MOMENTS OF TRUTH

REPORT

MOMENTS OF TRUTH
CUSTOMER SATISFACTION AND
RETENTION IN THE AUTO INSURANCE
CLAIMS AND REPAIR JOURNEY

© CCC Intelligent Solutions Inc. All rights reserved. 1

MOMENTS OF TRUTH

TABLE OF CONTENTS

Executive Summary 3
Introduction 5
Literature Review 5
Study Design 7
General Findings 8
Insurer Satisfaction Findings 11

Insurer Defection Findings 15

Repairer Satisfaction Findings 19

Methodologies 25
Multiple Linear Regression to Analyze the Moments of 25
Truth in Insurer and Repairer Customer Satisfaction

Logistic Regression to Analyze the Moments of Truth in 26

Insurer Customer Defection

Data Normalization 26

Recommendations 28
Limitations and Mitigations 29
Future Research and Development 30
Conclusion 31

© CCC Intelligent Solutions Inc. All rights reserved. 2

MOMENTS OF TRUTH

EXECUTIVE SUMMARY

CCC Intelligent Solutions Inc. undertook a study to identify the “moments of truth” in consumers’
satisfaction with their insurers and repairers after a vehicle accident and the subsequent claim and
repair journey. The study also examined the propensity to switch carriers after this journey.

The study evaluated 47 “moments” in the claims and repair journey after a policyholder had filed a
first-party claim. The moments studied included how consumers perceived communications, the
process, the empathy they received, overall time to repair, and more. The study sought to define the
critical points in time – or “moments of truth - in which carriers and repairers must perform well to
achieve a good outcome for customer satisfaction, and for carriers, customer retention.

Among the key findings is that when it comes to customer satisfaction, policyholders hold both
carriers and repairers accountable for outcomes that are the responsibility of other partners. For

© CCC Intelligent Solutions Inc. All rights reserved. 3

MOMENTS OF TRUTH

example, respondents are more satisfied with their carriers when they perceive overall vehicle
repair quality to be high, and they’re also more satisfied with their repairer when they receive clear
communications about how the claims process will work. This suggests that, in a consumer's mind,
the entire post-accident journey from “crash to keys” is one unified experience in which the
providers are, in some instances, indistinguishable from one another.

The research also casts doubt on a long-held belief by insurance claims professionals that customer
satisfaction, a metric by which claims teams measure their performance, helps predict customer
retention. In fact, the study found that most of the moments that helped the carrier achieve a
positive customer satisfaction score were relatively statistically insignificant in helping to
determine carrier defection – including the insurer satisfaction score itself. According to the
findings, 3 moments were the most powerful predictors of switching behavior:

In a total loss, the policyholder was upside down in their outstanding loan and was
able to cover the gap

The presence of an injury in the accident

Being a first-time claim filer (with any insurer)

When all 3 are present, there is greater than a 3x increase in the likelihood of the policyholder leaving
the carrier.

Other study findings include key moments in the repair satisfaction score, as well as the moments
that “didn’t matter” in each of the outcomes.

Overall, the study highlights the shared responsibility of both carriers and repairers in customers’
minds to get them back on the road, regardless of who is actually the responsible party. Study
findings underscore the need for a unified, customer-centric approach that focuses on
configurability, personalization, and retention management.

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MOMENTS OF TRUTH

INTRODUCTION
The auto claims and repair industries play a crucial role in getting people back to normalcy in the
aftermath of a vehicle accident. The process of restoring the customer to wholeness involves an
intricate web of insurers, repair facilities, tow, rental, salvage, lenders, and other providers, each
navigating their own unique goals and business challenges.

Two of the industry’s ongoing challenges have been how to improve customer satisfaction and
customer retention, as the cost of acquiring new customers1 far exceeds the cost of retaining
existing ones. In recent years, customer satisfaction scores have fluctuated while customer
defection is on the rise.2

This study aims to delve deeper into the factors impacting auto insurer and repairer customer
satisfaction and carrier policyholder retention, uncovering potentially hidden nuances to guide a
more informed path forward for the industry.

LITERATURE REVIEW
Based on a review of mainstream literature on the topics of customer satisfaction and carrier
defection in the auto claims and repair industry, this study appears to be the first of its kind to
uncover the interdependencies that exist between carriers and repairers on overall customer
satisfaction.

It is also among the first studies to look at how customer satisfaction impacts retention in the claims
industry. While it confirms some of what others have found, this study identifies new variables – or
“moments” - that can serve as a statistically reliable rubric for predicting when a policyholder is likely
to switch carriers.

This Accenture study3 found that dissatisfaction around the claims experience is a key reason
driving customers to switch insurers. Nearly one-third (30 percent) of dissatisfied claimants said

1
Insurance Thought Leadership: https://www.insurancethoughtleadership.com/customer-
experience/lowering-costs-customer-acquisition

2
LexisNexis Insurance Demand Meter Q4 2023
3
Accenture, “Why AI in Insurance Claims and Underwriting?” (2022)

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MOMENTS OF TRUTH

they had switched carriers in the past two years, and another 47 percent said they were considering
doing so. Additionally, this Bain and Company study4 found that a positive claim experience boosts
policyholder retention.

In April 2023, J.D. Power reported5 auto insurance switch rates had reached new highs as premiums
surged. In June 2023, they found that satisfaction with auto insurance had dropped 12 points year-
over-year6, the largest decline in the past 20 years. Later that same year, another J.D. Power study7
found that customer satisfaction with the claims process had improved, despite repair backlogs and
parts shortages.

The problem with these studies is that customers may often say one thing and do another. They
might report satisfaction, but according to a primer from Interdependent Insurance Agents of
Dallas8, mere satisfaction is not enough and there is no statistical correlation that says the customer
will stay with their provider.

Satisfaction with repairers has been widely under-reported. Another J.D. Power study found that
being easier to do business with, convenience, speed, and price are key drivers of customer
satisfaction.9

Overall, according to Accenture10, carrier customers who reported not being fully satisfied could
represent up to $34 billion in premiums annually, or up to $170 billion over the next five years.

For insurers, the cost of acquiring a new customer is higher than most businesses. William Blair &
Co. analyst Adam Klauber determined that carriers are spending an average of $487-$792 to acquire
a new customer11. When factoring in independent agencies, the average cost of customer
acquisition rises to $900 per customer.

4
Bain & Company: https://www.bain.com/insights/how-to-improve-customer-retention-in-property-and-
casualty-insurance-snap-chart/
5
J.D. Power 2023 U.S. Insurance Shopping Study, SM
6
J.D. Power 2023 U.S. Auto Insurance Study
7
J.D. Power 2023 U.S. Auto Claims Satisfaction Study, SM
8
https://www.iiadallas.org/page/75
9
J.D. Power 2023 U.S. Aftermarket Service Index (ASI) Study
10
Accenture, “Why AI in Insurance Claims and Underwriting?” (2022)
11
Insurance Thought Leadership: https://www.insurancethoughtleadership.com/customer-
experience/lowering-costs-customer-acquisition

© CCC Intelligent Solutions Inc. All rights reserved. 6

MOMENTS OF TRUTH

While customer acquisition is essential to the property and casualty insurance industry, a study
from Bain found that increasing customer retention rates by just five percent can increase profits
by anywhere between 25 and 95 percent.12

Bain also published a study that found property and casualty insurance carriers tend to perform
better on either customer acquisition or retention, but not both, and found that most new customers
have switched from another insurer.13

The relationship between customer satisfaction and switching behavior is complex and
inconclusive. Auto claims professionals often prioritize customer satisfaction, and while some
research suggests a strong link between satisfaction and retention, other studies indicate that high
satisfaction does not necessarily lead to customer loyalty. This underscores the need for further
auto claims and repair industry research to fully understand the dynamics of customer behavior in
this context.

STUDY DESIGN
The purpose of the study was to identify the “moments of truth” in the claims and repair journey.
There are dozens of moments in the “crash to keys” process, but the ones that matter are those with
the most significant impact on the final outcome. These are the moments that must be “won” in
order to have positive outcomes in insurer satisfaction, repairer satisfaction, and policyholder
retention (for carriers).

Conducting this study required gathering data about the outcomes (the dependent variables) and
the moments (the independent variables) from policyholders who had been through both a claim and
repair journey. Therefore, CCC commissioned a study of 2,400 policyholders, all of whom had:

1) Been in an accident within the past two years (August 2021-December 2023), AND
2) filed a first-party claim, AND
3) Completed a repair process (even if their vehicle was eventually totaled out)

12
Bain & Company: https://media.bain.com/Images/BB_Prescription_cutting_costs.pdf
13
Bain & Company: https://www.bain.com/insights/customer-behavior-loyalty-in-insurance-global-2016/

© CCC Intelligent Solutions Inc. All rights reserved. 7

MOMENTS OF TRUTH

If a respondent did not meet all 3 of these criteria, they were excluded from the study. For example,
the study did not include those who filed third-party claims, or pocketed their insurance payment
without completing a repair, or repaired the vehicle on their own (among other examples of those
who did not complete the entire journey.)

The survey of policyholders was conducted over the period between August and December 2023
regarding their car accident experiences that occurred within 2 years from the time of their survey
completion. This timeframe placed these drivers as having an accident during and immediately after
the pandemic, when repair cycle times were elongated.

The survey included over 120 questions covering various aspects of the claims and repair journey:

• 12 screening questions to check for eligibility and that respondents were paying attention
• 6 demographic questions
• 28 questions on Collision & Notification
• 51 questions on Claims Management Experience – Vehicle & Injury
• 18 questions on Rentals & Loaners
• 30 questions on Repair Experience

CCC engaged Magid Research, a prominent market research firm known for its expertise in
understanding consumer behavior and preferences across various industries, to conduct the
survey.

GENERAL FINDINGS
The 2,400 survey respondents were generally representative of the insurer and repairer customer
bases. Sixty-seven percent had a college degree, 84 percent were homeowners (either outright or
through a mortgage), and 64 percent had a household income of over $75,000.

© CCC Intelligent Solutions Inc. All rights reserved. 8

MOMENTS OF TRUTH

A Note on Demographics
The age groups of the respondents are listed in Figure 1. Those over 74 and under 25 were
intentionally removed to prevent bias.

Figure 1: Survey Respondent Demographics

Age Group % of Respondents

67% of respondents have

a college degree
25–34 28%

35–44 44% 84% are homeowners (either

outright or through a mortgage)

45–54 16%
64% have a household
income of over $75,000
55–74 12%

In general, satisfaction scores were very high for both insurers and repairers, averaging 4.4 out of 5
for both segments. Overall, 17% of the sample said they switched carriers after the claim. (Figure 2)

Figure 2: Insurer and Repairer Customer Satisfaction Outcomes

4.4 average insurer

satisfaction score

4.4 average repair

satisfaction score

17% percent of
switchers

© CCC Intelligent Solutions Inc. All rights reserved. 9

MOMENTS OF TRUTH

The Moments We Studied

The following moments outlined in Figures 3, 4, and 5 were considered independent variables to
control for in the linear and logistic regression models:
INSURER SATISFACTION | PROPENSITY TO SWITCH CARRIERS | REPAIR SATISFACTION

Figure
M OMEN 3:TInsurer
S W E SCustomer
T U D I E D Satisfaction
I N I N S U R E RMoments
S A T I S FStudied
ACTION
Claim Repair Center Repair Center Repair Center Claim Demographic/
FNOL
Experience Selection Experience Process Resolution Psychographic

• Injury • Clear comms about • How repair center • Satisfaction with • Able to influence • # of days to • Age
• Drivable claims process was chosen ability to get parts selection determine fault • Income
• How insurer • Empathy • Length of time to loaner • Length of time to • At fault or not • First Time
notified • How long to get schedule repair • Quality of loaner get vehicle back • Received Filer
• How long before initial estimate vs. own vehicle • Returned vehicle deductible back
notification • Received initial • Loaner after picking up • Underwater on
estimate immediately • Overall quality of total loss
• $ initial estimate available repair • Out of pocket for
• Rental offered • Frequency of rental
• Satisfaction with contact • Out of pocket for
ability to get rental • Mode of contact loaner
• Ability to complete
claims process
digitally
• Quality of rental vs.
own vehicle
• Rental immediately
available

INSURER SATISFACTION | PROPENSITY TO SWITCH CARRIERS | REPAIR SATISFACTION

MOverall,
O M EhowN satisfied
S W E were you
Dwith
I E Dyour
I Ninsurance
P R O Pprovider
N S I after the
Oprocess
S W I Twas finished? (Scale of 1 to 5)
Figure 4:TInsurer SCustomer
TU Defection EMoments
© CCC Intelligent Solutions Inc. All rights reserved.
TY T Studied CH
9
© CCC Intelligent Solutions Inc. All rights reserved.

Claim Repair Center Repair Center Repair Center Claim Demographic/

FNOL
Experience Selection Experience Process Resolution Psychographic

• Injury • Clear comms • How repair center • Loaner offered • Able to influence • # of days to • Age
about claims was chosen • Quality of loaner parts selection determine fault • Income
process vs. own vehicle • Length of time to • At fault or not • First Time
• Empathy • Frequency of get vehicle back • Received Filer
• Received initial contact • Returned vehicle deductible back
estimate • Mode of contact after picking up • Underwater on
• How long to • Quality of repair TL
receive initial • Clear estimated • Out-of-pocket
estimate timeline for for rental
• Rental offered repair • Out-of-pocket
• Ability to for loaner
complete claims • Likely TL
process digitally • Insurance
• Quality of rental Satisfaction
vs. own vehicle Score

As a result of the claims process related to your vehicle accident, did you switch to a different auto
insurance provider? 1 = Yes, 0 = No
© CCC Intelligent Solutions Inc. All rights reserved. 16
© CCC Intelligent Solutions Inc. All rights reserved.

© CCC Intelligent Solutions Inc. All rights reserved. 10

MOMENTS OF TRUTH

INSURER SATISFACTION | PROPENSITY TO SWITCH CARRIERS | REPAIR SATISFACTION

Figure
MOMEN 5:TRepairer
S W E S TCustomer
U D I E D I NSatisfaction
REPAIR SA Moments
T I S F A C Studied
TION
Claim Repair Center Repair Center Repair Center Claim Demographic/
FNOL
Experience Selection Experience Process Resolution Psychographic

• Injury • Clear comms about • How repair center • Loaner offered • Ability to influence • # days determine • Age
• Drivable claims process was chosen • Satisfaction with parts selection fault • Income
• How insurer • Length of time to • Length of time to ability to get loaner • How long to get • At fault or not
notified get initial estimate schedule repair • Loaner vs. own vehicle back • Received
• How long before • How initial vehicle • Returned vehicle deductible back
notification estimate was • Loaner immediately after picking up • Out of pocket for
• Satisfaction delivered available • Clear estimated rental
initial insurer • Rental offered • How car arrived at timeline provided • Out of pocket for
contact • Satisfaction with RF • Repair completed in loaner
ability to get rental • Frequency of timeframe provided
• Rental quality vs. contact • Charged for scan or
own vehicle • Mode of contact calibration
• Rental immediately • Transparent • # of scans or
available detailed calibrations
explanation of
repair needs
• RF Cleanliness
Satisfaction with
dropoff
• How final estimate
delivered
• $ final estimate

Overall, how satisfied were you with the repair shop’s performance on the overall repair process experience?
(1 to 5, with 5 being “very satisfied”)
INSURER SATISFACTION FINDINGS
23
© CCC Intelligent Solutions Inc. All rights reserved.

The Moments of Truth

The analysis on insurer satisfaction yielded 12 moments of truth –– 10 had a significant and positive
impact on insurer satisfaction, while 2 had a significant and negative impact.

The light blue bars on the charts in Figure 6 indicate a significant and positive impact. The orange
bars indicate the variable had a significant and negative impact. A moment that does NOT appear
on the graph had no meaningful impact, meaning it did not meet the threshold that made it
distinguishable from zero impact on the outcome. The order is also important – the moments are
listed in order of impact, from highest to lowest.

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 INSURER SATISFACTION | PROPENSITY TO SWITCH CARRIERS | REPAIR SATISFACTION

I N S U R OF
MOMENTS E RTRUTH
SATISFACTION

FigureMoments of Truth
6: Moments in Insurer
of Truth Satisfaction
in Insurer (N = 2,400
Satisfaction Respondents)
(N=2,400 Respondents)
Clear communication about claims process

Quality of repairs

Satisfaction with ability to get rental

Satisfaction with ability to get loaner

Empathy

Ability to complete claims process digitally

Received an initial estimate

Length of time to schedule repair

Length of time to get repaired car back

Customer influenced parts selection

Household income

First Time Claim Filer

Direction of Impact
© CCC Intelligent Solutions Inc. All rights reserved. 11
The data normalization process (See: Methodologies section) allowed us to compare the influence of
the different moments in an equitable way, and the results are shown as normalized coefficients in
the table below. The R2 for this model was .37.

Question Coefficient (Raw) Coefficient (Normalized)

Clear communication about claims process 0.128 0.201

Quality of repairs 0.190 0.150

Satisfaction with ability to get rental 0.233 0.113

Satisfaction with ability to get loaner 0.182 0.096

Empathy 0.054 0.095

Ability to complete the claims process digitally 0.043 0.070

Received initial estimate 0.177 0.070

Length of time to schedule repair -0.052 -0.068

Length of time to get repaired car back -0.058 -0.064

Customer influenced part selection 0.114 0.046

Household income 0.029 0.039

First-time claim filer 0.076 0.037

Note that neither the coefficients for variables (moments) that were not statistically significant, nor the intercept term is shown
above.

© CCC Intelligent Solutions Inc. All rights reserved. 12

MOMENTS OF TRUTH

To quantify the impact of each moment, the raw coefficient can be multiplied by the customer’s
score to ascertain the increase or decrease in insurer satisfaction score that would result from that
moment.

For example, the Clear Communication about the Claims Process moment was measured on a scale
of 1 to 10. If the customer gave full credit for this score (10 points), then the insurer satisfaction score
would increase by 1.28 points (on a scale of 1 to 5), showing the large impact of this one moment.

As another example, the “satisfaction with ability to get rental” moment was on a scale of 1 to 5. So,
if the insurer earned full marks for this moment from the customer, the insurance satisfaction score
increased by .233 x 5 or 1.165 points on a scale of 1 to 5.

The study also identified 22 moments that did not have a statistically significant impact on insurer
satisfaction. (Figure 7)

INSURER SATISFACTION | PROPENSITY TO SWITCH CARRIERS | REPAIR SATISFACTION

Figure
M O M E7:N Moments
T S W E S That
T U D IDid
E D –I And
N I NDid
SUR Not
E R- S
Significantly
A T I S F A C T IImpact
ON Insurer Satisfaction

Claim Repair Center Repair Center Repair Center Claim Demographic/

FNOL
Experience Selection Experience Process Resolution Psychographic

• Injury • Clear comms • How repair center • Satisfaction with • Able to influence • # of days to • Age
• Drivable about claims was chosen ability to get parts selection determine fault • Income
• How insurer process • Length of time to loaner • Length of time to • At fault or not • First Time
notified • Empathy schedule repair • Quality of loaner get vehicle back • Received Filer
• How long before • How long to get vs. own vehicle • Returned vehicle deductible back
notification initial estimate • Loaner after picking up • Underwater on
• Received initial immediately • Overall quality of total loss
estimate available repair • Out of pocket for
• $ initial estimate • Frequency of rental
• Rental offered contact • Out of pocket for
• Satisfaction with • Mode of contact loaner
ability to get rental
• Ability to complete
claims process
digitally
• Quality of rental vs.
own vehicle
• Rental immediately
available

Note: The light blue text in Figure 6 indicates a significant and positive impact. The orange text indicates the variable had a significant
and negative impact. The dark blue text indicates that the moment had no meaningful impact on insurer satisfaction (e.g. they were
moments that “didn’t matter.”)
© CCC Intelligent Solutions Inc. All rights reserved.
© CCC Intelligent Solutions Inc. All rights reserved.
12

© CCC Intelligent Solutions Inc. All rights reserved. 13

MOMENTS OF TRUTH

Finding #1
“Received deductible back” is not a moment that matters, except for lower income policyholders.

Initially, before controlling for income, receiving the deductible back was a “moment of truth” that
significantly impacted insurer satisfaction. However, once income was added to the model, the
significance of receiving the deductible faded. (Figure 8)

Figure 8: Impact of Getting Deductible Back on Insurer Satisfaction

Additional analysis found that insurer satisfaction scores were significantly impacted by receiving
the deductible back at lower household income levels. This may be because recovering $500 or
$1,000 is far more important to a household at a lower income level than to those at higher levels.
Because the majority of study respondents had higher levels of household income (64%), this effect
was overshadowed when income was included in the model.

The important point here is that different things matter to different people. Insurers should consider
ways to generate the highest number of optimal outcomes for every customer, and at lower income
levels, receiving their deductible back can be an important determinant in how satisfied a consumer
will be with their carrier.

© CCC Intelligent Solutions Inc. All rights reserved. 14

MOMENTS OF TRUTH

Finding #2

Empathy and digital communication mattered more to customer satisfaction for urban and
suburban drivers.

The study initially used all of the data to ascertain specific moments of truth, but when the model
was re-run with just the respondents who indicated that they lived in “urban” (52%) or “suburban”
areas (36%), the “Empathy” moment went from the fifth most important to the third most
important, and the “used text to communicate with repair facility” moment showed up as a moment
of statistical significance (compared with not showing up at all in the model for the overall sample).
(Figure 9) The R2 for this model was a respectable .36.

Figure 9: Moments of Truth in Insurer Satisfaction for Urban and Suburban

Residents (N = 2,112 Respondents)

INSURER DEFECTION FINDINGS

The study questionnaire asked those who switched carriers why they chose to leave, and the
number one response was an increase in premiums following the accident. However, everyone in
the sample was a first-party claimant, so it stands to reason that everyone in the sample would have
experienced some form of premium increase. Why did only 17% of them defect? This research
sought to determine which moments – aside from premiums – would drive a policyholder to leave
their insurer. (Figure 10)

© CCC Intelligent Solutions Inc. All rights reserved. 15

 INSURER SATISFACTION | PROPENSITY TO SWITCH CARRIERS | REPAIR SATISFACTION
MOMENTS OF TRUTH
WHAT RESPONDENTS SAID WAS THE REASON FOR
SWITCHING CARRIERS
Figure 10:
Question: WhatWhy
is the Switchers
primary reasonSwitched (N=403)
that led you to switch your insurance provider?

Question: What is the primary reason that led you to switch your insurance provider?
Why Switchers Switched (N=403)
Increase in insurance premiums following the accident
Had difficulties in repair process
Delay in claim processing or payout
Insurer would not approve my parts selection
Unsatisfactory rental policy
Disappointed with lack of support after accident
Did not receive empathy from insurer
Poor communication or customer service
Dissatisfied with how claim was handled
Other
Dissatisfied with payout or repair amount
Disagreed with the settlement amount

0.00% 5.00% 10.00% 15.00% 20.00% 25.00% 30.00%

% of Switchers
© CCC Intelligent Solutions Inc. All rights reserved. 15

For the logistic regression to predict the likelihood of switching, a model was trained with a menu of
independent variables on the first 80% of the data set. For the remaining 20% of the data set, the
model “keeps” the variables that help it predict the outcome with the highest success, and “discards”
any variables that are unhelpful in predicting the outcome. Any variables the model chose to “keep,”
therefore, are the “moments of truth,” and any that it chose to “discard” can reasonably be
considered a “moment that doesn’t matter.”

The Moments of Truth in Carrier Defection

The logistic regression model chose only 3 moments that helped it predict switching behavior with
an accuracy of 84.5% and an F1 score of 45%. (Figure 11) These moments are:

1. The policyholder had a loan gap and was able to cover their outstanding loan in a total loss
2. An injury occurred in the accident
3. They were a first-time claim filer

© CCC Intelligent Solutions Inc. All rights reserved. 16

 INSURER SATISFACTION | PROPENSITY TO SWITCH CARRIERS | REPAIR SATISFACTION

I N S UOF
MOMENTS R ETRUTH
R SWITCHING MODEL

Moments
Figure 11: The Threeof Truth inThat
Moments Insurer Switching
Predict (N=2,400
Switching Respondents)
Behavior

Able to cover upside down loan, TL

Accuracy: 84.5% Injury

First Time Claim Filer

Model Specification

• Satisfaction with insurer score1does NOT significantly help predict retention

TAKEAWAYS •𝑃(𝑠𝑤𝑖𝑡𝑐ℎ𝑖𝑛𝑔)
3 more pieces=of1information
+ 𝑒 !(#! $#"are needed
∗&" $## ∗&# $#$ ∗&$ )

18
© CCC Intelligent Solutions Inc. All rights reserved.

Moments (Features) Raw Coefficients (Beta values) Normalized Coefficients

Ability to cover upside down, TL 1.604 0.640

Injury -0.860 0.422

First time claim filer -0.563 0.272

Intercept (𝛽( ) -0.059 -2.918

In total, out of 2,400 sample respondents, there were 280 people who had experienced all 3
moments of truth – namely, they were upside in a total loss that they were able to financially cover,
they had experienced an accident in which there was an injury, and they were first time claim filers
– and of these 280 people, 55% switched carriers. Compared to the base switching rate of the entire
sample – 17% - this is a 3.2x likelihood to defect.

The study also found 26 additional moments that did not significantly impact insurer defection.
(Figure 12)

© CCC Intelligent Solutions Inc. All rights reserved. 17

MOMENTS OF TRUTH

INSURER SATISFACTION | PROPENSITY TO SWITCH CARRIERS | REPAIR SATISFACTION

MFigure
O M E N12:
T SThe
W EMoments
S T U D I EThat
D I N Did
P R –O and
P E NDid
S I TNot
Y T-OSignificantly
S W I T C H Impact Insurer
Defection
Claim Repair Center Repair Center Repair Center Claim Demographic/
FNOL
Experience Selection Experience Process Resolution Psychographic

• Injury • Clear comms • How repair center • Loaner offered • Able to influence • # of days to • Age
about claims was chosen • Quality of loaner parts selection determine fault • Income
process vs. own vehicle • Length of time to • At fault or not • First Time
• Empathy • Frequency of get vehicle back • Received Filer
• Received initial contact • Returned vehicle deductible back
estimate • Mode of contact after picking up • Underwater on
• How long to • Quality of repair TL
receive initial • Clear estimated • Out-of-pocket
estimate timeline for for rental
• Rental offered repair • Out-of-pocket
• Ability to for loaner
complete claims • Likely TL
process digitally • Insurance
• Quality of rental Satisfaction
vs. own vehicle Score

Note: The light blue text in Figure 11 indicates a significant and positive impact. The dark blue text indicates that the moment
had no meaningful impact on policyholder retention (e.g. moments that “don’t matter.”)
As a result of the claims process related to your vehicle accident, did you switch to a different auto
insurance provider? 1 = Yes, 0 = No
© CCC Intelligent Solutions Inc. All rights reserved. 19
© CCC Intelligent Solutions Inc. All rights reserved.

Finding #1
Insurer satisfaction scores may not be significant indicators of defection.

Insurer satisfaction score was a moment that was offered to the model to consider for inclusion,
and yet it was not chosen (it did not meaningfully help the model predict the switching outcome).
This signifies that insurer satisfaction scores may not be helpful in predicting whether a customer
remains with an insurer.

This is likely because satisfaction scores only reflect how the customer says they feel, while the
defection reflects what they actually feel by taking action to switch carriers. This is why it’s
important to study both satisfaction and propensity to switch - because what customers say isn’t
always what they do.

For claims departments, this means they not only need to win all the moments of truth that impact
insurer satisfaction, but they also need to gain insight into the 3 moments identified above in order
to flag whether a customer is at risk of defection.

© CCC Intelligent Solutions Inc. All rights reserved. 18

MOMENTS OF TRUTH

Finding #2
Policyholders with total loss vehicles that are sent to repair facilities are far more likely to switch
insurers.

A univariate analysis was conducted to highlight the impact of each of these moments singularly on
the outcome. Policyholders with total loss vehicles that were sent to repair facilities were 5x more
likely to switch than their repairable counterparts, while the presence of an injury made them 1.7x
more likely to switch. Being a first-time claim filer also increased their likelihood to switch, albeit
moderately.

This provides insurance claims professionals with a simple rubric for predicting switching that they
can provide to their counterparts on the retention or marketing teams. It may, for example, also
highlight additional underwriting opportunities to sell gap insurance, given the importance of the
impact of being upside down in a vehicle loan following a total loss.

Finding #3
Being a “first-time claim filer” seems to create contradictory behavior.

Being a first-time claim filer increases insurer satisfaction scores, but it ALSO increases the
customer’s propensity to switch carriers.

REPAIRER SATISFACTION FINDINGS

As with insurer satisfaction, satisfaction with repairers was modeled using a multiple linear
regression. The model identified 9 moments that impact repair satisfaction –– with 8 having a
positive impact, and 1 having a negative impact.

The light blue bars on the charts in Figure 13 indicate a significant and positive impact. The orange
bars indicate the variable had a significant and negative impact. A moment that does NOT appear
on the graph means it had no meaningful impact, meaning it was not statistically different than zero
impact on the outcome. The order is also important – variables are listed in order of impact, from
highest to lowest. The R2 for this model was .32.

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MOMENTS OF TRUTH

Figure 13: Moments of Truth in Repair Satisfaction

Question Coefficient (Raw) Coefficient (Normalized)

Transparent and detailed explanation of repair needs 0.104 0.154

Satisfaction with drop-off 0.175 0.143

Clear communication about claims process 0.050 0.081

Length of time to get repaired car back -0.080 -0.081

Frequency of contact was just right 0.272 0.075

RF cleanliness 0.047 0.071

Repair completed in timeline provided 0.195 0.058

Satisfaction with initial insurer contact 0.051 0.048

Clear estimated timeline provided 0.123 0.039

*Note that neither the coefficients for variables (moments) that were not statistically significant, nor the intercept term is shown above.

As with the multiple linear regression model for insurer satisfaction, the impact of each moment
on the repairer satisfaction score can also be quantified. For example, if a consumer gave full
marks for receiving a “transparent and detailed explanation of repair needs,” which was measured
on a scale of 1 to 10, their corresponding repair satisfaction score would increase by 10 x .104, or
1.04 points on a 5-point scale.

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MOMENTS OF TRUTH

The second moment, “satisfaction with drop-off,” was measured on a 5-point scale. So, if a
consumer gave the full 5 points for that experience, the repair satisfaction score was increased by
.875 of a point on a 5-point scale, showing the slightly lower but still large impact of this moment.

The study also identified 31 moments that had no significant impact on repairer satisfaction.
(Figure 14)

Figure 14: The Moments That Did – And Did Not - Significantly Impact
Repairer Satisfaction

Note: The light blue text in Figure 13 indicates a significant and positive impact. The orange text indicates the variable had a significant
and negative impact. The dark blue text indicates that the moment had no meaningful impact on insurer satisfaction (e.g. were
moments that “didn’t matter.”)

Finding #1
Customers’ number one moment for repairer satisfaction is getting a transparent and detailed
explanation of repair needs.

The top moment of truth impacting repairer satisfaction was whether the customer felt they had
been given a “transparent and detailed explanation of the vehicle’s repair needs” - even though the
insurer is the one paying for the repair. This goes against the industry’s age-old wisdom that speed
is what matters: “The consumer is not paying for the repair, so they don’t need or care to know how
their vehicle needs to be repaired.”

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MOMENTS OF TRUTH

It turns out that the length of time required to repair the vehicle is also a moment of truth but is
outweighed by the need to know the details of how the vehicle will be repaired. This suggests that
customers want to ensure the safety and reliability of their vehicle when they return to the road.

Finding #2
There are moments impacting repairer satisfaction that are not entirely within the repair facility’s
control.

Respondents are significantly more satisfied with repair facilities in moments that are actually the
responsibility of the insurer – namely, when they receive clear communication about how the claims
process will actually work and when they are satisfied with their first contact with the insurer. This
provides further reinforcement to the assertion that insurers and repairers are inextricably linked in
the consumer’s mind (see “Finding #3).

Finding #3
In general, insurers and repairers are very intertwined in the minds of consumers.

The answers to other survey questions validated that, in a consumer’s mind, insurers and repairs are
intertwined. For example, insurers greatly influence where consumers go to get their vehicles
repaired, as exhibited in Figure 15 below. Nearly one-third of consumers – the largest cohort – said
that the determining factor that informed where they took their vehicle for repair was a
recommendation from their insurer.

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MOMENTS OF TRUTH

Figure 15: What Was the Deciding Factor That Informed How You Chose
the Repair Shop or Dealer Service Center You Used to Fix Your Vehicle?
(N= 2,400)

The study also found that the customer’s interaction with the repair facility in turn influenced their
perception of the insurer.

Survey respondents were asked: “Did your interaction with the repair facility change how you
perceived your insurer?” and 42.5% said “Yes.” Those 42.5% were then asked: “How did your
interaction with the repairer change your perception of the insurer?” 83% said positively, 12% said
negatively, and the remainder said, “I don’t know.” (Figure 16)

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MOMENTS OF TRUTH

Figure 16: Repair Facility’s Impact on Perception of Insurer (N = 2,400)

Finding #4
Consumers want their repair facilities to communicate with them every 2-3 days.

Given that “frequency of contact was just right” was identified as a moment that mattered to
survey respondents, additional analysis was conducted to shed light on just how often consumers
wanted communications from their repair facilities.

Respondents were asked, “How often did you expect to be communicated with during the repair
process?” The study found that 88% of customers expected anywhere from daily to once-per-week
updates during the repair process, and nearly half expected communication from the repair
facilities every 2 to 3 days. (Figure 17)

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PECTATIONS AROUND FREQUENCY OF CONTACT
MOMENTS OF TRUTH

Figure How often

17: How didDoyou
Often Youexpect
Expectto
tobe
bein
in contact withthe
Contact with theRepair
repairCenter
center
During the Repair during
Process the repair process? (N=2,400)
(N=2,400)

Every 2-3 days

Once a week

Daily

Only as necessary

Every 2 weeks

Once a month

0% 10% 20% 30% 40% 50%

% of respondents

METHODOLOGIES
ligent Solutions Inc. All rights reserved.
For the dependent variables (the outcomes), respondents were asked to directly quantify:

• Insurer satisfaction: “Overall, how satisfied were you with your insurance provider after the
(claims) process was finished?” (scaled from 1 to 5)
• Insurer defection: “As a result of the claims process related to your vehicle accident, did you
switch to a different auto insurance provider?” (1 = Yes, 0 = No)
• Repairer satisfaction: “Overall, how satisfied were you with the repair shop’s performance
on the overall repair process experience?” (scaled from 1 to 5)

Multiple Linear Regression to Analyze the Moments of Truth in Insurer and

Repairer Customer Satisfaction
Multiple linear regression is a statistical method which enables the identification of patterns and
correlations within data sets, providing statistical measures of significance and predictive
capabilities. By controlling for other influencing factors, linear regression helps isolate the specific
impact of these moments of truth on satisfaction levels, offering quantifiable insights that can
inform targeted strategies for improving overall satisfaction.

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MOMENTS OF TRUTH

In the multiple linear regression models, the dependent variable was the insurer or repairer
satisfaction score, and the independent variables were factors that reflected each moment in the
claims and repair journey, from FNOL all the way to claim resolution. The study also controlled for
such demographic and psychographic factors as age, income, and whether they were a first-time
claim filer.

The factors which showed up as statistically significant were called the “moments of truth” that
impacted the ultimate outcome, and those that did not were defined as “moments that didn’t
matter.” The overall R2 of the statistical model is a measure of its explanatory power. In working with
real-world data involving human behavior, an R2 of at least .25 - .30 is the threshold to be considered
robust.

Logistic Regression to Analyze the Moments of Truth in Customer Defection

from Insurers
Whether an insured switched carriers at the end of a claim and repair journey was a binary decision.
That is, the dependent variable is either a 1 or a 0 (1 if they switched, 0 if they did not). In such cases
where the dependent variable is binary, a linear regression is imperfect because it assumes a
straight-line relationship between variables and the outcome.

For this reason, a logistic regression model, where the outcome is the probability of switching, was
used to determine the direction and relative magnitude of each moment of truth. One notable aspect
here is that in linear regression, the coefficients give a direct quantification of the impact. In logistic
regression, the coefficients represent the increase in the odds of switching (strictly, a logarithm of
the odds). A logistic regression model’s quality is evaluated by measuring precision (how accurate
are the model’s predictions of switchers) and recall rate (what percentage of switchers did the model
predict). These two measures are combined as an F1 score. In this model, an F1 score of at least 30%
was desired.

Data Normalization
Each variable – or “moment” - was analyzed for completeness and quality of responses. In cases
where a variable had missing data – for example, some respondents did not answer the question –
the missing values were inspected for the extent (e.g. was the proportion of missing responses
within acceptable limits?) and bias (e.g. was there a pattern in why they did not answer or was it truly
randomly missing). Following this, missing values were imputed with the median or mean response,

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MOMENTS OF TRUTH

when deemed appropriate. Each variable was then normalized using the standard deviation before
fitting the model.

STRATEGIC IMPLICATIONS
Study findings suggest several important insights, beginning with the industry’s shared
responsibility to ensure customers receive quality repair service and helpful information throughout
the claims process, no matter who may be “officially” responsible.

While insurers and repairers may operate as unique profit centers, the data suggests their
customers may not view them as separate. This is indicative of a value chain ecosystem, which Ernst
& Young defines as “sitting between original suppliers and end consumers of goods and services and
[is] characterized by many participants across many different role types.”14

Another key finding with significant implications for carriers is that customer satisfaction scores do
not help determine whether a policyholder will switch carriers. The 3 moments that were found to
best predict whether a customer will switch providers are the ability of the policyholder to cover
their outstanding loan in the case of a total loss, the presence of injuries, and being a first-time claim
filer. The momentum favors the carrier in most cases, e.g., the default is for customers to stay,
despite premiums increasing (in the sample, 83% of the first-party claimant respondents did not
switch carriers). However, in the presence of these 3 moments, their likelihood to switch is
heightened, which gives carriers a useful way to predict which of their claimants are most vulnerable
to leaving.

Collaboration across the claims and repair journey has other mutual business benefits. Survey
respondents indicated that insurers' recommendations were the determining factor in selecting
their repair facility. And when repairer satisfaction is strong, the study found that carriers benefit
as well, with the percentage of respondents in the “Very Satisfied” segment increasing by ~17%
points. (Figure 18)

14
Ernst & Young: https://www.ey.com/en_gl/alliances/seven-business-models-for-creating-ecosystem-
value

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MOMENTS OF TRUTH

Figure 18: Satisfaction with Insurer – Distribution %

RECOMMENDATIONS
For Insurers
As insurers have shifted focus from rate adjustments to growth strategies, retention has become a
bigger focus. Claims teams have historically been perceived as cost centers but in reality, they are
“insight centers” for the insurance organization as a whole, because no one else touches customers
as much as claims teams do. After all, once a policy is purchased, there is no further need for
interaction with the insurer until there is a problem.

The study illustrates that capturing insights from the claims process can help carriers know when a
policyholder might switch and identify those high-vulnerability customers for the carrier’s retention
team - in this case, policyholders who are upside down in their loans as the result of a total loss, had
an injury occur in their accident, or were first-time claim filers.

Knowing this information can help carriers formulate a plan to retain those customers, whether by
providing alternative vehicle financing options, or configuring coverages for a successful claims
experience. This can include offering gap insurance, rental coverage, and limiting out-of-pocket
expenses. Additionally, when there is an injury present, carriers can provide tailored, empathetic
experiences to address the specific needs and concerns of the affected policyholder. This might
include specialized medical assistance, expedited claims processing, and personalized
communication to ensure the customer feels supported and understood during a challenging time.

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MOMENTS OF TRUTH

For Repairers
According to the findings, repairers need to get 9 moments right, some of which are in the hands of
their insurer partners. To achieve a better satisfaction outcome in the top moments of truth,
repairers should provide transparent and detailed explanations of vehicle repair needs. This could
indicate how invested customers are in ensuring the safety and reliability of their vehicle when they
return to the road.

Repairers may also do well to focus on communication with their customers, providing a clear
timeline for when the repair will be completed, contacting their customers with just the right
frequency (a combination of modalities every 2-3 days), and meeting that timeline.

Finally, the study highlights the continued importance of a satisfying drop-off experience and the
cleanliness and organization of the repair facility. Combined, these recommendations highlight the
importance of repair process management for shops to ensure consistent and high-quality service.

For Both Insurers and Repairers

Because so many moments were technically in the hands of their partners, both insurers and
repairers should consider themselves to be part of a value chain ecosystem that provides an end-
result for their joint customer, namely, a return to normalcy. Therefore, the industry needs to take a
platform approach and use technology to orchestrate a seamless, unified customer experience
across the entire claims and repair journey.

LIMITATIONS AND MITIGATIONS

Certain limitations should be considered when interpreting the results of this study.

Statistical Significance Using P-Values

While p-values are a common measure of statistical significance, they have well-documented
limitations, particularly in the context of complex data sets and models. P-values can sometimes
lead to misleading conclusions due to issues such as p-hacking or over-reliance on arbitrary
significance thresholds (e.g., p < 0.05). To mitigate these issues, CCC supplemented p-value analysis
with cross-validation techniques.

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MOMENTS OF TRUTH

Specifically, CCC used incremental R2 contributions to assess the explanatory power of each
moment of truth and evaluated the ability of the models to generalize beyond the training data set.
This approach provides a more robust measure of the importance of each moment by examining
how well the models perform on unseen data, thus reducing the risk of overfitting. Nonetheless, it
is important to recognize these alternative measures also have limitations and should be interpreted
in conjunction with p-values rather than as definitive replacements.

Interpreting Coefficients
The interpretation of regression coefficients differs from a univariate analysis, where each moment
is analyzed in isolation. In contrast, the coefficients derived from the regression models offer
insights into the relationship between individual moments of truth and the outcomes of the auto
claims and repair process, and help quantify and distill what moments matter most; however, it is
critical to understand that these coefficients represent the effect of changing one moment while
holding all other moments constant, which can be unrealistic in real-world settings where multiple
moments often occur simultaneously and interact in complex ways.

As a result, the coefficients, which can provide valuable information about the importance of various
moments, may not fully capture the interconnectedness and the joint influence of the moments that
often occur together or depend on each other. To understand these, it may be necessary to augment
the research with further data sources or design surveys that explore these interactions in greater
detail.

FUTURE RESEARCH AND DEVELOPMENT

Future research includes delving more deeply into other moments of truth or other business
outcomes that matter, for example, in employee experience.

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MOMENTS OF TRUTH

CONCLUSION
This study highlights the critical role moments of truth play in shaping customer satisfaction and
influencing retention in the claims and repair journey. By strategically addressing these key
moments, carriers and repairers can improve customer satisfaction and retention and strengthen
the overall customer experience after an accident.

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