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Business Intel. & Analytics
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Artificial intelligence (AI) at its more basic tenet is the enablement of machine to think and process like humans.
Machine learning(ML) is a subset of AI that uses numerous statistical methods to train machines to improve at a certain task with experience, whereas the broader AI combines additional applications so that a machine can perform tasks, well, intelligently. ML algorithms learn from the data iteratively and allow computers to find different types of hidden insights without being explicitly programmed to do so. With these competencies, you can ask a specific question to a machine whether it be about sales, customer retention or fraud and get an answer. You may even get answers to questions you never thought about asking.
The volume, velocity, variety and veracity of data is constantly growing, allowing for more sophisticated and accurate predictive modelling and other analysis. Data-driven decisions increasingly make the difference between keeping up with competition or falling further behind. Machine learning, and AI more broadly, can be the key to unlocking the value of corporate and customer data and enacting decisions that keep a company ahead of the competition.
A customer lifetime value that we mentioned before is usually measured in the net profit this customer brings to a company in the longer run. If you’ve been tracking most of your customers and accurately documenting their in-funnel and further purchase behaviour, you have enough data to make predictions about most budding customers early and target sales efforts toward them. The more data, typically the more accurate your predictions will be.
Without customer insights, your marketing and ad creation efforts would be solely based on guessing. Machine learning for brands, specifically unsupervised, is essential to organizing data into groups based on what a customer is like and what they interact with, as well as figuring out how to interact and further your relationship with them.