Machine learning (ML) is one of the innovative technologies in the digital marketing industry. Many organizations started to incorporate machine learning into their products or services. Typically, a person gets confused between artificial intelligence (AI) and machine learning; therefore they assume that both technologies are the same. However, ML and AI are two separate units that just so happen to complement each other. Whereas artificial intelligence aims to harness certain aspects of the thinking mind, machine learning is helping humans to solve problems in a more efficient way. As a subset of AI, ML uses data to tech itself on how to complete a process with the help of AI capabilities. The expert system can help companies to find hidden knowledge available in consumer data for streamline marketing processes.
But, marketers were somewhat hesitant to incorporate the automatic learning system in their digital marketing strategies. Due to the positive impact of machine learning in various industries, sellers thought to integrate the system in marketing to get better performance and results. In digital marketing practices, the self-learning system can be used for helping sales assistants to broaden their understanding of target consumers and how they can optimize their interactions with them. Machine learning isn’t here to take over the jobs of digital marketers, but rather its main use is to enhance the digital marketing strategies and make the jobs of digital marketers easier.
The rise of machine learning in the digital marketing industry
The marketing people use the automatic learning system to understand, anticipate and act on the issues that their sales prospects are trying to resolve more quickly and with greater clarity from any competitor. Along with that, this system comprises utilizing data, content, and online channels to increase productivity and help digital marketers understand their target audience better. Plus, it takes to a new level of accuracy and speed for contextual content, marketing automation which includes cross-channel marketing campaigns and leads scoring, personalization, and sales forecasting. Now, let us try to understand how machine learning is shaping the digital marketing industry:
Predictive analysis for generating precise leads and results
Predictive analysis is simply the use of data, statistical algorithms, and techniques of machine learning to determine the likelihood of future conclusions based on data history. If predictive analysis blends with machine learning, it will make the salesperson life much easier. Machine learning models a neural network according to the required predictions. For instance, to model a neural network for financial institutions, which predicts debtor risk, a recurrent neural network (RNN) can be used. Further, while in practice to develop precise predictions, the neural system will require a huge amount of data sets of previous debtors. The inputs can be age, gender, current debt, income, etc.
Such predictive analysis backed by machine learning can be used in the ranking of prospects or lead scoring. Likewise, the models generated through the expert system can be trained to rank prospects or leads based on some criteria defined by the sales team as qualified buyers. As a result, the sales team can focus on the positive leads. In this way, marketers can save considerable time and resources as well as increase their sales.
An intelligent chatbot for improving the customer experience
Many organizations are using chatbots for enhancing the customers’ experience. Combined with machine learning, chatbots make the process of automating responses even easier. They simultaneously learn from the frequently asked questions from potential buyers and ease their search for the product or service they are looking for. The ability of ML-powered chatbots to immediately answer open questions is an example of customer service. Furthermore, these bots use natural processing of learning and machine learning to find the right answer. Along with that, chatbots can serve customers 24/7 and retain their data. Importantly, unlike human beings, they never lose their patience with customers. Customers may get angry, but the bot can always treat them well. Chatbots can respond to several requests from different customers at the same time, so waiting times will no longer be a problem.
Generate personalized content for marketing
It would be a challenging task to generate engaging content for online marketing campaigns—especially if they are personalized and consumer-centric campaigns. Typically, pulling off a successful campaign would take a few months of hard work and strategic planning. However, it becomes easy to develop natural and creative content on each topic with assistance from new AI-based tools. These tools allow the marketer to reduce the amount of time they spend tracking on the customers’ data, as well as enable them to better decipher the customers’ data to create actionable tasks that lead to campaign success. It’s important to remember that this is also applicable to email marketing campaigns as well. At present, it may seem like an unrealistic thing, however with AI and Machine Learning on board, it won’t take much time to launch such a massive campaign with a high success rate.
Whether machine learning is working or not?
One of the most important questions that we should always ask when evaluating or implementing new technology is that it is worth it or how we know it works? If machine learning is working, then the results will be shown in business. Furthermore, measuring ROI (return on investment) is a core concern for many marketers, especially when it comes to new technology. There will be an upsurge in the patrons. Therefore, with help from the expert systems like ML, the seller can identify customers faster and more accurately and generates leads easily.
Through enough data, it may even predict the type of offer most likely to re-engage the customer. The businesses will see higher revenues from upselling. ML can present customized and relevant upselling opportunities with higher response rates by leveraging data correlation, reviews, product popularity, customer behavior features, etc. Similarly, using intelligent chatbots businesses can enhance the customer experience and site searches to increase product discoverability. Hence, innovative technology provides us all with the opportunity to develop a more intimate and valuable relationship with customers and enables a richer, more engaging experience.
Conclusion
The present world of intelligent technologies and people have started begin to work together to take marketing initiatives to the next level. Marketing products or services will no longer be a tireless campaign to create, curate and share information of high value. Instead, digital marketers will be able to spread brand awareness in a way that’s more efficient and personal than ever. Therefore, people need to utilize the power of machine learning to improve their sales and their marketing team’s capabilities. This, as a result, can make a positive impact on their future marketing development and relationships with clients.
