23-Apr-2020
Most
health plans are not satisfied with the proportion of their former commercial
members who convert into Medicare members. This under-performance
is called the Age-in Conversion problem. And it challenges Medicare
plans trying to enroll their own individual and employer-sponsored health
plan customers.
A one-two punch.
1.
Age-in Conversion studies: Working with clients, Deft
Research has developed a consumer survey to create measures of the key
opportunities for improving age-in conversion. Our clients say survey
data will help them prioritize and focus the actions they will take.
2.
List Scoring Algorithms: Deft Research is also uniquely
positioned to address the Age-in Conversion problem with high quality
list scoring algorithms.
Each
part of this approach delivers its own value.
Age-in
Conversion studies almost always survey a health plan’s own members – or
persons of a certain age who were previously in IFM or employer plans and are
no longer. The surveys identify the strengths of competition, relative
brand values, and the member experience factors that influence age-in
choices. Without this decision support, health plan personnel have had
trouble aligning on a more positive future in which Age-in Conversion rates
rise.
The
list scoring algorithms enable health plans to apply market intelligence
to an entire list of consumers. These scores help clients make more
informed marketing decisions at the prospect level. To develop the
algorithms, Deft used both primary market research and additional data.
This leads to market insights specifically designed for health insurance marketing
decisions.
The new
2019 algorithms produce scores for:
·
Late to
Medicare Score – likely to delay enrollment in Medicare past age 65.
·
Prefer Medicare Advantage
Score – likely to prefer Medicare Advantage plans over other options.
·
Zero Dollar Premium
Preference Score -- likely to prefer a
Zero Dollar Premium MA plan over other MA options.
·
Prefer Medicare
Supplement Score -- likely to prefer
Medicare Supplement plans over other options.
·
High Dollar Med Supp
Score – likely to prefer a high premium Medicare Supplement (greater
than $200 monthly premium) over other MedSupp options.
·
Respond to Direct Mail
Score – likely to respond to Medicare related direct mail
solicitations.
·
Use an Insurance Agent
Score – likely to prefer using an insurance agent or broker for
advice.
When
list scoring is used, insurers report higher responses to direct mail, and
lower costs per sale. To accomplish a variety of goals, insurers may use
algorithmic scores alone or in combination with one another.
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