A guide to Digital Marketing with Artificial Intelligence

Published Oct 22, 2022 | Updated Oct 22, 2022

Artificial intelligence has become an essential staple of our daily lives. According to statistics, 71% of people prefer to search online using a voice query rather than typing. A further 62% of consumers are open to using AI to improve their buying experience.

Since customers are already open to adopting AI technology in their shopping and everyday lives, businesses also leverage AI for their marketing. Reports from Gartner show that AI will replace about 33% of data analysts in marketing.

This comprehensive article will explain what using AI for marketing is all about, its elements, challenges, and how to implement it. We show examples of how popular brands implement AI to grow their business.

Check out our blog for the latest marketing and conversion tips and practical guidance to boost your online marketing campaigns.

What is Artificial Intelligence in Digital Marketing (AI Marketing)?

Artificial intelligence in Digital marketing (also called AI Marketing and AI for marketing) is an organization’s use of Artificial intelligence to improve their overall marketing results.

Today’s marketing efforts have evolved beyond general advertising. Customers expect personalized offerings from businesses. They expect their favorite brands to know what they want and meet their needs quickly.

Marketers now realize that employing AI-powered marketing solutions is the fastest way to meet these demands. In today’s marketplace, AI marketing is not an option; it’s necessary. According to Statista, the market value of AI marketing is currently over $20 billion and expected to be over $100 billion by 2028 

Brands rely on AI to analyze customers’ behavior, predict their actions and develop the right strategy to meet their needs without wasting time or resources.

What is Artificial Intelligence (AI)?

There is no singular definition for AI due to its interdisciplinary nature. However, at the core of AI is the use of technologies that can perform tasks that require human intelligence.

From the business approach, AI refers to how technologies can operate at the level of human intelligence in business operations. The goal is to have machines work with human-like intelligence to save time and money.

The United States Patent and Trademark Office (USPTO) has identified a constellation of technologies that belong to the AI landscape. These include:

• Machine learning, 
• Knowledge processing, 
• AI hardware, 
• Natural language processing, 
• Evolutionary computation, 
• Computer vision, 
• Speech recognition, and 
• Planning/control.

What Are the Benefits of AI In Digital Marketing?

The benefits of AI in corporate marketing are huge. Three of every four customers expect companies to know their needs and expectations. This expectation is almost impossible to meet humanly due to the enormous amount of data marketers would have to sort through to understand the needs and expectations of one customer. 

AI marketing tools allow marketers to quickly sift through large volumes of data from social media, surveys, user statistics, and emails.

Here are some of the key benefits of AI in marketing:

• Stronger customer relationships

AI tools allow businesses to provide 24/7 customer support. Chatbots can help customers with general issues, allowing human support agents to focus on other vital activities. 

This approach enables enterprises to respond promptly to customer issues, build strong customer relationships and inspire loyalty. Financially, it reduces overhead costs and provides data for future marketing campaigns. 

• Automation

AI turns marketing data into actionable insights that can provide meaningful customer interactions and positively impact your marketing outcomes. 

Marketers use AI to scale their campaigns, offer customers personalized recommendations, and determine which marketing approach will provide the most ROI. Email marketers also use AI to optimize subject lines, generate and optimize marketing content and track the performance of their marketing campaigns.

• Minimal errors

Artificial Intelligence reduces errors in three critical areas: data gathering, analysis, and security. AI tools such as chatbots and website analytics tools can accurately source data from customer interaction and online behavior. Such data can be too voluminous for human analysts to sort independently. 

Using predefined criteria, AI converts big data into actionable insights. When it comes to data security, many organizations are now leveraging machine learning to identify threats and neutralize them to safeguard customer data and other critical business information.

• Cost saving

AI can take over repetitive tasks and reduce the chances of error to zero. Your business can afford to operate smoothly with fewer employees and save time. You can achieve less overhead costs, less time spent on everyday activities, and better overall performance.

• Increased ROI

The traditional approach to digital marketing is to experiment with multiple campaigns and choose the one with the best result. Although this approach works well every time, it translates into lost resources spent on abandoned campaigns. 

Using predictive customer analysis, AI eliminates the need for multiple campaigns by using data to determine the best marketing campaign for a preset audience. 

It produces individually tailored customer interactions at each customer journey stage, effectively increasing ROI on each customer contact.

• Increased personalization

AI is the secret behind personalized marketing. Many organizations use AI to create customized sales experiences on their websites, emails, social media platforms, online stores, and other customer contact areas. 

When done well, each customer will have a buying experience based on what they expect from the brand. Examples are product recommendations tailored to an individual customer’s shopping history and online activity.

• Smarter and faster decision-making

AI can harvest and analyze real-time data, allowing marketers to make smart, faster campaign decisions. 

With AI-powered campaigns, marketers can now determine the next course of action without waiting until the campaigns end. They can also quietly access and leverage data-driven reports for future marketing decisions.

Elements of AI in marketing

Three main elements of AI marketing that make it robust and advanced are:

• Machine learning

Machine learning refers to analyzing and recognizing patterns in massive amounts of data. It then uses these patterns to enable marketers to make informed decisions. Machine learning stores these patterns and adapts them based on new data. ML gets more accurate with every fresh data set.

• Data and analytics

Data is the new gold. The current volume of data in the digital universe amounts to over 44 zettabytes of data! It is impossible to sort through that data volume without AI. Big data analytics employs advanced analytical techniques to digest data into meaningful, insightful, actionable information.

• AI platforms

Machine Learning and big data analysis are too complex for most marketers. AI platform brings all the different aspects of AI marketing into a central, simple-to-use interface. 

Marketers with little to no technical skills can use these AI platforms to gain insights into customer behavior, analyze qualitative and quantitative data, and create personalized marketing based on customer feedback, interviews, comments, and reviews.

Challenges of Using AI in Digital Marketing

Like other forms of innovation, AI has its flaws and challenges. Let’s examine the common AI marketing challenges.

• Lack of IT talents and budget: 

The number one challenge most businesses face when adopting AI marketing is the complexity of setting up an AI framework. They don’t have the required infrastructure, in-house talent, or budget. 

Thankfully, AI tools such as Levity allow small and medium-sized businesses to leverage AI in their marketing activities without needing in-house infrastructure or developers. At the most, they only need to pay a monthly or yearly subscription fee.

• Insufficient data or inadequate data

AI runs on data. The more quality data you have, the better AI gets at providing insights. Businesses must ensure they have a constant source of clean and actionable data. This can be challenging as sometimes customers knowingly or unknowingly provide misleading data. 

Furthermore, most AI tools cannot tell if two or more users are behind an online instance. One example of this is the case of people with different likes shopping with the same device.

• Weak AI platform

These platforms run on human-generated codes. The quality of the underlying code determines how valuable an AI system is. Advanced AI platforms that provide accurate data analysis cost more than everyday AI platforms. 

• Privacy

Regulatory bodies and consumers are paying attention to how organizations source and use customer data. Digital marketers must ensure they source and use consumer data ethically and comply with standards such as GDPR. If they don’t, they risk heavy penalties and reputation damage. 

• Getting management support

While it is possible to know how effective a marketing campaign is, it can be difficult for marketers to demonstrate the immense value of AI tools in achieving campaign results. 

AI marketing generally improves customer experience and brand reputations in ways that can be hard to track and measure with traditional KPIs and measurement tools.

What are the use cases for AI marketing?

You can integrate AI into virtually all online marketing activities you undertake. Here are some of the most popular use cases of AI in marketing.

Ad targeting and ads media analysis

Every marketer knows that precise targeting is the key to generating ROI on a marketing campaign. However, defining your customer persona and how to target them can take a while.

AI platforms can help you understand your target audience, create a detailed customer persona and recommend the best place and time to run your ads.

You can also use AI tools to generate and optimize Ad copy based on online behavior and preferences of your audience.

Even better, there are AI analysis tools that will predict ad performance before they even go live. This prediction will ensure you don’t waste your budget on irrelevant ads that can repel customers and hurt your brand reputation.

When it comes to ad targeting and analysis, AI marketing can help you:

• Analyze your ad content before it goes live
• Generate insights from previous ads
• Use data to improve performance metrics and conversion rates
• Eliminate the guesswork by choosing relevant advertisements that work and convert
• Track ad performance during and at the end of ad duration.

Social Listening

Social listening means tracking online mentions of your brand and leveraging them to boost brand awareness. Doing this manually is time-consuming, inconvenient and often leads to errors.

AI platforms do all the heavy lifting by capturing online brand mentions and collating the results into one central platform. You can sift through the data and select the social engagement to leverage.

AI tools for social listening can help you.

• Discover social media trends you can repurpose for your messaging
• Discover potential leads from online brand engagement
• Understand why people mention your brand online
• Highlight the best influencers to work with
• Improve audience engagement on your social media content
• Address poplar issues or complaints mentioned by customers on social channels
• Monitor online brand awareness and social media performance
• Track keyword engagement and social mentions 

Sales forecasting

The key to earning more sales is meeting and exceeding customer expectations. AI marketing tools allow marketers to understand customer needs and expectations and use their findings to create the best customer experience.

Through AI systems, marketers can predict what customers will likely buy next and the brands and models that interest them the most. This predictive learning helps them to recommend products that could lead to higher sales.

 This way of leveraging Al helps businesses to balance their inventory to avoid overselling or selling out-of-stock products.

Sales forecasting AI tools can help you:

• Determine what steps to take to meet customers’ expectations and earn more sales.
• Understand customers based on online behavior and past purchases.
• Predict what customers are looking for in your online catalog.

Content Generation

AI writing tools can aid content creators in creating more compelling online content and marketing copies. 

While online content relies on human creativity, content creators can use AI writing platforms to generate and optimize content for blogs, websites, social media, and other publishing platforms.

Furthermore, they can use AI tools to automate specific tasks like social media content curation, email marketing subject lines, and ensuring content is free from errors and biases.

Other benefits of using AI content tools include

• Creating fresh social media content that increases your followers’ engagement.
• Moderating and generating an error and bias-free content.
• Quickly search online for content ideas.
• Highlight keywords that align with the target audience.

AI-enhanced PPC advertising

PPC advertising is often a bidding game. Marketers are leveraging AI to get the best ROI from PPC advertising. 

They also use it to track more advertising platforms than is humanly possible to get the most profitable PPC ad opportunities.

Other benefits of applying Artificial Intelligence in PPC (pay-per-click advertising) include

• Smart bidding
• Responsive ads
• Price optimization
• Dynamic search ads
• Performance analysis
• Account management
• Micro-moment targeting

Chatbots

Chatbots have become the poster child for AI marketing as they represent how AI can help businesses. Many brands employ chatbots to actively engage their web visitors and offer recommendations that turn them into customers.

Many businesses employ chatbots on their online store, landing pages, live chat support, and social media, primarily through Facebook Messenger.

Chatbots answer customer queries, provide helpful info to visitors, and direct complex issues to human support agents. This approach offers many benefits, such as 

• better customer service
• reduces the response time for each customer interaction, 
• builds customer relationships, 
• boots brand trust, 
• creates personalized and tailored content
• gathers data for marketing purposes
• reduces overhead customer service costs for businesses, and 
• allows the customer support team to focus on complex issues.

Generate Landing Pages

Many AI tools, such as Copysmith, allow you to generate landing page copy. You can start by selecting a template and customizing it to your needs.

AI-generated landing pages can help you:

• create compelling ad copy quickly;
• help you achieve your business goals more efficiently; 
• teach a new niche market; and
• generate specific data and insights.

Dynamic Pricing

Dynamic pricing (also called personalized pricing) is a pricing strategy wherein a product’s demand determines its price. The price automatically increases when the product gets into high demand, and when demand is normal, the price stays the same or goes lower.

Both eCommerce sites and other customer service brands use dynamic pricing. Companies like Amazon, Airbnb, and Uber are some of the companies that use dynamic pricing to reflect supply and demand for their products and services.

AI-powered dynamic pricing monitors your predictive analytics use cases such as cookies, history, searches, and other activities. It combines the data with inventory demand to determine your best prices.

On the one hand, this might seem unfair. After all, you might get higher prices for services and products that you need urgently.

On the other hand, dynamic pricing works to your benefit. You can get a product or service at rock bottom prices if there is little or no demand. For instance, if a hotel room is vacant for a long time, dynamic pricing can reduce costs to attract customers.

How To Use AI For Marketing

We’ve explained how Artificial intelligence works in marketing and its benefits. It is time to implement it. Here are six points to help you get started.

1. Establish your goals

Like every other aspect of your business, you need to aim to integrate AI into your existing marketing systems. Ask yourself the following equations. Your answers will help you set clear AI marketing goals.

• What do you want to achieve with AI marketing technology? Do I want more customers, improved marketing systems, broader audience reach, and so on?
• How will AI marketing technologies help my marketing team and customers? Will it save time and improve the customer buying experience?
• What is my budget for using an AI tool?
• Do I have quality data and the necessary skill set? Are there no-code AI tools that every member of my marketing tool can use to achieve our marketing goals?

2. Research and comply with data privacy standards

Depending on the nature and location of your business, you may need to find data privacy standards that apply to your company and implement an AI marketing platform. Most AI platforms don’t have inbuilt compliance, so you must ensure you don’t go beyond acceptable data use because of data acquisition and implementation. 

Ensure that you comply with regulatory rules and best customer data use practices when employing AI marketing platforms. You can also develop in-house data usage policy to maintain compliance and boost consumer trust.

3. Collect high-quality data

Getting quality data is the most crucial aspect of implementing AI in marketing. You need to ensure that the data are clean, accurate, and up to date. The quality of the data you feed into an AI tool determines the quality of actionable insights you get. 

You should also note that more data doesn’t always mean clean and actionable data. We recommend you focus on credible sources while building your database with data from your marketing campaigns, CRM, social media platforms, and websites. 

4. Maintain data quality

On the one hand, you should constantly monitor your data sources to ensure the data they collect is not misrepresented or tainted. You should also maintain and update your existing data to ensure they are complete, error-free, representative, accurate, and, most importantly, relevant.

5. Create an Integrated AI Marketing Strategy

The final step is to look for the best way to integrate AI marketing tools with your existing marketing strategy. You can use them to optimize marketing steps, automate repetitive tasks and handle labor-intensive activities such as data analysis or activities with a risk of inaccuracy, such as attribution.

Using AI makes most digital marketers find AI marketing tools most effective. Furthermore, combining AI marketing tools with effective digital marketing methods creates better measuring performance.

6. Select a robust AI platform

Once you’ve sorted out your AI marketing goals, data use policies to comply with, how to source and maintain high-quality data, and your AI marketing strategy, it is time to select an AI platform or platforms.

When selecting an AI tool, you should focus on options that:

• align your AI marketing goals;
• operates on advanced AI technology and a robust framework;
• provides broad application and functionality; and
• Falls within your long-term marketing budget.

Examples of Artificial Intelligence in Digital Marketing

Many famous companies owe much of their marketing success to Artificial Intelligence. Here are some notable examples of AI in marketing.

• Nike

Nike uses artificial intelligence to make personalized recommendations for its online customers. It also allows customers to search for products using conversational language and images without interacting with a person.

• Amazon

Amazon uses AI marketing to boost sales and provide the ultimate buying experience. Here are some instances. 

• Personalized shopping recommendations: Amazon provides customers with customized product recommendations that lead to a more enjoyable shopping experience. These recommendations rely on the customers’ historical purchases or similar products at different pricing points. The goal is to offer customers helpful information to help them make the purchase decision much more straightforward.
• Dynamic pricing: Amazon also employs dynamic pricing to gain the first-mover advantage when offering products to customers before the product launches in the competition stores. So instead of inundating customers with rapid price changes, the eCommerce store adjusts its pricing system based on the demand for the particular product.
• Personalized shopping: Aside from its product recommendation, Amazon also uses collaborative filtering to suggest products based on the preferences of other customers with similar shopping habits. It is the underlying technology behind the “Frequently Bought Together” feature. 
• Voice shopping: Amazon has integrated voice shopping into its marketing strategy via Alexa and Amazon Echo. Customers can now shop on Amazon without needing to type search queries.

• Starbucks 

Starbucks owes its home market and worldwide marketing success to its AI-driven marketing strategy. The company accesses data using big data analytics and Artificial Intelligence to extract key customer insights through its mobile app. 

Through this data, the company can gain insight into user behavior, know which products are popular, the time of purchases and how they compare with the competition. Starbucks then leverages these insights to create a personalized customer experience.

To ensure that their customers use the app (which is their primary source of data), Starbucks offers a Rewards Program. The company has successfully built its relationships with customers through this Rewards Program. For instance, the company provides free coffee to customers on their birthdays. 

They also allow customers to talk with the barista via the ‘My Starbucks Barista’ feature. This feature will enable customers to order coffee through voice assistance on the mobile app. 

• Facebook

Facebook is an industry leader in gathering and leveraging customer data and online behavior into actionable insights.

• Image recognition: Facebook uses advanced AI and machine learning capabilities for its image recognition technology. This technology allows Facebook to analyze images for tags and descriptions and enable precise recognition with minimal errors.
• Targeted advertising: Facebook has redefined advertising by allowing marketers to deliver ads to a distinct cluster of users. Facebook leverages advanced AI capability and deep learning to know which ads to show to whom. Through this method, Facebook allows you to choose your ads for people who will be interested, thereby streamlining your marketing strategy and saving cost and time.

Start Using AI in Digital Marketing 

AI has become a part of our daily lives, and digital marketing is no exception. Companies worldwide use AI to streamline and achieve their marketing goals.

It is up to you to join the moving train and take your business to the next level. However, it is evident that AI-powered marketing and tools are a must and not an option if you want to scale your brand.

If you want to learn more about optimizing your marketing campaigns and achieving better results, you can check out the resources in our blog.