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Using Artificial Intelligence in Marketing

Updated: Nov 9, 2023

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Change is the only thing that is always there. And the world of business is changing very quickly right now. With the rise of clever marketing tools and creative AI like ChatGPT, artificial intelligence (AI) marketing is becoming more important. This gives marketing teams a lot of chances to do more of what they already do best. As marketers, this is a very important benefit.

AI marketing uses customer and brand experience data along with aritifical intelligence in marketing technologies to give you very accurate information about your customer's journey and market trends. AI technologies like natural language processing (NLP), machine learning (ML), mood analysis, and others help you make decisions so you can stay ahead of competitors and be ready for the challenges of a changing market.

So, let's get down to the details of how AI is helping marketers and how y

ou can make the most of it.

How is AI used in marketing?

By 2030, 45% of the world's economy will be driven by marketing that is based on AI. It will be able to do this in a number of ways, such as by using data to improve products, offering personalized services, and changing what people want.

Here's a better look at it.

Social media listening

When AI is used to power social marketing, it makes you more productive by taking social listening to a whole new level. Aspect-clustering is used by aritifical intelligence in marketing systems to find and pull out useful information from social listening data, which can be made up of millions of data points in real-time.

Through social media mood analysis, they help you cut through the noise and get a clear picture of what the customer thinks. This lets you predict what your customers will do next and act strategically to get the results you want.

Examples of some social listening tools using AI: Followerwork, TweetDeck, and Social Mention.

Content generation

Intelligent social media management tools, like Later or Tweetdeck , look at data from social posts and reviews to find out what material your target audience is most interested in.

AI-powered platforms can also find buzzwords and triggers that can help you write more interesting blog posts, reply to customer comments more effectively, and come up with better product descriptions for your website. All of these add to what you're doing to get people interested in your brand so you can grow your market share and make more money.

Your nurturing efforts can also do better with ideas produced by AI. They help you come up with engaging ways to communicate with prospects at every stage of the sales process. AI prompts can help you come up with email subject lines that get more opens, create personalized content based on buyer personas, drive talks based on purpose, and interact with each prospect or client individually. This makes your relationships better and keeps people coming back, which boosts your sales.


Through lexical and statistical cues that drive smart processes, AI-driven smart automation gives social media managers and customer service teams the tools they need to improve business efficiency.

It helps you get your business goals done quickly by getting the guesswork out of things like scheduling posts at the best times for the most effect or putting incoming messages into categories. It also lets your brand speak with one voice to customers and cuts response time in half with rules-based features like our Suggested Replies.

Audience classification and personalization

Your omnichannel business strategies can be driven by AI marketing based on market segmentation, which matches your ads with the people most likely to buy your product or service.

You can also use automated advertising to make it easier to choose and set up digital ads that will give you the best return on investment (ROI). This makes it possible to use more personalized marketing strategies to build brand trust and make strong campaigns to raise brand awareness.

Data analysis for customer insights

AI and machine learning can help you learn important things about your customers in a variety of ways that will help you make smart marketing choices. Find out how people feel about your business and get a full audit of your customer service team's performance and metrics for social media activity.

This can help you respond quickly to changes in the market, set budget priorities based on what needs the most money, and get closer to your customers.

Reputation Management

Let's be honest: when it comes to your brand's image, you can control some things and you can't control others. Brands are being looked at more than ever because of social media. But with AI-powered brand image management, you can stop a possible threat to your brand before it becomes a big problem.

AI marketing tools make it easy to keep an eye on bad comments in real time, choose the right leaders and brand champions, and provide proactive customer service.

Competitive intelligence

AI tools can help you find ways to make your goods and services better and fill gaps in the market. Find out what your rivals' share of voice is and think of smart ways to be flexible in a market with a lot of competition. Also, use competition comparisons to compare how well you do on social media to how well your competitors do. This lets you change your approach or adjust your standards so you can stay ahead of the competition.

Multilingual advantage

For a business to have a global footprint, it must take into account different cultures and provide quick and good customer service. AI marketing tools make it easy to get customer insights from data in different languages, so you can figure out which approach is most likely to work in a certain region. You can also make sure that the people you want to reach find your social posts, replies, and ads relevant and in line with their culture norms.

What kinds of AI make marketing possible?

Powerful social marketing tools like Sprout use advanced AI technologies to give you the information you need to achieve. Semantic classification, named entity recognition, and aspect-based sentiment analysis help you get insights that are specific to your industry. Natural language processing helps you optimize social content and improve customer engagement, which all adds to your competitive advantage and share of voice.

Let's find out more about these tools.

1. A machine that learns

Machine learning (ML) uses statistical methods to look at social data for high-precision information about customer experience, public sentiment, and other marketing drivers. Once learned, ML models instantly do text mining, subject extraction, aspect classification, semantic clustering, and other tasks to give results in seconds.

AI-ML models get better as they handle more data over time, so they automatically upgrade themselves. This is great for growing your business while investing as little as possible in your tech stack in the future.

2. NLP stands for "natural language processing."

Your AI marketing tool is powered by NLP so that it can understand social listening data in a meaningful and contextual way. It uses a mix of rules-based lexical and statistical methods to help you find important information in a wide range of posts, messages, reviews, or comments.

When NLP algorithms are written for social listening, they can understand the data even if it's full of slang, code switches, emojis, abbreviations, hashtags, or writing mistakes. Natural language generation (NLG) makes the tool even better at helping you write great copy for posts, customer replies, and other things.

This gives you access to a larger audience for outreach efforts, better contact with current customers, and a better return on our investment in social media.

3. Search by meaning

In natural language processing (NLP), semantic search algorithms are very important because they help understand the meaning of a phrase or group of words without using keywords. These algorithms find important terms and put them into groups based on their meaning. This gets rid of the chance of repeats in text mining, especially when it comes to mood analysis, for a more accurate way to measure how customers feel about a brand or how well it does.

Knowing how strong your brand is compared to your competitors and keeping track of it against your standards can help you change your marketing and sales strategies to reach your long-term business goals.

4. NER (Named Entity Recognition) and neural networks

NER lets an AI tool find named things in a large amount of data. These entities could be CEOs, celebrities, locations, currencies, companies, or other important people, places, or things. It can find these things even if the spelling is wrong. NER is also a key part of making knowledge graphs because it sets up connections between things so that context and insights can be drawn from data.

Neural network (NN) algorithms, which are designed to work like the way a human brain processes information, remember these linked data points and keep adding them to their library of knowledge. Through deep learning, this is what makes it possible for ML models to give more accurate results over time.

So, you learn why certain brands keep showing up in your social listening data, what new market trends are on the horizon, which influencers would be a great fit and many other things that can help you improve your social marketing strategy.

5. Analysis of feelings

Sentiment analysis is the process of figuring out how customers feel based on their feedback. This can be a big help when it comes to managing online reviews. Algorithms that do sentiment analysis look at data from social listening, like poll answers, reviews, and new messages, both in real-time and in the past. They look at every part of the data that can be used to measure sentiment and give polarity numbers that run from -1 to +1. There are no points for neutral comments.

When customers talk about different parts of a business on social media, sentiment analysis tools look at the direction score of each part. The numbers are added up to get a sense of how customers feel about the company as a whole. This gives you an idea of how well your business is doing in the long run.

With this kind of information, you can grow your brand by reviewing and improving your social media content, changing your sales and marketing, getting better at managing your brand, better understanding what your customers want, and a lot more. Read more about the value of digital analytics.

The future of AI in marketing

AI marketing is making huge leaps forward at an incredible rate. Here are some of the ways it is making businesses better.

Vision by computer

AI marketing tools can use computer vision to get insights from digital data that isn't text and comes in the form of raw pictures. Computer vision helps solve important business problems every day. For example, it uses optical character recognition (OCR) to read information and signatures on checks and spot brand logos in videos. It can also pull text from pictures to make them easier to read.

Computer vision can be used in retail to find flaws in goods on an assembly line or to make sure stores are always full. It also helps improve biometric identification by making face recognition better. This makes it easier to find shoplifters, customers or employees in trouble, and a lot of other things.

AI-based apps

Conversational AI, like virtual assistants and smart robots, is going to change the way marketing has been done in the past. With focused messages, AI chatbot marketing can really boost the exposure of a business. They can increase involvement with current customers and prospects to get more leads, and they can also look at their data to give you detailed information for prediction and prescriptive marketing.

Virtual workers also streamline customer requests, make sure customers are taken care of 24/7, and route talks to the right team for the best results. All of these things lead to happier and more loyal customers.

AI that can predict and tell what to do

With predictive and prescriptive data, AI marketing tools are already a must-have for marketers. Prescription analytics sorts social listening data into groups based on what customers want, how they think, and what they plan to do. With this information, you can make ads, posts, and emails that reach the right people and get the best results. Streaming services are a great example of this because they use your past choices to show you material that fits your interests.

Predictive analytics lets you go further, so you can predict what will happen and make a business plan based on voice of customer data a long time before it happens. This means that you can make long-term business plans, evaluate risks, grow your market share, improve product ideas, and more.

Responsible AI

AI marketing also considers that the AI models we have now aren't perfect. To get real benefits and accurate business information from AI in business, it needs to be fair, safe, reliable, open to everyone, and clear. This means that AI tools need to be built with more care and trained with a wide range of data to get rid of biases.

Data protection, copyright, and governing rules are also being made to make sure that social and societal effects are taken into account and to be fair to both people and companies that make AI. This means that social networks and social marketing teams need to be aware of how they use AI tools to collect customer data, make content, show personalized ads to affect buying behavior, or for any other reason.

AI can help you make business plans that have an effect.

With the help of AI marketing insights, businesses can build a solid foundation for growth and future success by looking for new ways to sell their products and connect with customers. AI technologies like sentiment analysis, natural language processing (NLP), virtual bots, and others determine how quickly you can reach business goals, such as increasing sales or managing an unpredictable market.

With focused AI-driven customer data, you can create a more proactive social media marketing strategy to increase customer involvement, loyalty, and retention. And, in the end, growth in the market.

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