TikTok this month shared 5 ad targeting best practices to boost ad performance. According to TikTok, advertisers should start with broad targeting, explore manual controls as needed, enable smart targeting, create custom and lookalike audiences, and validate that more advanced techniques outperform broad targeting.
- Start with broad targeting. Broad targeting is the most effective solution for most advertisers. It allows TikTok's machine learning systems to optimize ad delivery and reach the right people. In TikTok's testing, ads that reach a "fairly broad" audience outperformed all others by a wide margin, with a 15% lower cost per acquisition and a 20% higher conversion rate.
- Explore manual controls as needed. There are some cases where it makes sense for advertisers to explore manual controls, such as when a business only operates in a specific geographic area or when targeting users with high spending power. However, TikTok recommends that advertisers start with broad targeting and test to ensure that their more advanced techniques outperform it.
- Enable Smart Targeting. Smart Targeting is a tool that advertisers can use to target specific interests, behaviors, or audiences. With Smart Targeting, TikTok launches an ad with the advertiser's exact targeting setting. If the system then observes that ad performance is declining, it will expand the targeting settings based on variables that the advertiser enables. According to TikTok, Smart Targeting has been proven to improve CPA by 5% for web conversion advertisers.
- Create custom and lookalike audiences. Custom audiences allow advertisers to build an audience specific to their targeting needs based on first or third-party data. Lookalike audiences are similar to broad targeting, but they are seeded with a custom audience. TikTok recommends that advertisers use broad lookalikes as the most effective choice for most advertisers.
- Validate that more advanced techniques outperform broad targeting. There is no one-size-fits-all approach to successful marketing, but broad targeting is the best approach for allowing TikTok's machine learning systems to optimize ad delivery. TikTok recommends that advertisers test and validate each optimization to ensure that it outperforms broad targeting.