Fit Life CoveredA case study in Digital Life Insurance Distribution

Todd Seabaugh

September 26, 2017

VP Business Initiatives, RGAx

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WHO IS

RGAx is a wholly owned subsidiary of Reinsurance Group of

America

• Entrepreneurs

• Execution Managers

• Actuaries

One of our mandates is to find innovative means to “Prime

the Pump” of life insurance sales to the middle market.

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THERE ARE 1.2MM ACTIVE CROSSFIT ATHLETES IN THE US, OF WHICH, 28% HAVE NO LIFE COVERAGE, AND 58% BELIEVE THAT THEY NEED ADDITIONAL PROTECTION.

Original Problem Statement

March 2016

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Why we believe they are not seeking protection?

No one is marketing to them based upon their active lifestyle

• Could it be because of their likely preferred pricing placement?

There are few digital sales efforts bringing life solutions to this market

• Health IQ

The value proposition of fully underwritten term life insurance has not

been well communicated

• “Your premiums could be 50% lower than the standard non-smoker”

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Can we succeed with “Affinity-based” marketing?

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Why “CrossFit” Athletes?

We surveyed 1000 athletes in 11 gyms from across the US. Our Survey Findings:• 89% college educated

• Analytical, Type A, Driven to Succeed, Many 1099

• 50% have income of $50K-125K / 35% see income of $125K+

• Believe staying physically active provides an edge in life

• Believe products and services do not recognize their fitness/wellness

• Believe they would buy life insurance with preferred pricing

• Treat the gym like its own kind of “church”

• Do things outside of the gym together

• Provide care for one another when sick or suffer a financial or personal loss

• Recommend products and services to one another that they find useful

• (Fat Tanks, Chiropractors, Financial Advisors, Attorneys, Lifting shoe brands, etc., etc., etc.)

Our message: Work Hard. Be Rewarded.

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What we believed about this groupHypothesis: We can sell protection by employing strategic content that satisfies:

• Need for protection (Peace of Mind)

• Need to compare (Competitive Personality)

• Need for data (Analytical Personality)

• Need for someone to recognize my fitness work (Ego)

Survey of 1000 athletes further reinforced the following:

• Want rewards for their commitment to a fit lifestyle,

• Want preferred pricing,

• Want to compare themselves to others,

• Want a digital application process

• Understand that it takes effort to qualify for preferred pricing and are

willing to make that effort

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So we built our siteMVP Site: mylifecovered.com

• Fitness and Life insurance content mix

• One term product with a single carrier

• Online quoting engine with a detailed “needs analysis”

• Standard Non-Smoker and Preferred Plus Pricing in a single quote result

• One option: Apply Online

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Marketing the site

We promoted the site with Google AdWords spend and SEO

• Google AdWords for life insurance were very expensive to acquire!

• $18-40/click depending upon the phrase

• “Inexpensive Life Insurance”

• “Term Life Insurance”

• We tried using long tale AdWords but no one was searching for what we were bidding for:

• “Life insurance quotes for the fit”

• “Life insurance for healthy and active adults”

• “Life insurance for fit and healthy adults”

• Etc.

Our sales were unimpressive, but our advertising spend was significant

Carrier ACarrier B

Carrier C

Carrier D

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Major Pivot 1No “meaningful” success.

• We believed the name was not direct enough: • Rebranded the site as fitlifecovered.com

• We believed the lengthy needs analysis we presented was too hard and time consuming: • Simplified our quote request

• Full Needs Analysis

• I know how much I make (we multiplied times 10 for coverage)

• I know how much I need

• I know how much I can afford

• We believed people wanted to compare: • Created 6 additional carrier relationships and offered quotes on 5 carrier products with each quote request

• We believed people might prefer to talk with an advisor (though they said online was preferred):• Created options to apply online or by phone with a tele-agent

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Pivot 1 ResultsWe created about the same number of impressions

• So the cost per impression remained relatively constant

• Cost per lead decreased by almost 50%

• Cost per application decreased by a similar 50%

• Cost per lead was still 80x our target cost

• Surprise: Many of our leads, particularly those wanting to apply online, were NOT in our target at all

• Drug use

• Medical Conditions

• Turned down by other carriers

• Etc.

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Intended Audience

Actual Applicants

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Major Pivot 2CrossFitters were still not buying. - - - 1.4MM Americans CrossFit, but 54MM Americans belong to some health club or studios, maybe we should broaden the audience appeal.”

• We redesigned the site:• Gone with “Work Hard. Be Rewarded.”

• In with “Training is all about you. Life insurance is all about them.”

• We broadened our exposure• More articles on health

• More articles on nutrition

• More articles on general fitness & nutrition

• We changed our ad spend• We dropped Google AdWords, (remember, it was bringing us unqualified applicants)

• We added Facebook Direct Advertising to actives between 25-45, interested in HIIT, running and cycling

• We added Taboola-style advertising in web sites known to be visited by actives

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15

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Pivot 2 ResultsWe were now giving quotes to the right people

• Cost per impression went down significantly (< $2.00/1000 impressions)

• Cost per lead decreased by 40 times

• Cost per lead was still 2x our target cost however, but no longer 80x!

• Applicants were now in our target market

• Completed Application volume however remained disappointingly low (1 for every 98 leads)

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Funnel Process

Aw

are

ne

ss

Con

sid

era

tio

n

Tra

nsa

ctio

n (

Qu

ote

)

Rese

arc

hApplication Underwriting Offer Customer

97% Drop Off

Facebook

Videos

Taboola Ads

Social Media

Google AdWords

“Get a Quote”

Content Consumption

Life/Nutrition/Fitness/Health

To

o D

ifficult

To

o M

an

y Q

ue

stions

To

o M

an

y T

hin

gs I d

on

’t k

no

w

To

o L

on

g!

To

o M

an

y a

dd

ed r

eq

uir

em

ents

To

o M

uch

Tim

e to

re

thin

k d

ecis

ion

or

lose

in

tere

st

Lo

st in

tere

st

Hig

he

r th

an

Pre

ferr

ed

Plu

s

To

o d

ifficult to

co

mple

te

We have an emotional product and a situation

where emotion can come and go long before

conversion

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Through Web Marketing, finding a digital Life Insurance

Audience, within affinities, is really difficult

Google AdWords

Easy to find the eyes

Looking for

Life Insurance

Social Media Ads

Easy to find the eyes

Of Active, Healthy

Adults in a specific

Age rangeActive/H

ealthy &

Lookin

g f

or

Life I

ns

Neither platform gives you Active, Healthy & Interested in Life Insurance purchase.

You need additional data to find the intersection.

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Our Key Learnings

• With innovation, the “big idea” is just the beginning• You will find numerous smaller ideas and hypothesis to test

• You will need to be nimble, and open to directional changes, to avoid unnecessary spend

• Success likely comes incrementally, as individual tests reveal conversion improvements and failings

• Developing a dedicated team to support the big idea is paramount. Shared duty resources aren’t able to find the focus or passion to drive you to success

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Our Key Learnings

• Life Insurance being largely “sold, not bought”, makes for a difficult online conversion• It is difficult to build Trust online, and Trust is central to Life sales

• Agent assisted sales (for us) yielded better results

• Removing friction is key• Because of this, fully UW product sales remain difficult to complete

digitally

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Our Key Learnings• Finding Life Insurance interest, at the affinity group level, is still hard

• Google is working on services allowing you to cross-segment your advertising (right now, they are AdWords “one-dimensional”)

• Finally, Evaluate innovation managers based on whether they executed disciplined experiments, not on ROI.

• Pro formas are great for telling you how much you will spend (or budget to spend)

• Pro formas are rarely “spot on” when it comes to revenue assumptions

• Holding innovation managers to Pro forma revenue projections as their primary success measure is very unrealistic

• Evaluate innovation managers based on running disciplined experiments

• Efficient spend

• Timely analysis

• Quick recognition of failures and successes

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Thank you

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