Personalization and Machine Learning for Social and Search
Personalized search is now being used in major social media platforms that tailor social media profiles to their users. Because of social media profile personalization, marketing messages may not be reaching the audience you thought were seeing them. However, social data can be analyzed and refined in order to break through the social personalization filters and reach your audience on social media. While the major social media platforms (Facebook, LinkedIn, Twitter, Youtube, Google+ and Pinterest) are personalizing user profiles, marketers can create a plan to reach social users effectively. This search and social media marketing class, Personalization and Machine Learning for Social and Search, instructed by Katherine Ong, shows how marketers can create data driven strategies that break through personalization filters and reach the target audience on social.
What You'll Learn:
- How to breakthrough the search or social filter to reach your target audience
- How schema, semantic web and machine learning make personalization possible
- Why marketers need to use data to craft marketing messages and plans that will be effective.
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