As you build your custom ad product, you'll likely contemplate what targeting features you should offer. One feature you'd be wise to consider is negative targeting.
Negative targeting is where you set rules targeting a certain audience - but then exclude some segment within it. It can also be called exclusion targeting or domain blocking. In the past it's been referred to as 'blacklisting' as well, but the ad industry is rightly moving away from this term.
For instance, let’s imagine a situation where an advertiser wants to show ads to the state of New York, but not to New York City itself. Here, they could employ geotargeting of New York while implementing negative geotargeting of the NYC metro area.
As with all targeting options, you have to weigh the feature's potential revenue with the opportunity cost to build it. Some reasons to prioritize negative targeting include:
Implementing negative targeting involves a few steps:
The complexity of this will depend on the use case and level of automation.
For instance, contextual negative targeting - such as excluding news articles containing distressing topics - could be done through AI/ML that parses page content and passes relevant keywords.
If your negative targeting involves user-level data like demographic or behavioral data, you'll need a data management platform tied to a persistent ID. This ID would need to be passed in every ad request so your ad server can cross-reference the DMP to see if the user falls under an excluded segment.
Your internal or self-serve UI would need the ability to set negative targeting rules.
The implementation of this will depend on your vision; using the above example, you could have a checkbox where you exclude 'Socially-Sensitive Content'...or you could let advertisers choose specific words they don’t want to appear alongside (a more complicated approach).
Finally, you’ll need to architect your system to handle positive and negative targeting at scale, without small exclusions increasing load times and slowing down your site/app.
There are many ways to approach this, and it will also vary based on the type of targeting (such a geo, context, demographic, etc).
For example, if you're looking to incorporate contextual negative targeting (where advertisers can block, say, sensitive social topics), this is where we'd recommend your system have a feature we call Keyword Targeting - a way to create rules for targeting (or negatively targeting) keywords attached to each ad request.
Using Kevel's keyword targeting tools as an example, you could:
Please note: we are not a law firm - we recommend consulting a lawyer for this. Below is for informational purposes only.
Geolocation negative targeting is the same, as long as you aren't sharing the full IP Address/GPS data with a third-party.
The demographic/behavioral use cases are more grey since they could involve PII. The conservative route would be to prompt consent for EU users (and for the CCPA to enable opt-outs if requested), but we recommend talking with your lawyer to determine if this is needed.
The cost of building this feature will depend on the size of your engineering team and the scope of the project. This is where integrating your ad product with Kevel can expedite the process, as Kevel provides turnkey access to negative targeting functionality.