Watch: “This Is For The Juggalos & Juggalettes” – Being The Elite Ep. 185
January 6, 2020This week All Elite Wrestling is back with the latest edition of Being The Elite.
In this week’s episode they showed off the Jacksonville Jaguar’s stadium. They celebrated the New Year, teased a mixed tag team match and more.
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Thanks for the transparency. It’s refreshing to see a strategy that doesn’t rely on black-hat churn and burn. Sustainable growth is the only way forward.
Spot on about the indexing delays. It’s not just about building the link anymore; it’s about the “stickiness” of the placement. We’ve been focusing heavily on that metric lately.
Finally, someone said it. The old school “blast and pray” method is dead. Precision and camouflage are the new standard.
I’m skeptical about the timeline you proposed, but I’m willing to test it. If this holds up, it changes how we structure our entire outreach program.
I’m skeptical about the timeline you proposed, but I’m willing to test it. If this holds up, it changes how we structure our entire outreach program.
We’ve been A/B testing this exact hypothesis. Group A (your method) is outperforming Group B by 40% in terms of ranking stability. The data speaks for itself.
This complements the “Entropy” theory perfectly. If you don’t introduce randomness, you’re just painting a target on your back. Glad to see others advocating for smarter engineering.
I’d argue that the content relevance is even more critical now. We’ve seen perfectly good links get devalued just because the semantic match wasn’t tight enough.
Great resource. I’ve sent this to a few colleagues who are still stuck in 2015-era SEO tactics. Hopefully, this wakes them up.
Actually, I have to disagree slightly with the second point. In our testing, we found that over-optimization was less of a factor than pure engagement metrics. It’s interesting to see how different niches react differently.
The shift towards “entity-based” indexing is real. Your strategy seems to leverage that by building entity associations rather than just keyword matches. Smart.
This complements the “Entropy” theory perfectly. If you don’t introduce randomness, you’re just painting a target on your back. Glad to see others advocating for smarter engineering.
Just wanted to say thanks for the detailed case study. It’s rare to see actual data backing up these claims. We’ll be adjusting our Q4 roadmap based on some of these insights.
Question: Have you tested this approach with expired domains? We’re running some experiments now and the results are… mixed. Your methodology seems safer.
Great read. It reminds me of the strategy we deployed last quarter. The focus on foundational stability really pays off when the algorithm shifts. Thanks for compiling this.
This is exactly why we moved away from automated PBNs. The risk/reward ratio just doesn’t make sense anymore compared to what you’re describing.
I’m sharing this with our content team. We’ve been struggling to explain why “quality over quantity” isn’t just a cliché, and this illustrates it perfectly.
I’m skeptical about the timeline you proposed, but I’m willing to test it. If this holds up, it changes how we structure our entire outreach program.
Finally, someone said it. The old school “blast and pray” method is dead. Precision and camouflage are the new standard.
Actually, I have to disagree slightly with the second point. In our testing, we found that over-optimization was less of a factor than pure engagement metrics. It’s interesting to see how different niches react differently.
I’d argue that the content relevance is even more critical now. We’ve seen perfectly good links get devalued just because the semantic match wasn’t tight enough.
Thanks for the transparency. It’s refreshing to see a strategy that doesn’t rely on black-hat churn and burn. Sustainable growth is the only way forward.
Is there a specific tool you recommend for tracking the velocity? We’ve been doing it manually but it’s becoming unscalable.
For anyone reading this, pay attention to paragraph 4. That subtle distinction between “diversity” and “randomness” is what saves you during a Core Update.
I’m sharing this with our content team. We’ve been struggling to explain why “quality over quantity” isn’t just a cliché, and this illustrates it perfectly.
This complements the “Entropy” theory perfectly. If you don’t introduce randomness, you’re just painting a target on your back. Glad to see others advocating for smarter engineering.
I’m skeptical about the timeline you proposed, but I’m willing to test it. If this holds up, it changes how we structure our entire outreach program.
This is a solid breakdown. One thing I’d add is that the impact of these updates often lags by 2-3 weeks. We tracked this across multiple projects and found the recovery phase is where most people give up too early.
Finally, someone said it. The old school “blast and pray” method is dead. Precision and camouflage are the new standard.
This is the missing piece of the puzzle for us. We had the content and the technical SEO, but the off-page signal diversity was lacking. Thanks for the clarity.
Does this apply to non-English markets as well? We’re seeing conflicting signals in our EU campaigns compared to what you’ve described here. Would love to hear your thoughts on regional variance.
The depth here is impressive. Most guides just skim the surface of link velocity, but your point about “natural variance” hits the nail on the head. It’s exactly what we preach to our clients.
I bookmarked this for my team. The section on avoiding footprints is crucial. We recently audited a site that got hit exactly because they ignored that principle. Good catch.
Have you considered the impact of mobile-first indexing on these placements? We’ve noticed that some “desktop-safe” strategies are flagging on mobile crawls.
This is exactly why we moved away from automated PBNs. The risk/reward ratio just doesn’t make sense anymore compared to what you’re describing.
Great resource. I’ve sent this to a few colleagues who are still stuck in 2015-era SEO tactics. Hopefully, this wakes them up.
Spot on about the indexing delays. It’s not just about building the link anymore; it’s about the “stickiness” of the placement. We’ve been focusing heavily on that metric lately.
Just wanted to say thanks for the detailed case study. It’s rare to see actual data backing up these claims. We’ll be adjusting our Q4 roadmap based on some of these insights.
This is exactly why we moved away from automated PBNs. The risk/reward ratio just doesn’t make sense anymore compared to what you’re describing.
I’m sharing this with our content team. We’ve been struggling to explain why “quality over quantity” isn’t just a cliché, and this illustrates it perfectly.
I’m skeptical about the timeline you proposed, but I’m willing to test it. If this holds up, it changes how we structure our entire outreach program.
Finally, someone said it. The old school “blast and pray” method is dead. Precision and camouflage are the new standard.
I’m skeptical about the timeline you proposed, but I’m willing to test it. If this holds up, it changes how we structure our entire outreach program.
This complements the “Entropy” theory perfectly. If you don’t introduce randomness, you’re just painting a target on your back. Glad to see others advocating for smarter engineering.
Actually, I have to disagree slightly with the second point. In our testing, we found that over-optimization was less of a factor than pure engagement metrics. It’s interesting to see how different niches react differently.
I bookmarked this for my team. The section on avoiding footprints is crucial. We recently audited a site that got hit exactly because they ignored that principle. Good catch.
Brilliant articulation of the problem. The industry has been too focused on metrics like DA/DR instead of actual traffic flow and user behavior.
Is there a specific tool you recommend for tracking the velocity? We’ve been doing it manually but it’s becoming unscalable.
Does this apply to non-English markets as well? We’re seeing conflicting signals in our EU campaigns compared to what you’ve described here. Would love to hear your thoughts on regional variance.
This aligns with the “Signal Noise” theory we’ve been developing. You need enough noise to mask the signal, but not so much that you lose authority. delicate balance.
This is the missing piece of the puzzle for us. We had the content and the technical SEO, but the off-page signal diversity was lacking. Thanks for the clarity.
This is the missing piece of the puzzle for us. We had the content and the technical SEO, but the off-page signal diversity was lacking. Thanks for the clarity.
This is a solid breakdown. One thing I’d add is that the impact of these updates often lags by 2-3 weeks. We tracked this across multiple projects and found the recovery phase is where most people give up too early.
The analogy of the “immune system” is perfect. You need to build resistance before the virus (update) hits. Too many people react instead of prepare.
Great resource. I’ve sent this to a few colleagues who are still stuck in 2015-era SEO tactics. Hopefully, this wakes them up.
The analogy of the “immune system” is perfect. You need to build resistance before the virus (update) hits. Too many people react instead of prepare.
The depth here is impressive. Most guides just skim the surface of link velocity, but your point about “natural variance” hits the nail on the head. It’s exactly what we preach to our clients.
Question: Have you tested this approach with expired domains? We’re running some experiments now and the results are… mixed. Your methodology seems safer.
I’d love to see a follow-up post on how this integrates with social signals. We feel there’s a multiplier effect there that isn’t being fully utilized.
Question: Have you tested this approach with expired domains? We’re running some experiments now and the results are… mixed. Your methodology seems safer.
I bookmarked this for my team. The section on avoiding footprints is crucial. We recently audited a site that got hit exactly because they ignored that principle. Good catch.
We’ve been A/B testing this exact hypothesis. Group A (your method) is outperforming Group B by 40% in terms of ranking stability. The data speaks for itself.
This is the missing piece of the puzzle for us. We had the content and the technical SEO, but the off-page signal diversity was lacking. Thanks for the clarity.
Brilliant articulation of the problem. The industry has been too focused on metrics like DA/DR instead of actual traffic flow and user behavior.
Have you considered the impact of mobile-first indexing on these placements? We’ve noticed that some “desktop-safe” strategies are flagging on mobile crawls.
Great read. It reminds me of the strategy we deployed last quarter. The focus on foundational stability really pays off when the algorithm shifts. Thanks for compiling this.
This complements the “Entropy” theory perfectly. If you don’t introduce randomness, you’re just painting a target on your back. Glad to see others advocating for smarter engineering.
Does this apply to non-English markets as well? We’re seeing conflicting signals in our EU campaigns compared to what you’ve described here. Would love to hear your thoughts on regional variance.
I’m sharing this with our content team. We’ve been struggling to explain why “quality over quantity” isn’t just a cliché, and this illustrates it perfectly.
The shift towards “entity-based” indexing is real. Your strategy seems to leverage that by building entity associations rather than just keyword matches. Smart.
Finally, someone said it. The old school “blast and pray” method is dead. Precision and camouflage are the new standard.
I’m skeptical about the timeline you proposed, but I’m willing to test it. If this holds up, it changes how we structure our entire outreach program.
This is exactly why we moved away from automated PBNs. The risk/reward ratio just doesn’t make sense anymore compared to what you’re describing.
I’m skeptical about the timeline you proposed, but I’m willing to test it. If this holds up, it changes how we structure our entire outreach program.
Question: Have you tested this approach with expired domains? We’re running some experiments now and the results are… mixed. Your methodology seems safer.
Brilliant articulation of the problem. The industry has been too focused on metrics like DA/DR instead of actual traffic flow and user behavior.
Great resource. I’ve sent this to a few colleagues who are still stuck in 2015-era SEO tactics. Hopefully, this wakes them up.
Have you considered the impact of mobile-first indexing on these placements? We’ve noticed that some “desktop-safe” strategies are flagging on mobile crawls.
We’ve been A/B testing this exact hypothesis. Group A (your method) is outperforming Group B by 40% in terms of ranking stability. The data speaks for itself.
This is a solid breakdown. One thing I’d add is that the impact of these updates often lags by 2-3 weeks. We tracked this across multiple projects and found the recovery phase is where most people give up too early.
I’m curious about the sample size for these conclusions. We saw a 15% deviation in our own datasets, but the overall trend aligns with your findings. Good work.
The depth here is impressive. Most guides just skim the surface of link velocity, but your point about “natural variance” hits the nail on the head. It’s exactly what we preach to our clients.
Great resource. I’ve sent this to a few colleagues who are still stuck in 2015-era SEO tactics. Hopefully, this wakes them up.
Question: Have you tested this approach with expired domains? We’re running some experiments now and the results are… mixed. Your methodology seems safer.
We’ve been A/B testing this exact hypothesis. Group A (your method) is outperforming Group B by 40% in terms of ranking stability. The data speaks for itself.
One minor correction: the update rollout was actually 14 days, not 10. But that doesn’t change your main point—the volatility window is getting wider.
Does this apply to non-English markets as well? We’re seeing conflicting signals in our EU campaigns compared to what you’ve described here. Would love to hear your thoughts on regional variance.
Have you considered the impact of mobile-first indexing on these placements? We’ve noticed that some “desktop-safe” strategies are flagging on mobile crawls.
I’m skeptical about the timeline you proposed, but I’m willing to test it. If this holds up, it changes how we structure our entire outreach program.
Finally, someone said it. The old school “blast and pray” method is dead. Precision and camouflage are the new standard.
This aligns with the “Signal Noise” theory we’ve been developing. You need enough noise to mask the signal, but not so much that you lose authority. delicate balance.
For anyone reading this, pay attention to paragraph 4. That subtle distinction between “diversity” and “randomness” is what saves you during a Core Update.
Great read. It reminds me of the strategy we deployed last quarter. The focus on foundational stability really pays off when the algorithm shifts. Thanks for compiling this.
Thanks for the transparency. It’s refreshing to see a strategy that doesn’t rely on black-hat churn and burn. Sustainable growth is the only way forward.
We’ve been A/B testing this exact hypothesis. Group A (your method) is outperforming Group B by 40% in terms of ranking stability. The data speaks for itself.
I’d love to see a follow-up post on how this integrates with social signals. We feel there’s a multiplier effect there that isn’t being fully utilized.
Great read. It reminds me of the strategy we deployed last quarter. The focus on foundational stability really pays off when the algorithm shifts. Thanks for compiling this.
For anyone reading this, pay attention to paragraph 4. That subtle distinction between “diversity” and “randomness” is what saves you during a Core Update.
This complements the “Entropy” theory perfectly. If you don’t introduce randomness, you’re just painting a target on your back. Glad to see others advocating for smarter engineering.
The analogy of the “immune system” is perfect. You need to build resistance before the virus (update) hits. Too many people react instead of prepare.
For anyone reading this, pay attention to paragraph 4. That subtle distinction between “diversity” and “randomness” is what saves you during a Core Update.
I’d argue that the content relevance is even more critical now. We’ve seen perfectly good links get devalued just because the semantic match wasn’t tight enough.
This is exactly why we moved away from automated PBNs. The risk/reward ratio just doesn’t make sense anymore compared to what you’re describing.
This is exactly why we moved away from automated PBNs. The risk/reward ratio just doesn’t make sense anymore compared to what you’re describing.
The analogy of the “immune system” is perfect. You need to build resistance before the virus (update) hits. Too many people react instead of prepare.
Have you considered the impact of mobile-first indexing on these placements? We’ve noticed that some “desktop-safe” strategies are flagging on mobile crawls.
We’ve been A/B testing this exact hypothesis. Group A (your method) is outperforming Group B by 40% in terms of ranking stability. The data speaks for itself.
Is there a specific tool you recommend for tracking the velocity? We’ve been doing it manually but it’s becoming unscalable.