Blog

How AI And ML Can Improve Marketing Analytics

Introduction

For any business to prosper, it is essential to maintain proper ties with the customers. These ties could be supported by understanding their needs and desires and delivering the products with the same sophistication. Having a firm grip over the thought process of the customers helps companies to have a profitable business. Whether it is a business in the IT sector or not, the critical factor in growing the sales of any product is to cling to the right set of customers by guessing their choices.

Considering the IT industry, ever since the inception of computers, the technological world is evolving every day. These evolutions have brought together many businesses by creating various algorithms that help people understand and guess a customer's purchasing habits, desires, and needs. This is achieved using complex algorithms, namely Artificial Intelligence (AI) and Machine Learning (ML).

What is Artificial Intelligence And Machine Learning?

The terms Artificial Intelligence and Machine Learning are used quite a lot these days when promoting an electronic product of sorts. The most common example of this is when a new TV is launched; one of the prominent features is upscaling the image using Artificial Intelligence. AI, in layman terms, means the ability of a computer or a machine or a robot to perform actions like a human being, such as mimicking perception, learning, solving problems like a human, and decision-making capabilities alike. As the name suggests, for all the tasks that a person can perform, a machine could perform the same but with a shortcoming of emotions and consciousness. Feelings cannot be mimicked by the device or understood; rather, the machine can learn from the behaviour of a human whether the person is angry, happy, or shows some other emotion.

Machine Learning, on the other hand, is an algorithm similar to Artificial Intelligence, but unlike Artificial Intelligence, it doesn't require explicit instructions to improve itself; rather the algorithm learns and adapts itself by learning from the previously inputted data. If we were to compare Machine Learning and Artificial Intelligence, Machine Learning is a subset of Artificial Intelligence. AI can do everything that ML does but not vice versa. Though, Machine Learning is a superset of Deep Learning. An example of Machine Learning is the Speech Recognition ability. It could be used to translate the spoken words into a textual format.

What Are the Benefits Of ML and AI?

Discussing the benefits of Machine Learning is used by the e-commerce giant that delivers products throughout the globe to distinguish and analyze apparent patterns of an individual on its website or the application. This gives an insight into the sales of any of the products in their catalogue to the seller and puts forth suggestions for the customers about the products they might like and paraphernalia. This requires no human intervention and is automatically analyzed by the algorithm.

As the algorithm gains more data, it keeps on changing and adapting the algorithm to perform tasks with great simplicity avoiding any further development by the coder or the developer.

Artificial Intelligence, mainly an algorithm of Machine Learning, is better at performing and providing valuable data. It keeps on learning from the previously gathered data and, unlike a human, has next to zero errors if the algorithm is programmed right. Apart from being factually correct, AI helps reduce the workforce as it is available 24x7 and can be used to perform the same tedious and monotonous process repeatedly without being bored and tired.

Deploying Digital Assistants, developed using AI, helps large companies cut costs on their customer care team by gathering the information from a customer beforehand and then connecting to the customer care executive.

Implementation of ML And AI For Market Analysis

An average joe these days relies on high-end customization and personalization of any product they use. If the consumer's application has no positive impact on the consumer at the first encounter, they may try and find other alternatives. To provide the consumers with a seamless experience, right from the first encounter to checking out a product, ML and AI come in handy. Embedding AI and ML in the integrated marketing solutions and platforms help the marketer study the dynamic exhibition of customer's activities across the platform and derive optimal insights into a customer's patterns.

Long gone are the days of targeting certain individuals by the spray-and-pray method. With the onset of modern techniques, ML and AI can target an individual with ads of their liking and concern. To market a product, the company needs to analyze a vast amount of data, conceptualize it, translate it into meaningful data and display it in a contextual format.

The gathering of the said data and analyzing it is done by collecting data through various channels, on the user end such as web browsing, logging data of the consumer with their consent, or their patterns on multiple websites.

Examples Of AI And ML In Marketing Unit

The best example of AI and ML in marketing is e-commerce websites. As a person browses through the product catalogue, the ML tracks the footprint of the browsing history and decodes a pattern. After understanding this pattern, the AI generates lists of sponsored products and ads to display on the homepage whenever the consumer revisits the website. Suppose a person visits a website for a particular product after browsing for a while and not purchasing the product. In that case, it will be displayed as a targeted ad to the consumer on various platforms to buy it later and sometimes with a slight discount from competitors.

Pricing of a product also depends on various factors, and in the competitive market, the data regarding the purchase and selling capabilities of a product are determined using AI. The pricing is accounted for in real-time. Another factor that keeps a business afloat is by managing the logistics and supply chain. Machine Learning is used to forecast the demand of a product to maintain inventory to tap the market correctly and prevent the business from losing out to the competitors. This also saves a ton of costs to the company.

People barely visit the second page of a search engine. To accurately display the content a person searches for on the first page, it is obtained using Machine Learning by various search engines and the industry giants. Years of data are analyzed to understand what a person wants to get in the results searched for, whether an answer to a question, a weather report, etc. Apart from web results, an eye-catching subject to an email can also be generated using Artificial Intelligence.

To assert dominance over the market in the respective field, a business must gather as much information as possible and analyze this information to develop products and services that will garner some cash flow. Having people look into the dynamic data will only increase the workforce and costs for the business. Implementing an algorithm, Artificial Intelligence will save the vast business loads of cash and resources and focus primarily on marketing to the individuals of interest and investing in research and development of a product.

Conclusion

Whether you're a businessman or not, more likely than never, one has encountered an instance curated specially for you as suggested by an Artificial Intelligence. Targeting an audience in the modern-day and age has become profoundly easy with the help of these tools. Regarding marketing and its strategies, it is essential to maintain a set view of an individual consumer and keep track of their interactions through the ecosystem of partner businesses.

Achieving this is only possible through blockchains. Blockchains help in sharing data to partnering business and other business if need be and provides a good insight into the brands and even customers. Introducing blockchain and Artificial Intelligence, and Machine Learning into marketing helps determine fraudulent data, ascertaining risks, and minimizing costs. Integrations of blockchains and ML, as well as AI, prove beneficial to the businesses right from their inception as they complement each other.

Traditional marketing tactics have since become obsolete as they provided limited insight into the consumer's buying pattern and behaviour. Present-day marketing teams are leveraging their tactics using the Artificial Intelligence and Machine Learning models and the blockchain model. The industry will continue the practice until a new and more viable option is available. A critical fact to note is that the prominent use of AI is in the marketing industry and other fields such as consumer goods, medical equipment, and an individual's lifestyle.