Information Design for Selling Search Goods and the Effect of Competition

This paper studies a search goods seller's optimal design of consumer pre-search information. Unlike the existing literature, I allow the consumer to have private information on her outside option value, which turns out to be important in shaping the seller's optimal signal. To accommodate this, a relaxed problem approach is developed. When the outside option value has unimodal distribution, I show that the optimal signal would pool all match utilities above a threshold and fully reveal for those below the threshold. Based on this characterization, I provide two comparative statics results. The first shows that higher product quality leads to less accurate pre-search information for consumers. The second shows that allowing the consumer to postpone some search cost leads to lower seller profit and may also (unexpectedly) lead to lower consumer welfare even if the price is fixed. My approach also enables me to consider competition among multiple sellers. In particular, I show that as competition gets increasingly strong, the pre-search information converges to full information, which extends the corresponding result for experience goods. My approach also helps to highlight the key similarity and dissimilarity between information designs for search goods and experience goods, which is discussed throughout the paper.