How to Use AI for Marketing: Benefits & Examples

How to Use AI for Marketing: Benefits & Examples

Patricia Orza

Content Queen

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Alexa, what's the weather like today?

Mostly cloudy with chances of showers and maybe even a thunderstorm!

Amazon's Alexa is a great example of how integral Artificial Intelligence (AI) has become in our daily lives. From smartphones to smart gadgets, AI is everywhere.

AI usage is at an all-time high. In fact, 71% of people prefer voice search to perform a query over traditional typing. Additionally, 62% of consumers are willing to use AI for a better buying experience. There's never been a better time for marketers to capitalize on the growing interest and use AI to personalize customer experiences.

When customers are ready to adopt AI technology, what’s stopping you and your business?

To clear up general confusion and hesitation about using AI for marketing, here's a comprehensive breakdown of what it is, how it's conquering the consumer market, and how you can use AI to grow your business.

What is AI for marketing?

AI for marketing is exactly what it sounds like—Artificial Intelligence that enables organizations to improve their overall marketing efforts. AI automates everyday marketing tasks like scheduling and sending emails and predicting campaign performance. It also goes beyond that by personalizing experiences for both marketers and consumers.

Marketing efforts have evolved beyond door-to-door salesmanship. With more and more online activities, consumers expect businesses to know what they want and meet their needs quickly. Since speed, efficiency, and personalization play a big part in a customer journey, using AI to forecast demand and make smart decisions isn't just a luxury; it’s a necessity.

9 AI marketing use cases

Regardless of what online marketing activities you undertake, there’s a good chance that AI influences them in one way or another. Here are some use cases of AI in marketing.

1. Content moderation and generation

Content moderation is a popular example of a mundane, time-consuming, and error-prone activity. Automation is the only way to get this right, and you needn’t look further than AI-powered platforms to make moderation easy.

Levity's content moderation feature lets you quickly search through thousands of images and a large amount of text, freeing up your team's time to focus on more critical tasks. With Levity, you can moderate and generate error and bias-free content.

Flow on Levity to moderate user generated content
Moderate content with Levity

2. Ad targeting and ads media analysis

Who do you want your ads to target? What are your customer personas? Where can they see your ads, when, and how?

AI platforms help you create targeted ads that get the right people to engage with your ads at the right time. They also allow you to analyze your ads before they even go live.

Levity, for instance, predicts ad performance before you test it. Ads are expensive—you may burn holes in your wallet if you keep testing ads without evaluating their performance. Irrelevant ads can turn customers off and make them lose trust in your business.

How can AI help?

  • Test your ad content before publishing
  • Train your AI model with historical ad data to get better results
  • Get data-driven performance metrics and improve conversion rates
  • Lower costs by choosing relevant ads that work and convert
Flow on Levity to estimate ad performcance
Check your ad performance with Levity

3. Social Listening

Social listening involves capturing online mentions of your brand and repurposing them to increase brand awareness. Manually capturing brand mentions is inconvenient, time-consuming, and doesn't give you an accurate picture. Why bother when AI can do the heavy lifting for you?

AI platforms like Levity unify your social listening experience in one place. You can then cut through the noise and choose which social engagements to prioritize.

Why use an AI solution for social listening?

  • Understand the sentiment behind a mention
  • Discover social media trends and optimize your messaging
  • Discover potential customers to start conversations with
  • Find influencers to collaborate with
  • Actively engage with your audience
  • Address customer complaints or other issues mentioned on social channels
  • Monitor your social performance and adjust as needed
Flow on Levity to track keyword engagement
Capture and prioritize social mentions with Levity

4. Churn predictive analytics

AI can also be used to help predict customer churn. How? By analyzing the responses to your net promoter score survey, general customer sentiment, and previous communications with the client.

For example, you likely have tonnes of data from previous interactions with clients. Some of these clients are still with you; others aren’t. By analyzing past conversations and communications with clients you’re able to identify common characteristics amongst customers who’ve stopped using your services. This can help you step in and nurture business relationships before it’s too late.

5. Data analysis

AI analytics use machine learning techniques to analyze data on the go, provide key customer insights, uncover patterns, and establish data relationships. With AI tools, you can determine what works and doesn't for your business and how your customers interact with you.

Data-based insights facilitate decision-making. You can easily decide how to adjust your marketing campaigns based on the information at hand.

6. Image recognition

Image recognition is a staple in Artificial Intelligence. It uses deep learning to detect patterns in images and videos. You can identify places, objects, and actions to learn more about your customers and auto-tag and label items when needed. This type of data classification helps marketers segment customers and create more targeted campaigns.

7. Personalized design

Hyper-personalization is one of the most useful AI capabilities for marketing. It enables you to target customers based on their needs rather than simple demographic categories or groups.

AI helps tailor your company's messaging to individual customers, attracting and retaining them.

8. Chatbots

For some, AI is synonymous with chatbots. Well, they’re not wrong. A chatbot is a true representation of the basic things AI can do. Most websites now have a chatbot as nobody wants visitors to leave without taking action.

Chatbots simplify customer service by answering general customer queries and escalating complex issues to customer service teams. This helps build better customer relationships and increase trust in your brand, whilst also enabling your customer support team to focus on more complex issues.

9. Dynamic pricing

Dynamic pricing isn’t limited to eCommerce sites. Companies like Uber, Airbnb, and Major League Basketball—basically anyone who’s a seller—use dynamic pricing to reflect supply and demand for their products and services.

AI-powered dynamic pricing matches inventory with demand and automatically changes the prices. For example, when a product is in high demand, prices may rise, and when demand is normal, prices tend to stay the same or go down.

Examples of Artificial Intelligence in marketing

Artificial Intelligence is deeply rooted in many successful companies and drives their marketing. Let's look at some popular examples of AI in marketing.

Amazon

Personalized shopping

Amazon offers real-time personalization and recommendations via its recommendation algorithm branded as the “Frequently Bought Together” feature. It uses collaborative filtering to predict a customer’s preferences based on other customers.

Upselling combined with AI propelled Amazon forward in the marketing game. It succeeded by putting customers' preferences and needs first and using AI technology to create a framework that satisfied these needs during their shopping journey.

Amazon's future looks even brighter as it incorporates enhanced features like voice shopping via Alexa and Amazon Echo into its marketing strategy. It will be interesting to see how Amazon continues to use AI to offer even more customer-centric, personalized solutions.

Dynamic pricing

Amazon's catalog is huge, with 400 million products and 2.5 million daily inventory changes. Managing such an extensive database isn’t easy—even for a company as big as Amazon. This is where dynamic pricing comes into play.

Amazon's machine learning engine uses the fundamental demand and supply rule to predict market demand for a product and analyze factors that drive engagement and conversions.

For example, when a product's inventory is low and demand is higher, prices may increase but are consistent with market behavior, user values, and fair pricing. This doesn’t hinder a consumer's purchase.

Amazon also uses advanced marketing strategies like tracking user behavior on its site to adjust its prices. Dynamic pricing can be observed during certain times when prices may fall or rise depending on demand, supply, and market changes.

Starbucks

Starbucks held the highest share of the US coffee shop market, with ownership of 40 percent of all US coffee stores in 2020. What drives Starbucks' success not only in its home market but around the world? Its AI-driven marketing strategy.

Starbucks uses big data analytics and Artificial Intelligence to analyze its vast volume of data and extract key customer insights. The mobile app alone has over 17 million users, so Starbucks has no shortage of data. It uses AI to understand user behavior, such as which products are popular with users, when they purchase them, and how they compare to the competition. All of this insight and market research help Starbucks personalize the customer experience.

Starbucks' digital flywheel program is a cloud-based AI engine that creates highly personalized customer recommendations based on location, weather, special occasions, and more. It also refines Starbucks' targeted marketing strategy by proposing personalized offers on its app and via newsletter.

‘My Starbucks Barista’ is a new addition to the Starbucks mobile app. It's a virtual assistant that allows customers to order using AI to understand voice commands or messages. Starbucks is at the peak of AI-assisted hyper-personalization.

Facebook

Image recognition

Facebook's image recognition technology is one of the first in its field. It has come a long way since the photo tagging feature and is now incorporating advanced AI and machine learning capabilities into its business model.

Facebook not only analyzes images for tags and descriptions but also trains its AI models with the deep learning program DeepFace, enabling precise recognition with minimal errors. This advanced engine is taking Facebook's image recognition capabilities to a new level.

Targeted advertising

The first names that pop up when we hear targeted advertising are Facebook and Google. Both tech giants have redefined advertising by creating target clusters and ads based on customer preferences.

Facebook focuses heavily on targeted advertising to achieve the highest market cap and edge out the competition. Deep learning also plays a big part here, as Facebook uses deep neural networks to determine which ads to show to whom intelligently. This is helpful for marketers in a specific niche with a defined target audience. Facebook gives you the tools to show customers what they actually want to see, streamlining your marketing strategy and saving cost and time.

easyJet

UK-based airline easyJet is one of the companies in the aviation industry using AI to improve customer experience. Their strategy of leveraging data science across different facets of the airline industry brought them outstanding results. They reduced costs, increased revenue streams, and drove customer satisfaction.

Firstly, easyJet uses machine learning to understand how to stock up planes to avoid waste. This is based on consumer habits and behavior as well as external conditions such as weather and season.

EasyJet also banks on a recognition system that analyzes documents such as passports to gather customer information without the customer having to type. Their advanced recognition system helps them process more documents faster, saving flyers the hassle of filling out yet another document.

Artificial Intelligence and data science are the backbone of easyJet's marketing strategies. They use the two technologies to make sense of their data and analyze customer feedback to make the necessary improvements.

Results?

In the first half of 2018, 75% of easyJet's seats were from returning customers, equivalent to a whopping 63 million passengers. Now that’s what we call impressive AI marketing!

Elements of AI in marketing

AI marketing includes some fundamental elements that make it so powerful and advanced. Here are the three main elements.

Machine learning

Machine learning is an Artificial Intelligence technique that can analyze a huge amount of data and train and learn automatically over time. In the context of marketing, machine learning examines various pieces of information and enables marketers to make informed decisions.

For example, machine learning can help marketing teams recognize certain patterns in user behavior, such as the time they visit a website, the products they browse, and the areas that need improvement. ML stores these records and learns to adapt to changing circumstances, saving marketers time otherwise spent on manual analysis.

Data and analytics

Data is a gold mine.

The entire digital universe currently contains over 44 zettabytes of data! It’s an impossible amount of data for humans to sort through—so what do you do with it?

Big data analytics is a subset of data analysis that uses advanced analytical techniques to make sense of a large amount of data. This process mainly boosts marketing activities by analyzing existing data to obtain meaningful, insightful, and actionable information.

AI platforms

Working with AI can sometimes seem too technical. Marketers have a lot to handle and don't have the time to delve into the complex framework that makes up ML or big data analytics.

They want a central interface that brings all their workflows together in one place and helps them function with little technical know-how or coding skills.

AI platforms like Levity do just that. Levity is a no-code AI solution that gives you the freedom to organize all your workflows in one place. What’s better? It continues training AI models over time, so you can be sure your AI predictions are only getting better.

For example, Levity’s AI solution provides insights regarding how customers use your product. Levity combines qualitative and quantitative data into valuable insights to tailor your marketing based on customer feedback, interviews, comments, and reviews.

Flow on Levity to classify customer insights
Customer insights at your fingertip with Levity

Benefits of Artificial Intelligence for marketing

AI offers countless benefits to marketers—take a look.

Build stronger customer relationships

AI tools like chatbots provide 24/7 customer support, meaning they’re always available to help customers. This allows customer service teams to save time responding to common queries and focus on other important tasks and complex queries.

When customers feel heard, they come back to you for more solutions. You build not only strong customer relationships but also loyalty and good word-of-mouth.

Faster data-driven decision making

Human brains can only interpret and analyze so much. You need marketing tools to sift through mountains of data and drive your decision-making. AI-powered systems generate helpful marketing insights and reach the right customers at the right time. You can craft your messaging based on these insights and make it meaningful and engaging to convert.

Boost campaign ROI

With improved decision-making, you stand a better chance of developing content that resonates with your audience and converts. You can run campaigns based on historical information about the type of content your audience engages with and add value to their journey. This affects your bottom line and increases your campaign's return on investment (ROI).

Personalize content with customer data

As mentioned previously, data analysis is critical to creating relevant, personalized messages and content. If you don't know your customer's preferences—what they want and don't want—it's difficult to gauge and create something that works for them. It's like shooting an arrow in the dark and hoping to hit the bullseye—unlikely.

Customer data such as demographics, buying history, and location can help you identify prospects interested in your products or services. The best way to get and decode this data is with artificial intelligence.

Visualize customer journey

Customer journey mapping helps visualize the customer experience at different touchpoints. With a visual map or strategy, you can better understand what your customers want at varying stages of their journey. Why should a customer buy from you? What is unique about you? How do you meet their needs? All of this is data-driven decision-making.

With the right AI technology, you can design custom journey maps and optimize your customers’ digital experiences. Understand what you need to get customers to reach out to you and how to engage them.

Improve user experience

Let's say you're designing a landing page to sell sleeping bags. What characteristics would you need to determine your target audience, and would it help if you knew their browsing habits? If you're a local business, you'll likely appeal to local travelers, but if you're a global chain that ships worldwide, your page needs to be tailored to have universal appeal.

This contributes to the user experience—how users behave and interact with your business.

It's difficult to get all these insights with manual research. AI automates manual work and provides the necessary information to improve user experience. The insights eliminate human bias and are based solely on simulated intelligence. Your users are seen for who they are and not how you think they should be.

Automate repetitive tasks

Repetitive tasks are monotonous, drain energy, and take time. Marketers feel tired and sometimes demotivated doing the same thing over and over. AI automates mundane tasks like scheduling, reporting, answering common human queries, and more. The time and money saved with AI can be used to solve complex problems and innovate. This improves employee productivity and morale.

Challenges of AI marketing

AI is a technology. No matter how sophisticated, it's not without its challenges and flaws. Let's look at some common AI marketing challenges.

Lack of IT infrastructure and talented developers

There’s a good reason why most companies are reluctant to adopt AI—they lack adequate IT infrastructure and talented developers. How can anyone work with machine learning techniques, data science, and deep neural networks if they don't have the technical knowledge?

Furthermore, many small businesses cannot afford to set up a complex AI framework. They just don't have the budget and choose to look the other way.

Maybe they're not looking in the right direction—No-code AI tools like Levity are a great solution for AI in small businesses. You can perform all your marketing activities with just a few commands. With Levity, you can train your model with your own data to understand your processes, systems, and users, and increase automation.

You don't need to set up any elaborate infrastructure or have a qualified workforce to automate your workflows. Levity does this for you.

Insufficient data or inadequate data

In order to train your AI model, you need quality data—which isn't always easy to come by. More data doesn’t automatically translate to clean and actionable data. This is a big challenge in AI marketing.

Since most of your decision-making depends on the AI’s predictions, you need to ensure your training data is clean and organized. Faulty data delivers faulty predictions.

Weak AI platform

You need an AI platform that can meet your needs. Humans create AI platforms, and the platforms’ strength depends partly on human capabilities. Mistakes happen when building an app or tool, and can result in a weak or incoherent AI system.

However, advanced AI technology and deep neural networks have business applications that ensure accuracy and correct data analysis.

How to use AI for marketing

Now that the basics are out of the way, it’s time for implementation. Here are four easy steps to get started.

1. Establish your goals

Every business and every aspect of that business should be chasing a goal. This also applies to AI marketing. Before you integrate AI into your existing systems, set clear goals. Ask yourself:

  • What do you want to achieve with AI technology? Is it to get more customers, improve existing systems, market to a broader audience, and so on?
  • How will it help your team and customers? Will it save time and improve customer experience?
  • Do you have the budget to use an AI tool?
  • Do you have the right data and the necessary know-how? Using no-code tools will ensure any team member can implement AI automation.

2. Collect high-quality data

Once you've set your goals, consider whether you’ve got quality data.

Look for credible sources that can provide helpful training data and build your own database from your campaigns, CRM, and websites. The quality of your output depends on what you feed your AI system, so collecting clean and actionable data is extremely important.

3. Maintain data quality

Data can become corrupt and inconsistent if not maintained regularly. It should be error-free, complete, relevant, representative, and accurate.

4. Select a powerful AI platform

After all of this, it boils down to the AI platform you choose for your marketing journey. To hit the ground running, you need a tool that:

  • Meets your AI needs
  • It is intricately built on advanced AI technology and a strong framework
  • Provides broad functionality
  • Aligns with your goals

For example, opt for a low-code or no-code solution like Levity—here are some key features:

  • Create custom AI models on the go. Build AI models that fit your needs based on the workflows you want to automate, images, documents, text, and more.
  • You don't have to be an expert to use Levity. As a no-code AI solution, Levity is easy to use and requires no special expertise.
  • Levity caters to businesses of all sizes. Size is not a bar for Levity. Works for small businesses, medium-sized businesses, and even corporations.
  • Built on a powerful AI Engine. Levity features powerful AI while offering a simple user interface. It’s built on advanced technologies like AutoML, providing users with a strong and resilient platform to operate on.
  • Trains AI models to improve over time. You can train your AI with relevant training data to evolve. This helps you in times of crisis or market changes. Levity makes your AI capable of adapting to any situation.

Start using AI in marketing today

AI is no longer the future—it’s very much part of the present. Companies all over the world are using AI to improve their marketing efforts—whether it’s by predicting campaign success or analyzing customer sentiments.

Start your AI in marketing journey by signing up to Levity today, and begin optimizing your customer’s experience fast.

Frequently Asked Questions

How is AI used in marketing?

AI is used in marketing to generate meaningful insights and help make data-driven decisions. AI automates day-to-day marketing efforts, saving time and money while empowering marketers to learn more about their customers and provide the right solutions.

Is AI the future of marketing?

AI is certainly the future of marketing as it offers superior capabilities in terms of automation and analytics.

Simply put, AI can perform some tasks better than humans and saves us the trouble of wasting time on mundane activities. Customer demands and expectations are growing unprecedented, and Artificial Intelligence is the only way to meet these demands.

How will AI affect marketing?

Contrary to what many marketers believe and fear, AI is not here to replace humans. Instead, it improves human input by automating repetitive tasks and improving the customer experience. AI is here to make marketing better and easier.

Can AI be used for content marketing?

AI can be used for content marketing and improve it. Many AI tools cover different facets of content marketing, including content outline, creation, competitor analysis, search engine optimization, keyword analysis, content syndication, editing, and more.

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