Colt Sliva On Becoming A SEO Engineer & Visualizing Search Graphs

Colt Sliva came out to my outside office spot to chat SEO with me. I asked him a bunch of personal questions to start, to make him tense up - just kidding. We spoke about his career, he is the SEO engineer at iPullRank, the place is run by Mike King who I spoke to before. He got into SEO by helping him mom create a blog and then writing some content and making money with Google AdSense. He did some development in school, did some art in school and then got a jobs working in marketing and doing SEO and content for these companies. He also did a lot of development work at those companies. He wanted to do more SEO and he found Mike King and he clicked with Mike, Mike hired him to work on more intense SEO at his firm. We then dug a bit into the search graph, knowledge panels, entities and more. He said he learned about this by digging into white papers on the topic of how search engines work. He first started with PageRank’s algorithm and he said you can use Python to help you visualize these algorithms. Colt got pretty technical with the conversation, talking about Eigenvector centrality. In graph theory, eigenvector centrality is a measure of the influence of a node in a network. Relative scores are assigned to all nodes in the network based on the concept that connections to high-scoring nodes contribute more to the score of the node in question than equal connections to low-scoring nodes. He does this to better visualize the algorithms. He gave some examples of how the knowledge graph works with a bicycle. We then spoke a bit about knowledge panels, which you might find as fun as talking about bikes. More next week but you can learn more about Colt Sliva @SignorColt.