Recommended domain auctions, where you can buy good dropped domains
1) https://www.dropcatch.com/
2) https://auctions.godaddy.com/
3) https://www.namecheap.com/market/

For specific GEOs, it makes sense to pay attention to local domain auctions, for example for Polish market I personally recommend https://www.aftermarket.pl/.

This is how the statistics of earnings on Gambling affiliate with Revenue Share model may look when attracting players who spend good amount of money. Since the launch of the site - 4 months.

A checklist for backlink analysis of the dropped domain before you buy/participate in an auction:

Link analysis is best done with ahrefs (ahrefs has the most active robot, so the link database is the most complete and up-to-date).
1) Check both the quality of referring sites (in terms of their organic visibility and the strength of their link profile (DR)), and the relevance of their niches.
2) Analyze the profile for the anchors from the grey areas (viagra, adult, gambling, etc.) and anchors in other languages (there are exceptions, when the dropped domain was a serious international company, or the dropped domain is selected for a specific language GEO).
3) Analyze the way links are placed - the links should be mostly contextual, leading from good publications. If we see links from comments, from the profiles of forums - just avoid this domain. Links from directories (directories of sites) may be present if the dropped domain is owned by a company, but they should not be the majority.
4) On the tab "Overview" look for suspicious bursts of links in the past (this can be a signal of SEO spam by bad SEOs or hackers who hacked the website).

Important: do not be lazy to check the links manually. After the initial analysis, I always recommend taking a few hours to go to the sources of links, check their quality, not only by SEO metrics, but also from a user perspective. A good signal is when donor publications themselves have organic visibility for relevant keywords. Such links are the most effective. Remember that buying a dropped domain is always risky, even if the backlinks profile is "clean", there can always be other factors that will nullify its trust. Therefore, investing time in a thorough analysis makes a financial investment in buying a dropped domain less risky.

As a follow-up to the previous post about brand mentions. Google first claimed to consider brand/site mentions (implied links) more than 8 years ago in patent US8682892B1 Of course, there had been work in this direction long before that. At that time, there was not yet such a clearly working system with knowledge graphs, and in general it is more difficult to accurately determine the association of a mention with a particular company/site than by a conventional <a href"'>link leading to a particular URL (which is a unique identifier). This brings to mind the principle of off-site signaling for Google My Business profiles via Citations, where initially "linking" was by three key parameters known as NAP (Name, Address, Phone). That is, Google could quite accurately associate the presence of a company listing in a directory with a GMB profile if they had the same business name, address and phone number. That's why NAP is important (so that all listings have the same name, address and phone number).

Now that more and more data and links are available in the Knowledge Graph, also due to the active use of Schema markup by companies, I assume that for companies that are represented in the Knowledge Graph, the conditional "weight" or "impact" of mentions can be significantly higher.

As a follow-up to the previous post about brand mentions. Google first claimed to consider brand/site mentions (implied links) more than 8 years ago in patent US8682892B1 Of course, there had been work in this direction long before that. At that time, there was not yet such a clearly working system with knowledge graphs, and in general it is more difficult to accurately determine the association of a mention with a particular company/site than by the usual <a href"'>link leading to a particular URL (which is a unique identifier). This brings to mind the principle of off-site signaling for Google My Business profiles via Citations, where initially "linking" was by three key parameters known as NAP (Name, Address, Phone). That is, Google could quite accurately associate the presence of a company listing in a directory with a GMB profile if they had the same business name, address and phone number. That's why the NAP is important (so that all listings have the same name, address and phone number).

Now that more and more data and links are available in the Knowledge Graph, also due to the active use of micro-labeling by companies, I assume that for companies that are represented in the Knowledge Graph, the conditional "weight" or "impact" of mentions can be much higher.

I have repeatedly mentioned in my posts that by uniqueness of content, I mean not so much the technical uniqueness of the text (when no repetitions are found by exact occurrence). But more about uniqueness in terms of the information itself. We are now in an environment where Google algorithms, instead of focusing on "keywords", focus on the concepts and entities, their properties and relations, and determine the context vectors and context hierarchy, quite accurately "picking out" the facts from the content. That is why I believe that the uniqueness of content in the current reality should be understood as the unique value that this or that content brings to the web.

Did you know that most of the links offered by various vendors and "guest post" providers do not work at all? And site metrics don't play a role here. Instead of the "negative" link juice, which could potentially be used to attack your competitors, Google simply disables the transfer in general link juice for sites that are under suspicion. So leaking thousands of dollars "for nothing" is more than a common problem.