customers from churning.
Building post sales opportunities through
• Additions or improvements based on previous purchases
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• Tracking insights regarding losing customers
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Cross Sell and
upsell Campaigns
After
Sales Engagement
Product and
Service Improvement
Customer
Satisfaction Campaigns
• Making customers aware about new features and optimizations
through email, webinar
• Add text here
• Requesting feedback and offering support
• Add text here

Customer Treatment Framework
18
The firm will target its customers by testing various strategies in terms of offers and will check their performance through feedback.
Offer 1
Offer 2
Offer 3
Offer 1
Offer 2
Offer 4
Offer 5
Offer 2
Offer 6
Testing
multiple strategies
Tracking customer
responses on various offers
Campaign refining on basis
of customer response
Likely Churner
Update modes
based on
response data
Update modes
based on
response data
Feedback Loop Feedback Loop

19
Dashboard
Churn Management
Introduction

• Customer information collected from
different email campaigns types –
promotions, discounts
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• Gender
• Age
• Income
• Education level
• Socio economic characteristics
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• Subscription date
• Customer spending per visit
• Subscription history
• Page views
• Brand preferences
• Add text here
Data Collection
Through Campaign
History
Customer
Demographic Data
Customer Behavior
Data
Various Customer Attributes to Look For
20
The firm will explore various features from data. The available data is analyzed per user basis.

Proactive re-
Engagement
Preventing Churn through Predictive Analytics
21
Projecting the probability of future outcomes, events based on current and historical data. It utilizes different statistical techniques such as machine learning, pattern
recognition through data mining, etc.
Machine Learning
Algorithms provide information regrading
shared behavioral pattern of customers who
already abandon purchasing
Check behavior of current customers
against the patterns and alert about
potential churners
Get informed about the customer’s
pain points and choosing effective
retention actions
Existing Customers
Churned Customer
History
Pattern
Recognition
Predictive Model
Customers at
risk of Churn
Happy Customers

Machine Learning Process – Problem Understanding
22
The customer churn prediction through machine learning is initiated through understanding the insights through two methods – classification and regression.
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30%
40%
50%
60%
70%
80%
-1 0 1 2 3 4 5 6 7
ChurnProfitability
# Customer Service Calls
Problem Understanding
Two types of problems to solve
Classification
• Data scientists categorize customers in different class/category
(churner/non churner)
• Categorizing based on pricing plan downgrading
o Will customer churn or not
o Will customer renew its subscription
Regression
• Probability estimate of churn per customer –
o Estimate about customers that are likely to get churn in a specific
time period

Machine Learning Process-Data Collection, Preparation and Preprocessing
23
Once the insights are identified, data collection sources are selected for further predictive modeling. After that, dataset is prepared with a set of attributes representing
behavior patterns related to customer engagement level for specific product/service.
Data Collection
Recognizing various sources of data for churn prediction –
• CRM systems –customer information from sales and customer support records
• Feedbacks on review and social media platforms
• Add text here
Data Preparation and Preprocessing
Recognizing various sources of data for churn prediction –
• Feature engineering – Predicting outcomes by selecting most relevant attributes depicting different behavior
patterns related to customer engagement level with product/service. Features can be –
o Customer demographic features – education, level, income
o User behavior feature – lifecycle stage, active session length
o Support features – sent queries, customer satisfaction score

Machine Learning Process – Modelling and Testing
24
The firm can consider in between two churn prediction model – decision tree and random forest. These models are capable in detecting potential churners with desired level
of accuracy.
› Data sample splits into two or more homogeneous sets with most
significant differentiator in input variables
› Tree initiated from root node – best predictor
› Add text here
› Add text here
Root node
Interior node Interior node
Leaf node
Leaf node
Interior node
Leaf node
Leaf node
Interior node
Leaf node
Leaf node
› High prediction accuracy with numerous decision trees
› Each tree classifies data instance based on attributes
› Forest selects classification with maximum votes
› Add text here
› Add text here
Decision Tree Random Forest
Voting
P1
P2
Pm
TreemTree2Tree1
Predicted Class
A
Decision Tree

Predicting Customer Churn
25
After deploying churn prediction model, the firm will become capable in predicting churn probability of various customers on basis of various attributes such as NPS,
transaction usage, etc.
Customer Transaction Usage NPS Churn Probability Churn Prediction Comments
Customer 1 Medium 201.4 0.112 Yes Add text here
Customer 2 Low 153.2 .265 No Add text here
Customer 3 High 127.5 .741 Yes Add text here
Customer 4 Low 161.3 .878 Yes Add text here
Customer 5 Low 254.4 .281 No Add text here
Customer 6 Add text here Add text here Add text here Add text here Add text here

Customer Journey Analytics (1/2)
26
The firm can also measure churn rate using customer journey analytics tools by mapping entire customer journey by analyzing various touchpoint encountered.
7K 21.7K 332 29K
Return in Store
7.1K 21.7K 313 29.2K
Coupon Spent
6.9K 21.5K 340 28.7K
Reward Sent
7.4K 22.1K 251 29.7K
Web Searched
7.6K 11K 11.3K 29.9K
Product Searched
7.6K 11K 18.6K
Product Compared
7.6K 7.6K
Cart Abandoned
Key Takeaways
› Marketing team will keep track of crucial
customer touchpoints which will deliver
more value, affect future interactions and
will prove to be fruitful in driving new and
repeatable clients
› The analysis will help in uncovering crucial
steps that will drive more value
› Add text here
› Add text here

Customer Journey Analytics(2/2)
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The firm can also measure churn rate using customer journey analytics tools by mapping entire customer journey by analyzing various touchpoint encountered.
46.6K
Signed Up for
Online Banking
1.6K
Apply for Loan
11K
Downloaded
Mobile App
2.9K
Open Cd
46.6K
Tie 1
256K
Account
Closed 1
581K
120-day Customer
Satisfaction
1.9K
Account
Closed
22.3K
Enrolled in Direct
Deposited
Call made to
customer Support
2.9K
Key Takeaways
› Marketing team will keep track of crucial
customer touchpoints which will deliver
more value, affect future interactions and
will prove to be fruitful in driving new and
repeatable clients
› The analysis will help in uncovering crucial
steps that will drive more value
› Add text here
› Add text here

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Dashboard
Churn Management
Introduction

Impact of Successful Implementation of Churn Management
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This slide portrays the overall impact of churn prevention and benefits associated to it.
Benefit Category Benefit Description Annual $ Impact
Decreased churn
Revenues increased
Higher cross - selling revenues
Customer retention rate
Revenues generated
Add text here
Add text here
$3.3M
$0.4M
65% increase
$4 - $5 M
Add text here
Add text here
Reduce Churn and
Drive Upsell Revenue
Enhanced
Customer Engagement
Improved
Customer Retention

30
Dashboard
Churn Management
Introduction

Dashboard – Customer Purchase Tracking (1/2)
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The firm is looking forward to track customer experience by tracking various touchpoints in order to handle issues such customer churn. KPIs mentioned in the dashboard
are measured regularly across the organization.
Path to Purchase
Repeat Purchase
-0.5
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1.5
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2.5
3
3.5
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0.8
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Group
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Group
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Group
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Group
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Group
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0.6
0.8
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Group
1
Group
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Group
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Group
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Group
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Group
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-0.03
0.07
0.17
0.27
0.37
0.47
0.57
0.67
Group
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Female Music
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14000
-25
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125
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425
Sep-20 Oct-20 Nov-20 Dec-20
Sales Q1 2020
Summary
Summary
Summary
Participants
11.6K
Participants
29.8K
Participants
9.1K
Customer activity
Landing page per group test
Total cart value per month
Total repeat sales after coupon
Add to cart by product category
Total revenues by category
Reward conversion per group
Product viewed per category
Reward conversion per group
Coupon conversion rate per group
Add cart/ product view
New chart
Total repeat sales after reward
Total cart value per month
Checkout by month
8.35K 29.2K
34.3K
14.5K

Dashboard - Customer Purchase Tracking (2/2)
32
The firm will track down the customers activities in terms of revenues generated. Customers are bifurcated in segments such as existing, new, lost and active.
Existing New Lost Active
Customers 6419 1.5% 624 14.8% 1869 49.9% 5174 12.3%
Revenue $425k 0.9% $31k 9.7% $139k 66.5% $317k 15.1%
Avg Bill $66.17 0.7% $50.33 18.4% $74.44 27.9% $61.27 27.6%
Existing,
6,419
New, 624
Active,
5,174
Churned,
1,669

Customer Churn Management for Profit Maximization Icons Slide
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30 60 90 Days Plan
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90 Days Plan
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30 Days Plan
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60 Days Plan
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Our Mission
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Vision
Mission
Goal

Our Team
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Designation
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Roadmap for Process Flow
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About Us
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