The effect of previous causal knowledge on the persuasive strength of confirming covariation data

Consumers are often exposed to causal claims (e.g., a new pill that claims to treat acne) that are occasionally accompanied by data indicating that the product (target) performed better than another product (referent). In this study, we examined the effect of such data on persuasion as a function of target–referent similarity in causal features. Consistent with current theorizing suggesting that structural and specific preexisting causal knowledge affects data interpretation, we propose that data that are consistent with expectations will be more persuasive than data that are inconsistent with expectations. Specifically, we contend that the structural schema “control of variables” we use leads us to expect that two categories (products) that are similar in features will perform the same and two categories that differ in features will differ in performance. In addition, our specific knowledge on causal powers leads us to expect the target to perform better than the referent only if it has more causal features. Thus, when confronted with data indicating a target performed better than a referent with fewer causal features, the reasoner will find it easier to explain the data, and hence, the difference in performance will be perceived as larger, and the message will be more persuasive (e.g., belief in the causal claim and willingness to purchase the product) than when the target has the same causal features as the referent. The results of three studies revealed the expected pattern for different products, promising different effects in different communication contexts.