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How Can Machine Learning Transform B2B Companies?

December 21, 2018 | Machine Learning


How Can Machine Learning Transform B2B Companies?How Can Machine Learning Transform B2B Companies?

Ask as many B2B or B2C marketers as you can: What’s the most important aspect of any business? Almost all of them would unanimously suggest – understanding and reaching the customers.
Over the years, it has been observed by the market leaders that B2C businesses have been more willing to incorporate Machine Learning and its related technologies compared to the B2B companies. An apparent reason for this might be the higher stakes in terms of investment that many B2B enterprises fear about, making them reluctant to adopt Machine Learning into their business. Another reason is the ease of data availability and accessibility for B2C companies. For B2B enterprises, this data availability is not as plentiful and consequently there is a comparative limitation to its accessibility.
But at the same time, industry giants like Microsoft, Amazon, Google, Airbnb, Facebook, Netflix, and more of the likes have been full-fledged patrons of Machine Learning incorporating it extensively into their business. So, the question is why B2B businesses should adopt Machine Learning and how it can transform them? What is Machine Learning and how it gives businesses a competitive advantage?

Understanding Machine Learning and its value proposition

Machine Learning is a subset of AI and data is the key to Machine Learning. Algorithms learn from a certain amount of data and then apply that learning to make informed decisions. In other words, Machine Learning is about the ability of machines to learn from a set of data. This learning by information processing enhances the algorithm, thereby providing better estimates and future predictions.
Forrester Research predicts that by 2020, businesses adopting Machine Learning, AI, and Deep Learning, the Internet of Things (IoT), and Big Data will take away more than $1.2 trillion from their less-informed peers.
Machine Learning is all about automated tasks, and its application spans a wide range of industries. A data security firm can employ ML to track down malware, while a finance company can use it to enhance their profitability.

Machine Learning in the B2B World

Data-driven marketing has a great potential to improve an organization’s competitive position because it helps in predicting the customers’ intent. This will not only help in engaging and anticipating the customers better, but also driving greater marketing results. In other words, the availability of data and translating it into actionable strategies focusing upon the complete customer journey determines business success. In the future, an organization’s ability to thrive in the market will be determined by how well they apply their data.
The MIT Technology Review Insights in association with Google conducted a recent survey of about 1400 marketing executives in which industries mainly from the B2B sector ranked among the top handful that are adopting and applying Machine Learning and Data Analytics.
B2B companies must, therefore, focus on collecting and analyzing information as much as possible. This is because when these chunks of information are provided to the Machine Learning algorithms, we gain insights about what drives the customer behavior.
The technology world is flourishing with innovations and Machine Learning is not exempted from this wave. The algorithms are becoming more refined and capable to predict concisely. B2B companies, thus, must ensure to strengthen their data backbone to leverage the innovations in Machine Learning to their advantage. They must standardize and unify their data storage from which it is easier to be accessed and harnessed.

Train your workforce in Machine Learning

In our discourse so far, we have emphasized on the benefits of Machine Learning for B2B companies. Now it is your turn to partner with a professional emerging technology training provider for training your workforce in Machine Learning and other technologies that are anticipated to cause widespread disruption across industries.

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