Navdeep S. Sahni

Effect of Temporal Spacing between Advertising Exposures: Evidence from Online Field Experiments

This paper aims to understand the impact of temporal spacing between ad exposures on the likelihood of a consumer purchasing the advertised product. I create an individual-level data set with exogenous variation in ad exposure and its spacing by running online field experiments. Using this data set, I first show that (1) ads significantly increase the likelihood of the consumers purchasing from the advertiser and (2) this increase carries over to future purchase occasions. Importantly, I also find evidence for the spacing effect: the likelihood of a product’s purchase increases if it’s ads are spread apart rather than bunched together, even if spreading apart involves shifting some ads away from the purchase occasion. Accounting for the spacing effect is important to detect the effects of repeated advertising. Because the traditional models of advertising do not explain the data patterns, I build a new memory-based model of how advertising influences consumer behavior. Using a nested test, I reject the restrictions imposed by the canonical goodwill stock model (Nerlove and Arrow, Economica, 29(114):129–142, 1962), in favor of the memory-based model I propose. Additionally, I use the estimated parameters to simulate counterfactual scenarios and show that the advertisers’ profits might be lower if the features of the memory model are not accounted for.

How do firms make money selling digital goods online

We review research on revenue models used by online firms who offer digital goods. Such goods are non-rival, have near zero marginal cost of production and distribution, low marginal cost of consumer search, and low transaction costs. Additionally, firms can easily observe and measure consumer behavior. We start by asking what consumers can offer in exchange for digital goods. We suggest that consumers can offer their money, personal information, or time. Firms, in turn, can generate revenue by selling digital content, brokering consumer information, or showing advertising. We discuss the firm’s trade-off in choosing between the different revenue streams, such as offering paid content or free content while relying on advertising revenues. We then turn to specific challenges firms face when choosing a revenue model based on either content, information, or advertising. Additionally, we discuss nascent revenue models that combine different revenue streams such as crowdfunding (content and information) or blogs (information and advertising). We conclude with a discussion of opportunities for future research including implications for firms’ revenue models from the increasing importance of the mobile Internet.

Advertising Spillovers: Evidence from Online Field-Experiments and Implications for Returns on Advertising

I analyze the impact of online ads on the advertisers competitors, using data from randomized field experiments on a restaurant-search website. I find significant positive causal effects of ads on the chances of sales for non-advertised restaurants. The spillover benefits are concentrated on restaurants that serve the advertisers cuisine and have a high rating on the website. The extent of spillovers also depends on the intensity of the advertising effort. The spillovers are largest when the intensity (frequency) of advertising is low. As the intensity increases, the spillovers disappear and the advertiser gains more. These patterns are consistent with the following mechanism: ads increase the chance of consumers buying the advertised product, but also remind consumers of similar (non-advertised) options. Higher ad intensity leads to a stronger direct effect favoring the advertiser and can offset the spillover caused by the broader reminder.

Do Targeted Discount Offers Serve as Advertising? Evidence from 70 Field Experiments

The prevalence and widespread usage of email has given businesses a direct and cost effective way of providing consumers with targeted discount offers. While these discounts are expected to increase the demand for the promoted products, are they effective in increasing revenues? Do they have effects beyond acting as price reductions? We study these questions using individual-level data from 70 randomized experiments run by a large online ticket resale platform. We estimate the redemption rates of the offers and also measure the broader impact of emailed promotions by comparing purchases by individuals who received the experimental promotions with purchases by those who did not receive the offers because of the experimental randomization. We find that the offers cause the average expenditure to increase significantly, by

An Experimental Investigation of the Effects of Retargeted Advertising: The Role of Frequency and Timing

3.03 (a 37.2% increase) during the promotion window. However, the redemption rate of these offers is low. Importantly, ninety percent of these gains are not through redemption of the offers. The individuals who spent more on the platform in the past are more responsive to the offers; and the effect of the offers is significantly higher among individuals who did not transact on the platform in the year before the offer was given. Interestingly, the promotion causes carryover to the week after the promotion expires; we find that spending increases by

Effects of Targeted Promotions: Evidence from Field Experiments

1.55 in the week after the offer expires. Additionally, we find evidence for cross category spillovers to non-promoted products - offers not applicable to a ticket genre cause an increase in spending in that genre. We conclude that emailed offers can serve as a form of “advertising” for the firms products rather than tools of price discrimination.

Personalization in Email Marketing: The Role of Noninformative Advertising Content

In collaboration with an online seller of home-improvement products, the authors conduct a large-scale randomized field experiment to study the effects of retargeted advertising, a form of internet...