If you’re still unsure of machine learning and it’s benefits, consider these scenarios
In 2016, Google’s net worth was reported to be $336 billion, and this is largely due to the advanced learning algorithms the company employs.
Google was the first company to realize the importance of incorporating machine learning in business processes. And the technology powerhouse doesn't stop at any given point; it keeps modifying its algorithms to better suit the needs of its users continuously.
And how does it accomplish the difficult task of observing the browsing pattern of thousands (or millions) of its users?
The answer is simple. By analysing the data, which it has accumulated by introducing machine learning to its business operating model.
This is just one example of how machine learning processes in the recording and processing of data can help businesses grow.
Here are three more ways in which machine learning can help various business sectors:
- It removes physical restrictions
If we have accomplished one thing by automating and digitalizing business processes, it is that we have removed the physical limitations that restrict growth.
Before the technological age, what was the biggest problem faced by businesses? Operating within a limited space accessible only by a limited number of people. For a designer, it was necessary to completely clear out the previous inventory before utilising the shelf space for new designs. By embracing machine learning and diving into the world of ecommerce, you don't ever have to worry about running out of shelves.
- It provides a deeper understanding of your consumers
With the introduction of automated processes, businesses have become increasingly consumer-centric. To be able to survive the competition of catering to your customers’ needs, you as a business owner have to understand the needs of your consumers.
If you do not deliver what consumers are looking for, there is a high probability that you will lose potential customers to competition. Machine learning plays an important part in solving the mystery of consumer preferences. All required information is hidden behind the data accumulated by the business. You just have to crunch the code, and voila—you know what your customers are actively searching for.
- It automated processes, boosting efficiency
Imagine standing in line in a supermarket; someone with a long haul is standing ahead of you and the cashier’s machine suddenly breaks. It’s a nightmare, right? You could be spending those precious minutes watching your favourite series on Netflix.
Now imagine that the machine is not broken but in fact was never invented. The cashier has to manually enter every purchase and tally it with the existing stock. Incorporating automated processes to record inventory stock and purchase order data is not a luxury, it’s a necessity in today's world. Machine learning has increased the efficiency of businesses and minimized the room for error.
Source: Swang Lee Wang
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This is a great post. I think with the collection of big data, machine learning will be a vital part in analyzing that data, and spitting out a readable format for us to understand. Machines need to be able to make decisions on what data points, in a large subset of data are interesting and which are not.
As more data gets collecting, we simply cannot keep up. Machines will help us organize this data to provide value back to the end user. I loved the example that you used about Google, because they seem to be leading the pack in this way.
Cheers!
-@mattboyd