AI Marketing: a simple guide

Putting AI in marketing

As an 80s kid, when I think of AI, films like The Terminator, Blade Runner, and The Matrix come to mind. Dystopian nightmares controlled by artificial overlords. No wonder there’s a certain apprehension toward the tech.

But this is not the reality of today’s AI. Instead, we’re seeing significant benefits across all functions of our lives, from safer car journeys to kicking spam from our inboxes.

In this AI Marketing Guide, we look at how it’s now actively helping marketers, and the benefits it can bring.

Contents

• What AI technologies can be used in marketing?
• What are the benefits of AI for Marketers?
• Example AI marketing tools
• Challenges and considerations of AI Marketing
• The future of AI in marketing

What AI technologies can be used in marketing?

One thing that can put off marketers from AI is that it feels impenetrable. It comes with its own technical language that isn’t always easy to understand. First up, are some of the terms you will come across and what they mean.

Some of the two-word phrases that are mentioned in conversations around AI over 13 months. Talkwalker Social Listening & Consumer Intelligence Platform.

AI (artificial intelligence)

Let’s start with the basics. Artificial Intelligence, or AI, is the ability of machines to perform tasks that typically require human intelligence, such as learning, reasoning, problem-solving, and decision-making. While AI is not capable of true human-like intelligence, it could transform many industries and improve our lives in various ways.

Machine Learning

Machine learning is a subset of AI that involves training algorithms to make decisions based on data. Data is fed in and insights come out. The more data the algorithms receive, the more accurate they are.

In marketing, machine learning is already used for a variety of tasks, including predictive analytics, customer segmentation, and recommendation systems. It can be used to optimize marketing campaigns and increase the effectiveness of customer targeting.

Large Language Models

Language models are neural networks that have been trained on a large body of language data. This AI can learn the relationship between words and phrases to 

• generate new text, 
• translate between languages, 
• perform other natural language processing tasks, such as question answering, classification, or summarization.

Large language models are pre-trained on much bigger datasets - 1,000x larger neural networks. With all this extra data, they’re capable of performing a wide range of tasks with little or no additional training.

In marketing, we’re seeing large language models used for tasks such as content generation, copywriting, and even customer support. You can also find them integrated into chatbots and virtual assistants to provide more natural and human-like interactions with customers.

Natural Language Processing

Natural language processing (NLP) is a field of AI that deals with how computers can understand, interpret, and generate human language. In NLP, computers are trained to understand natural language inputs, such as text, and use this information to make decisions or provide responses.

In marketing, NLP is used for a variety of tasks, including sentiment analysis, chatbot development, and content generation. Sentiment analysis, for example, uses NLP to decide whether a brand mention is positive, negative or neither. This information can then be used to improve customer service, inform product development, and optimize marketing campaigns.

Visual analytics

Visual analytics enables platforms to understand and interpret visual information, such as pictures and videos. Simply turning hard to interpret images into qualitative insights.

In marketing, visual analytics can be used for logo recognition, to detect a logo in social images and videos. This can provide a broader understanding of how consumers interact with a brand. Not just how they write about it, but how they engage with it in their daily lives.

Visual analytics can also be used for visual search, allowing customers to search for products using images rather than text. This can make the shopping experience much more intuitive and user-friendly. If you see something you like, take a pic, share it, and quickly find it in your favorite shop. That’s a better experience for your user, and a faster way for you to make a sale.

Image analytics can help you identify when your brand logo is shared online, whether that’s in images or videos. Talkwalker Social Listening & Consumer Intelligence Platform.

What are the benefits of AI for Marketers?

AI-powered marketing offers numerous benefits that help us reach our goals more effectively. Here are some of the key benefits:

Improved efficiency and effectiveness

One of the most significant benefits of AI marketing is improved efficiency and effectiveness. Automation can help marketing teams streamline routine tasks, freeing up time and resources for you to focus on more strategic and creative jobs.

Think of AI as a support tool, that does the heavy lifting for you. Doing the P.I.T.A. tasks that you could do, but wouldn’t be an efficient use of your time.

AI can do things like analyze  thousands/millions of data points to find trends or patterns. A task that could take you hours, in a matter of minutes. And better still, you won’t hear it complain about doing it. 

This means you can be more efficient with your time, and focus on the fun tasks of marketing. That includes the creative side and the actionable side that will drive revenue for your business.

Personalized experiences for customers

AI can also help deliver more personalized experiences to customers. AI-powered tools can analyze customer data and behavior, then deliver relevant content marketing messages to your customers. 

Personalization can have a big impact on your brand, with personalized CTAs performing 202% better.

AI can provide that more personal experience for all your consumers. Boosting sales, improving customer engagement, and increasing loyalty.

Enhanced decision-making

AI can help marketers make better decisions. Predictive analytics and forecasting tools can analyze large data collections to make predictions about future trends and customer behavior. Enabling you to make more informed decisions. This can boost your marketing performance, removing the reliance on gut-instinct, and instead driving more data-driven decisions.

Increased ROI and conversion rates

All of these things put together can make a positive impact on your business. Boosting your conversion rates across the board, and helping you focus more on the tasks that will deliver future revenue.

And better still, it can also help reduce costs, as you and your team become more time effective.

Example AI marketing tools

Depending on what you want to achieve, there’s a wide variety of AI tools available. Here’s just a small sample of what you could start using now to boost your campaigns..

Social listening AI tools

Talkwalker

Ok, I may be biased, but Talkwalker is the leader in AI when it comes to social listening. And you can see why. Often social listening uses large data sets. We’re talking potentially millions of brand mentions, that without AI, would be impossible to manage.

With artificial intelligence, you can segment your data, get easy-to-understand summaries, and pull additional insights from visual analytics and sentiment analysis.

Why Talkwalker? It’s the first and only social listening platform  to include large language models. Blue Silk™  GPT is now able to

• Classify data easily. Forget spending hours on complicated Booleans, and instead let the AI organize your data for you in a matter of clicks.

• Get simple, easy-to-understand briefs. Instead of spending hours reading reviews, surveys, or emails, you can get an overview of consumer opinions in a few simple sentences.

• Bringing the power of GPT to social listening.

Personalization and targeting AI tools

Optimizely

Optimizely provides personalization and experimentation software for businesses looking to improve digital experiences. Its AI-powered platform analyzes customer data and behavior to deliver personalized experiences and targeted messages to individual customers. Optimizely's suite of products includes experimentation and testing tools, personalization and recommendation engines, and customer insights and analytics. The platform can create and run experiments to test hypotheses and make data-driven decisions about marketing strategy.

Dynamic Yield

Dynamic Yield is an AI-powered personalization platform that helps businesses optimize customer experiences across channels. Allowing marketers to analyze customer data and behavior to deliver personalized experiences in real-time. This includes personalized product recommendations, targeted messages and promotions, and customized content based on individual preferences and behavior.

The company was acquired by McDonald's in 2019, highlighting the growing importance of AI-powered personalization in the food and beverage industry.

Predictive analytics and forecasting tools

KXEN

KXEN was a software company that provided advanced analytics and machine learning solutions for businesses. It helped businesses analyze large datasets and make data-driven decisions. Its predictive analytics enabled businesses to anticipate customer behavior and trends, and optimize accordingly.

KXEN was acquired by SAP in 2013 and has since become part of the SAP Predictive Analytics suite of tools.

Alteryx

Alteryx provides a platform for data preparation, blending, and analysis. Its software is designed to enable organizations to gain insights from data more efficiently and effectively. Alteryx's platform offers a wide range of tools for data preparation, including data cleansing, data blending, and data transformation.

Alteryx is used by organizations across a range of industries to gain insights from data and make more informed decisions.

Automation and optimization AI tools

Marketo

Marketo is a marketing automation software that provides a suite of tools to help businesses streamline marketing. It uses AI for automated decisions and to optimize routine marketing tasks, such as lead nurturing, email marketing, and ad targeting. Marketo's AI algorithms can analyze large amounts of customer data to determine the most effective marketing tactics. The platform also provides personalized recommendations for customer engagement, lead scoring, and cross-selling opportunities. 

Pardot

Pardot is now part of Salesforce’s Marketing Cloud Account Engagement. It’s a marketing automation platform that helps businesses streamline marketing processes and improve sales efficiency. Pardot offers a range of features, including email marketing, lead nurturing, and lead scoring, that allow marketers to engage their audience more effectively.

It uses AI and machine learning to automate routine marketing tasks, allowing marketers to focus on more strategic activities. For example, the platform can use AI to analyze customer behavior and send personalized messages to customers based on their preferences.

Content creation AI tools

Articoolo

Articoolo offers marketers an AI-powered content creation platform. Its technology uses natural language processing to automatically generate unique and high-quality articles, summaries, and product descriptions on any topic. Users can simply input a topic and the platform generates a unique article. One that’s optimized for search engines and can be used for various purposes such as marketing, blogging, or academic research.

Persado

Persado is an AI-based platform that creates persuasive, personalized marketing content. The platform analyzes customer behavior and generates marketing messages that are tailored to consumers’ unique preferences and needs. Persado's platform can create content across various channels, including email, social media, and digital advertising. The platform's AI engine can also learn and optimize its content creation based on the performance of previous campaigns.

Chatbots and virtual assistant AI tools

MobileMonkey

MobileMonkey is a chatbot builder platform that allows businesses to create custom chatbots for customer communication on multiple messaging channels. It uses AI to enable chatbots to respond to inquiries and automate customer service tasks. Users can also customize their chatbots with drag-and-drop features and advanced automation workflows. Additionally, MobileMonkey provides analytics and reporting tools to track chatbot performance and customer engagement.

Tars

Tars uses AI to develop and manage chatbots and virtual assistants that can interact with customers and provide support, guidance, and recommendations. AI chatbots can be integrated into websites, messaging platforms, or mobile apps, providing 24/7 customer service. Marketers can also use AI chatbots to automate routine tasks, such as answering FAQs, and provide personalized experiences to customers.

Challenges and considerations of AI in marketing

If you are going to integrate AI into your marketing strategy, there are some considerations to keep in mind.

Data privacy and security concerns

Marketing organizations collect a vast amount of customer data in order to target more effectively. This data can include sensitive information such as customer names, addresses, financial information, and browsing history. 

With 76% of users thinking companies must do more to protect their data online, brands need to be diligent in protecting this data. That includes ensuring that you are following all relevant laws and regulations, such as GDPR in the European Union. Talkwalker is fully GDPR compliant.

AI bias and fairness

Another challenge of using AI in marketing is the risk of amplifying existing biases. AI algorithms are only as unbiased as the data they are trained on. If the data used to train algorithms is biased in some way, the AI will reflect that.

To address these risks, you need to incorporate as broad a range of data as possible. For example, when it comes to social listening you should include a data source such as the Twitter Firehose. This provides you with an unbiased view of everything happening on that social network, with a wide range of views and demographics. By adding in other sources such as Facebook, Instagram, Quora, blogs, and reviews, you get a broad and diverse data set.

Cost and implementation challenges

Adding AI into marketing efforts can be a significant investment. AI tools and technologies can be complex, and organizations need to have the necessary resources and expertise to effectively implement and use AI. There are also ongoing costs associated with maintaining and updating AI algorithms and systems.

It could be more cost-effective to integrate a platform with AI capabilities, rather than invest time and money creating your own.

Ensuring human interaction and personal touch

While AI can automate and optimize many marketing tasks, it’s important to ensure that customers still have opportunities for human interaction.

Don’t lose the personal touch in the marketing process.

Consumers value human connections and often prefer to engage with real people when making purchasing decisions.

Remember, AI is there to do the heavy lifting, not to fully take over the role. For example, to get more effective insights, you should still include insight experts who can dig under the data, and uncover the human stories beneath.

The future of AI marketing

The future of AI in marketing looks bright, with new and emerging technologies expected to bring further innovation to the field.

Emerging AI technologies and its potential impact on marketing

New AI technologies are constantly being developed, with the potential to change the way marketers like you approach your work.

For example, generative adversarial networks (GANs) are a type of machine learning algorithm. These can generate new and unique data, such as images, text, or audio. In marketing, GANs could be used to generate creative and personalized content for customers, such as product recommendations or personalized advertisements.

Predictions and trends for AI Marketing

The use of AI in marketing is expected to continue to grow in the coming years. With an increasing amount of data being generated, AI will play a crucial role in helping marketers make sense of it all. The emphasis will be on personalization, predictive analytics, and automation. With AI tools used to deliver more targeted and relevant experiences to customers.

Conclusion

Love it or hate it, the AI revolution is here. It will change the marketing landscape, and your role within it. Like many revolutions, you have a choice, jump on board and see what you can gain from the new opportunities.

Or risk getting left behind in its wake. It’s up to you.

Click below to learn more about how AI can help boost your marketing efforts.