If a digital marketing manager was to upgrade their keywords to broad match, which behavior should they incorporate into their routine optimization efforts in order to guide machine learning?
- Disregarding suggestions to add relevant new keywords
- Removing negative keywords that could block relevant traffic
- Adding Customer Match lists that contain data more than 90 days old
- Adding more phrase and exact match keywords in order to improve reach
Explanation:
The selected answer is **Removing negative keywords that could block relevant traffic**. Incorporating the behavior of removing negative keywords that could block relevant traffic into routine optimization efforts is essential when upgrading keywords to broad match in order to guide machine learning effectively. Broad match keywords allow ads to be shown for a wide range of search queries, including variations and synonyms, which can lead to increased traffic and exposure. However, this broader reach also poses the risk of displaying ads for irrelevant or low-converting searches. By regularly reviewing and refining negative keyword lists, digital marketing managers can prevent ads from appearing for irrelevant searches, thereby improving the relevance and quality of traffic directed to their website. This proactive approach not only enhances the performance of broad match campaigns but also provides valuable guidance to machine learning algorithms, allowing them to better understand the advertiser’s preferences and objectives and optimize campaign performance accordingly. Therefore, incorporating the behavior of removing negative keywords that could block relevant traffic into routine optimization efforts is crucial for guiding machine learning effectively and maximizing the success of broad match keyword campaigns.