Colt Sliva on turning into an web optimization engineer and visualizing search charts

Colt Sliva came to my field office to talk to me about SEO. At the beginning I asked him a few personal questions to keep him tense – just kidding. We talked about his career, he’s the SEO engineer at iPullRank, the place is run by Mike King with whom I spoke before. He started SEO by helping his mom create a blog and then write some content and make money on Google AdSense. He developed something in school, made some art in school and then got a job in marketing and SEO and content for these companies. He also did a lot of development work in these companies. He wanted to do more SEO and found Mike King and he clicked with Mike. Mike hired him to work on more SEO at his company.

We then dug a little into the search graphs, knowledge panels, entities, and more. He said he found out about this by delving into white papers on how search engines work. He started with PageRank’s algorithm and said that you can use Python to visualize these algorithms. Colt got quite technical with the conversation when he talked about eigenvector centrality. In graph theory, the eigenvector centrality is a measure of the influence of a node in a network. All nodes in the network are assigned relative ratings based on the concept that connections to nodes with high ratings contribute more to the rating of that node than equal connections to nodes with low ratings. He does this to better visualize the algorithms.

He gave some examples of how the knowledge graph works with a bicycle. We then talked a bit about knowledge panels, which might be as fun as talking about bicycles.

More next week, but you can find out more about Colt Sliva @SignorColt.

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