About Life Coverage Analytics
This new syndicated research program provides a clear, consistent way to assess whether life insurance coverage is truly adequate, how large unmet opportunities really are, and where growth is realistically attainable.
Life Coverage Analytics is an annual, repeatable research program that will enable year‑over‑year assessment of coverage adequacy and industry progress.
Purpose‑Built for the Commercially Addressable Market
This research will survey U.S. adults ages 25–75 with household income of $25,000 or more, the population where life insurance decisions are most relevant, affordable, and actionable. There is also opportunity to explore other traditionally underserved consumer segments through oversamples. This intentional design ensures that estimates of coverage adequacy and gaps translate directly into realistic growth opportunities for sponsors.
Key Questions to Answer
- Who is uninsured or underinsured and by how much?
- Where do consumer perceptions align or conflict with modeled coverage needs?
- How does coverage adequacy vary across life stages and segments?
- Which segments represent the greatest realistic growth opportunity?
Perceived Need vs. Actual Need Measured Together
In a single integrated research program, this study goes beyond attitudes to directly compare:
- Consumers’ own perceptions of whether they need life insurance and how much coverage they have or want
- A rigorous, transparent coverage adequacy model estimating whether they objectively need coverage and by how much
This side-by-side view reveals where perception and reality diverge, helping sponsors identify where education, advice, distribution, product design, or messaging can have the greatest impact.
A Coverage Gap Model Sponsors Can Use and Adapt
Sponsors receive access to the coverage adequacy model itself, not just topline findings. The model enables sponsors to:
- Drill into opportunities by segment, life stage, or demographic group
- Quantify unmet need in terms of people, percentages, and total face amount opportunity
- Modify model assumptions to reflect their own strategic priorities, products, or planning scenarios
For more information, fill out the form or contact Eric Sondergeld at ericsondergeld@greenwaldresearch.com.
Interested in Life Coverage Analytics?
Complete the form to learn more about becoming a sponsor for this research program.
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