Posted by randfish
Today I’m going to make a crazy claim—that in SEO today, there are times, situations, and types of analyses where correlation is actually MORE interesting and useful than causality. I know that sounds insane, but stick with me until the end and at least give the argument a chance. And for those of you who like visuals, our friend AJ Ghergich and his intrepid team of designers created some nifty graphics to accompany the piece.
Once upon a time, SEO professionals had a reasonable sense of many (or perhaps even most) of the inputs into the search engine’s ranking systems. We leveraged our knowledge of how Google interpreted various modifications to keywords, links, content, and technical aspects to hammer on the signals that produced results.
But today, there can be little argument—Google’s ranking algorithm has become so incredibly complex, nuanced, powerful, and full-featured, that modern SEOs have all but given up on hammering away at individual signals. Instead, we’re becoming more complete marketers, with greater influence on all of the elements of our organizations’ online presence.
Web marketers operate in a world where Google:
- Uses machine learning to identify editorial endorsements vs. spam (e.g. Penguin)
- Measures and rewards engagement (e.g. pogo-sticking)
- Rewards signals that correlate with brands (and attempts to remove/punish non-brand entities)
- Applies thousands of immensely powerful and surprisingly accurate ways to analyze content (e.g. Hummingbird)
- Punishes sites that produce mediocre content (intentionally or accidentally) even if the site has good content, too (e.g. Panda)
- Rapidly recognizes and accounts for patterns of queries and clicks as rank boosting signals (e.g. this recent test)
- Makes 600+ algorithmic updates each year, the vast majority of which are neither announced nor known by the marketing/SEO community
Given this frenetic ecosystem, the best path forward isn’t to exclusively build …read more