SEO
You Can’t Compare Backlink Counts in SEO Tools: Here’s Why
Google knows about 300T pages on the web. It’s doubtful they crawl all of those, and at least according to some documents from their antitrust trial we learned they only indexed 400B. That’s around .133% of the pages they know about, roughly 1 out of every 752 pages.
For Ahrefs, we choose to store about 340B pages in our index as of December 2023.
At a certain point, the quality of the web becomes bad. There are lots of spam and junk pages that just add noise to the data without adding any value to the index.
Large parts of the web are also duplicate content, ~60% according to Google’s Gary Illyes. Most of this is technical duplication caused by different systems. However, if you don’t account for this duplication, it can waste more resources and create more noise in the data.
When building an index of the web, companies have to make many choices around crawling, parsing, and indexing data. While there’s going to be a lot of overlap between indexes, there’s also going to be some differences depending on each company’s decisions.
Comparing link indexes is hard because of all the different choices the various tools have made. I try my best to make some comparisons more fair, but even for a few sites I’m telling you that I don’t want to put in all of the work needed to make an accurate comparison, much less do it for an entire study. You’ll see why I say this later when you read what it would take to compare the data accurately.
However, I did run some tests on a sample of sites and I’ll show you how to check the data yourself. I also pulled some fairly large 3rd party data samples for some additional validation.
Let’s dive in.
If you just looked at dashboard numbers for links and RDs in different tools you might see completely different things.
For example, here’s what we count in Ahrefs:
- Live links
- Live RDs
- 6 months of data
In Semrush, here’s what they count:
- Live + dead links
- Live + dead RDs
- 6 months of data + a bit more*
*By a bit more, what I mean is that their data goes back 6 months and to the start of the previous month. So, for instance, if it’s the 15th of the month, they would actually have about 6.5 months of data instead of 6 months of data. If it’s the last week of the month, they may have close to 7 months of data instead of 6.
This may not seem like a lot, but it can increase the numbers shown by a lot, especially when you’re still counting dead links and dead RDs.
I don’t think SEOs want to see a number that includes dead links. I don’t see a good reason to count them, either, other than to have bigger and potentially misleading numbers.
I only say this because I’ve called Semrush out on making this type of biased comparison before on Twitter, but I stopped arguing when I realized that they really didn’t want the comparison to be fair; they just wanted to win the comparison.
There are some ways you can compare the data to get somewhat similar time periods and only look at active links.
If you filter the Semrush backlinks report for “Active” links, you’ll have a somewhat more accurate number to compare against the Ahrefs dashboard number.
Alternatively, if you use the “Show history: Last 6 months” option in the Ahrefs backlink report, this would include lost links and be a fairer comparison to Semrush’s dashboard number.
Here’s an example of how to get more similar data:
- Semrush Dashboard: 5.1K = Ahrefs (6-month date comparison): 5.6K
- Semrush All Links: 5.1K = Ahrefs (6-month date comparison): 5.6K
- Semrush Active Links: 2.9K = Ahrefs Dashboard: 3.5K = Ahrefs (no date comparison): 3.5K
What you should not compare is Semrush Dashboard and Ahrefs Dashboard numbers. The number in Semrush (5.1K) includes dead links. The number in Ahrefs (3.5K) doesn’t; it’s only live links!
Note that the time periods may not be exactly the same as mentioned before because of the extra days in the Semrush data. You could look at what day their data stops and select that exact day in the Ahrefs data to get an even more accurate, but still not quite accurate comparison.
I don’t think the comparison works at all with larger domains because of an issue in Semrush. Here’s what I saw for semrush.com:
- Semrush Dashboard: 48.7M = Ahrefs (6 month date comparison): 24.7M
- Semrush All Links: 48.7M = Ahrefs (6 month date comparison): 24.7M
- Semrush Active Links: 1.8M = Ahrefs Dashboard: 15.9M = Ahrefs (no date comparison): 15.9M
So that’s 1.8M active links in Semrush vs 15.9M active in Ahrefs. But as I said, I don’t think this is a fair comparison. Semrush seems to have an issue with larger sites. There is a warning in Semrush that says, “Due to the size of the analyzed domain, only the most relevant links will be shown.” It’s possible they’re not showing all the links, but this is suspicious because they will show the total for all links which is a larger number, and I can filter those in other ways.
I can also sort normally by the oldest last seen date and see all the links, but when I do last seen + active, I see only 608K links. I can’t get more than 50k rows in their system to investigate this further, but something is fishy here.
More link differences
The above comparison wouldn’t be enough to make an accurate comparison. There are still a number of differences and problems that make any sort of comparison troublesome.
This tweet is as relevant as the day I wrote it:
It’s almost impossible to do a fair link comparison
Here’s how we count links, but it’s worth mentioning that each tool counts links in different ways.
To recap some of the main points, here are some things we do:
- We store some links inserted with JavaScript, no one else does this. We render ~250M pages a day.
- We have a canonicalization system in place that others may not, which means we shouldn’t count as many duplicates as others do.
- Our crawler tries to be intelligent about what to prioritize for crawling to avoid spam and things like infinite crawl paths.
- We count one link per page, others may count multiple links per page.
These differences make a fair link comparison nearly impossible to do.
How to see where the biggest link differences are
The easiest way to see the biggest discrepancies in link totals is to go to the Referring Domains reports in the tools and sort by the number of links. You can use the dropdowns to see what kinds of issues each index may have with overcounting some links. In many cases, you’re likely to see millions of links from the same site for some of the reasons mentioned above.
For example, when I looked in Semrush I found blogspot links that they claimed to have recently checked, but these are showing 404 when I visit them. Semrush still counts them for some reason. I saw this issue on multiple domains I checked. This is one of those pages:
Lots of links counted as live are actually dead
Seeing the dead link above counted in the total made me want to check how many dead links were in each index. I ran crawls on the list of the most recent live links in each tool to see how many were actually still live.
For Semrush, 49.6% of the links they said were live were actually dead. Some churn is expected as the web changes, but half the links in 6 months indicates that a lot of these may be on the spammier part of the web that isn’t as stable or they’re not re-crawling the links often. For some context, the same number for Ahrefs came back as 17.2% dead.
It’s going to get more complicated to compare these numbers
Ahrefs recently added a filter for “Best links” which you can configure to filter out noise. For instance, if you want to remove all blogspot.com blogs from the report, you can add a filter for it.
This means you’ll only see links you consider important in the reports. This can also be applied to the main dashboard numbers and charts now. If the filter is active, people will see different numbers depending on their settings.
You would think this is straightforward, but it’s not.
Solving for all the issues is a lot of work
There are a lot of different things you’d have to solve for here:
- The extra days in Semrush’s data that you’ll have to remove or add to the Ahrefs number.
- Remember that Semrush also includes dead RDs in their dashboard numbers. So you need to filter their RD report to just “Active” to get the live ones.
- Remember that half the links in the test of Semrush live data were actually dead, so I would suspect that a number of the RDs are actually lost as well. You could possibly look for domains with low link counts and just crawl the listed links from those to remove most of the dead ones.
- After all that, you’re still going to need to strip the domains down to the root domain only to account for the differences in what each tool may be counting as a domain.
What is a domain?
Ahrefs currently shows 206.3M RDs in our database and Semrush shows 1.6B. Domains are being counted in extremely different ways between the tools.
According to the major sources who look at these kinds of things, the number of domains on the internet seems to be between 269M–359M and the number of websites between 1.1B–1.5B, with 191M–200M of them being active.
Semrush’s number of RDs is higher than the number of domains that exist.
I believe Semrush may be confusing different terms. Their numbers match fairly closely with the number of websites on the internet, but that’s not the same as the number of domains. Plus, many of those websites aren’t even live.
It’s going to get more complicated to compare these numbers
Part of our process is dropping spam domains, and we also treat some subdomains as different domains. We come up close to the numbers from other 3rd party studies for the number of active websites and domains, whereas Semrush seems to come in closer to the total number of websites (including inactive ones).
We’re going to simplify our methodology soon so that one domain is actually just one domain. This is going to make our RD numbers go down, but be more accurate to what people actually consider a domain. It’s also going to make for an even bigger disparity in the numbers between the tools.
I ran some quality checks for both the first-seen and last-seen link data. On every site I checked, Ahrefs picked up more links first and on most Ahrefs updated the links more recently than Semrush. Don’t just believe me, though; check for yourself.
Comparing this is biased no matter how you look at it because our data is more granular and includes the hours and minutes instead of just the day. Leaving the hours and minutes creates a biased comparison, and so does removing it. You’ll have to match the URLs and check which date is first or if there is a tie and then count the totals. There will be some different links in each dataset, so you’ll need to do the lookups on each set of data for comparison.
Semrush claims, “We update the backlinks data in the interface every 15 minutes.”
Ahrefs claims, “The world’s largest index of live backlinks, updated with fresh data every 15–30 minutes.”
I pulled data at the same time from both tools to see when the latest links for some popular websites were found. Here’s a summary table:
Domain | Ahrefs Latest | Semrush latest |
---|---|---|
semrush.com | 3 minutes ago | 7 days ago |
ahrefs.com | 2 minutes ago | 5 days ago |
hubspot.com | 0 minutes ago | 9 days ago |
foxnews.com | 1 minute ago | 12 days ago |
cnn.com | 0 minutes ago | 13 days ago |
amazon.com | 0 minutes ago | 6 days ago |
That doesn’t seem fresh at all. Their 15-minute update claim seems pretty dubious to me with so many websites not having updates for many days.
In fairness, for some smaller sites it was more mixed on who showed fresher data. I think they may have some issues with the processing of larger sites.
Don’t just trust me, though; I encourage you to check some websites yourself. Go into the backlinks reports in both tools and sort by last seen. Be sure to share your results on social media.
Ahrefs now receives data from IndexNow
This will make our data even fresher. That’s ~2.5B URLs / day in March 2024. The websites tell us about new pages, deleted pages, or any changes they make so that we can go crawl them and update the data. Read more here.
Ahrefs crawls 7B+ pages every day. Semrush claims they crawl 25B pages per day. This would be ~3.5x what Ahrefs crawls per day. The problem is that I can’t find any evidence that they crawl that fast.
We saw that around half the links that Semrush had marked as active were actually dead compared to about 17% in Ahrefs, which indicated to me that they may not re-crawl links as often. That and the freshness test both pointed to them crawling slower. I decided to look into it.
Logs of my sites
I checked the logs of some of my sites and sites I have access to, and I didn’t see anything to support the claim that Semrush crawls faster. If you have access to logs of your own site, you should be able to check which bots are crawling the fastest.
80,000 months of log data
I was curious and wanted to look at bigger samples. I used Web Explorer and a few different footprints (patterns) to find log file summaries produced by AWStats and Webalizer. These are often published on the web.
I scraped and parsed ~80,000 log file summaries that contained 1 month of data each and were generated in the last couple of years. This sample contained over 9k websites in total.
I did not see evidence of Semrush crawling many times faster than Ahrefs for these sites, as they claim they do. The only bot that was crawling much faster than Ahrefsbot in this dataset was Googlebot. Even other search engines were behind our crawl rate.
That’s just data from a small-ish number of sites compared to the scale of the web. What about for a larger chunk of the web?
Data from 20%+ of web traffic
At the time of writing, Cloudflare Radar has Ahrefsbot as the #7 most active bot on the web and Semrushbot at #40.
While this isn’t a complete picture of the web, it’s a fairly large chunk. In 2021, Cloudflare was said to manage ~20% of the web’s traffic, up from ~10% in 2018. It’s likely much higher now with that kind of growth. I couldn’t find the numbers from 2021, but in early 2022 they were handling 32 million HTTP requests / second on average and in early 2023 they had already grown to handling 45 million HTTP requests / second on average, over 40% more in one year!
Additionally, ~80% of websites that use a CDN use Cloudflare. They handle many of the larger sites on the web; BuiltWith shows that Cloudflare is used by ~32% of the Top 1M websites. That’s a significant sample size and likely the largest sample that exists.
How much do SEO tools crawl?
Some of the SEO tools share the number of pages they crawl on their websites. The only one in the chart below that doesn’t have a publicly published crawl rate is AhrefsSiteAudit bot, but I asked our team to pull the info for this. Let me put the rankings in perspective with actual and claimed crawl rates.
Ranking | Bot | Crawl Rate |
---|---|---|
7 | Ahrefsbot | 7B+ / day |
27 | DataForSEO Bot | 2B / day |
29 | AhrefsSiteAudit | 600M – 700M / day |
35 | Botify | 143.3M / day |
40 | Semrushbot | 25B / day* claimed |
The math isn’t mathing. How can Semrush claim they’re crawling multiple times as fast as these others, but their ranking is lower? Cloudflare doesn’t cover the entire web, but it’s a large chunk of the web and a more than representative sample size.
When they originally made this 25B claim, I believe they were closer to 90th on Cloudflare Radar, near the bottom of the list at the time. Semrush hasn’t updated this number since then, and I recall a period of time where they were in the 60s-70s on Cloudflare Radar as well. They do seem to be getting faster, but their claimed numbers still don’t add up.
I don’t hear SEOs raving about Moz or Sistrix having the best link data, but they are 21st and 36th on the list respectively. Both are higher than Semrush.
Possible explanations of differences
Semrush may be conflating the term pages with links, which is actually mentioned in some of their documentation. I don’t want to link to it, but you can find it with this quote: “Daily, our bot crawls over 25 billion links”. But links are not the same thing as pages and there can be hundreds of links on a single page.
It’s also possible they’re crawling a portion of the web that’s just more spammy and isn’t reflected in the data from either of the sources I looked at. Some of the numbers indicate this may be the case.
Y’all shouldn’t trust studies done by a specific vendor when it compares them to others, even this one. I try to be as fair as I can be and follow the data, but since I work at Ahrefs you can hardly consider me unbiased. Go look at the data yourselves and run your own tests.
There are some folks in the SEO community who try to do these tests every once in a while. The last major 3rd party study was run by Matthew Woodward, who initially declared Semrush the winner, but the conclusion was changed and Ahrefs was ultimately declared to be the rightful winner. What happened?
The methodology chosen for the study heavily favored Semrush and was investigated by a friend of mine, Russ Jones, may he rest in peace. Here’s what Russ had to say about it:
While services like Majestic and Ahrefs likely store a single canonical IP address per domain, SEMRush seems to store per link, which accounts for why there would be more IPs that referring domains in some cases. I do not think SEMRush is intentionally inflating their numbers, I think they are storing the data in a different way than competitors which results in a number that is higher and potentially misleading, but not due to ill intent.
The response from Matthew indicated that Semrush might have misled him in their favor. Here’s that comment:
In the end, Ahrefs won.
Check our current stats on our big data page.
While Semrush doesn’t provide current hardware stats, they did provide some in the past when they made changes to their link index.
In June 2019, they made an announcement that claimed they had the biggest index. The test from Matthew Woodward that I talked about happened after this test, and as you saw, Ahrefs won that.
In June 2021, they made another announcement about their link index that claimed they were the biggest, fastest, and best.
These are some stats they released at the time:
- 500 servers
- 16,128 cpu cores
- 245 TB of memory
- 13.9 PB of storage
- 25B+ pages / day
- 43.8T links
The release said they increased storage, but their previous release said they had 4000 PBs of storage. They said the storage was 4x, so I guess the previous number was supposed to be 4000 TBs and not 4000 PBs, and they just got mixed up on the terminology.
I checked our numbers at the time, and this is how we matched up:
- 2400 servers (~5x greater)
- 200,000 cpu cores (~12.5x greater)
- 900 TB of memory (~4x greater)
- 120 PB of storage (~9x greater)
- 7B pages / day (~3.5x less???)
- 2.8T live links (I’m not sure the total size, but to this day it’s not as big as the number they claimed)
They were claiming more links and faster crawling with much less storage and hardware. Granted, we don’t know the details of the hardware, but we don’t run on dated tech.
They claimed to store more links than we have even now and in less space than we add to our system each month. It really doesn’t make sense.
Final thoughts
Don’t blindly trust the numbers on the dashboards or the general numbers because they may represent completely different things. While there’s no perfect way to compare the data between different tools, you can run many of the checks I showed to try to compare similar things and clean up the data. If something looks off, ask the tool vendors for an explanation.
If there ever comes a time when we stop winning on things like tech and crawl speed, go ahead and switch to another tool and stop paying us. But until that time, I’d be highly skeptical of any claims by other tools.
If you have questions, message me on X.
SEO
8% Of Automattic Employees Choose To Resign
WordPress co-founder and Automattic CEO announced today that he offered Automattic employees the chance to resign with a severance pay and a total of 8.4 percent. Mullenweg offered $30,000 or six months of salary, whichever one is higher, with a total of 159 people taking his offer.
Reactions Of Automattic Employees
Given the recent controversies created by Mullenweg, one might be tempted to view the walkout as a vote of no-confidence in Mullenweg. But that would be a mistake because some of the employees announcing their resignations either praised Mullenweg or simply announced their resignation while many others tweeted how happy they are to stay at Automattic.
One former employee tweeted that he was sad about recent developments but also praised Mullenweg and Automattic as an employer.
He shared:
“Today was my last day at Automattic. I spent the last 2 years building large scale ML and generative AI infra and products, and a lot of time on robotics at night and on weekends.
I’m going to spend the next month taking a break, getting married, and visiting family in Australia.
I have some really fun ideas of things to build that I’ve been storing up for a while. Now I get to build them. Get in touch if you’d like to build AI products together.”
Another former employee, Naoko Takano, is a 14 year employee, an organizer of WordCamp conferences in Asia, a full-time WordPress contributor and Open Source Project Manager at Automattic announced on X (formerly Twitter) that today was her last day at Automattic with no additional comment.
She tweeted:
“Today was my last day at Automattic.
I’m actively exploring new career opportunities. If you know of any positions that align with my skills and experience!”
Naoko’s role at at WordPress was working with the global WordPress community to improve contributor experiences through the Five for the Future and Mentorship programs. Five for the Future is an important WordPress program that encourages organizations to donate 5% of their resources back into WordPress. Five for the Future is one of the issues Mullenweg had against WP Engine, asserting that they didn’t donate enough back into the community.
Mullenweg himself was bittersweet to see those employees go, writing in a blog post:
“It was an emotional roller coaster of a week. The day you hire someone you aren’t expecting them to resign or be fired, you’re hoping for a long and mutually beneficial relationship. Every resignation stings a bit.
However now, I feel much lighter. I’m grateful and thankful for all the people who took the offer, and even more excited to work with those who turned down $126M to stay. As the kids say, LFG!”
Read the entire announcement on Mullenweg’s blog:
Featured Image by Shutterstock/sdx15
SEO
YouTube Extends Shorts To 3 Minutes, Adds New Features
YouTube expands Shorts to 3 minutes, adds templates, AI tools, and the option to show fewer Shorts on the homepage.
- YouTube Shorts will allow 3-minute videos.
- New features include templates, enhanced remixing, and AI-generated video backgrounds.
- YouTube is adding a Shorts trends page and comment previews.
SEO
How To Stop Filter Results From Eating Crawl Budget
Today’s Ask An SEO question comes from Michal in Bratislava, who asks:
“I have a client who has a website with filters based on a map locations. When the visitor makes a move on the map, a new URL with filters is created. They are not in the sitemap. However, there are over 700,000 URLs in the Search Console (not indexed) and eating crawl budget.
What would be the best way to get rid of these URLs? My idea is keep the base location ‘index, follow’ and newly created URLs of surrounded area with filters switch to ‘noindex, no follow’. Also mark surrounded areas with canonicals to the base location + disavow the unwanted links.”
Great question, Michal, and good news! The answer is an easy one to implement.
First, let’s look at what you’re trying and apply it to other situations like ecommerce and publishers. This way, more people can benefit. Then, go into your strategies above and end with the solution.
What Crawl Budget Is And How Parameters Are Created That Waste It
If you’re not sure what Michal is referring to with crawl budget, this is a term some SEO pros use to explain that Google and other search engines will only crawl so many pages on your website before it stops.
If your crawl budget is used on low-value, thin, or non-indexable pages, your good pages and new pages may not be found in a crawl.
If they’re not found, they may not get indexed or refreshed. If they’re not indexed, they cannot bring you SEO traffic.
This is why optimizing a crawl budget for efficiency is important.
Michal shared an example of how “thin” URLs from an SEO point of view are created as customers use filters.
The experience for the user is value-adding, but from an SEO standpoint, a location-based page would be better. This applies to ecommerce and publishers, too.
Ecommerce stores will have searches for colors like red or green and products like t-shirts and potato chips.
These create URLs with parameters just like a filter search for locations. They could also be created by using filters for size, gender, color, price, variation, compatibility, etc. in the shopping process.
The filtered results help the end user but compete directly with the collection page, and the collection would be the “non-thin” version.
Publishers have the same. Someone might be on SEJ looking for SEO or PPC in the search box and get a filtered result. The filtered result will have articles, but the category of the publication is likely the best result for a search engine.
These filtered results can be indexed because they get shared on social media or someone adds them as a comment on a blog or forum, creating a crawlable backlink. It might also be an employee in customer service responded to a question on the company blog or any other number of ways.
The goal now is to make sure search engines don’t spend time crawling the “thin” versions so you can get the most from your crawl budget.
The Difference Between Indexing And Crawling
There’s one more thing to learn before we go into the proposed ideas and solutions – the difference between indexing and crawling.
- Crawling is the discovery of new pages within a website.
- Indexing is adding the pages that are worthy of showing to a person using the search engine to the database of pages.
Pages can get crawled but not indexed. Indexed pages have likely been crawled and will likely get crawled again to look for updates and server responses.
But not all indexed pages will bring in traffic or hit the first page because they may not be the best possible answer for queries being searched.
Now, let’s go into making efficient use of crawl budgets for these types of solutions.
Using Meta Robots Or X Robots
The first solution Michal pointed out was an “index,follow” directive. This tells a search engine to index the page and follow the links on it. This is a good idea, but only if the filtered result is the ideal experience.
From what I can see, this would not be the case, so I would recommend making it “noindex,follow.”
Noindex would say, “This is not an official page, but hey, keep crawling my site, you’ll find good pages in here.”
And if you have your main menu and navigational internal links done correctly, the spider will hopefully keep crawling them.
Canonicals To Solve Wasted Crawl Budget
Canonical links are used to help search engines know what the official page to index is.
If a product exists in three categories on three separate URLs, only one should be “the official” version, so the two duplicates should have a canonical pointing to the official version. The official one should have a canonical link that points to itself. This applies to the filtered locations.
If the location search would result in multiple city or neighborhood pages, the result would likely be a duplicate of the official one you have in your sitemap.
Have the filtered results point a canonical back to the main page of filtering instead of being self-referencing if the content on the page stays the same as the original category.
If the content pulls in your localized page with the same locations, point the canonical to that page instead.
In most cases, the filtered version inherits the page you searched or filtered from, so that is where the canonical should point to.
If you do both noindex and have a self-referencing canonical, which is overkill, it becomes a conflicting signal.
The same applies to when someone searches for a product by name on your website. The search result may compete with the actual product or service page.
With this solution, you’re telling the spider not to index this page because it isn’t worth indexing, but it is also the official version. It doesn’t make sense to do this.
Instead, use a canonical link, as I mentioned above, or noindex the result and point the canonical to the official version.
Disavow To Increase Crawl Efficiency
Disavowing doesn’t have anything to do with crawl efficiency unless the search engine spiders are finding your “thin” pages through spammy backlinks.
The disavow tool from Google is a way to say, “Hey, these backlinks are spammy, and we don’t want them to hurt us. Please don’t count them towards our site’s authority.”
In most cases, it doesn’t matter, as Google is good at detecting spammy links and ignoring them.
You do not want to add your own site and your own URLs to the disavow tool. You’re telling Google your own site is spammy and not worth anything.
Plus, submitting backlinks to disavow won’t prevent a spider from seeing what you want and do not want to be crawled, as it is only for saying a link from another site is spammy.
Disavowing won’t help with crawl efficiency or saving crawl budget.
How To Make Crawl Budgets More Efficient
The answer is robots.txt. This is how you tell specific search engines and spiders what to crawl.
You can include the folders you want them to crawl by marketing them as “allow,” and you can say “disallow” on filtered results by disallowing the “?” or “&” symbol or whichever you use.
If some of those parameters should be crawled, add the main word like “?filter=location” or a specific parameter.
Robots.txt is how you define crawl paths and work on crawl efficiency. Once you’ve optimized that, look at your internal links. A link from one page on your site to another.
These help spiders find your most important pages while learning what each is about.
Internal links include:
- Breadcrumbs.
- Menu navigation.
- Links within content to other pages.
- Sub-category menus.
- Footer links.
You can also use a sitemap if you have a large site, and the spiders are not finding the pages you want with priority.
I hope this helps answer your question. It is one I get a lot – you’re not the only one stuck in that situation.
More resources:
Featured Image: Paulo Bobita/Search Engine Journal
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