Practical Applications of Machine Learning

AI and ML represent the cutting edge of technology. But how does that translate into deliverable benefits to your business?

The area of machine learning is advancing at a rapid pace. The biggest online names such as Google, Amazon and Microsoft have all launched machine learning platforms, and in using their products every day, we have been gradually exposed to the effects of machine learning without even realising it.

Email providers use machine learning in their spam detection software, Facebook uses it to automatically “recognise” faces and topics for easy tagging and search engines like Google get to know your habits and preferences to deliver tailored results to your search queries.

These types of applications are interesting and useful to everyone, of course, but the benefits of machine learning are not just for internet giants. Here, we take a look at some examples of how any business can take advantage of machine learning to improve its operational efficiency and deliver better results to customers.

More accurate data entry and reporting

One thing that has not changed in the world of data analytics is the axiom of “garbage in / garbage out.” However, today’s machine learning tools don’t just help analyse the data that is at their disposal, they can also enhance the quality of that data.

Duplicated or inaccurate data are significant obstacles to any business that seeks to automate its internal processes. Machine learning algorithms use predictive modelling techniques to improve the quality of the data. They use discovered data to enhance the data entry process. At its simplest, that means fewer inaccuracies and duplication, but it also means the technology can take over the task itself, freeing up human workers to devote their time to tasks that are of higher value to the company and more interesting for the worker.

Data entry is just the start. Already, there is natural language processing technology under development that can analyse text, understand its content and use that understanding to prepare reports for management and other stakeholders.

Better product recommendations

We have all seen it on Amazon or Netflix. You buy, download or watch a TV box set and it will immediately suggest others that might be of interest to you. The more you consume, the better the system understands your tastes and the more often it gets it right, making suggestions that are as good as those of family or friends. It’s handy for you, but ultimately, it is all about improving the customer experience and therefore increasing consumer loyalty and bolstering the bottom line.

You don’t have to be an ecommerce business on the scale of Amazon to use this technology to achieve the same results. Whether you are a clothes retailer, an insurance provider or an SEO agency, machine learning can match your product or services with the people who want to buy them.

This works in two ways – one is the “Netflix” example above, where an existing customer has his or her attention drawn to additional products or services that will likely be of interest. But the really interesting part is through segmentation analysis, where machine learning allows software to reach out to the most promising cold or warm leads via social media or email.

Better, faster and cheaper

These are just a couple of examples of how machine learning can automate tasks such as data entry, report preparation and market analysis, doing the work faster, cheaper and more effectively than manual methods could ever hope to achieve.