Neuron writer only comes short due to the number of repetitions for each keyword. Terms that have great weight like "crypto" only show up a couple of times when you paste the list from neuron writer but appear tens of times when extracted by AI due to all the variations. If you would use the recommended number of repetitions from neuron you'd get a huge score. Big love

@wordsatscale

9 ай бұрын

ok, noted!

An interesting comparison would be to write articles using those same LSI keyword lists for each of the Top resulting ones. I still don't get why NeuronWriter came up short. I suspect there is more to it than just a list of LSI keywords? But very strange results and is making me almost regret I just purchased 3 codes for NW :) thanks for doing the leg work as usual.

@wordsatscale

9 ай бұрын

no problem)

@byronhorde5892

9 ай бұрын

Since you have 3 codes for NW, if anything, after your article is written, you can utilize the option under AI-Writing... "FAQ with unused terms". Using that option does bump the score up. That could help with your "almost regret".🙂

Hey there. Hope you’re doing good. Just some constructive remarks here about your methodology. 1) I think the 27 score baseline for Neuron isn’t really fair. Put it simply, Neuron’s score also evolves with the frequency of some keywords and it seems that keywords variations provided by AI result in a greater of repetition of those keywords than the Neuron keyword list which is more streamlined (less repetitions = lower score). 2) Moreover, the score is calculated on Neuron LSI keywords themselves, so it does not make any sense at all to create a baseline for Neuron if you think about it. Neuron is your scale and the keyword list is part of the graduation along with repetitions, variations, text length, etc. 3) Finally, since AI contains some randomness (other word for creativity), you would need to repeat this exercice maybe an 100 times to see if there is any significant difference, but I don’t think there is… This applies for other AI comparison too, just sayin’. Hope this will help, thank you for your videos anyway, always pleasant to watch.

@wordsatscale

9 ай бұрын

Ok, good to know! Thanks!

Harpa is amazing!! The things it can do!

@wordsatscale

9 ай бұрын

agreed

Very interesting. The next problem is generating an article that uses all of these keywords.

@wordsatscale

9 ай бұрын

yep)

Hello, Pawel from Neuron here. This video was mentioned by one of Neuron users, and i would love to add some remarks how to make this comparison better ;) Basically, I see that NEURON won this test, giving fewer points to text with a lower chance to rank. higher content score = higher chance to rank. What kind of ranking chances do you have using list of leywords? A. Neuron takes into consideration more factors than just terms, like terms stuffing, headers, etc. In your example best if you check "checklist" as you get MINUS points for keyword stuffing (keyword ratio to text, keyword density, etc) B. You are comparing terms versus full text => so it is calculated differently as a "stuffing mechanism" is triggered on our side with heavier minus points C. Neuron recommendations are checked when content score is measured, so using text generated with AI will triger some of them, but its more like randomly generated fit for "content score". Hope this helps ;)

@wordsatscale

4 ай бұрын

noted

Perplexity is powered by Claude so it makes sense they provided basically the same list of keywords

@wordsatscale

4 ай бұрын

Perplexity is also powered by 3 other models)

You could copy the list of LSI keywords from one of the methods you tested and add those keywords into 'the terms in article' (probably the extended terms) in NeuronWriter. Then you could copy the ChatGPT prompt from the dropdown list and get Claude 2 to create a blog using NW's keywords plus the others added. I might try this. Can you put the prompts you used to get your LSI lists in the comments below your video, please?

@wordsatscale

9 ай бұрын

sure, will do

Can you please do a video about finding low competition keyword?

@wordsatscale

9 ай бұрын

I've got plenty on my channel)

Great work doing this comparison But for me 27 score for neuronwriter is highly understandable because if you just staff the keywords and gave you a high score This will be a negative point for me and make it look "stupid" cause from what i understand neuronwriter take on consideration the syntax and how much time you mentioned the keywords on each paragraph I mean neuronwriter is giving us the logical and the most reasonable result 😊

@wordsatscale

2 ай бұрын

noted

Harpa is capable of using claude2, bard, chatgtp versions 3.5 and 4. Which one of them was it set?

@wordsatscale

9 ай бұрын

Gpt-4

What is the most appropriate way to reach out to you? I've been hoping to be able to get.Unto you.

@wordsatscale

9 ай бұрын

All the contacts are here: wasuniverse.com

I could still return neuron writer but then how would you test your optimization

@wordsatscale

5 ай бұрын

))

I was surprised that Bing did not win

@wordsatscale

9 ай бұрын

yeaah

you then have lsi and nlp keywords? then what? how can we create full lenght articles with these keywords?

@wordsatscale

21 күн бұрын

You can use a 1-click seo prompt from my chatgpt library

What video recorder do you use to make your videos?

@wordsatscale

9 ай бұрын

Camtasia

How to extract NLP entity free

@wordsatscale

9 ай бұрын

same as LSI, same basic prompt