A question from someone who's been out of SEO for a while..
I built 100-200 backlinks on a 2 week old site and popped in ranked at around 40.
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What does that say about the keyword difficulty? How does a top 3 spot look?
It's been a while since I've done this and I can't remember how the google dance goes.
Just want to know if this page is worth investing in further.
My advice would be never to shoot 100 - 200 backlinks at a two-week-old site. Looks unnatural and you will not see that site again once it disappears into the abyss. Focus on your content. I just ranked a zero backlinked post in a 14100/month search that is climbing steadily. Now sitting at 11. It danced around a bit on page 3 and 4 and is starting to settle. It was a post about the top 50 hottest ---------- post as the other ranking posts were top 20 at most. Easy win :)
Keyword difficulty is RELATIVE. It depends on your niche and competition level
You're definitely on the right track but I'm afraid that given your unnatural link BOMB DROP, you might get stuck in the 20 to 40 range.
I suggest you not only use a more natural footprint but also EARN some high quality backlinks besides building the bulk of your link network
Oh yeah thanks, that jogs my memory. You can’t just mash your way up. I forget how I used to do this... damn I think I would bookmark first, build links in dozens instead of hundreds until about 3 months in then hammer it with 100 a week or so. Does that work in 2020/19?
You're better off acquring 5 high quality links a month than 200 shit links a week.
Google is the type of "partner" that conducts security opposition research on their leading distribution partner, while conveniently ignoring nearly a billion OTHER Android phones with existing security issues that Google can't be bothered with patching.
Deliberately screwing direct business partners is far worse than coding algorithms which belligerently penalize some competing services all the while ignoring that the payday loan shop funded by Google leverages doorway pages.
BackChannel recently published an article foaming at the mouth promoting the excitement of Google's AI:
This 2020-to-2020 Transition is going to move us from systems that are explicitly taught to ones that implicitly learn." ... the engineers might make up a rule to test against—for instance, that “usual” might mean a place within a 10-minute drive that you visited three times in the last six months. “It almost doesn’t matter what it is?—?just make up some rule,” says Huffman. “The machine learning starts after that.
Of course, there's a patent for that. In Modifying search result ranking based on implicit user feedback they state:
user reactions to particular search results or search result lists may be gauged, so that results on which users often click will receive a higher ranking. The general assumption under such an approach is that searching users are often the best judges of relevance, so that if they select a particular search result, it is likely to be relevant, or at least more relevant than the presented alternatives.
If you are a known brand you are more likely to get clicked on than a random unknown entity in the same market.
And if you are something people are specifically seeking out, they are likely to stay on your website for an extended period of time.
One aspect of the subject matter described in this specification can be embodied in a computer-implemented method that includes determining a measure of relevance for a document result within a context of a search query for which the document result is returned, the determining being based on a first number in relation to a second number, the first number corresponding to longer views of the document result, and the second number corresponding to at least shorter views of the document result; and outputting the measure of relevance to a ranking engine for ranking of search results, including the document result, for a new search corresponding to the search query. The first number can include a number of the longer views of the document result, the second number can include a total number of views of the document result, and the determining can include dividing the number of longer views by the total number of views.
Attempts to manipulate such data may not work.
safeguards against spammers (users who generate fraudulent clicks in an attempt to boost certain search results) can be taken to help ensure that the user selection data is meaningful, even when very little data is available for a given (rare) query. These safeguards can include employing a user model that describes how a user should behave over time, and if a user doesn't conform to this model, their click data can be disregarded. The safeguards can be designed to accomplish two main objectives: (1) ensure democracy in the votes (e.g., one single vote per cookie and/or IP for a given query-URL pair), and (2) entirely remove the information coming from cookies or IP addresses that do not look natural in their browsing behavior (e.g., abnormal distribution of click positions, click durations, clicks_per_minute/hour/day, etc.). Suspicious clicks can be removed, and the click signals for queries that appear to be spmed need not be used (e.g., queries for which the clicks feature a distribution of user agents, cookie ages, etc. that do not look normal).
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