The Complete SMO / SEO Guide for Business & Brands in Social Media.Author: Joshua Berg ©
① Are social signals phasing out SEO for more user perceptive search?
② Learning from collective preferences en masse using social media.
③ An explanation of Social Media Optimization and its earlier definition.
④ The seventeen early rules of Social Media Optimization, the way it was.
⑤ SMO's relationship with SEO and the growing intelligence of search algorithms.
⑥ Is it time to rewrite SMO rules? User experience first, then search optimization.
⑦ The all new principles of SMO, Focus on the user and all elSEO will follow.
ⓐ Create - Maximize your creativity with original quality content.
ⓑ Relate - Create relatable content, or make your content relatable.
ⓒ Captivate - Fun and interesting content stands out from the noise.
ⓓ Arouse - Arouse emotion; it is the one constant of all viral success!
ⓔ Enjoy - Have Fun! All the most popular media personalities enjoy it.
ⓕ Share - Seek shareable (quality) content; reciprocate sharing with movers.
ⓖ Acknowledge - Acknowledging others encourages engagement, reciprocation.
ⓗ Contribute - Find ways to contribute desired value & quality to your audience.
ⓘ Influencers - Identify key influencers (movers) to foster connections with.
ⓙ Communities - Existing communities can expand your reach & effectiveness.
ⓚ Reputation - Build personal reputation & brand, as a reliable qualified source.
ⓛ Engagement - Tag - Cite - Respond - Comment - Proactively seek to engage.
ⓜ Authority - Become a notable authority in a particular field of expertise.
ⓝ Leadership - Lead in social with new and original ideas; be a Thought Leader.
ⓞ Social - Be sociable, try to reach the individual person, visualize the reader.
ⓟ Media - Learn to master the media platforms you need to reach your goal.
ⓠ Optimization - Technically optimize; target content, keywords integral to SMO.
⑧ Authorship & Google+ is a royal romance, the marriage of Search & Social Media.
⑨ This is just my Pilot Episode; here's some of the related SMO topics coming soon.
⑩ Let's travel 10 years into the future and see where Google Search is going.
"73% say they process information more deeply, thoughtfully when they share it." NYTimes
① Are social signals phasing out SEO for more user perceptive search?▔▔▔▔▔▔▔▔▔▔▔▔▔▔▔▔▔▔▔▔▔▔▔▔▔▔▔▔▔▔▔▔▔
Traditional SEO techniques, many of which have been overused up until now, continue to be more finely scrutinized by each new search engine update that comes out. With Google Search that has caused a relatively large proportion of the somewhat over-optimized sites to get penalized and dropped down in search rankings. The biggest drawback of the traditional SEO concept and techniques, is that they focus mostly on the technical aspects of websites and their promotion, rather than the user experience and quality of the content. Ultimately the epidemic over optimizing of website content created an unprecedented level of web pollution by meaningless keyword rich content, quite worthless and even detestable to the average user.
Along comes social media and the knight in shining armor indisputable, it is users themselves who will decide the experience they wish to pursue and from which can be learned the collective preference of masses. Social signals then become the holy grail for algorithmically understanding users desired experience en masse in order to move toward more perceptive and comprehending search. One particular search giant realizing their algorithmically incurable deficiency in this arena, set about to build the ultimate social media platform which might better tap into universal intelligence and preference to maturate artificial intelligence and perception on a scale unprecedented.
As search comprehension increases, so too does the importance of social signals to the progression of higher intelligence search, making social media indicators the natural replacement for many of the more technical astute aspects of SEO.
Jennifer Wortman Vaughan, in her thesis Learning From Collective Preferences, explains:
Machine learning has become one of the most active and exciting areas of computer science research, in large part because of its wide-spread applicability to problems as diverse as natural language processing, speech recognition, spam detection, search, computer vision, gene discovery, medical diagnosis, and robotics. At the same time, the growing popularity of the Internet and social networking sites like Facebook has led to the availability of novel sources of data on the preferences, behavior, and beliefs of massive populations of users. Naturally, both researchers and engineers are eager to apply techniques from machine learning in order to aggregate and make sense of this wealth of collective information.
② Learning from collective preferences en masse using social media.▔▔▔▔▔▔▔▔▔▔▔▔▔▔▔▔▔▔▔▔▔▔▔▔▔▔▔▔▔▔▔▔▔
Learning from the collective preferences of many users using social media and data mining tools, has become an entire field of specialization on its own. There has recently been considerable research, advancements in knowledge and software designed specifically for this purpose. More businesses have also sprung up in this industry, dedicated to helping companies and high profile individuals with Social Mood Research, to provide them with analysis and real-time feedback via social media.