The document discusses utilizing business intelligence and analytics to optimize customer retention through a multi-channel strategy. It provides an example of a wireless provider that implemented a multi-channel retention campaign involving identification of at-risk customers, targeted texting, direct mail, and outbound calls. This approach filtered customers into the most effective channels and offers based on analytics, achieving a 340,912 customers saved at a cost of $14.65 per customer versus the control group's 202,500 customers saved at $127.04 per customer. The multi-channel strategy improved retention rates while lowering costs.
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Multichannel Retention Strategies: A Steady Diet of Low-Hanging Fruit
1.
2. 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
⢠Real World example of an effective Multi-Channel
Retention campaign utilizing Analytics and Cost-
Progressive Channel Strategy
5. ⢠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 thatâs just the costs
of activating and deactivating
services.
Customer Churn Costs
6. $
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⢠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 new
customers just to keep one.
⢠Hundreds of studies have
proven that most companies
spend $10 to acquire a new
customer for every $1 spent in
retention strategies!
Customer Churn Costs
Knowing this, why
donât we invest
more in our current
customers?
8. Case Study: AccuQuote
⢠A leading provider of term life insurance
⢠The Challenge
⢠Inbound leads needed to be better prioritized for
the sales team
⢠âWe knew that 20% of our leads were unlikely to
move through to paid status â the problem was
that we didnât know which leads were which.â
⢠Sean Cheyney, Vice President of Marketing and Business
Development
9. 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
10. 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 â agents
gained an extra hour to spend on cross-sell and
needs analysis
⢠No loss of sales in the segment that received
email only
11. 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
12. 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
13. 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
14. 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
15. $ $
Customer A Customer B
Are all Customers created equal?
16. $ $
Calculate the Customer Lifetime Value
Formula for CLV
Present Value = Future
Value/(1+i)n
where
(1+i) = Interests and
n = No of Years
17. $ $
FirstâŚWho 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?
⢠When looking at how to keep my customersâam I recording (properly) why
they left?
18. $ $
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 ROI
⢠Develop a customer contact strategy. Some companies have
a policy of six touches per year, remembering that a bill is not
a touch
⢠Use analytics to predict defection. An updated 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 ROIâs for your customers
19. $ $
Customers are Different
⢠Customer A
⢠High usage
⢠Infrequent complaints
⢠High end equipment
⢠No threats of leaving
⢠Customer B
⢠Low usage
⢠Frequent complaints
⢠Low end equipment
⢠Frequent threats of leaving
How you doinâ?
20. $
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$
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
⢠PURLâs
⢠Targeted Mail
⢠Telemarketing
⢠Pay attention to how your
customer WANTS to interact
with youâŚNOT how itâs
convenient for you to contact
them.
21. Multi-Channel Campaign
⢠Client Profile:
⢠National Wireless provider with âtens of millionsâ
of customers
⢠Regional competition driving variable offers that
were hard to manage
⢠Brick and Mortar stores carry significantly higher
cost structure
22. Challenge
⢠Shrinking retention budgets
⢠Increasing mail costs
⢠Diminishing response rate to static Direct Mail
offers
⢠Basic RFM segmentation strategy did not
accurately reflect âchurnâ
23. 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
24. 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
25. Multi-Channel Campaign
Control Campaign Results
(Direct Mail Sent to Every Customer)
Units Cost
Customers
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
27. 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
28. Multi-Channel Campaign
Payment issues
2.225 m customers
to be targeted
Certain geographies
Do not contact
2.25M customers
to be targeted
Filter out
Propensity to churn
Over-utilization
Contract expiration
Old equipment
Low usage
IDENTIFICATION
TEXT MESSAGING
DIRECT MAIL
OUTBOUND
PHONE CALL
IDENTIFICATION
29. Multi-Channel Campaign
IDENTIFICATION
TEXT MESSAGING
DIRECT MAIL
OUTBOUND
PHONE CALL
Keep
customer
away from
retail
outlet
160k
calls
8 % RR
Do not text
Non-
responders
E-Verification
E-Contract
Offer Based
on
BI Model
Offer Based
on
plan type
Phone
exclusive
offer
Inbound
Call
Personalized
Text
2.0M
Filter
225k
removed
Old equip/
No text
capability 160K Calls
@ 8% RR
TEXT MESSAGING
Offer Based
on
BI Model
30. Multi-Channel Campaign
IDENTIFICATION
TEXT MESSAGING
DIRECT MAIL
OUTBOUND
PHONE CALL
Do Not Mail
E-Verification
E-Contract
Inbound
Call
Personalized
Mail Piece
1.38M
Filter
ROI Filter:
Usage/
Profitability
Non-
Responsive
to Mail
Keep
customer
away from
retail
outlet
DIRECT MAIL
461K
Removed
Phone
Exclusive
Offer
Personalized
Geography
Offer Based
On BI Model
Offer Based
On Plan Type
Demographic
Psychographic
Drivers
55K
Calls @
4% RRROI Filter:
Usage/
Profitability
Offer Based
On BI Model
Demographic
Psychographic
Drivers
31. Multi-Channel Campaign
IDENTIFICATION
TEXT MESSAGING
DIRECT MAIL
OUTBOUND
PHONE CALL
Do Not Call
E-Verification
E-Contract
Inbound
Call
Outbound
Call
675K
Filter
Respondents
to Text or
Direct Mail
Non-
Responsive
to Phone
Keep
customer
away from
retail
outlet
Billing
Cycle
405K
Contacts
Made
Offer Based
On BI Model
Offer Based
On Plan Type
Phone
Exclusive
Offer
74K
Calls
OUTBOUND
PHONE CALL
More
Stringent
ROI Filters
649K
Removed
Offer Based
On BI Model
More
Stringent
ROI Filters
33. Multi-Channel Campaign
Multi-Channel Campaign Results
Metric Cost
Customers
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
34. 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
Marketing Efforts
26.76% 3.09%