Artificial intelligence (AI) is often used in marketing efforts where speed is essential.
There are many misconceptions around AI-based marketing and marketing automation. Both concepts are not the same, as they both serve different purposes.
Marketing includes much more than just advertising or selling your goods and services after you have produced them. It is a broad concept that includes multiple actions such as brand building, forecasting, decision-making, customer relationship management and many others. Managing these actions becomes even more daunting when you factor in the requirements of hundreds of customers. As a result, businesses are increasingly turning to automation to streamline their marketing-based operations. There are several people who may confuse standard automation tools with the complex systems of AI in marketing. There are a few differentiating areas when it comes to marketing automation and AI in marketing. By understanding the application areas of AI-based marketing and marketing automation, we will get a better idea of their differences.
As you know, AI can be applied to a wide number of application areas in organizations. In fact, several AI applications, like chatbots, are used for the purpose of automation-related tasks too. However, marketing automation does not usually necessitate the involvement of big data analytics or decision-making. Marketing tasks that are automated are generally the repetitive ones that need a lesser degree of human involvement.
One of the main differences between marketing automation and AI-based marketing is that, unlike the latter, the former needs well-defined parameters and commands fed into a specialized automation system. Process automation systems are used to perform sequential and simple segment-based tasks, data consolidation, and the creation of reports. In short, these are the tasks that may waste the potential of human workers, who can instead be drafted into tasks that require thinking, leadership, troubleshooting, and decision-making skills. Unlike standard automation systems, AI-powered marketing tools do not need pre-defined parameters and commands to be provided to them. AI algorithms constantly undergo alterations using machine learning with the help of large datasets. For marketing purposes, these datasets are made up of the files in your product and purchase records as well as big data sourced from the world wide web to understand demand trends in the market. Using those datasets, the algorithms start learning ways to automate marketing tasks that are much more complicated than the ones that a standard automation tool handles.
The deployment of marketing campaigns is useful to how well a product or service can be promoted to its target audience. Automation allows your business to create, deploy and modify the rules and regulations of a marketing campaign based on factors such as demand trends, the production of a new product and similar others. In short, automation simplifies and streamlines the process. On the other hand, AI algorithms allow your business to create incredibly relevant and personalized marketing campaigns by closely studying the market patterns and facilitating demand forecasting.
Automation tools are heavily rule-based. So, if an automation tool is programmed to follow a certain command, it can follow it perfectly until eternity. Naturally, AI is more flexible and, therefore, is employed in much bigger and more complicated marketing tasks. There is a running theme across these differences. AI can carry out — and even improve — all the tasks that automation tools can do, but the other way around is not true. Automation in marketing guarantees speed and metronomic persistence in tasks such as segment creation, data entry, marketing campaign deployment. The involvement of AI in marketing guarantees accuracy in demand forecasting, inventory management and other extended functions of modern business marketing.
AI implementation is expensive. Therefore, businesses that can afford it use the technology only for certain tasks in which its capabilities can be put to good use. AI is not required for simple automation tasks, like auto emails, IVR and text messages. Essentially, every business would want to get the most out of their AI-powered systems, and several organizations successfully use the technology for marketing tasks. Here are some of the application areas of AI in marketing.
This is one of the more advanced and conceptual applications of AI in marketing. Next-best decision marketing is a decision-making technique that allows businesses to adopt a customer-centric approach to every type of marketing activity. Keeping the customer in mind, an AI system considers the most optimal set of actions that can be taken for individual customers before selecting the 'best' one. The so-called 'next best option' (new services, offers, products, propositions) is then determined by the system after considering factors such as product popularity, customer's interests, etc. These factors are balanced with the available resources present and the monetary viability of such options. Businesses use AI for such tasks instead of following rigid automation commands for decision-making. The next-best decision-making process mostly gets the task of selecting the optimal campaigns and segments (formulated with the help of predictive analysis) for specific customers from a large pool of options right for businesses.
The modern omnichannel retail model followed by most industry behemoths makes it mandatory for businesses to adopt a personalized approach to marketing. Unsurprisingly, personalization is one of the most common use cases of AI in marketing. AI algorithms are incredibly adept at identifying customer choices regarding products, services and offers. The decision-making process involved in personalization is optimized due to the sheer scale and speed of such algorithms. They scan the internet and the customer records maintained by your business to suggest personalization-driven next steps to marketers. Common use cases of personalization include the deployment of AI models for search result autocomplete on business websites, product recommendations, self-optimizing marketing campaigns and customized texts generated by chatbots.
Big data is another key player in marketing today. As we know, businesses maintain the records of their customers in segmented databases. This data is too vast and dynamic to be assessed and analyzed by a human being. So, organizations use machine learning and AI to gather insights from such data oceans. Machine learning algorithms can be employed to ascertain patterns in customer information before individual clusters are made based on those patterns. AI can also be used to power analytic models such as multi-touch attribution and marketing mix modeling to analyze the success rate of marketing campaigns using various Key Performance Indicators (KPIs).
Digital marketers can employ programmatic advertising to boost their ROI. Once again, AI models are used to analyze data in real-time to forecast the result of digital marketing campaigns for different segments of your target audience. With those forecasts, your business can adjust bidding and pricing strategies, and make advertising content more relevant to increase demand for certain products or services.
Generally, businesses use the services of third-party AI service providers to set up and implement the technology for marketing functions. However, shady service providers may offer simple automation tools in the name of AI-based marketing systems to unsuspecting business owners. Here are some of the common red flags that must be detected early on, so that business owners can save themselves from getting duped at the hands of scammers:
AI-based marketing systems require large and diverse datasets for training and development. If service providers tell you that their product can be implemented successfully without thousands of datasets to train on, they are lying through their teeth. You must steer clear of such service providers and suggest close business colleagues to do the same!
Use cases are a good indicator of whether a given product can leverage AI for marketing purposes or not. The real cognitive capabilities of a system can be assessed by evaluating factors such as data, training models, and outcomes.
Developing and implementing AI-based solutions is not everybody’s cup of tea. Such things are carried out by highly qualified and experienced machine learning engineers, data scientists, data analysts, and a bevy of experts. Businesses can conduct a light evaluation of the staff that is tasked with setting up the "AI" ecosystem for them. If the workers are found to be incompetent, the service provider cannot be trusted.
AI seeks to replicate the working of the human brain. So, the more knowledge an AI model gains, the better it performs in real-world marketing operations. So, business owners and certified network administrators must know how to verify the authenticity of an AI system. This is carried out to determine how well an AI model learns from marketing databases and other marketing-related operations. If the service provider cannot exhibit how their tool — deployed in other companies for marketing functions — has learned and improved over time, then it is not an AI-powered system.
As we have seen, marketing automation is just a drop in the ocean of AI-based marketing. The two concepts are not synonyms of each other. In fact, marketing automation can be considered to be nothing more than just a subset of AI-based marketing.
Naveen is the Founder and CEO of Allerin, a software solutions provider that delivers innovative and agile solutions that enable to automate, inspire and impress. He is a seasoned professional with more than 20 years of experience, with extensive experience in customizing open source products for cost optimizations of large scale IT deployment. He is currently working on Internet of Things solutions with Big Data Analytics. Naveen completed his programming qualifications in various Indian institutes.