Reverse engineering of cyberRank

I am trying to solve the following problem which looks like don’t have obvious answer.

While developing the app I tried to design more simple google adwords like interface. Immediately I found two amazing benefits of the protocol we a building in the context of conventional digital marketing:

  1. We can prove views of the spark
  2. We can have provable attribution of commercial transaction with particular spark

Both properties combined are kinda the Holy Grail of digital marketing. But in order to implement the interface I do need an algorithm which will answer the following question:
How to estimate amount of CYB and backlinks needed to promote particular piece of content in the context of particular keyword. Any ideas are appreciated.

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How about calculating a table of semantics according to weight? It will be similar to what we have for relevance now. i.e. when there are enough from words to calculate, can we calculate which words have which weight and make this info open. This will create a sub market for semantics too. As this will be open information


Top linked words on block #X

  • cyber: 1 GCYB
  • google: 0.5 GCYB
  • BTC: 5 GCYB

Or. We can provide a mix of the ranking. Not just calculate the CYB that were used to link those, but also other params. Current rank, etc

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It’s hard for me to say what the price should be. Perhaps this requires an auction.