Marketing could possibly be the biggest gainer from artificial intelligence when compared to all other business departments. Understanding consumer requirements, matching them to services and products, and convincing them to purchase – these are the three main functions of marketing, all of which AI may significantly enhance.

Chief marketing officers are using technology more and more frequently. Three of the top five AI goals were marketing-related, according to a Deloitte worldwide study of early AI adopters: improving current offerings, creating new services and products, and strengthening relationships with customers.

Despite the advancements that AI is making in marketing, in the future, we believe it will play an increasingly significant role across every aspect of function. If you are looking to adopt AI in marketing, here is what you need to know.

What is Artificial Intelligence (AI) in Marketing?

To predict your customer’s next move and improve the customer experience, artificial intelligence in marketing (AI Marketing) leverages customer data and AI fundamentals like machine learning. AI in marketing has two benefits: faster operations and better intelligence/insights.

AI is a tech tool B2B marketers are using more and more. Because AI plays a role, data is analyzed more quickly and accurately, providing insights that may be used to develop campaigns that are more successful. AI may assist marketers in identifying the accounts that are most likely to convert when using account-based marketing.

To guarantee optimum efficiency, AI marketing solutions analyze data and customer personas, and buying journeys to discover how to engage with them most effectively. They then give them personalized messages at the right moment in time without help from marketing teams.

Many B2B organizations now employ AI to support marketing teams’ decisions or to carry out more tactical duties that do not require a lot of human finesse.

Where to Use AI in Marketing

You must be familiar with the most common uses of artificial intelligence in marketing if you are new to the discipline. Fortunately, AI today needs zero coding effort and is available to deploy as ready-to-use tools or embedded features. You can use artificial intelligence for:

• Making sense of data: Massive volumes of marketing data from numerous campaigns and programs may be simply gathered and sorted by using AI. Alternatively, this would have to be manually sorted.

• Paid campaigns: AI forecasts an organization’s most profitable media and advertisement placements. This increases the ROI of your marketing plan and helps you reach the demographic you are targeting.

• Business intelligence: AI marketing solutions assist businesses in selecting the most effective marketing or business expansion strategy on the basis of historical data or external data sources.

• Text recommendations: Long and brief elements of content may be created using sophisticated artificial intelligence for marketing strategies. This might apply to blog posts, online material, email headers, video subtitles, and more.

• Natural Language Processing (NLP): A human-like language is currently being created by AI-based technologies for chat creation, customer support bots, experience personalization, and other applications.

• Personalizing CX: A website, social media post, or email are instances of marketing assets that AI automatically adjusts for the benefit of the customer. It personalizes the CX as per the buyer’s previous decisions and encourages certain actions, like clicking on links, signing up for products and services, or making purchases.

Download – Whitepaper (What Does AI Have to Do With Marketing?)

Getting Started with Artificial Intelligence in Marketing: What Are the Options?

For companies implementing AI in marketing for the first time, there are, essentially, three ways to go about it: install a marketing AI app, use an AI feature in an existing marketing software, or use an AI-enabled task automation tool.

1. Install a marketing AI app

The easiest way to think about these is as distinct or precisely defined AI programs. They are different from the main channels via which your customers discover, purchase, or get help for utilizing your services, as well as from the paths you use to promote, offer for sale, or provide support for those offerings. For example, one can look at Jasper, a technology that uses the GPT3-model to create marketing content that seems natural or Optimove, an AI tool that maps the CRM journey using multidimensional data.

2. Use an AI feature in an existing marketing software

These AI apps are frequently less apparent to consumers, marketers, and salespeople than stand-alone ones since they are integrated into already-existing systems. For instance, platforms that manage the whole process of purchasing and placing promotional content have AI and machine learning embedded that makes split-second judgments on which digital advertisements to show consumers.

CRM system manufacturers are progressively incorporating machine learning features into their designs. One of the features of Salesforce’s Sales Cloud Einstein suite is an AI-based lead-scoring mechanism that evaluates B2B client leads based on their chance of successfully completing a transaction.

3. Use an AI-enabled task automation tool

These programs carry out systematic, repetitive tasks that only call for a small amount of intellect. They can carry out activities based on a fixed set of rules or run an operation as per a predefined sequence – but they cannot manage complex tasks like layered and sophisticated customer requests.

A program that promptly sends each new client a welcome email is one example. This category also includes simpler chatbots like those offered by Facebook Messenger along with other social media platforms. This type of AI in marketing is often used in contact centers to automatically make recommendations to callers.

“Can I Use Generative AI in Marketing?”

This is a frequent question among B2B marketers in 2023, as generative AI tools such as ChatGPT and Bard are disrupting the industry. The short answer is yes, and there are three compelling ways in which generative AI could potentially be used in B2B marketing.

1. Ask ChatGPT to generate low-volume and long-tail keywords

Traditional keyword analysis employs a variety of techniques, but they all involve human labor. Platforms like ChatGPT may make keyword study more efficient for marketers. For instance, the command “List the five most important semantically associated words and concepts for the (X) sans description” retrieves the keywords that have the closest relationship with the given subject matter.

2. Incorporate AI-generated content into your campaigns

The process of generating content requires an extensive amount of labor, much as keyword research. Marketers have never-before-seen opportunities to enhance every aspect of content creation and distribution using ChatGPT and other comparable platforms. These models may provide content that seems human-composed while maintaining the brand’s tone of voice and identity.

AI must be balanced with an additional level of human oversight, however. Although these models assist in accelerating the development of material, human context remains essential for ensuring coherence, reliability, and cultural significance. Additionally, not all scenarios—like those involving journalistic or organic articles—will be appropriate for AI marketing.

3. Perform advanced data analysis (some technical effort involved)

A new age of marketing data visualization is being ushered in by generative AI models. These techniques allow for the building of complicated network visualizations, real-time data tracking, and dashboard building. This type of AI in marketing, however, does require specialized plugins and the knowledge of how to use them.

For instance, OpenAI’s ChatGPT introduced a plugin named Code Interpreter in March 2023. You can add data files to the Alpha version and use Python to carry out regression and descriptive analyses, hunt for trends in your data, or even produce visualizations if you are granted access to the Alpha variant. We can expect more tools in the area very soon.

Conclusion: Watch Out for 5 Factors when Implementing AI

Like any technology, the use of artificial intelligence in marketing comes with a few caveats. Remember to:

• Be patient while training the AI: Artificial intelligence (AI) marketing technologies are not programmed to instantaneously understand what is required to accomplish marketing objectives. To learn about organizational goals, consumer preferences, and historical patterns, grasp the broader context, and develop competence, they need time and training.

• Quantify the value you expect from AI: It may be challenging for B2B marketing teams to obtain support from corporate decision-makers. While KPIs like ROI and efficiency are simple to measure, it might be harder to demonstrate how marketing using AI has improved client experience or brand reputation.

• Invest in privacy since AI is data-hungry: Teams in charge of digital marketing must make sure they are handling customer data responsibly and in conformity with regulations like the GDPR.

• Think long-term: Since AI is a more recent acquisition in the B2B marketer’s toolkit, there aren’t currently any well-established best practices. Consider more than merely the immediate advantages when thinking about the long-term impacts of AI in marketing.

• Prepare for a culture shift: The daily activities of marketing are being altered by the rise of AI marketing. Marketers have to decide which tasks must be eliminated and which ones are to be added on/expanded.

AI can play an important role in your B2B marketing strategy, and it is necessary to overcome AI marketing fears to achieve the best possible outcomes. Eventually, as AI becomes ubiquitous, marketers that do not use this technology will risk falling behind in a future that’s defined by AI in marketing automation.