If you recommend a product to me and I buy it, how much should you be paid by the seller? And if your sole interest is to maximize the amount paid to you by the seller for a sequence of recommendations, how should you recommend optimally if I become more inclined to ignore you with each irrelevant recommendation you make? Finding an answer to these questions is a key challenge in all forms of marketing that rely on and explore social ties; ranging from personal recommendations to viral marketing. In the first part of this paper, we show that there can be no pricing mechanism that is “truthful” with respect to the seller, and we use solution concepts from coalitional game theory, namely the Core, the Shapley Value, and the Nash Bargaining Solution, to derive provably “fair” prices for settings with one or multiple recommenders. We then investigate pricing mechanisms for the setting where recommenders have different “purchase arguments”. Here we show that it might be beneficial for the recommenders to withhold some of their arguments, unless anonymity-proof solution concepts, such as the anonymity-proof Shapley value, are used. In the second part of this paper, we analyze the setting where the recommendee loses trust in the recommender for each irrelevant recommendation. Here we prove that even if the recommendee regains her initial trust on each successful recommendation, the expected total profit the recommender can make over an infinite period is bounded. This can only be overcome when the recommendee also incrementally regains trust during periods without any recommendation. Here, we see an interesting connection to “banner blindness”, suggesting that showing fewer ads can lead to a higher long-term profit.
A solution is provided wherein an identification of a user who is producing low value to a web page or service is received, wherein the identification was determined by measuring web page usage patterns for the user. Advertising is then presented on the web page or service for the user according to a retraining program, wherein the retraining program is designed to retrain the user's behavior so that the user no longer produces low value and wherein the retraining program presents advertising in a different way than would be presented without the retraining program. In this paper, we develop an analytical approach to modeling consumer response to banner ad exposures at a sponsored content Web site that reveals significant heterogeneity in (unobservable) click proneness across consumers. The effect of repeated exposures to banner ads is negative and nonlinear, and the differential effect of each successive ad exposure is initially negative, though nonlinear, and levels off at higher levels of passive ad exposures. Further, significant correlations between session and consumer click proneness and banner exposure sensitivity suggest gains from repeated banner exposures when consumers are less click prone. For a particular number of sessions, more clicks are generated from consumers who revisit over a longer period of time, than for those with the same number of sessions in a relatively shorter timeframe. We also find that consumers are equally likely to click on banner ads placed early or late in navigation path and that exposures have a positive cumulative effect in inducing click-through in future sessions. Our results have implications for online advertising response measurement and dynamic ad placement, and may help guide advertising media placement decisions. The seeming contradiction between “banner blindness” and Web users' complaints about distracting advertisements motivates a pair of experiments into the effect of banner ads on visual search. Experiment 1 measures perceived cognitive workload and search times for short words with two banners on the screen. Four kinds of banners were examined: (1) animated commercial, (2) static commercial, (3) cyan with flashing text, and (4) blank. Using NASA's Task Load Index, participants report increased workload under flashing text banners. Experiment 2 investigates search through news headlines at two levels of difficulty: exact matches and matches requiring semantic interpretation. Results show both animated and static commercial banners decrease visual search speeds. Eye tracking data reveal people rarely look directly at banners. A post hoc memory test confirms low banner recall and, surprisingly, that animated banners are more difficult to remember than static look-alikes. Results have implications for cognitive modeling and Web design. 