Ad tech constantly evolves, but typically in small shifts. As consumers become increasingly concerned about data privacy, however, the laws and restrictions that result may force the industry to make seismic changes sooner rather than later.
Many targeting practices that drive revenue now also drive disdain - leaving publishers justifiably confused on how to balance user data with company profit. They now have to determine how to offer advertisers valuable ad placements without undermining users’ trust and PII (personally identifiable information).
Indeed, by revisiting how you target, you may even increase your ad revenue. This article will offer examples to explain how.
Please note: We are not a law firm. This article is informational and does not offer legal advice. Please speak to a lawyer before determining which targeting tactics work best for your business.
Context has historically focused on overall site content. MarketWatch.com sells slots to Ameritrade; The Bump secures direct deals from EverydayFamily. You should definitely keep doing this - but context is much more than just your brands’ stereotypical user.
Here are eight innovative ways to rethink contextual targeting:
Ticketmaster, the premier site for live events, could just offer site-wide targeting for their banner ads.
But why stop there? Ticketmaster also has categories like ‘Family’ and ‘Arts & Theater’. By letting advertisers target specific subcategories, they could invite new advertisers who wouldn’t normally have bought slots - like “The Book of Mormon” paying to appear in the ‘Arts & Theater’ section.
Allrecipes employed a micro-view of context by offering food brands a way to place their sponsored food item next to the generic ingredient.
For example, an Allrecipes user viewing this recipe will see Whole Foods’s promotion of 365 Everyday Value eggs under the egg ingredient listing. They even offer store location information based on the zip code they entered (which doesn’t involve PII).
As a community discussion site, Reddit offers content on an array of topics. Rather than inundate its users with what could be irrelevant ads, it uses its sub-categories - or subreddits - to match ads with specific discussions, such as this promoted post in r/engineering:
Xometry and other advertisers will pay more for these niche placements than they would for site-wide ads. By doing this, Reddit can help advertisers reach their target audiences without any PII.
Quora, the world’s largest Q&A site, lets advertisers appear alongside specific questions.
In this example, Kevel, who provides APIs for companies to build their own ad server, is targeting users looking at questions involving the phrase 'ad server':
More and more brands are employing tags and hashtags to filter or easily identify content. For instance, Twitter's newly-launched ad product permits advertisers to target users based on tweeted terms, like anyone who used #coffee recently.
This innovative targeting option provides the relevance advertisers seek with zero PII. Just knowing a user tweets about coffee will appeal to Peet’s, Coffee-Mate, and others.
Music streaming platforms like Pandora and Spotify can forego PII in lieu of targeting by the station users are listening to.
For example, Pandora targets users in the mood for workout music with a playlist curated and sponsored by Propel.
Like TV commercial buys, video and podcast publishers can target users based on the context of the content the user is currently viewing or listening to.
For example, a podcast producer like PRX can target subscribers of its “Criminal” podcast with ads related to criminal justice - such as a local lawyer or a true crime book publisher.
You can also use companion ads to reach audiences. This targeting tactic uses context - but with ad context instead of page content.
By grouping ads designed to be served simultaneously, such as on the top and bottom of your page, you can reinforce the same message and create a valuable ad experience.
You’ve likely seen this format on YouTube. In this example, Grammarly’s bonus ads accompany the instream ad. The companion ad reinforces the brand message while the video ad plays.
This behavior is great because it can be passed in the ad request for targeting - without being saved or turned into PII.
We encourage you to consider these examples, which use search, action, and filters in intriguing ways that respect user privacy while attracting more ad revenue.
Search targeting refers to targeting users based on a search they just did - such as putting “new car” into a search box. These searches indicate a high intent to purchase (especially eCommerce site searches). Generally such ads involve sponsored listings but you could also tailor banner or other ads based on specific keyword searches.
Both Edmunds and Etsy offer great search targeting to deliver highly relevant and valuable ads.
Let’s say an Edmunds user in Durham, North Carolina searches for a Subaru Forester. Based solely on that search term - and the zip code they entered - Edmunds can serve an ad from Subaru for that exact car.
Subaru needs no PII for this - and yet such targeting is worth orders of magnitude more than site-wide ads. Using search intent alone - even without cookies, demographic data, or IP address - is enough for Edmunds to serve a high-revenue ad.
Similarly, Etsy uses sponsored listings to match users’ search terms with premium ad placements.
A user who searches for ‘Valentine’s Day gifts for her’ will see ads across the top row, paid for by handcrafters who are specifically targeting these keywords, given how relevant their product is to the search.
Another form of intent is action. For instance, Uber could allow advertisers to target specific destinations inputted by the user, such as in-app ads from Lululemon for anyone going to the mall.
Or, Eventbrite could build a platform where if someone “saves” a specific event (like a concert), that could trigger and ad refresh that incorporates “music interest” advertisers could target against.
While action doesn’t indicate the same intent to buy as a search does, it’s still a powerful signal of potential value.
Users may use your site to filter and compare - and you can use their choices to infer which ads to serve them.
For instance, someone looking for dry cleaners near Morrisville, North Carolina on Yelp will see a variety of filter options like price and distance. This is data that could be incorporated into the ad request for targeting (for example: anyone who wants $$$ or $$$$ is bucketed into a “high value” segment).
A dating site like Tinder also serves ads based on users’ filters. A Tinder user looking for women ages 20-25 can be served ads featuring only young women, like this ad promoting National Adopt A Shelter Pet Day. This is compelling because while gender itself is considered PII - targeting their current filter would not be (as you can’t assume gender based on this data).
As a publisher, you’re using only these user intentions and actions to improve your targeting. Neither you nor your advertisers need to know a user’s age, gender, orientation, or other personal details to create high-value ad experiences.
Traditional geolocation targeting uses a person’s exact IP address or GPS data to determine their location. Under privacy laws, this is considered PII. Fortunately, you can truncate an IP address and lat-longs (such as removing the octet) before sending it through a location lookup service.
While this means you can’t target their specific neighborhood, it’s more than enough data to know their general location (like city, DMA, or zip code). This presents a great opportunity to secure ad revenue from local businesses, brands with limited city reach, and large brands with city-level roll-outs. For instance, a brand like Dunkin’ Donuts can serve ads in a specific DMA to drive traffic to their newest franchise.
Alternatively, you can infer location through search intent, like if a user on Zillow is looking for homes for sale near 27701.
Knowing their city means you can also do weather targeting - such as The Weather Channel working with Jeep to show different creatives based on the user’s current weather conditions.
In addition to context, intent, and location, here are a few more non-PII targeting ideas that could bolster your platform’s profit margins: