NeuralText Review: 4-in-1 SEO & A.I Content Suite. But is it up to mark?
Overview + Summary
After diving deep into the app, I realized this tool can be broken up and sold as 4 different tools.
Keyword research, Keyword clustering, Content optimization, and A.I. Content.
It’s literally 4 in 1.
Which can be a good or bad thing depending on how mature they are.
- Functionality: 2/5
- Easy to Use: 2/5
- Overall User Experience: 2/5
- Support: ❓
- Deal Structure: 3/5
- Roadmap: ❓
- Overall: 2.5/5
Core Features Score:
- Keyword Research Tool: 3/10
- Research History: 4/10
- Keyword Cluster: 4/10
- Content Brief: 6/10
- Content Templates: 4/10
- Content Grader (Content editor): 3/10
- Smart Copy (A.I Content): 6/10
- Overall Score: 4.2/10
Check out each of the features below with the pros & cons and screenshots.
Keyword Research Tool
First of all, the user interface is not appealing. Looks very basic and lack insights.
What is the banner doing up there taking up 30% of the screen space?
In comparison, take a look at 2 of my other favourite keyword research tool — Ahref & Keywordtool.io
Worse of all, the keyword results from NeuralText does not seem relevant.
I searched for Technical SEO, but these are the top few results…
Out of 15 keyword results on the top, I’ve only managed to highlight 4 that are highly relevant.
I’m sure “Google analytics” and “Google search console” on the top are also relevant, but they are not as closely related to the main search term.
What I feel lacking are categories to group these keywords.
Take Ahref for example, they group the keywords into 4 different categories, and researchers can find what they need easier.
You can see that the broad terms “Google search console” also showed up on Ahref, but it’s grouped under “Also talk about…”
At a glance you know that they are somewhat related but not too closely related to the main search term.
For NeuralText, they simply give you a bunch of keywords and you’ll have to filter and sort it by yourself. There’s no proper organization and categorization.
Another UX problem can be found at the “PPC competition” section.
Ideally, this should tell us how competitive a keyword is.
But what is 0.21 or 0.47? Should I assume that the maximum is 1 and 0.8 is very competitive and 0.1 means it’s less competitive?
It might be intuitive to you, but not so for a new user.
Since there are some guesswork that is needed, why not make it easier by just giving us a percentage and tell us if it’s easy or hard to rank?
Here’s an example on keywordtool.io and Ahref:
Apart from the lack of organization and categorization, I find the keyword output decent. And the keyword search volume and cost per click (CPC) data accurate.
My guess is they use the free Google keyword planner API, and that’s why a few tools that I tested produced similar results.
Keyword Research Score: 3/10
This is the place where it keeps all your previous search history.
I can either “go to report” which consumes no credits since I’ve done the search before or export it in a CSV.
The user experience here again is below average.
Upon clicking on the “Download” button, I would expect a CSV file directly in my downloads folder. But instead, I was asked to go to the “export centre” to download.
Why the extra steps?
Research History Score: 4/10
I was excited to test this feature as not many keyword tools out there (including Ahref/ Keywordtool.io) can automatically group your keyword into clusters.
Keyword clusters are intended to help you find related keywords to rank for in your main article.
And create only one article for multiple keywords to avoid keyword cannibalization.
I got to say that the UI & UX is below average here… again.
In comparison, here is how WriterZEN’s Keyword cluster looks:
Instead of asking to upload a CSV file, all I have to do on WriterZEN is to do a search.
Speaking of which… Why the extra steps of uploading a CSV file on NeuralText? Couldn’t the app create a keyword cluster automatically based on my past search results?
Now I have to go back to my search result, export it as CSV, come back here, and upload as CSV again.
I feel that the design is not well thought out.
They seem to be different apps built independently and simply put together in one dashboard. There’s no native integration even between features of the same tool.
Now, let’s look at the results.
For UI/ UX, WriterZEN is better. You can also click on “show ideas” to reveal other keywords with it’s search volume and other data.
This is not possible with NerualText, you would have to go back to the keyword research tool and search for these new keywords one by one.
What’s interesting is NeuralText does not have a cluster for the seed keyword, “Technical SEO”.
Short tail keywords like this usually have many other long tail keywords as sub-keywords. And you can rank for all of them by writing a comprehensive article.
Example: technical seo for beginners, technical seo issues…
At WriterZEN we can see they have a keyword cluster for “Technical SEO” with 37 other sub-keywords you can rank for:
Despite missing the main seed keyword, and having some random clusters showing up at the top, I found a few potential keyword clusters that were discovered by NeuralText but not found on WriterZEN.
“On-page SEO” is one of them. But their sub-keywords are a bit misleading as off-page SEO is totally different from on-page SEO.
If I were to choose one for keyword clustering, I’d go for WriterZEN.
Research History Score: 4/10
This section here is like Frase where they lay out all the necessary info for you to write a comprehensive article.
- Competitor’s content
- SERP Intent (not in Frase)
- Keyword search volume (not in Frase)
- SERP results
They even have 2 features that are not available in Frase. (above in bold)
I like the SERP intent feature (which was also available in BIQ), where it tells you what TYPE of article Google likes to rank.
Is it informational or navigational content?
Write something that Google loves to rank.
The question section is what you would imagine. A bunch of questions scrapped from Quora and Google SERP. Very handy.
The layout is a little buggy here. They scrape the top 18 results and display the data here for you. But there’s a huge white space that takes up 70% of the screen.
I prefer Frase’s layout, where they display the content editor on the left, and the results on the right.
While browsing, I usually take notes of my research findings directly on the content editor.
If I were to use NeuralText, I would need to take notes at a separate doc.
The outline resembles Postpace where they scrape not just the main headings but also all the subheadings of the top 10-20 results.
This one is nice.
This allows you to pick out the common sub topics that people are writing about and include them in your article.
And also learn quickly about the subject by browsing the sub-headings.
I later learnt that you can click on the sub-headings and automatically add it to the “notes” section which will show up in the content editor. But this was not clear while I was exploring the section (Ux problem).
Content Brief Score: 6/10
There were no instructions on how to use the content templates.
But I later realized that it is designed for you to export it out and share with your writers. (I feel they should have called this content briefs instead)
The templates are quite helpful for beginners and you can create your own as well.
On the right sidebar, there are a few other resources such as questions, notes, sources, etc where you can move them over to your brief simply by clicking.
Personally, I prefer the one over at Frase.
It looks better, has more data, and is easier to use.
One major flaw here is they do not have the suggested topic/ keywords displayed here in the content brief. These are topics that you should include in your article to have the highest chance of ranking.
Why not include it here where you’ll be creating a brief for your writers?
They do have the “relevant topics” section but the suggestions are different from those found in their Content editor (we’ll go through in a bit). Which makes me believe they are not the same.
Either way, the “relevant topics” suggestions are not that relevant either.
I believe they were chosen simply based on the number of times they were mentioned in ranking articles.
Content Template Score: 4/10
In my opinion, the follow 2 areas are the most important for content editors.
- The quality of the topic/ keyword suggestion
- The UX.
The topic/ keyword suggestion lacks quality with too many single-word topic suggestions that are often irrelevant.
How is “site” and “website” the top topic to cover in an article about “technical SEO”.
I believe they get these data simply by looking at the frequency of the words being mentioned by the top ranking websites.
Google is getting smarter, simply stuffing keywords like these will not help you rank.
Compare this to Frase’s suggestion:
Better, but still lacking.
Here is MarketMuse’s suggestions:
Much more relevant topics with greater depth.
Would I write and optimize my content based on NeuralText’s suggestion?
Sadly, not at this moment.
As for the UX, Neuraltext left out all the important research data that they provided earlier.
Apart from the suggested topics on the right, there’s no way to access “questions”, “people also ask”, “sources”, “stats” and more.
Which is a pity because they had already done all the heavy lifting earlier. Why not show it here as well?
In comparison, Frase have them all in the content editor:
One thing that stands out for Neuraltext is they have the GPT-3 long form generator and other A.I tools directly in the content editor.
This, I believe, is something that Frase is working on right now.
The quality of the their A.I generation is pretty decent too. Nice.
Sadly, due to the poor topic suggestions, I won’t be able to write my article directly in their content grader and will have to write it on another platform with better topic suggestions.
That means I can’t take advantage of their natively integrated GPT-3 long form generator.
Content Grader Score: 3/10
The smart copy section is like a GPT-3 tool on it’s own. Not related to the rest of the NeuralText toolkit.
It has the usual marketing/ copywriting tools that you see, (facebook ads, email subject lines and etc)
And of course the long form editor as well.
After a few quick searches, I found the output quality similar to ContentBot and other GPT-3 tools.
As for the long form editor, they used the exact same flow as Conversion.ai.
You’ll first be required to write a description, the keyword, followed by generating the headline and intro paragraph using A.I.
After which, you can access their free flow content editor where you type in some content and then hit “generate” to get the A.I to write for you.
Personally, I like this flow because it fits the natural flow of writing articles.
And it’s smart because these 3 data can then be fed back into the A.I. engine to spit out even more relevant copy later on.
In Shortly, it’s the same. You have to fill up these 3 components in order to improve the output quality.
Anyhow, I found the quality of both the headline and the blog intro not as good as Conversion.ai.
Here are the output of both:
As for the output quality of the free flow long form editor, I’d say that they are both quite similar.
While testing the Smart copy feature, I found a frustrating bug.
After returning to the dashboard, I’m unable to access the previous Smart copies or campaigns that I’ve created.
Here you can see 3 test campaigns, and nothing happens when I click on them.
The campaign name is clickable, but only brings me back to the selection page where I’m asked to select a new template.
Imagine you write 2,000 words, go to bed, and wake up the next day not being able to access all the work you’ve done.
I hope they fix this soon.
Content Grader Score: 3/10
As you can see, Neuraltext attempts to do many things at once but excels in none of them.
The overall idea is good, but the quality of the data and the usability has to be improved for widespread adoption.
Considering this is essentially three tools in one (Keyword research, keyword clustering, content optimization, and A.I writing), the team will need to work extra hard to make them all stable. Additionally, they will require three times the resources.
Invest in the tool if you can accept its inconvenience and believe in its roadmap & team to get through it.