Term Insurance vs Endowment Policy Preference Survey
Map how individual insurance buyers evaluate coverage needs, compare premium structures, and choose between protection and savings-linked plans, so you can sharpen acquisition targeting, refine product positioning, and improve conversion across policy segments.
CONTEXT & RELEVANCE
Why run this survey now
Most life insurers don't lose policy conversions purely on premium pricing. They lose them due to misread protection intent, savings-versus-coverage confusion, advisor bias, income-stage misalignment, and trust gaps at claim stage, none of which fully show up in policy issuance data or distributor sales reports.
If you are...
- Term product head, life insurer
- Endowment portfolio manager
- Bancassurance or agency distribution lead
- Actuarial pricing or product strategy lead
- Chief marketing officer, retail life
You're likely facing...
- Term vs endowment conversion drop-offs
- Advisor-driven product push vs buyer intent
- Endowment = savings/low-risk perception
- Term = no-return objection at point-of-sale
- Income-stage misfit: wrong product, right customer
This will help answer...
- Primary preference drivers by income segment
- Conversion drop-off stage by product type
- Term vs endowment segment split
- Premium sensitivity and tenure tolerance
- Switching triggers at renewal stage
RESEARCH THEMES
What This Survey Investigates
Eight interconnected research themes that map the complete policyholder journey from initial need recognition to long-term policy retention.
Discovery & Triggers
- Life-stage events prompting purchase
- First information source consulted
Preference Drivers
- Pure protection vs. savings orientation
- Premium affordability vs. maturity benefit
Product & Coverage
- Sum assured adequacy perception
- Rider selection and add-on uptake
Purchase Friction
- Drop-off points in application journey
- Medical underwriting barriers
Pricing & WTP
- Monthly premium comfort range
- Price sensitivity across income segments
Servicing & Retention
- Premium payment mode preferences
- Policy servicing channel satisfaction
Trust & Credibility
- Claim settlement ratio awareness
- Brand trust vs. agent trust hierarchy
Competitive Positioning
- Insurer shortlist and switch intent
- Aggregator vs. direct channel split
SAMPLING STRATEGY
Tell us about your ideal sample
Help us understand your target respondent profile. Select what applies, we'll design the optimal sample plan based on your inputs.
METHODOLOGY
Survey approach
For the Term Insurance vs Endowment Policy Preference Survey, we recommend a quant-first design with flexible data-collection modes to balance reach, depth, and verification.
EXECUTION PROCESS
How we execute
A proven 9-step process from scoping to delivery, designed to ensure quality, speed, and actionable insights.
Define the decision frame
Confirm objectives, target cohorts, geographies, and reporting cuts
Define the decision frame
Design the instrument
Build workstream modules mapped to outputs (drivers, friction, pricing, retention, trust)
Design the instrument
Lock the questionnaire
Review wording, sequencing, LOI, and competitive context; approve final version
Lock the questionnaire
Pilot and calibrate
Test comprehension and ease quality; refine quotas and remove friction where needed
Pilot and calibrate
Run fieldwork
Execute collection with active quota management and feasibility controls
Run fieldwork
Assure quality
Dedupe, attention checks, speed/consistency rules, removals with audit trail
Assure quality
Prepare the dataset
Clean data and deliver codebook/variable definitions
Prepare the dataset
Analyse and synthesise
Driver ranking, leakage diagnostics, pricing bands, segment insights
Analyse and synthesise
Deliver and align
Executive deck (optional dashboard) and leadership readout with recommendations
Deliver and align
COMMERCIAL TERMS
Request a Commercial Proposal
Pricing depends on cohort, geography, sample size, approach, LOI, and deliverables. Configure below for an indicative estimate.
Select Sample Size
Geography
Select Mode of Survey
Length of the Interview
$0.00
+ applicable taxes
Cost Breakdown
Note: Estimate is indicative only. Final pricing is subject to scope finalization after discovery call.
REFERENCE CASELETS
Reference
Real-world examples of survey work in the life insurance preference space.
Life cover adequacy perception & product fit (India)
OBJECTIVE
WHAT WE DID
DELIVERED
Life cover adequacy perception & product fit (India)
Savings-linked policy messaging & trust signals (South India)
Life cover adequacy perception & product fit (India)
OBJECTIVE
A mid-size private life insurer needed to isolate how salaried urban earners and self-employed professionals evaluate sum assured adequacy , and which financial triggers push each segment toward a coverage review or policy upgrade decision.
WHAT WE DID
Ran a structured quant survey across 8 cities with 600 respondents, capturing income-to-cover ratios, trigger events, advisor influence, digital versus branch channel preference, and willingness to pay across three premium bands for each segment.
DELIVERED
A segment-level coverage preference map , a ranked list of purchase trigger events by income band, a pricing corridor for each segment, and a set of channel levers to convert fence-sitters at the point of renewal.
FREQUENTLY ASKED QUESTIONS
Common Questions
Answers to frequently asked questions about this survey mandate.
What decisions will this survey enable?
Who is the buyer vs who are the respondents?
Can we see differences between first-time buyers, existing term policyholders and existing endowment policyholders?
How will you measure policy preference beyond simple ratings?
Will the survey map the full policy purchase journey and drop-offs?
Can this survey inform product and pricing strategy?
How will findings improve our distribution and advisor enablement strategy?
Still have questions?
Schedule a discovery call to discuss your specific needs and get a custom quote.