SMO

The Power of Social Media

Social media optimization (SMO) was originally designed to drive traffic from social media sites such as bookmarking sites and social networks. However, SMO is now significantly more important and not simply because social networking has grown but for example SMO also improves SEO performance. Good SMO will drive traffic from both shortest social site referrals and from search engines.

Social media optimization (SMO). At this time the core focus was driving traffic to websites from social sites.

This remains the core purpose of SMO as outlined in Wikipedia “SMO is similar to search engine optimization in that the goal is to generate traffic and awareness for a website. In general, social media optimization refers to optimizing a website and its content in terms of sharing across social media and networking sites.”

The SEO

This has changed over the years as social networks have changed and also as search engines have looked to social signals to help rank content. Wikipedia says “social media optimization is becoming increasing

ly important for search engine optimization, as search engines are increasingly utilizing the recommendations of users of social networks such as Facebook, Twitter, and Google+ to rank pages in the search engine result pages.”

Probably traditional SEO focused on the technical structure of website

s rather than the user experience or even the quality of content itself. SMO is very concerned with the quality of

the content, the authority of the author and the user experience of interacting with the content and the author. These aspects of SMO can help improve SEO performance as search engines increasingly look for social signals to aid the ranking of pages.

Social signals may not as simple as the number of shares or the size of a person’s network. For example, the network size may be less important than who is in the network and who interacts with a user’s content. Social networks provide vast volumes of data which can be analyzed to identify patterns and collective preferences. Machine learning, the construction of systems that can learn from data, is increasingly being applied to this data to develop new insights so search engines are likely to use something more complex than just the number of shares.