Thu, Feb 20, 2014
Machine learning has proved to be greatly beneficial for almost every industry. From retail (Amazon), to entertainment (Netflix) and healthcare (Lively), businesses in all kind of industries are using machine learning to enhance their products and services, but also and most importantly, to increase their profits.
Coming from a marketing and business background, I personally find machine learning a game changer. That being said, sometimes its overwhelming to think about all the possibilities that something like predictive analytics or natural language processing has to offer. Just in 5 minutes you could imagine 10 different ways - from big solutions, to small fixes - you can take advantage of this exciting technology.
The challenge is to think outside the box in order to implement an algorithm that creates value for your business while not losing focus with other tempting ideas. It’s better to start small and grow from there, than thinking about a solution that revolutionises your industry.
Some examples of companies that are using machine learning in a small but extremely effective way:
Stack Overflow has built a model that predicts which new questions will be closed for not being useful for the community (off topic, not constructive, not a real question, or too localized). This model helps to save time to the moderation team and improve questions quality.
Orlando Magic basketball team uses machine learning to predict which games would oversell and which would undersell in order to adjust prices and maximize profits.
SouthWest Airlines uses data to learn about what products to promote, to which customers, via what channel and when to do it.
If you aren’t sure how to start using machine learning in your business, try focusing in one area at a time, taking into consideration the size of data available (regarding that area) and the benefits resulting of using said data.
Do you know other examples of businesses using machine learning to improve their products or services in a small but creative way? Share them in the comments!
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