A new study in the Journal of Marketing shows that the design of websites used for buying health insurance combined with high-quality big data can produce big savings for consumers. When health insurance products are ordered such that the best options for the consumer appear first in the presented list, this strongly improves consumers' decisions. If the list is also partitioned to show a small number of options first (with an easy option to click through to see all options), this further improves consumers' decisions. However, importantly, if the best options are not at the top of the list, partitioning can harm consumer decision quality.

1. From: Dellaert, Johnson, Duncan, and Baker (2022)
Choice Architecture for
Healthier Insurance Decisions
Ordering and Partitioning Together Can
Improve Consumer Choice

2. From: Dellaert, Johnson, Duncan, and Baker (2022)
Example – Health Plan Ordering
Ordered by deductible Ordered by predicted yearly cost

3. From: Dellaert, Johnson, Duncan, and Baker (2022)
How Ordering and Partitioning Improve Consumer Choice
Consumers tend to pay more attention to alternatives that are
presented in the initial positions of an ordered list.
Paradoxically, high-quality ordering and low cost of searching
may cause consumers to search too much.
• Consumers overestimate the benefits of further search and are more likely to erroneously
select a product further down the list.
Partitioning a set introduces a small additional effort by
consumers to inspect further alternatives after an initial set.
This single small additional cost can prevent further search and
focus attention on best alternatives.

4. From: Dellaert, Johnson, Duncan, and Baker (2022)
Incentive aligned experiments
We conducted multiple framed-field experiments with consumers in the U.S..
Consumers chose insurance plans on behalf of someone else in a simulated
U.S. health insurance market. The same alternatives were shown to all
participants.
Consumers were given monetary rewards for better quality choices and also
a fixed payment for participation.
We measured the amount overpaid compared to best fitting health
insurance plan.
Experimental design basis: ordering quality (high vs. random) by
partitioning (yes vs. no).

5. From: Dellaert, Johnson, Duncan, and Baker (2022)
Study 1: High quality ordering with
partitioning improves consumer choice
Consumers overpay less
when they view a well-
ordered list and when that
list is partitioned.
Our results show that this is
because they pay more
attention to high quality
options.

6. From: Dellaert, Johnson, Duncan, and Baker (2022)
Study 2: Partitioning with a low-quality
ordering harms consumer choice
When consumers view a list
that is ordered poorly,
partitioning actually causes
them to make worse
choices (in this case,
overpay for insurance).
For random ordering, the
impact depends on the
options that happen to be in
the partitioned set.

7. From: Dellaert, Johnson, Duncan, and Baker (2022)
Conclusion
Ordering based on a high-quality user model combined with
partitioning improves individuals’ decisions. Together they
increase consumers’ attention to the best alternatives.
Partitioning combined with ordering can harm decision quality,
when predictive user model quality is (very) poor.