As the market becomes increasingly volatile, it helps to secure tools that help you grow with the rapid changes, most of which were previously unpredictable. 

Artificial intelligence (AI), big data and analytics, machine learning (ML), natural language processing (NLP) and other advanced AI platform solutions are helping marketing teams and organizations optimize their campaigns, reduce risks and increase their return on investment (ROI). Artificial intelligence consultants advise high-level organizations to use AI data analytics in their marketing operations to make better predictions. In summary, AI is the future if you want to stay competitive.

This article considers how AI contributes to marketing in the current economic and social structure and offers best practices to help you develop an AI marketing strategy that boosts performance.
 

Artificial Intelligence Marketing at a Glance

AI marketing has emerged as an essential component of marketing that leverages AI technology to understand consumer behavior and implement strategies that suits their needs.
 

AI utilizes big data analytics, ML and other advanced processing technologies to learn about the audience, which helps organizations make decisions that dovetail with their goals and clients’ needs. AI tools rely on large volumes of data to enable them to make predictions and grow — the more they gain access to valuable data, the better they become. That is why 63% of advertising technology leaders in the United States are utilizing AI to navigate the turbulent future of advertising.

Top marketing agencies and departments understand that data is only helpful if understood within context. This makes it clear why corporations that demonstrate high revenue growth is more likely than their competitors to utilize AI in their marketing efforts. It allows them to identify patterns and connect data that optimizes campaign execution.  

AI marketing is crucial because traditional marketing strategies are limited in areas where consumer behavior changes rapidly — which is the case in many industries today. With AI marketing, you can follow the trends to know which areas to target and how to approach those avenues. These tools allow you to implement marketing campaigns that boost your ROI. Whether you are focusing on content generation, web design or pay-per-click (PPC) advertising, you can use AI to automate the process. 

For example, when it comes to email campaigns, most entities gauge success for email activities depending on clicks and open rates. AI takes email campaigns to the next level by helping you make decisions based on facts rather than guesswork. It also allows you to send personalized emails to multiple recipients, even according to their time zones and demographics. 

AI technology can be semi or fully automated depending on the level of freedom and responsibility you give to the software. Semi-automated marketing AI tools allow humans to have some control over the system and processes. On the other hand, fully automated AI marketing software reserves control over developing, designing and implementing those strategies that drive results. Fully automated AI tools are primarily used in limited instances, at least for now. 

Unsurprisingly, some have criticized the broad application of AI in marketing because they replace human efforts in marketing. On the contrary, AI allows the marketing team to have better insights into the market structure and approach prospects with products and services that are useful to them. It reduces waste and maximizes resources. 
 

Marketing and AI Technologies 

Artificial intelligence helps organizations streamline marketing operations and optimize their campaigns. It also eliminates human errors and enables you to connect better with your customers. Let us consider the various AI technologies and how they contribute to marketing in more detail. 
 

AI Technologies

 The common AI technologies include the following:

• Machine learning: This technology uses algorithms and statistical models to analyze and make predictions from data patterns, allowing computer systems to learn and adapt without explicit instructions. It eliminates the guesswork by capitalizing on vast amounts of data to provide objective insights. You can then apply these insights to personalizing services, media buying, audience targeting and other marketing segments. 
• Natural language processing: The technology builds machines that understand, interpret and respond to speech and text as humans do. Marketers use it to extract meaningful information, such as personalities and consider moods from social media and other platforms. Marketers and developers also use them for automated communication integration in software like chatbots. 
• Computer vision: This field of AI enables computers to derive meaningful information from digital images and videos to take action and make recommendations. It trains computer systems to perform functions akin to human visions, only that they utilize cameras, algorithms and data — they help marketers see better. Computer vision performs multiple marketing tasks such as brand logo tracking, consumer emotions logging, customization and original content generation. 
• Neural networks: Stimulated neural networks (SNNs) or artificial neural networks (ANNs) are crucial components of deep learning algorithms. They help marketers discover complex patterns in human behavior and group them into digestible cohorts, enabling proper content strategies. Marketers are, therefore, able to understand complex consumer segments, automate marketing and improve sales forecasting. 

 

Applications of AI Technology in Marketing

The various facets of AI technology have numerous applications in marketing. It is essential to delve deeper into the different aspects of marketing that AI improves:

• Content creation: Content marketing is the most effective digital technique and AI can help marketers create various kinds of content, such as blogs, articles, marketing materials, videos and product descriptions. Human content creators also use AI for advanced keyword research and other tools to boost content performance on the internet. 
• PPC advertising: AI is useful for executing PPC campaigns, especially on a large scale. AI-powered PPC tools enable competitor, audience and keyword research, headline optimization, ad description and more. ML helps marketers, in-house or agency, locate new ways for optimizing layout, copywriting, bids and targeting. 
• Web design: AI’s capabilities help web developers and designers enhance user experience with intelligent personalization on your website. For example, it allows you to analyze hundreds of data points about a single user according to their demographics, location, devices and website interaction to display the best-fitting content and offers. Additionally, you can enable push notifications for specific visitors to deliver the right messages at the right time. 

 

 

• Programmatic media buys: A challenging part of marketing is determining where to place messaging and advertisements. With AI, marketers can leverage machine learning to bid real-time ad spaces on channels relevant to their target audience. The result is highly accurate because it uses purchase history, interests, buyer intent and location.
• Message delivery: Different kinds of consumers have unique personalities that affect how each receives and responds to specific information. Machine learning enables you to track how consumers react to the messages sent so you can build a complete profile.
• Predictive marketing analytics: Marketing today is data intensive, with volumes of data flowing into organizations daily. This makes it challenging for marketing teams to comb manually through these resources and use them meaningfully. AI simplifies the process by combining ML, models, datasets and algorithms to predict human behavior.
• Dynamic pricing and demand forecasting: You can use the data AI analyzes to predict the demands of certain products and services and offer optimal prices that fit consumers’ budgets and spending power. As the needs change, the software adapts and makes price adjustments to suit the current market. Also, since each industry and business model is unique, the tools can be tailored to deliver the best results. 
• Chatbots: Chatbots are one of the most common AI tools currently used for marketing. Chatbots use natural language processing to augment customer service agents. Customers with queries can refer to them and receive quick, accurate responses. 

 

How to Use AI in Marketing Strategies 

 

Most digital marketers make the mistake of applying various AI tools to develop marketing solutions without embarking on careful evaluations that optimize their usage. Although AI is beneficial, its application may not automatically guarantee successful campaigns. Therefore, It helps to plan and execute carefully to achieve the desired results. The following should guide you:
 

1. Establish Your Goals

Your organization’s goals, visions and objectives should determine the AI tools you need to address specific areas of your business, not the other way around. You want to avoid situations where you adopt specific AI tools merely because they are growing in popularity and everybody is using them or because they look attractive. Although that approach may coincidently lead to some progress, it is not the recommended starting point. 

Lay down your organization’s goals to clearly define what you want to achieve. Then assess the areas or gaps you want the AI systems to assist you in scaling. Establishing clear KPIs helps you assess the success of AI-augmented marketing campaigns and is essential for qualitative goals. 

Integrating AI marketing tools into your existing marketing strategy and company structure is essential rather than creating a stand-alone unit. The tools are more efficient when well-integrated with the rest system. The reason is that there is less friction and conflict between various structures and departments. Also, the new AI marketing system boosts the performance of the previously established frameworks.
 

2. Identify Data Sources and Quantity

AI is a data-hungry system, which means you must have large volumes of data at your disposal to get started with AI marketing. The data helps the system to make accurate analyses and predictions and helps them grow through the ML process.

AI has two types of data sources — primary and secondary. Primary data sources are those originated by the researcher. Examples include data from customer relationship management (CRM), enterprise resource planning (ERM), previous marketing campaigns, organization’s website data and surveys. 

Secondary data sources are already existing data collected by organizations and agencies to conduct analysis. Classic examples are government publications, publications by independent researchers and organizations, journal articles and staging websites. Third-party data may also include location, weather data, demographics and other information that can influence purchase decisions. 
 

3. Secure a Data Science Talent

Gathering sufficient data is only one part of the AI marketing process. It is also one of the relatively more straightforward steps. The challenging part involves using the data collected to make informed decisions. It is vital to secure a data science talent with expertise in sifting out quality data and using them to generate accurate predictions.

Third-party technology organizations have the resources to perform data management, collection and analysis tasks at a high level. Employing such services is an excellent way to get your AI marketing programs off the ground. 
 

4. Maintain Data Quality

AI analysis and predictions are as good as the data with which you feed them. In other words, ML and AI marketing systems rely on data to work, learn and grow. The system performs best when provided with quality and error-free data. When assessing the quality of data, it is crucial to take into account four factors. These are integrity, accuracy, consistency and completeness. 

Implement standard quality assurance methods, which include setting benchmarks and auditing frameworks. Enable precise controls to provide an in-depth quality assessment and use high-quality training data to mitigate bias. 
 

5. Set Your Privacy Standards

Data privacy is a topical issue in AI-backed operations because of its sensitivity. While your system accumulates, stores, processes and uses data to perform its functions, ensure that it complies with privacy standards and policies. This helps improve your organization’s brand by retaining trust and mitigating legal hurdles. 

Put data privacy at the core of the developer’s radar and reinforce security effectively. Remove all identifiers and unique data points and limit control and access to the information within the organization. Also, continuously audit how the data is accessed. Another essential consideration is testing your algorithm to assess how much data is sufficient to perform efficiently. 
 

6. Partner With a Trusted Technology Expert

Securing the services of an AI solutions expert with business operations and marketing knowledge can help you increase your ROI. Such professionals have the resources and personnel to help you design a model tailored to your business needs. This is crucial because it takes the load off your shoulders, allowing you to concentrate on other essential tasks. 
 

AI Marketing Predictions and Trends 

Since its inception, AI has made tremendous strides in the marketing industry. We continue to see significant technological advancements and can only expect them to get better and more sophisticated. Here are seven AI marketing predictions and trends:

1. AI systems will continue to grow and be employed in business operations in the U.S. It is estimated that the market for AI in marketing will value more than 107.5 billion dollars by 2028. 
2. Eighty percent of marketers believe that AI is a revolution rather than a trend that will revitalize how industries approach their work.
3. Sales and marketing departments prioritize ML and AI for the success of market revenue 40% more than other industry departments.
4. Over 40% of marketers agree that AI email marketing improves market revenue.
5. Marketing companies, sales departments and customer services roles rely on process automation to increase their market revenue share. AI software will perform the repetitive and tedious market tasks such as data collection and analysis. This is necessary to reduce human errors that often result from fatigue and stress and can generate faster and more accurate results at a reduced cost.
6. AI transforms corporate operations by helping them generate high revenue with easier monitoring and evaluating the end-to-end value chain through digital transformation. 
7. AI helps marketers mitigate security risks by studying network patterns to detect suspicious activity. This will cause the advancement in AI in cybersecurity over the coming years.

 

Is AI a Part of your Marketing Technology Stack? 

Incorporating AI into your marketing strategy allows you to yield optimum results. It reduces costs, mitigates risks and human errors, streamlines operations and helps you stay competitive. Marketers leverage AI and ML in content generation, PPC advertising, web designing, predictive marketing analysis and aspects of marketing to provide personalized customer service and maintain a high conversion rate. Ensure you implement AI marketing strategies that meet the best standards and practices to receive the full benefits. 

BDO Digital is a world-renowned digital strategies company that helps clients thrive. We work with high-level executives across various industries to offer premium digital solutions. Contact us now to help you develop your marketing technology.