by Richard Hamer, Founder and Chief Strategy Officer 08-May-2019
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:
·
Group
Retiree Score– likely to be covered
by an employer group retiree program (and therefore a bad prospect for
individual Medicare insurance).
·
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.
For more information, contact Catherine
Mandler at 612-436-8313, cmandler@deftresearch.com.
https://blog.deftresearch.com/resources/aic-list-scoring?utm_campaign=2019%20AIC&utm_medium=email&_hsenc=p2ANqtz-_X70KBjTfyHHKw9zqUksOD2p03-WJHGD6qqzEdIMEtgY5MYhf1yOgGNnnMWPRJPWOu0wvWjz1vSLgBMQ2dqp14xTMbWnET8ml2HHVORpYI3oopu3c&_hsmi=73196794&utm_content=73196794&utm_source=hs_email&hsCtaTracking=236ec6b7-240b-4818-aba5-3e1776be2b10%7Ca1f8509e-81b6-4e33-b129-7192ef51e429
No comments:
Post a Comment