Mass Personalization with Customer-Centric Technique: Artificial Intelligence

AI_Mass Personalisation

The marketing campaign is used to be considered as promotional activities, which is now drawing more attention in the digital era because each action made by the organization can be closely observed by the customers just with a few clicks. Besides, if the decoded message conveyed by the campaign has havoc, it will not only plummet the sales but also deteriorate the brand equity. In addition, the generic practice was followed to deal with tens and thousands of customers in conventional marketing activities that are losing their grip on understanding the customers and their engagement.

Fortunately, the latest technologies have facilitated the marketers to reach a wider audience with a personalized approach based on the behavioral data gathered over a period of time. The customer-centric technique has a higher chance of success in conversion of audience to buyers who can be transformed into loyal customers if their emotions are understood well. Digital marketing has its own significant advantages in coping with customers with respect to what device they use, where they locate, in which product they spend a maximum time, etc. Due to these benefits, digital marketing campaigns are growing in leaps and bounds. As per the Global Media Intelligence report published this year by eMarketer, the budget to expend on advertising on digital platform will be hiked up by 2.4 percent and smartphones will be the one that predominantly contributes to the digital device platform globally.

On the other hand, personalized shopping is gaining popularity. For example, if the search results shown by the search engine are personalized based on the users’ browsing history and explored results by some other users with similar interests, the experience of the customers will be pleased and also it saves their time. For each user, a separate profile is created based on the interest and preference given by the user paving the way for developing user interest hierarchy that can be used for collaborative filtering. These profiles are used by the algorithms to analyze and recommend the right results for the right user at the right time.

Artificial Intelligence has taken the personalized approach to the next level with respect to online advertising, spam detection, conversational bots and others. Machine learning, a subset of artificial intelligence, has advanced various applications, namely, customer targeting, automated online advertisement, automatic speech recognition and natural language processing.

For instance, Google uses machine learning to create creative assets for online advertisements, to do automated bidding and to make various automated elements. Most of the e-commerce sites have started using machine learning to enhance the customer experience by providing the specific product category with customized discounts. These discounts are not same for all users, which are particularly designed for distinctive users shown only for a specific time span. Handling millions of customers with unique features to serve them is not feasible at all with a limited workforce; however, artificial intelligence plays a vital role to tackle this problem. In other words, this kind of mass customization would not be possible without this advanced technology. Hence, we should deploy artificial intelligence as much as possible in all fields to have a better life experience.