Machine learning uses data to help predict outcomes presenting usable analytics that help prime marketers to succeed. That is the simplest way to explain it. For marketers, this is the main driving force behind things such as Facebook newsfeed ads and chatbots. It has already made an impact on how data is used to effectively improve the customer experience. This means businesses can find deeper knowledge from consumer data to greatly improve marketing processes.
The practice of collecting basic demographic information from customers to create a successful business marketing strategy is one of the past. In recent times, there has been a major shift in the way that businesses interact with their customers. The digital space has spread so far and wide that it has had a lasting influence on virtually everything we do. As a result, the conventional approaches to marketing that were prevalent even as early as a few years ago are considered severely ineffective today. The rapidly growing popularity of Big Data means that marketers need to embrace sophisticated approaches to processes and perform in-depth analysis of customer data, preferably in real-time.
Artificial intelligence in marketing uses online and offline customer data along with concepts such as machine learning, natural language processing, social intelligence, etc. to gauge your audiences' future actions. It allows you to target audiences with the appropriate message at the right time through the relevant marketing medium to guide them through the marketing funnel. In this article, we will look at how organizations can use artificial intelligence and Machine Learning (ML) in marketing to their full potential. We'll start by understanding the fundamental concepts, followed by their use cases and the benefits of AI and ML. John McCarthy, an American computer scientist, coined the term Artificial Intelligence in 1955.
Every second of every day, companies are inundated by massive volumes of data from diverse sources: sensor data, clickstream data, location data, social data, video data, and so forth. But the pace at which enterprises can leverage this data to sense and respond intelligently to customers lags well behind the pace at which data is exploding. Fortunately, advances in marketing automation and artificial intelligence (AI) are enabling enterprises to respond to the data challenge. We are at the threshold of a new era in marketing that I call sentient marketing - a vision for customer engagement that is powered by data, scaled with automation, and personalized through AI. Sentient marketing is a set of capabilities and processes that enable enterprises to create personalized customer engagement at scale and in real-time.
AI and machine learning are making the customer experience more personalized and contextual than ever before. Banks and credit unions are using advanced technology to make websites, emails, digital advertising, social media and other content more efficient and effective. This is increasing marketing ROI as well as customer satisfaction. Subscribe to The Financial Brand via email for FREE!There is a great deal of discussion of the potential value of artificial intelligence, machine learning and robotics in banking. Unfortunately, much of the implementation of these technologies lags the potential by a significant margin.