How Natural Language Processing Is Reshaping Marketing Strategy

Thanks to successive technological evolutions, digital marketing has evolved rapidly and remains in a state of flux. The marketing tenets of 2010 are obsolete in 2020, and in another decade, there will be a significant shift in marketing due to technological advancements.

For instance, the advent of the internet and web domain changed the way marketers communicate with their target market. Some years later, Google and Facebook became internet sensations. Each platform allowed marketers to connect with their audience in a personal way.

Today, artificial intelligence (AI) is coming to the fore, and progressive marketers have recognized AI as a significant player in future marketing. For marketers, artificial intelligence can improve productivity by eliminating repeat tasks, reducing error, automating data analysis and reporting. When these benefits add up, it translates to saved time and money and significant revenue generation.

AI has many important implications for several industries. Still, it is particularly ubiquitous for the marketing industry with a slew of AI-powered applications and solutions from customer relationship management solutions to content management platforms and more.

This article reviews the history of AI, the importance of AI to marketers, and practical use cases.

What Is AI and Why Should Marketers Care?

The history of AI goes back to 1950 when a British mathematician and computer scientist Alan Turing asked, "Can machines think?”

As computers became more sophisticated, scientists realized that they could perform several functions like a human being or even better. So from a performance standpoint, computers can be more efficient and effective than humans in certain areas like memory, storage, and endurance.

Alan Turing's decades-old question set off the events that led to the development of Artificial intelligence in computing. To date, computer programmers and AI specialists use the Turing test developed by Alan Turing to assess a computer's intelligence. The test ascertains whether a computer's intelligence can be distinguished or equivalent to human intellect.

Today, artificial intelligence refers to the science of making computers smart, and humans are the standard of intellect. According to research, computers would be smart enough to substitute humans in most work roles by 2050.

Although we are 30 years from the estimated time, artificial intelligence is reshaping marketing strategy in many ways. AI can help marketers tell better stories and improve marketing while driving down costs and reducing downtime.

There is a high chance that you use an AI-powered tool for marketing. Chatbots, automatic logo makers, Grammarly, and Google keypad are excellent examples of AI-powered applications.

If you use any of the listed tools, then you're already enjoying the benefits of artificial intelligence. AI-powered tools simplify processes and raise the quality of work done in a specific time.

According to the McKinsey Global Institute, artificial intelligence will generate approximately $2.6T in marketing and sales. Considering the fast-paced growth of AI technology, the forecast will be a reality.

Natural Language Processing: How AI Speaks Human

Natural Language Processing (NLP) makes computers capable of reading and analyzing human language.

NLP is a component of Artificial intelligence, making computers capable of reading unstructured data like the English language. Usually, NLP technology is paired with NLG (Natural Language Generation) to read and write or suggest text to users.

NLP use cases

Information retrieval - When you enter a term into Google's search bar, the system processes the text, checks the database for the information, and returns a relevant result. Google performs this process with NLP technology.

Information extraction - Google products like Chrome use NLP to read user data and extract non-identifiable information.

Language translation - Google translate uses NLP technology to read a text for translation.

Spam filters - Facebook, Twitter, Gmail, Yahoo Mail, and other web platforms use NLP to identify and block questionable content posted or shared by users. This use case of NLP prevents violation of user rights, scam schemes, and more.

Auto prediction and correction - Keyboard applications for Android and iOS smartphones are built with NLP to read user text and check for error, tone, or hurtful words. When the app detects any labeled word or mistake, the user receives a notification with suggestions to change it.

There are many ways to use NLP technology to improve user experience, increase productivity, and drive down costs. For marketers, NLP-powered tools can help automate tasks such as event scheduling, audience analysis, communication, and more.

NLP In Modern Digital Marketing

There are several use cases of natural language processing technology in marketing, and as technology evolves, there will be more use cases. With that in mind, digital marketers must find ways to utilize AI to improve performance and remain above the curve in terms of work relevance.

Improve Personalization Efforts

As a marketer, you can use NLP apps to personalize messages at scale. NLP based tools can read consumers' messages and use the data to generate a contextual response through natural language generation.

Consumers love brands that communicate in a familiar tone. It creates a sense of friendship and builds loyalty. As a marketer or business owner, you can communicate with your entire customer base in a way that will resonate with them the most without spending hours learning their preferences.

Personalized Push Notifications

Personalizing push notifications, which have become an important way for businesses to interact with their customers, makes them more effective as users are more likely to notice them when compared to notifications with a general message.

Companies like Tripadvisor use previous user actions to send tailored messages via push notifications. These messages look a lot less salesy and pushy and more accurately reflect the user’s interests.

Tailored Website Content

There are plenty of websites that already use content filtering to customise the client’s website experience. Using machine learning, the website content changes based on universal data sets like trending topics and recently published articles. This ensures visitors always have a fresh experience.

Brands like Netflix and Etsy use machine learning to gather information on their visitors and then group them based on their interests. Then, these groups are shown content which will resonate with them the most.

Segmented Email Messaging

Using predictive analytics, marketers are able to segment their emails, providing the most relevant information to each customer based on their preferences. Hyper-personalised content is quickly becoming the norm in email marketing, putting emphasis on the right tone of voice, the right offers, the right time of day, and the personal touches.

Analyse Customer Sentiment

NLP applications can analyze social media content about a business, otherwise known as customer sentiment analysis.

A lot about marketing involves feedback and response. Marketers can use NLP powered tools to monitor whether the discussion about their brand on social media or across the web is positive or negative and respond accordingly.

Sometimes, sentiment analysis apps are built into social media platforms, such as Twitter or social media tools like Hootsuite.

Twitter allows brands to use social listening to evaluate how customers talk about the current events, like introduction of a new item on the menu or announcing a product release date, and change their decisions based on the customer sentiment. Twitter partners, like Sprinklr and Brandwatch, can comb through old tweets on the topic to evaluate the customer sentiment from the past as well as evaluate what customers talk about in real time.

Get New Topics and Keywords

Several use cases have shown that NLP powered tools can generate good topic ideas and keywords for writing content. Hubspot blog topic generators and Portent are excellent examples of topic generators. These tools require a phrase or a word to generate relatable ideas.

Automated Content Generation

Machine learning is invaluable for marketers when it comes to saving time on producing content. From generating small content pieces to creating entire websites - marketers can reap great benefits from introducing NLP to their workflow.

Video Generation

AI-based tools can ease video production by generating video scripts, visuals, music and voice overs:

  • NLP models like GPT-3 can generate entire scripts based on a short description
  • Tools like Synthesia can generate footage without the need for an expensive filming crew, actors or equipment
  • AI-generated music, like JukeBox library, allows to avoid copyright issues and provide a truly unique soundtrack

Automatically Generated Advertising Texts

Machine learning makes creating advertising content a matter of minutes. Tools like Wordsmith can generate various texts, like SEO-friendly product descriptions, manuals and advertising brochures, which are virtually indistinguishable from ones written by humans.

More advanced tools can create an entire narrative, describing not only the product itself, but what customer problem it fixes, comparing it to rivaling brands and standard approaches to resolving said problem.

Instagram Captions

Automatic caption generation for social media platforms like Instagram can greatly cut down time on marketing efforts as well as increase posting frequency and customer engagement.

Recently we were commissioned to build an AI-powered Instagram Caption Generator.

After consultation and project assessment, we identified the steps of building an automatic Instagram Caption Generator. First, we needed to develop an application that receives an image as input and generates an appropriate caption for an Instagram post. For the project to be considered successful, the generated text must be identical to human-written text because a caption generated by a robot is unlikely to sell anything.

The client gave us data for a training sample: 600.000 images with descriptions and 600.000 captions with hashtags that users wrote for these images.

The model first identifies objects present in the photo:

Person Human Advertisement Poster Brochure Paper Flyer Beverage Drink Cup Coffee Cup

After which it generates a caption:

My little fluffy buddy looking at my plants

This is the perfect spot to sit by the water - the best view and most beautiful food. Thank you for your advice!

#seedsarethebest #cotswolds# cotswolds #nationaldogday #myboysboy #myboys #imstillliving #imstillbornonthisfarm #ponytail #sisterhood

We have created a model that uses photos to generate captions that match human-written texts in vocabulary and phrasing. The model adds appropriate emojis and hashtags to the text so that the post is even more similar to the post of a regular Instagram user.

Website Development Using Simple English

NLP tools can not only generate or analyse natural language, but transform text into commands. This can make working with complex marketing tools, like website creation, much easier and faster by introducing simple English.

There are a number of tools which use NLP as input, like custom Figma integrations which allow the user to simply describe a page section using simple English to create it. These tools also generate HTML ready to use for building a website.


Will AI replace digital marketers?

One of the common reasons why people don’t like the idea/use of AI is the fear that AI will replace them at their jobs. This fear is not irrational because technology has made several roles obsolete in the last decade. However, the introduction of technology to an industry or process only improves output and allows workers to specialize in fields that cannot be automated. In the end, technology will help people focus on enjoying the human experience more than ever.

For digital marketers, artificial intelligence will help improve work quality and quantity, as explained with AI’s current use cases. Digital marketers can use AI to create short content such as an email, image description, and alt-text. Also, savvy marketers use AI to proofread their content to improve quality.


Without question, natural language processing and other artificial intelligence technology are reshaping marketing strategy. As a business or marketing agency, owning an AI-powered tool will help improve productivity and also create another revenue stream through software licensing.

If you want to build a custom AI tool to automate content creation and free up staff for vital tasks, drop us a line.