Because of space constraints in the typical 30-or 60-second DTC prescription-drug commercial, superimposed text descriptors or “supers,” are necessary for providing additional information. Existing research on the importance of supers’ formatting is either technologically out of date (e.g. not applicable to flat-screen TVs and other devices) or not focused on Rx drug advertising. FDA guidance on supers is vague. It states that they should be “reasonably visible to a person under typical viewing condition” (nothing on text size), and “in a font color that reasonably contrasts with the background visuals.” The latter is based on thinking that “low contrast may minimize the prominence of disclosure and lead to a misleading risk presentation”—which the new study, scheduled for publication in the June issue of the JAR, counters.
How much can text size and contrast affect awareness and attitudes? More than we’ve known.
The research, a collaboration of RTI International and the FDA, tested the effects of device type, level of contrast and supers size in DTC commercials, on several outcome measures. “There is reason to expect that variations in text size and contrast will cue supers as being more or less important in an advertisement,” the authors write. The outcome measures were organized into three broad categories: awareness and encoding of the supers, fair-balance-related perceptions and attitudes. Three size levels of supers and two levels of background contrast were tested on more than 1,200 participants. They watched different versions of a TV ad for a fictitious asthma drug on either a flat-screen TV or a tablet.
Among the findings: Larger supers were more noticeable and memorable than smaller ones, and small supers can minimize the perception of risk, relative to presentations of drug effectiveness. Also, high-contrast supers were less noticeable than low-contrast ones, bucking earlier research and tablet users had more favorable views of the ad.
The study’s limitations left an open door to further research. Replication studies should involve drugs for treating illnesses other than asthma, expand the aspects of supers and include time on-screen and dual-modality issues. Future research should also test the effects of supers on other devices, screen sizes and screen resolutions.
Find the study here.
Versions of voice-activated devices, also known as voice AI, include Amazon’s Alexa and Alibaba’s Tmall Genie. Such devices can perform a variety of tasks, including online shopping. The advantage is that they allow for smoother searches which can equate to increased purchases. Many questions, however, remain for consumer researchers. For instance, how does the use of voice AI affect the consumer purchase journey?
One issue is whether or not search options presented by voice could lead to consumers deferring searches and purchases, given the nature of how information is presented by voice AI. On the plus side, online shopping, rather than in-store browsing, could lead to a broader range of products, which might facilitate impulse buying.
The results (of this study) show that consumers on average spend 23% more as a result of adopting the voice AI, corresponding to approximately US $630 million increase in sales revenue every year.
In this study, Chenshuo Sun, Zijun (June) Shi, Xiao Liu, Anindya Ghose, Xueying Li and Feiyu Xiong analyzed consumer-level browsing and purchase records from an online retailer. The purpose of the study was to determine the impact on shopping behavior through a voice AI device. Their findings are eye-opening. Voice AI adopters search more and spend an average of 23% more than a set of matched, non-adopters. While the effect on search is greatest for younger female consumers, the effect on spending is greatest for younger male ones.
Researchers discovered that while increase in search declines soon after adoption, increase in purchase remains statistically significant after eight weeks. Additional analyses demonstrate that these effects result from reducing the cost of search, leading to greater purchases of products that do not require active search or comparison, such as product categories with low substitutability or high purchase frequency.
Read the full MSI white paper here.