08 Mar 2025 Search

(This post includes several updates and links to later literature, and may be updated more in the future)

A new paper is out, collecting some of the top arguments in favor of personalized advertising: The Intended and Unintended Consequences of Privacy Regulation for Consumer Marketing by Jean-Pierre Dubé, John G. Lynch, Dirk Bergemann, Mert Demirer, Avi Goldfarb, Garrett Johnson, Anja Lambrecht, Tesary Lin, Anna Tuchman, Catherine E. Tucker. It’s probably going to get cited this privacy law season. But, as an Internet optimist, I’m still not buying the argument that personalized advertising has important benefits that need to be balanced with privacy. Looking at the literature, it is more likely that certain risks are inherent to personalization as such and that reducing personalization is more likely to be a bonus benefit of privacy protection than a trade-off.

Some notes and links follow.

p. 3 We do not consider legal arguments for consumer privacy as a fundamental right or concerns about access to personal data by malign actors or governments.

Avoiding malign actors is the big reason for restricting personalized ads. And malign actors are numerous. The high-profile national security threats are already in the news, but most people will encounter miscellaneous malware, scams, rip-offs and other lesser villainy enabled by ad personalization more often than they have to deal with state or quasi-state adversaries. There is no hard line between malign actors and totally legit sellers—not only does the personalized ad business have plenty of halfway crooks, you can find n/m-way crooks for arbitrary values of n and m.

Ad personalization gives a bunch of hard-to-overcome advantages to deceptive sellers. Although scams are generally illegal and/or against advertising platform policies, personalization makes the rules easier to evade, as we see with some ways that Facebook ads are optimized for deceptive advertising. Most personalized ads aren’t clustered at the good (high-quality pair of shoes in your size, on sale, next door!) or bad (malware pre-configured for your system) ends of the spectrum. Advertisers at all levels of quality and honesty are present, so any framework for thinking about ad personalization needs to take that variability into account.

p. 3 Some privacy advocates assume, incorrectly, that personalized marketing based on granular consumer data is automatically harmful…

Treating personalized advertising as harmful by default is not an assumption, but a useful heuristic based on both theoretical models and real-world experience. personally, I don’t pay attention to your ad if it’s personalized to me—it’s as credible as a cold call. But I might pay attention to your ad if it’s run in a place where the editors of sites that cover your industry would see it, or your mom would. (update 30 Jul 2025: even Google uses the word “protection” to describe not serving personalized ads) Yes, it is possible for professors to imagine a hypothetical world in which personalization is beneficial, but that only works if you make the unrealistic simplifying assumption that all sellers are honest and that the only impact of personalization is to show people ads that are more or less well matched to them. The theoretical arguments in favor of personalized advertising break down as soon as you level up your economic model to consider the presence of both honest and deceptive advertisers in a market.

See Gardete and Bart, Tailored Cheap Talk: The Effects of Privacy Policy On Ad Content and Market Outcomes. Our research suggests that another peril of sharing very high quality targeting information with advertisers is that ad content may become less credible and persuasive to consumers. An advertising medium that allows for personalization is incapable of conveying as much information from an honest seller to a potential buyer as an advertising medium that does not support personalization.

Mustri et al., in Behavioral Advertising and Consumer Welfare, find that products found in behaviorally targeted ads are likely to be associated with lower quality vendors and higher product prices compared to competing alternatives found among search results.

Lin et al., in The Welfare Effects of Ad Blocking, found that ad blocker users have fewer reported regrets with purchases and an improvement in subjective well-being. This study, however, blocked ads in general, not just personalization.

p. 8 Which Consumers Care Most About Privacy, and Do Privacy Policies Unintentionally Favor the Privileged?

Lots of studies show that, basically, some people really want cross-context personalized advertising, some people don’t, and for the largest group in the middle, it depends how you ask. (references at the 30-40-30 rule). But the difference in consumer preferences is not about privilege, it’s about information level. See Turow et. al, Americans Reject Tailored Advertising and Three Activities That Enable It. That study includes a survey of privacy preferences before and after informing the participants about data practices—and people were more likely to say they do not want tailored advertising after getting the additional information.

In the Censuswide study Who’s In the Know: The Privacy Pulse Report, the experienced advertisers surveyed in the USA (people with 5 or more years of ad experience) were more likely than average to use an ad blocker (66% > 52%), and privacy is now the number one reason for people to use one. It is reasonable for policy-makers to consider the preferences of better-informed people—which is already a thing in fields such as transportation safety and public health. And do wealthier people choose privacy over personalization, or do people who choose privacy build more wealth?

p. 11 Poorer consumers live in data deserts (Tucker 2023), causing algorithmic exclusion due to missing or fragmented data. This exclusion thwarts marketing outreach and may deprive them of offers, exacerbating data deserts and marginalization.

Instead of speculating about this problem, personalized advertising proponents who are concerned about some people not being tracked enough can already look at other good examples of possibly under-surveilled consumers. Early adopters of privacy tools and preferences are helpfully acting as the experimental group for a study that the surveillance business hasn’t published anything on. If people on whom less data is collected are getting fewer win-win offers, then the privacy early adopters should have worse consumer outcomes than people who leave the personalization turned on. For example, Apple iOS users with App Tracking Transparency (ATT) set to allow tracking should be reporting higher satisfaction and doing fewer returns and chargebacks. So far, this does not seem to be happening. (For a related result, see Bian et al., Consumer Surveillance and Financial Fraud. Consumers who deliberately placed themselves in a data desert by changing ATT to disallow tracking reported less fraud.) Click this to buy better stuff and be happier

And there’s little evidence to suggest that if a personalized ad system knows someone to be poor, that they’ll receive more of the kind of legit, well-matched offers that are targeted to the more affluent. Poor people tend to receive more predatory finance and other deceptive offers, so may be better off on average with ads less well matched to their situation.

p. 13 More broadly, without cross-site/app identity, consumers enjoy less free content

This depends on how you measure content and how you define enjoy. The Kircher and Foerderer paper states that, although children’s games for Android got fewer updates on average after a targeted advertising policy change by Google,

Only exceptionally well-rated and demanded games experienced more feature updates, which could be interpreted as a sign of opportunity due to better monetization potential or weakened competition. However, considering that we observed these effects only for games in the highest decile of app quality and demand and given that the median user rating of a game is 4.1 of 5, our findings suggest widespread game abandonment.

By Sturgeon’s Law, a policy change that benefits the top 10% of games but not the bottom 90% (which, in total, account for a small fraction of total installs and an even smaller fraction of gameplay) is a win for the users.

Another relevant paper is Kox, H., Straathof, B., and Zwart, G. (2014). Targeted Advertising, Platform Competition and Privacy by Henk L.M. Kox, Bas Straathof, Gijsbert Zwart :: SSRN.

We find that more targeting increases competition and reduces the websites’ profits, but yet in equilibrium websites choose maximum targeting as they cannot credibly commit to low targeting. A privacy protection policy can be beneficial for both consumers and websites.

When both personalized and non-personalized ad impressions are available in the same market, the personalized impressions tend to go for about double the non-personalized. But it doesn’t work to artificially turn off some data collection for a fraction of ad impressions, observe that revenue for those impressions is lower (compared to impressions with the data that are still available), and then extrapolate the revenue difference to a market in which no impressions have the data available.

It is also important to consider the impact of extremely low-quality and/or illegal content in the personalized advertising market. Much of the economic role of ad personalization is not to match the right ad to the right user but to monetize a higher-value user on lower-value content. The surveillance economy is more like the commodification economy. Surveillance advertising companies are willing to pursue content commodification even to the point of taking big reputational risks from feeding ad money to the worst people on the Internet (Hiding in Plain Sight: The Ad-Supported Piracy Ring Driving Over a Billion Monthly Visits - deepsee.io, Senators Decry Adtech Failures as Ads Appear On CSAM Site). If advertising intermediaries were more limited in their ability to put a good ad into a bad context using user tracking, the higher-quality content sites would enjoy significantly increased market power.

p. 14 Restrictions to limit the effectiveness of digital advertising would likely disproportionately disadvantage small businesses, since nine out of ten predominantly use digital advertising, especially on Meta

Are small businesses really better off in the surveillance advertising era? Although personalized Big Tech advertising is the main ad medium available to small businesses today, there is clearly some survivorship bias going on here. The Kerrigan and Keating paper states that, While entrepreneurship has rebounded since the Great Recession and its aftermath, startup activity remains weak by historical standards. This period of time overlaps with the golden age of personalized advertising, after widespread adoption of smartphones but before Apple’s ATT, the EU’s GDPR, and California’s CCPA. If personalized advertising is so good for small businesses, where are the extra small businesses enabled by it? We should have seen a small business boom in the second half of the 2010s, after most people in the USA got smartphones but before CCPA and ATT. Instead, the surveillance advertising era has coincided with buying more and more of our stuff from fewer and fewer companies.

Jakob Nielsen may have provided the best explanation in 2006’s Search Engines as Leeches on the Web, which likely applies not just to search, but to other auction-based ad placements like social media advertising. An auction-based advertising platform like those operated by Google and Meta is able to dynamically adjust its advertising rates to capture all of the expected incremental profits from the customers acquired through it. (Or, in performance marketing terms, You need to keep pushing your budget until cost per marginal incremental acquisition = marginal [lifetime value of a customer].)

Part of the missing small business effect may also be caused by platform concentration. If, instead of an advertising duopoly, small businesses had more options for advertising, the power balance between platform (rentier) and small business (entrepreneur) might shift more toward the latter. See also Crawford et al., The antitrust orthodoxy is blind to real data harms. Policy makers might choose to prioritize pro-competition privacy legislation such as surveillance licensing for the largest, riskiest platforms in order to address competition concerns in parallel with privacy ones.

(Update 11 May 2025) Another interesting piece of missing research: If advertising on Big Tech platforms is so good for small local businesses, then the Big Tech companies should have been able to publish a study showing that people who use the Big Tech apps more are spending more money with small local businesses. The Big Tech companies have been working the good for small business angle for long enough that it’s hella sus that they don’t have any numbers on correlations between usage of their apps and buying from small local businesses. (Maybe usage correlates with spending more money on sports betting, cryptocurrency, and in-game purchases, and less on local products and services? More: Studies on behavioral advertising that probably already exist)

(Update 2 Nov 2025) Small business outcomes can also be cross-checked from the customer side, because for every sale by a legitimate business, there is a positive outcome for some customer. If personalized advertising is a benefit to legitimate small businesses, then people who receive more personalized advertising should be more satisfied in their role as consumers, and so far the data seems to show the opposite.

p. 15 Since PETs are costly for firms to implement, forward-looking regulation should consider how to incentivize PET adoption and innovation further.

In a section about how so-called privacy-enhancing technologies (PETs) have equal perceived privacy violation and bigger competition issues than conventional personalization, why recommend incentivizing PETs? The works cited would better support a recommendation to have a more detailed or informative consent experience for PETs than for cookie-based tracking. Because PETs obfuscate real-world privacy problems such as fraud and algorithmic discrimination, it would be more appropriate to require additional transparency, and possibly licensing, for PETs.

PETs, despite their mathematical appeal to many at Big Tech firms, have a long list of problems when applied to the real world. The creeped-out attitude of users toward PETs is worth paying attention to, as people who grow up in market economies generally develop good instincts about information in markets—just like people who grow up playing ball games can get good at catching a ball without consciously doing calculus. Policymakers should pay more attention to user perceptions—which are based on real-world market activity—than to mathematical claims about developers’ PET projects. PETs should be considered from the point of view of regulators investigating discrimination and fraud complaints, which are often difficult to spot on large platforms. Because PETs have the effect of shredding the evidence of platform misdeeds, enabling the existing problems of adtech, just in a harder-to-observe way, they need more scrutiny, not incentivization. (More: PETs and public policy)

Coming soon: a useful large-scale experiment

Policymakers may soon be able to learn from what could be the greatest experiment on the impact of ad personalization ever conducted.

If Meta is required to offer Facebook users in the European Union a meaningfully de-personalized ad experience (and not just the less personalized ads option that still allows for personalization using fraud risk factors like age, gender, and location) then there will be a chance to measure what happens when users can choose personalized or de-personalized ads on a service that is otherwise the same.

Personally, I bet that users with the personalization turned off will have better outcomes as consumers, but we’ll see. I’m pretty confident that personalized ads will turn out to be worse because tools and settings that tend to make personalization less effective have been available for a while, and if choosing the privacy option made you buy worse stuff, the surveillance companies would have said so by now.

Conclusion

I put these links and notes together to help myself out when someone drops a link to the Dubé et al. paper into an Internet argument, and put them up here in the hope that they will help others. Hardly anyone will read all the literature in this field, but a lot of the most interesting research is still found in corners of the library that Big Tech isn’t actively calling attention to.

Thanks to Fengyang Lin for reviewing a draft of (the original version of) this post.