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You created the one percent

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First published in 2015

 

As promised, here is your checklist for redirecting finance in a more positive direction. It is important for you to circulate it to as many people as possible to encourage them to do the same. You can do as little or as much as you choose, but the more people redirecting their lives away from feeding what is now a seriously malfunctioning machine the better. The 1 percent that everyone complains about only became the 1 percent because the 99 percent put them there.

My suggestion is that you do one thing at a time, so that you do not become bogged down with the details.

If you are in Europe, sign this https://stop-ttip.org/

And this https://secure.38degrees.org.uk/page/s/eu-ttip-petition#petition

And this https://www.change.org/p/to-the-eu-and-uk-governments-do-not-sign-up-to-ttip

Open an account with an ethical bank, again I have posted links to some of the banks which market themselves as ethical investors on the Better Person Project  You will find them under the appropriate drop down menu.  The reason I suggest this before doing anything else is because changing all your monthly payments over to a new account is a pain in the neck, and considering the other slightly more time consuming things I will be adding to this list, it is important that you start with this.

This means that you will be encouraging positive rather than negative investments from the banks that you choose to deal with.  If we can encourage a swing towards ethical investment, it will influence the more mainstream banks to do the same.  One person matters. One thousand people matter.  One million people and we have actually achieved something. You matter.  Open the account.  If your country is not represented, find the bank in your country that invests ethically and add it to the website, please.

In the event that you hold savings, consider investing a little in a ‘lend with care’ or social capital project as you will achieve two things – first, the person you are lending to will not have to go to a bank and give them more business, and second, you will get a much better interest rate than the banks have been offering. Again, I have added links on the Better person project site, and if you find more, or better ones, you are free to add them without fear of my scraping your data, or whatever.

Stop shopping with large retailers such as supermarkets, ‘iconic’ brands etc.  The big global fashion labels in particular, are owned by about 6 investment companies.  Not that they are particularly evil investment companies, but if you wish to achieve an impact in terms of diversifying the market, you want to feed the smaller companies until they are in a position to compete.

Supermarkets are a menace, because you are lulled into giving them a proportion of your income every week, so one company benefits disproportionately by cutting costs or advertising more widely.  This is easy for a raw foodist, because chances are if you are shopping in a supermarket, you are paying too much already.  Non raw foodies will find it more difficult.

I completely understand as I sometimes do the shopping at 3am and Asda (Walmart) is the only one open, but if we are to start making a dent in this, it starts at home. Reducing your spend to the minimum and using your spending power to encourage competitors is key.

As a side effect, smaller retailers are frequently located in places where it is more practical to walk, and you may be able to use your car less.

Communications companies are just as outgrown.  Investigate smaller companies who offer the same services that you currently enjoy.  It is worth considering spending slightly more in order to grow a competing company, rather than get additional TV channels that you do not even watch thrown in as part of a deal to maintain the economic status quo with a company like Sky, Virgin or the equivalent.

It is a question of habit, and being aware that the price of convenience is the difference between being forced into a minimum wage job by a giant retailer, or opening a store yourself, if that is what makes you happy. Just as thinking before you eat makes a difference, so does thinking before you let a penny out of your wallet.

Bear in mind, if you choose to do this, that it was not entirely your fault that you were sucked into a situation where your government became powerless against the businesses that supported them.  The original book goes into quite a lot of detail as to how it was done, and how people were weakened in the face of ultra convenience.  I shall take a look at publishing the finished material, but for now – I think this is enough for us to be getting on with.  If we can get around the time consuming problems associated with rechannelling our own money, it will make it much easier for the next wave of people that get on board.

 

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72 Comments

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  25. 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.

  26. 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.

  27. 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.

  28. 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.

  29. For anyone reading this, pay attention to paragraph 4. That subtle distinction between “diversity” and “randomness” is what saves you during a Core Update.

  30. I’ve been following this topic for a while, and your analysis on the structural shifts really adds a new perspective. We’ve noticed similar patterns in our internal data at SignalLayer, specifically regarding the volatility timeline.

  32. 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.

  33. Question: Have you tested this approach with expired domains? We’re running some experiments now and the results are… mixed. Your methodology seems safer.

  35. 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.

  36. 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.

  37. 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.

  38. 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.

  39. 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.

  41. 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.

  42. Brilliant articulation of the problem. The industry has been too focused on metrics like DA/DR instead of actual traffic flow and user behavior.

  43. 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.

  47. 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.

  48. 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.

  50. 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.

  52. I’ve been following this topic for a while, and your analysis on the structural shifts really adds a new perspective. We’ve noticed similar patterns in our internal data at SignalLayer, specifically regarding the volatility timeline.

  54. 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.

  55. I’ve been following this topic for a while, and your analysis on the structural shifts really adds a new perspective. We’ve noticed similar patterns in our internal data at SignalLayer, specifically regarding the volatility timeline.

  56. Great resource. I’ve sent this to a few colleagues who are still stuck in 2015-era SEO tactics. Hopefully, this wakes them up.

  57. 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.

  58. 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.

  59. 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.

  60. 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.

  61. 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.

  62. 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.

  64. I’ve been following this topic for a while, and your analysis on the structural shifts really adds a new perspective. We’ve noticed similar patterns in our internal data at SignalLayer, specifically regarding the volatility timeline.

  67. 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.

  68. 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.

  70. For anyone reading this, pay attention to paragraph 4. That subtle distinction between “diversity” and “randomness” is what saves you during a Core Update.

  71. For anyone reading this, pay attention to paragraph 4. That subtle distinction between “diversity” and “randomness” is what saves you during a Core Update.

  72. 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.

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