Some of the digital marketing challenges that can be addressed through machine learning algorithms include:
- Helping digital media planners and buyers determine each media or ad position based on qualitative and quantitative research that is outside your own website or app. This expanded view may encourage media planners and buyers to focus on quality buying of of ad inventory reducing cost of untargeted or unqualified ad inventory.
- Enabling digital marketers to anticipate, identify and qualify audiences at the point of entry, and personalize content to maximize conversions or session outcomes. This will make content much more relevant and tailored to consumers. Also this personalization can be extended to multiple devices the audience uses.
- Providing content feeds to digital users based on their interests, past interactions or other important factors. Social media platforms have some limited capacity in prioritizing newsfeed content order based on viewing, timings, and likelihood to consume. So many top tier online experiences train consumers to expect a custom experience. So not providing priority content will disappoint.
- Ranking visitors by value to the business. Not all traffic has equal value. Rapid website testing can be enabled and also personalization of page layouts, offers, messages, creative and content can be greatly improved by algorithms that have the means to assess the expected value of each visitor
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