Head keywords. Long-tail keywords. The chunky middle. The chonky thorax. Is it any wonder why most people outside of SEO think we’re talking gibberish? Ask a dozen SEOs what keywords qualify as “long-tail” and you’ll get 13 opinions and 17 fistfights.
What we can agree on is that — due to Google’s advancements in Natural Language Processing (NLP) — the long tail of search has exploded. However, I will argue that NLP has also imploded the long tail, and understanding how and why may save our collective sanity.
What is the long tail of SEO, exactly?
The long tail of search is the limitless space of low-volume (and often low-competition) keywords. Tactically, long-tail SEO centers on competing for a large number of low-volume keywords[1] instead of focusing on a small set of high-volume keywords.
Long-tail SEO encourages us to let go of vanity[2], because high-volume, so-called “vanity” keywords are often out of reach or, at best, will empty our bank accounts. Low-volume keywords may be less attractive on the surface, but as you begin to compete on hundreds or thousands of them, they represent more traffic and ultimately more sales than a few vanity keywords.
You’ve probably seen a graph of the long tail like the one above. It’s a perfectly lovely power curve, but it’s purely hypothetical. And while you may smile and nod when you see it, it’s hard to translate this into a world of keywords. It might help to re-imagine the long tail of SEO:
I’m not sure the “reclining snowman of SEO” is ever going to catch on, but I think it helps to illustrate that — while head keywords are high-volume by themselves — the combined volume of the long tail eclipses the head or the middle. Like