by Carrie Haubensak | Mar 24, 2022 | Insurance Industry
Creating the most effective marketing campaign
is a challenge. It is made more
difficult when marketing teams must make decisions without input from
consumers. Part of the creative mystique is having the insight into human
nature and the good taste to know what will work. But in many situations, the
genius of the marketing team is not tested by real measurement and so we never
know what works best and what might have worked better. Since the rollout of a
marketing campaign requires the commitment of millions of dollars by the
marketing organization, testing marketing concepts ahead of time seems like a
good idea for validating perceptions and assuring a satisfactory return on this
investment.
Often marketing campaigns are presented as
whole cloth – imagery, headlines, supporting ad copy, and layout are presented
at once. Two or three options are usually provided and the decision must be
made from there based on what the decision maker likes best.
The traditional idea of treating a promotional
piece as whole cloth leads us to think of testing two or more versions of a
promotion in an attempt to determine which version is most likely to generate
the desired consumer response – this is known as A/B testing. While often
standard procedure, A/B testing sometimes fails because it doesn’t yield
meaningfully different measures of version performance. The failure of A/B
testing to help distinguish a winning version leads teams back to reliance on
the judgment of a small group of decision makers.
Deft Research has developed a testing approach
based on Conjoint analysis that measures the relative impact of each
component of a promotion. Conjoint analysis has been used extensively in
package design research. Here, Deft has adapted this methodology to
testing health insurance advertising.
This approach enables us to measure each
component’s contribution to the overall impact so that the most effective
components can be brought together by the creative team. It shows the most
effective combinations of components and how that effectiveness varies between
different market segments.
To accomplish one of these studies, a survey
is programmed that allows different versions of each promotional component to
be displayed in varying combinations to consumers. Consumers then respond to
side-by-side combinations and are asked to indicate to which ad they are most
likely to respond. Research objectives can focus on building brand awareness
and impression, or generating interest (want to know more), or motivation to
act (click on a link, or call the 800 number, etc.)
The programmed survey pulls layouts, images,
headlines, ad copy, and calls to action from several proposed promotions into
computer generated “versions”.
A study like this can test hundreds of versions and generate tens
of thousands of consumer responses. The outcome of such research is a
measurement of the appeal or effectiveness of each version of each component.
With this information, researchers and marketing teams can assemble the ideal
combinations.
We may recommend research designs that use
traditional survey questions, Max-Diff exercises, or conjoint analysis to
accomplish the goals of the client.
Conjoint analysis is a flexible method that
allows the interests of the client to dictate what is measured. In this article
we have provided several ideas about how imagery, headline, ad copy, and
calls-to-action can be measured for their impact on consumers. The consumer
impact can be measured along one or more dimensions – for example, relevance,
likelihood to consider, likelihood to perform a call-to-action and others.
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