During the past 2 years the behavior of consumers has significantly changed in favor of the eCommerce industry, with an exponential growth in the...
AI for Ads Optimization
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Implementing AI models in ads campaigns deliver up to 7% increase in CTR and a boost of up to 30% in the ROI of online marketing budgets, according to JOT Media.
Potential of data
In simple terms, such models require internal metrics such as keywords, ad text, bid, length and sentiment of the text to offer a forecasted result of dominant KPIs like clickthrough rate. For an even more accurate prediction, external factors such as data about the weather, media news and events along with bank holidays can be successfully implemented into the AI models.
The information is then processed through machine learning methods like time series analysis using regression. The algorithm receives large amounts of precise and reliable data from your ad networks (e.g. Google Ads, Facebook Ads) that gets processed through standardized mathematical approaches to find conclusive relationships.
Finally, after the model extracts pattern information and conveys which keywords are likely to increase impressions and CTR, the last step in shopping ads optimization is finding the right moment when the customer sees the personalized ad. It can also indicate the perfect timing for launching a campaign, depending on responsiveness patterns and other events that might negatively affect buyer behavior.
An ads optimization model can significantly increase the performance of marketing campaigns by leveraging valuable information that would otherwise not be fully tapped into or missed out on.