Customer lifetime value for insurance agents was presented by Scott Boren to the BIG Insurance Group in Southern California. The lecture was designed to share insight from his consulting firm and the impact a customer lifetime strategy can have on an insurance agent's service, marketing, and in identifying developing customer personas.
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Optimize Insurance Marketing with Customer Lifetime Value Framework
1. Presented by: Scott Boren
Co-Founder and Partner Quantum Sight
Marketing
CUSTOMER LIFETIME
VALUE
1
President IronPoint Insurance Services
An optimized customer strategy framework
2. Partnership of Two Companies
Quantum Sight Marketing is
an analytic marketing
consulting firm specializing in
product and consumer
marketing analytics.
Quantum Sight Marketing
also has an insurance
practice focused on:
Distribution Analytics
Loss Cost Modeling
Credit Model Development
Product Design and
Development
Operations and Claims
Analytics
IronPoint Insurance Services
is an Independent retail
insurance agency.
Focused on Preferred
Personal Lines and built on
the Customer Lifetime Value
model.
Affiliate program for startup
agencies.
Preferred Appointments
Agency Management System
Errors & Omissions Insurance
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And more….
2
Quantum Sight Marketing,
LLC
IronPoint Insurance Services
3. Who the heck is this guy?
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• Director of Research and Development: Led team to design, develop
and implement new national auto insurance product, including credit model
and point-of-sale system.
• Director of Product Management: Led West Region and managed P&L in
excess of $2.1B.
• Senior Product Manager: Managed the California Auto Insurance Market
for the leader in Direct Response auto insurance. Responsible for all P&L,
product design, performance, and revue growth. Was part of the West
Region leadership team responsible for Quality of Sales, Services and
Underwriting.
• Mid-West Zone Product Manager: Worked at esurance shortly after their
initial start-up. Was part of the team of product managers who
implemented a new product design and expansion into new states of
opportunity. Managed their growth in the Mid-West in excess of 20%
annually.
• Product Manager: Worked up from Product Analyst to assume the role of
Product Manager of the state of California. At the time California
represented nearly half of the companies exposure and was a top 20
market share company in the state, and a leader in the nonstandard auto
market here in CA.
4. Marketing Analytics
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There is a growing push across most business
categories to apply analytics to solve or assist
in solving business questions.
Examples are all around us---- the selections
provided to you by Netflix, airline ticket pricing,
credit card offers and rates, and much more…
Insurance has long used analytics in pricing:
Conventional actuarial practices
Recent use of multivariate pricing techniques.
5. Insurance Analytics – Not Just Loss
Costs
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Loss cost modeling used in personal lines
insurance in the US is getting more advanced.
Over 80% use advanced multivariate tools to solve
pricing.
Many companies are using similar analytics to
study consumer behavior.
Consumer Demand
Elasticity (Price Sensitivity)
Predict Retention (Policy Life Expectancy – PLE)
Marketing Mix Models (MMM)
Marketing Response Models
…and Customer Lifetime Value
6. Critical Measurements of CLV
Intrinsic
Loyalty/
CLV ($)
?
•Predictive
•Segment-”able”
•Separates customer &
company
Service
and
Sales
Data
Custome
r
Insights
VOC
Optimized
CLV
Strategy
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7. What is Customer Lifetime
Value
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The monetary value each customer generates over
the lifetime of their engagement with YOUR agency.
The Customer Lifetime Value
Framework
Current Relationship
Revenues
Predicted Customer
Tenure
Predicted Future Revenue
44 Year old married couple
purchases a new car and shops
your agency for liability +
Physical damage coverage.
Premium is $150 monthly.
Model predicts the policy
survival months of for this policy
based on variables input to rate
the auto insurance policy.
Policy tenure is predicted at 60-
months.
Cross-Sell probability models
predict ability of agency to pick-up
other lines of business (eg.
Home and/or life). Probability of
cross-sell of home is 60% @
$100 Monthly for auto + home
and survives 120 months)
Auto Policy Monthly Premium
$150
x 60 Survival
Months
+ [(.60 x $100) x 120 months] =
$16,200
$16,200 of premium equals agency revenues of $2,400 @ 15%
commission rate
Cross –
Sell
Models
8. Why is this Important to me?
The analysis suggests that
investment in developing a high
CLV customer base produces
better margins. How do we find
these customers?
High Mid Low
25x
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Customer Lifetime Revenue
(CLV) $16,200 $8,100 $2,835
Lifetime Commissions $2,430 $1,215 $425
Acquisition Costs $125 $125 $125
Lifetime Margin $2,305 $1,090 $300
% of Current Book 15% 50% 35%
High CLV
customers bring
in 25x more
revenue to your
agency.
12.5
0.5
0
Hig
h
CLV
Avg
CLV
Low
CLV
9. Develop a Revenue based
Segmentation
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If you can predict the lifetime revenue value of
a customer at the point-of-sale, what might you
change?
How you segment your customers?
Align your agency practices with these new
segments?
Align products offered to meet new needs?
Change your service levels for specific
segments?
Reconsider how, where, and when you market or
advertise?
10. Revenue Based (CLV)
Segmentation
Using market analysis one can identify the
predictors of CLV, segment membership, and
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Segment 1:
Comfort Seekers
• 40+ years old
• Have assets
• Find Insurance
complicated
• Desire
Relationship
• Education
• Tend to be a
Higher CLV
customer.
Segment 2:
Ambivalent
• 30+ years old
• Want things
easy
• Educated
• Low hassle
• Prefer phone or
email
relationship.
• Don’t have a
preference
(online or agent
OK).
Segment 2: Do It
Yourself
• Younger group
• Place a low
value on
insurance.
• Distrust
Insurance
Company/Agent
• Likely to
purchase online.
• Price sensitive
• Low CLV
consumer.
develop actionable profiles.
11. CLV and Agency Best Practices
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Some agencies already locate these
consumers….what are the best practices? Where
can I find these consumers?
What would a survey of the
agents with a book of high
CLV reveal?
My CLV best practices Checklist
Here is a list of places we market
to find all of our best clients:
____ 1. Direct Mail
____ 2. Telemarketing (ex-dating)
____ 3. Internet
____ 4. In-Person Contact
____ 5. Local Advertising
(Newspaper)
____ 6. Centers of Influence
Maybe it’s not directly
attributable to the marketing mix,
and it has to do with business
practices?
What are the business habits of
the agents with the highest mix
of high CLV customers?
1. What is the sales craft?
2. What is the cross-sell
philosophy
3. How and when do they
approach cross sell?
4. Does marketing matter? Why?
5. Staff training?
12. Forming Good CLV Agency
Habits
3.50
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The agents who have the highest concentration of
high CLV customers have common agency best
practices.
0 1 2 3 4 5
1.00
Number of CLV Best Practice
Traits
Relative Difference in High CLV
CLV Best Practices
Count
Where do You
Network?
What Affiliations do
you have?
What is your Cross-
Sell Philosophy?
When do you
attempt to cross-sell?
What is your sales
craft? Consultative?
13. Can You use CLV in Marketing?
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Including a CLV measure in your direct mail
campaigns will improve your ROI.
Conventional
Segmentatio
n
Segmentatio
n including
CLV
Expected
Response
Expected
Response
Expected
Response
Do
Not
Mail
Do
Not
Mail
14. CLV Optimized Direct Mail Business
Case
Before CLV Focus Optimized for CLV
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Mailed to 500,000
Households
• 0.05% Return
• 1000 Respondents
• 100 Converted Leads @
and average of $1,250
lifetime revenue each.
Total expected lifetime
revenue return = $125,000
(premium) or $18,750
Commission
Mailed to 350,000
Households
• 0.04% Return
• 750 Respondents
• 75 Converted Leads @
and average of $2,750
lifetime revenue each.
Total expected lifetime
revenue return = $206,250
(premium) or $30,937
Commission
Basis for mailing was conventional
response model. Targeted all likely
respondents
Targeting both High and Mid CLV
along with response model, company
reduced costs and increased
revenues.
15. CLV Broadcast Ad Business
Case
Conventional
Copy Testing
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Ads can be optimized using CLV to improve
messaging, aid recall and consideration for best
ROI.
CLV
Optimized
Copy Testing
Ad Recall
55%
Consideration
36%
AD ROI
87%
OPTIMIZED FOR CLV
Ad Recall
45%
Consideration
24%
AD ROI
67%
PRE-CLV
16. Goal: Use CLV to Optimize Marketing
Mix
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Radio
Interne
t
TV
Print
Radio
Interne
t
Direct
Mail
TV
Print
Direct
Mail
Pre-
CLV
Post-
CLV
Total
Radi
o
Internet
TV
Print
Direct
Mail
Total
Radi
o
Internet
TV
Print
Direct
Mail
Pre-
CLV
Post-
CLV
Work with ad agency to target
High and Mid CLV in conjunction
with CLV marketing mix model to
optimize marketing spend.
CLV allows marketing managers
to justify expenditure, more easily
calculate ROI, and produce
results.
Marketing Mix
Allocation
Marketing Mix
ROI
17. CLV Implication on Operations
If time is your “shelf space” where should you spend
25x
High CLV consumers exhibit
higher overall Retention.
Basically, most of your revenue
comes from a small % of
consumers types.
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12.5
0.5
0
Top
10
%
Avg Bottom
10%
CLV Impact on
Revenue
120
60
0
Top
10
%
Avg Botto
m
10%
Retention in
Months
As already exhibited, the
higher CLV consumer provides
better lifetime revenue.
it?
On the % of the book that makes you the most
money!
18. Additional CLV Consideration
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Customer Loyalty
Consideration
CLV is intrinsic to the consumer, but their loyalty to
YOUR agency is largely determined at the Point-of-
Acquisition and On- Sale.
Boarding
Post Sales Service
Transactions
80% 20%
19. Key Take Aways
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A CLV strategy integrated into your current
strategy, can elevate your ROI.
Segmenting consumers on a CLV/Revenue
basis can change your marketing mix
allocation and improve ROI on marketing
spend.
CLV is intrinsic to the consumer and largely
not causal.
Loyalty is determined largely at the point-of-sale.
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Scott A. Boren
President IronPoint Insurance Services
Partner Quantum Sight Marketing, LLC
Editor's Notes
Life Time Value customers generate for a company with no stimuli (Good or Bad) from the company.
Different for each customer
Predictive (identify as early as prospecting stage)
Powerful segmentation tool
Most important! Seperates Loyalty drivers (who you attract vs. what you do!)