When digital ad campaigns first begin, the ads delivery system uses machine learning to optimize your results. Each time one of your ads is shown, the delivery system (such as Facebook or Google) learns more about the best people to target, times of day to show the ad, placements, and creatives to use. During the learning phase, the delivery system is exploring the best way to deliver your ad set – actively trying different audiences, placements, and more – so performance has not yet stabilized.
In addition to the machine learning, the ads strategist(s) monitor the results and manually optimize the ads. Therefore, both the delivery system and the ads strategist are working daily to analyze and improve your ads. This takes time.
While we completely understand the anxiousness to see your paid ad campaigns begin to show significant results, the learning phase occurs when a new ad set is created or significant edit to an existing ad or ad set are made. Typically, performance stabilizes after an ad set receives around 50 optimization events within a 7-day period.The main optimization process can take an elapse time of around 30 days.
Naturally, when initially getting started with paid advertising, one’s first impulse is to figure out what is going “wrong”, or “why haven’t my ads brought in the $1M I need, right now!” 😉 , it’s best to wait to consider your results after a few weeks. Ad sets exit the learning phase once their performance stabilizes. If seven days have elapsed since a significant edit and an ad set has still not exited the learning phase, then there is a factor that needs to be examined.
During this period, we are continually monitoring, analyzing, and optimizing all aspects of your ads. First, we look at whether we are obtaining enough impressions. Then if there are enough impressions but not enough leads, then we optimize and test variations of ads and/or landing pages. All of this takes time.