1. 9/30/2011
Agenda
• Identifying Churn and measuring Life Time Value
• Cost of Acquisition vs. Retention
• Utilization of Business Intelligence and Analytics to
identify optimal channel(s) for your customer or donor
• Real World example of an effective Multi-Channel
Retention campaign utilizing Analytics and Cost-
Progressive Channel Strategy
$
$ $
$ $ Acquisition
$
$
$ $
$ $
$
$ $
$ Current Customers
$
$ $ $
Farmer Retention Farmer Acquisition
1

2. 9/30/2011
What is Customer Churn?
$
$ $ Simply stated:
$ $ $ It’s the act of losing
$ your customers
$
$ $ due to competitive
$ $ pressure,
$
$ $ unhealthy
relationships,
$ financial
$ $ $ constraints, etc.
REACTIVE! How do most of us
deal with customer
churn?
Customer Churn Costs
• The average consumer service
company experiences between
30% and 70% customer churn
annually
• The average company has
between a 60% and 70%
probability of success selling
more services to a current
customer. These figures drop to
a 20% to 40% probability, and
then to a 5% to 20% probability,
when selling to former
customers or prospects,
respectively
• Last year, customer churn
collectively cost wireless
operators an estimated $10
billion. And that’s just the costs
of activating and deactivating
services
Customer Churn Costs
$
$ $ • As little as a 5% reduction in
customer churn can boost net
$ $ profits by as much as 20%
$
$
$ • A 5% monthly churn rate for a
services industry means a
$ $
company has to acquire 1.7
$ digital customers just to keep
$ one
$ $
$ • Hundreds of studies have
proven that most companies
$ spend $10 to acquire a new
$ donor for $1 spent in retention
$ $ strategies!
Knowing this, why
don’t we invest
more in our current
customers?
2

3. 9/30/2011
Customer Acquisition
$
$ $
$ $ $
$
$
$
$ $
$
$ $
$
$
$ Incentives
$ $
Modeling/Profiling
Technology
Target Marketing
Advertising
Case Study: AccuQuote
• A leading provider of term life insurance
• The Challenge
• Inbound leads needed to be better prioritized for
the sales team
• “We knew that 20% of our leads were unlikely to
move through to paid status – the problem was
that we didn’t know which leads were which.”
• Sean Cheyney, Vice President of Marketing and Business
Development
Case Study: AccuQuote
• The Solution:
• Score leads based on their likelihood to convert
to policies
• Leads are ranked on a scale of 1 to 10 with 1
being most likely to convert and 10 being least
likely
• The most likely-to-purchase prospects are then
moved to the top of the queue for the outbound
dialer and handled by live agents
• Leads that are judged to be less likely to convert
are contacted through email or passed to
trainees
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4. 9/30/2011
Case Study: AccuQuote
• The Result
• 4-5% increase in sales conversion overall
• Increase in conversion plus decrease in expense
leads to lower cost of acquisition
• A boost to sales team productivity — agents
gained an extra hour to spend on cross-sell and
needs analysis
• No loss of sales in the segment that received
email only
Case Study: Education Client
• A leading provider of educational support
services to consumer households
• The Challenge
• Thousands of leads coming in and being
distributed to franchise owners
• Dissatisfaction from franchise owners over
quality of leads
• Need to prioritize efforts to maximize revenue
• 3% lift in conversion equates to over $30mm in
additional revenue
Case Study: Education Client
• The Solution
• A multi-channel approach to following up on
leads based on lead quality
• Use a combination of phone, email and direct
mail to contact high potential consumers
• Use a lower cost contact method for lower
potential leads
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5. 9/30/2011
Case Study: Education Client
• Example:
• High potential customers receive premium DVD,
personalized direct mail piece directing
consumer to personalized URL, email and
phone contacts on a set schedule over 2 weeks
• Low potential customers receive postcard only
Case Study: Education Client
• The Result
• Compared to a control group, the test group
utilizing a tiered, multi-channel approach saw a
41% increase in initial enrollments within the
targeted groups
• An overall 8% increase in conversion overall
• A 360% ROI
Are all Customers created equal?
$ $
Customer A Customer B
5

6. 9/30/2011
First…Who do you WANT to keep?
$ $
Formula for CLV
Present Value = Future
Value/(1+i)n
(1+i) = Interests N = No of Years
First…Who do you WANT to keep?
• The customer lifetime value can be used to drive decisions
such as which customers to target, how much to spend on
$ saving them, what is the most effective media to use to
$
communicate with them, and how best to serve them to
ensure that they remain loyal for years to come
• Common questions that service providers should be asking
to be used in analytics:
• Am I accurately capturing, on a per-subscriber basis, all relevant revenue and
cost events?
• Am I capturing information necessary to identify different types of churn; e.g.
structural, voluntary, and non-payment churn?
• What can the data tell me that I can act upon?
• Can I tell if my business is changing based on my data?
• Am I using the right data?
• When looking at how to keep my customers—am I recording (properly) why
they left?
Utilizing Business Intelligence in Retention
• First, you have to decide who you WANT to save
• Analytic data models and human analysis combine to return
$ recommendations on upselling and retaining individual
$
customers drives real value for providers
• Develop a customer contact strategy. Some companies have
a policy of six touches per year, remembering that a bill is not
a touch
• Don’t rely on statement stuffers to communicate
• Use analytics to predict defection. A modern database can
identify potential churners with an accuracy of better than
90%
• Understand the causes of churn and use this information in
your analytics
• Develop Lifetime Value ROI’s for your customers
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7. 9/30/2011
Customers are Different
How you doin’?
$ $
• Customer A • Customer B
• High usage • Low usage
• Infrequent complaints • Frequent complaints
• High end equipment • Low end equipment
• No threats of leaving • Frequent threats of leaving
BI Analytics for Filtering
$ $ • Data modeled to provide which
customers deliver the best ROI
$ $ for targeting
$ • Second, channel segmentation
$ $ utilized to maintain impression
count while reducing costs
$ $
• Channel options can include:
$ $ • Email
$ • Mobile
$ $ • Social
$
• PURL’s
• Targeted Mail
$ • Telemarketing
$
Multi-Channel Campaign
• Client Profile:
• National Wireless provider with “tens of millions”
of customers
• Regional competition driving variable offers that
are hard to manage
• Brick and Mortar stores carry significantly higher
cost structure
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8. 9/30/2011
Challenge
• Shrinking retention budgets
• Increasing mail costs
• Diminishing response rate to static Direct Mail
offers
• Basic segmentation strategy did not accurately
reflect “churn”
Solution
• Utilize Business Intelligence to identify likely to
churn customers
• Utilize variable print and screen technology to
unlock variable offers and segmentation
• Propose a multi-channel and cost-progressive
strategy to increase ROI and marketing
effectiveness
• Employ multiple call center strategies to reduce
talk time and expense
Multi-Channel Campaign
• Control Retention Program:
• Basic segmentation strategy based on contract
expiration
• Direct Mail offers driven by current plan and
usage only
• Timing starts at 90 days to expiration and
continues through 60 days after contract
expiration
• Drive customer to inbound phone call for
contract signing
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9. 9/30/2011
Multi-Channel Campaign
Control Campaign Results
(Direct Mail Sent to Every Customer)
Customers
Units Cost Saved
Customer Base 30,000,000
Identification Filter 0
Customer Sent Direct Mail 30,000,000 $21,600,000
Inbound Calls from Direct Mail 750,000 $4,125,000 202,500
Total Cost of Direct Mail Campaign $25,725,000
Direct Marketing Cost per Customer Saved $127.04
Multi-Channel Campaign
Multi-Channel Customer Retention Strategy
IDENTIFICATION
TEXT MESSAGING
DIRECT MAIL
OUTBOUND
PHONE CALL
Strategies Employed
• Business Intelligence Group and Analytical
Modeling
• Variable Scripting and Offers
• One-to-one Direct Mail/Digital Printing
• Target Routing/Skill Based Routing
• IVR Verification
• Best Time To Call/Bucket Calling Efficiency
Based Dialing Strategies
• Front-end (Starter) / Back-end (Closer) Based
Dialing Strategies
9

10. 9/30/2011
Multi-Channel Campaign
Propensity to churn
IDENTIFICATION
IDENTIFICATION
Over-utilization Filter out
TEXT MESSAGING Contract expiration
Old equipment
Payment issues
DIRECT MAIL
Low usage
Certain geographies
OUTBOUND
PHONE CALL Do not contact
2.225 mcustomers
2.25M customers
to be targeted
Multi-Channel Campaign
Personalized E-Verification
Inbound
Filter Text E-Contract
Call
2.0M
IDENTIFICATION Keep
Do not text Offer Based
Non- on customer
responders BI Model away from
retail
outlet
TEXT MESSAGING
TEXT MESSAGING Old equip/ Offer Based
No text on
capability plan type 160K Calls
@ 8% RR
DIRECT MAIL Phone
225k
exclusive
removed
offer
OUTBOUND
PHONE CALL
Multi-Channel Campaign
Personalized
Inbound E-Verification
Filter Mail Piece
1.38M
Call E-Contract
IDENTIFICATION Keep
Do Not Mail Personalized
customer
away from
retail
Non- Offer Based outlet
Responsive On BI Model
TEXT MESSAGING
to Mail
55K
Offer Based Calls @
ROI Filter: On Plan Type 4% RR
Usage/
DIRECT MAIL
DIRECT MAIL Profitability
Geography
461K
Removed
OUTBOUND Demographic
PHONE CALL Psychographic
Drivers
Phone
Exclusive
Offer
10

11. 9/30/2011
Multi-Channel Campaign
Outbound
Inbound E-Verification
Filter Call
675K
Call E-Contract
IDENTIFICATION Keep
Do Not Call Offer Based
On BI Model customer
away from
retail
Non-
outlet
Responsive Offer Based
TEXT MESSAGING On Plan Type
to Phone
74K
Calls
Respondents Phone
to Text or Exclusive
DIRECT MAIL Direct Mail Offer
Billing 405K
OUTBOUND Cycle Contacts
PHONE CALL Made
More
More
Stringent
Stringent
ROI Filters
ROI Filters
649K
Removed
Multi-Channel Campaign
$
$ $ • Filtered out undesirable
customers in order to
$ $ $ curb further investment
$ $
• Used modeling and
$ $ analytics to filter through
$ contact channels as well
$ $ as crafting offers
$ $
$
• Utilized variable print and
screen technology to
$ $ ensure a customizable
experience
• Focused on efficiency and
maximizing ROI
Telemarketing
Direct Mail
Texting/Email
Multi-Channel Campaign
Multi-Channel Campaign Results
Customers
Metric Cost Saved
Customer Base 30,000,000
Identification Filter (27,775,000)
Text Filter (225,000)
Customer Sent Text 2,000,000 $80,000
Inbound Calls from Text 160,000 $880,000 83,200
Direct Mail Filter (460,920)
Customer Sent Direct Mail 1,379,080 $992,938
Inbound Calls from Direct Mail 55,163 $303,398 28,685
Outbound Telemarketing Filter (648,719)
Outbound Telemarketing Universe 675,198
Outbound Telemarketing Contacts 405,119 $2,329,432 190,406
Inbound Calls from Outbound TM 74,272 $408,495 38,621
Total Cost of Direct Marketing Campaign $4,994,261 340,912
Direct Marketing Cost per Customer Saved $14.65
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12. 9/30/2011
Multi-Channel Campaign
Multi-Channel Campaign Summary
Control Multi-Channel
Customers Saved 202,500 340,912
Direct Marketing Campaign Cost $25,725,000 $4,994,261
Cost per Customer Saved $127.04 $14.65
Sales Revenue of Saved Customers $96,130,800 $161,837,687
Percent of Saved Revenue Spent on Direct
26.76% 3.09%
Marketing Efforts
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