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What is Natural Language Processing (NLP)?

Natural Language Processing permits machines (i.e. robots and smart devices) to separate and decrypt human language. It is at the foundation of every AI-based service technology we use, from interpretation software, chatbots, spam channels, and web search engines to punctuation correction software, voice assistants, and web-based media monitoring programs.

What Happens in the Process of Natural Language Processing (NLP)?

Natural Language Processing includes a variety of mechanisms for decoding human language, and keywords, ranging from quantifiable and AI-based approaches to rules-based and algorithmic approaches. Important NLP tasks include index and parsing, lemmatization/ stemming, grammatical point labeling, language recognition, and recognized evidence of semantic links. If you ever charted rulings in grade school, you’ve already completed these projects physically.

In general terms, NLP assignments break down language and keywords into other limited, introductory pieces, attempt to get connections between the parts, and probe how the details cooperate to make meaning. 


Here are 7 steps of the process summarized to help you understand how NLP works:

  1. Content Order

A semantically grounded record, including hunt and ordering, content warnings, and duplication discovery. 

  • Subject Exposure and Displaying

Precisely catch the significance and motifs in textbook assortments and apply progressed disquisition to communication, analogous to improvement and determining. 

  • Corpus Analysis

 Comprehend corpus and record structure through yield perceptivity for errands like examining successfully, planning information as a donation for fresh models, and planning to display approaches. 

  • Contextual Extraction

 Naturally, pull organized data from textbook-grounded sources. 

  • Document Summarization

 Feting the disposition or emotional conclusions inside a lot of communication, including normal feeling and assessment mining. 

  • Report Synopsis Creation

 Accordingly, creating objectification of enormous communication assemblages and identifying addressed cants in multi-lingual corpora.

  • Machine Interpretation

Machine interpretation programmed textbook interpretation or converse starting with one language also onto the coming. 

The overall motion of Natural Language Processing (NLP) is to take crude language words and use phonetics and computations to change or enhance the communication to convey more prominent worth.

How Can NLP Your Facebook Ads & Detailed Targeting?

If you have ever experienced difficulties in Facebook’s detailed targeting & reaching the right audiences on Facebook, chances are, you haven’t set the right target audience for your ad, so there is a high likelihood you’re marketing to the wrong people, you might be missing a handful of keywords and better structure to hit a goldmine.


If you are a digital marketer, digital agency, or an Upwork \ Fiver freelancer, then probably you are well aware of how intense, and time-consuming the detailed targeting process is, deciding upon the right ratio between Demographics, Behavior & Interest is more like art for those who manage to master it.
Mainly, due to the fact that building an audience requires a great deal of understanding of the right ratio between Demographics, Behavior, and Interest as well as learning how to engage them via new keywords.

For instance, in 2017 during my days as a Growth Manager working for
WeAreDevelopers, a developers job marketplace startup in Vienna, Austria.

At that time, WeAreDevelopers produced as well cool conferences for everything developers related in 2018 (still do today as well) including Steve Wozniak (Legendary Co-founder of Apple) Joel Spolsky (founder of Stackoverflow), and more geniuses of our generation.

My job was to target various developers segments including:
Frontend Developers
Backend Developers
ios Developers
Blockchain Developers
Machine Learning Experts
QA Experts

And help convert them to our rapidly growing developers’ job platform directly through ads, or indirectly via the conference promotion.

After months and months of constantly changing, adding, erasing and building audiences with unstable results, I have noticed after some research is that the vast majority of developers worldwide are Star Wars fans (me being one as well)

So I did some small modifications (doing my own keyword suggestion research),
I modified our audiences, and included more Star Wars and Jedi keywords along with some software developers tend to use and highly to like and express their “Interest” on Facebook, and included them in our detailed targeting.

But that wasn’t enough for me, I did some custom ratio adjustments for the right balance between Demographics, Behavior, Interest, and Voila!

In a week, our CTR increased from 0.89% to -1.67. The Conversion Rate rose from 9.21% to 12.60, selling 37% more tickets to the conference and opening new targeting opportunities for the entire marketing team.


To conclude.

The optimization of our everyday work is not only beneficial, but it is also a necessity in this day and age. Today through Machine Learning growth marketers can optimize their keyword research automatically using NLP keywords tools, which ultimately, help them discover quality niches & build new Facebook audiences automatically, and save the most precious commodity of all, time.

If you are open to learning more about how your Facebook audiences can be optimized via Natural Language Processing & Machine Learning, try Instigo Audiences.

Generating targeting specs created on the spot, curated for your exact purposes.

To learn more about Instigo Audiences visit: Instigo Audiences