AI In Marketing: Harness The Power Of Automation In 2024

Marketers are often stuck with questions such as: Can we use AI in marketing? How can we use AI in marketing? etc. Today, in our blog, we have answered all of these questions, enabling you to harness the power of artificial intelligence. Since AI has entered our lives, it has become an inseparable assistant in automating all repeatable tasks. Approximately 8 0 % of marketers now use AI to improve their teams’ efficiency; why should you be left behind? Delve into the blog and learn about the usage of AI in marketing.

Table of Contents

What Is AI In Marketing?

AI in marketing refers to harnessing the power of artificial intelligence to automate a task that would otherwise have taken much more time. Speed matters a lot in marketing, and that is where AI comes into the picture, with its ability to analyze data and read economic trends. It can enable quick and effective decision-making.

Let’s check the multi-dimensional use cases:

Data Analysis: It eliminates the requirement of manually sorting the data collected from different marketing campaigns and programs.

Media Buying: One of the major concerns for marketers is ROI (Return On Investment) on advertisements or campaigns they are about to launch. With AI tools, you can easily predict the best media for your marketing campaign, providing you with the best ROI.

Automated Decision Making: As discussed earlier, it automates your decision-making by analysing historical data and external inputs.
Others: It can also help you with real-time personalisation, natural language processing, content generation, and other tasks.

Types of AI marketing solutions

There are various types of artificial intelligence marketing solutions that you can choose from as per your requirements:

Machine Learning: Various machine learning tools use advanced algorithms to analyse historical data and provide the most effective strategy based on that data. Thus, they save time, money, and energy and enable users to avoid past mistakes.

Big Data and Analytics: Data is the new fuel that is a prerequisite for developing any effective strategy. However, as we advance in the digital age, extracting important details from the data has become quite cumbersome. This is where marketers can use AI to crunch this pile of data into something tangible to build a solid marketing strategy.

AI Marketing Tools & Platforms: These are various micro AI tools that can be used in marketing tasks, such as generative AI for content generation. Content marketers widely use tools like Grammarly to improve the quality of their content.

How Is AI Changing Digital Marketing?

Centralised Data: We have constantly mentioned using AI to crunch data into meaningful information. But that’s not all AI can do with data. It can even collect data from various sources and store it at a centralised location.

Virtual Agents: These are the AI-powered chatbots that work around the clock for customer support. They not only just chat but also collect user data and leverage it to improve the customer experience and sales.

Targeted Lead Generation: AI can easily crunch large chunks of data into tangible profiles to build robust profiles and social media trends for more focused lead generation campaigns.

Timely Messaging: As mentioned earlier, it crutches and collects the data. AI used in marketing collects data on clients’ behavioural patterns and determines the best ad delivery time. By sending messages when clients are most receptive, AI helps optimise campaign ROI and ensures timely and relevant customer interactions.

How to use AI In Marketing

Establish Clear Goals: To use the AI tool effectively and efficiently, establish clear standards for measuring its performance. You must think of AI as just any other employee who needs to accomplish certain goals that are part of your plan. It becomes crucial for you to set KPIs (Key Performance Indicators) for qualitative analysis, such as customer satisfaction.

Adhere to Data Privacy Standards: When feeding data to your AI model, ensure that you do not breach regulators’ rules and conventions. Establish a strict policy around data consumption and usage so that you do not blur the line between ethical and unethical.

Consider Data Quantity and Sources: AI in marketing typically requires a good amount of data to deliver results. This will help the AI marketing tool learn about customer preferences, external trends, and other factors that influence the success of AI-enabled marketing campaigns. You can also supplement this data with second—and third-party data, such as location and weather data, to incorporate external factors influencing purchase decisions.

Acquire Data Science Talent: It is unsurprising that many marketing teams lack expertise in data or AI. To unleash AI’s full potential in the market, consulting with a third-party company or organisation specialising in data collection, analysis, and training AI tools is advisable.

Ensure Data Quality: Machine learning and AI marketing programs rely on data, so it is crucial to maintain high data quality. Ensure the data fed into your AI marketing program is standardised and error-free to drive reliable insights and potentially lead to effective decisions. Before implementing AI marketing programs, your marketing teams should collaborate with data management teams and other departments to establish data cleansing.

The Challenges of AI In Marketing

Training employees: Incorporating AI in marketing can be challenging. You need to train your employees on AI marketing tools so they can use them effectively. Though AI uses advanced algorithms to perform, it also requires time and guidance to align with your organisational goal, customer preferences, methodologies, etc.

Data quality: As we have already told you, AI feeds on data! Hence, it is necessary that you provide your AI tool with high-quality and relevant data. By high-quality data, we mean that it should closely align with your customer preferences, reviews, etc., to create effective marketing strategies.

User data security and privacy: Another crucial dilemma between marketers is what data to use and what not to. With AI, there is a rise in various organisations, such as the General Data Protection Regulation (GDPR), which has imposed strict guidelines for using data collected by AI. Hence, it becomes the duty of the digital marketer to use data ethically.

Employee adoption: It can be hard to convince top-level management to invest in AI software, and it is also quite difficult for employees to adopt AI. Though quantifiable metrics like ROI and efficiency are easily measurable, demonstrating AI’s impact on customer experience and brand reputation requires the right measurement tools. It becomes crucial for the digital marketing teams to effectively communicate the value of AI marketing investments to business stakeholders and provide training and support to facilitate employee adoption.

Developing best practices: AI is a technology of today; hence, its long-term consequences are not known yet. Therefore, it becomes the duty of the digital marketer to think strategically before making any final decisions.

Wrapping It up

We hope to provide comprehensive details on using AI in marketing; AI is a rapidly growing technology used in marketing across various business domains. If you want any other details on the upcoming tools and software in finance, the market, or any other industry, comment below.

Frequently Asked Questions

What is the best example of AI in marketing?

Netflix using AI personalization for movie recommendations and Wowcher using AI personalization to create social media posts and ads are some of the best examples of AI in marketing.