How To Apply Machine Learning In Business

Firstly you need to understand the difference between Artificial Intelligence (AI) and Machine Learning (ML).  Machine learning is a subset of AI. ML is an established programming model which uses large amounts of data to make predictions. It can assist with the automation of daily human processes, make decisions and apply a certain level of judgement.

In order for you to know how to apply machine learning in your business, you need to first identify the problems you want it to solve.

Define Your Problem

Study your business data to identify the problem. If standard business rules and logic are not enough to solve it, then you may need Machine Learning enabled. Get clear on the issues before employing any ML technology.

Identify which areas are human-intensive, highly repetitive and currently require staff to review a large amount of data.

Then you need to apply the numbers. Understanding the potential impact of the problem is key. Know how much time you need to solve it and how long a model will have to run before you get some results.

Finally, what are you going to do with the data you gather? How will it be of use to you?

What Can Machine Leaning Be Used For?

Machine learning gathers data into your database. This data can help you gain more insight in most areas: In other words, that problem you want to solve. ML provides a more comprehensive analysis of that data and more efficient management.

Here are some examples of ways that you can use ML in your business:

Analysing Sales Data

These days there is plenty of sales focussed data available thanks to the explosion of online activity. Sales teams can access metrics from a variety of areas including social media platforms and website visits. They can also conduct split testing, or A/B testing, to further analyse the variants that drive conversions.

However, with so much data available, it is a mammoth task to undertake for an already overburdened sales team. It is extremely time consuming and can lead to necessary insights being lost and opportunities being missed.

According to analytics company SAS “Machine learning will significantly speed up this laborious process and quickly uncover those valuable insights and useable information. “

Fraud Detection

Unfortunately, with the rapid growth and ease of shopping online, comes the opportunity for fraudsters to pounce.

Business owners are finding that despite employing a multitude of online security measures, the criminally inclined will still find a way to commit fraud.

As the number of online transactions increases, so do the number of security steps that a business needs to take. This slows down the purchase process and can harm the customer experience. Even when extra measures have been put in place, they are often still ineffective against fraud.

Machine learning is a much more efficient way of improving the fraud detection process as it detects patterns. ML uses the algorithms to determine if the activity is likely to belong to the card holder or if it looks suspicious. It can then inform the customer or the business of any unusual activity as it happens before any fraud can take place.

This real-time analysis searches out those anomalies and enables you to take immediate action. By identifying any problems at the time they happen, rather than days or weeks later, your business reputation stays in tact.

Personalised Recommendations

Machine Learning can analyse the spending habits and interests of your customers to be able to recommend products that they are more likely to want. This saves you time and money advertising generally to the masses and helps you to target your ideal customer for each of the goods or services you offer.

Getting your product or service in front of the right audience increases your chance of making sales. It is that simple.

Final Thought

If you decide you do need Machine Learning in your business, be clear on what it is you want it to do. What do you want to do with the analytics? Also be clear on what algorithm is going to work for you.

You may not need a fully customised algorithm, but even ones that are standard may need tweaking to suit your business. Always speak to an expert to ensure the ML system you invest in will do the job you want it to do.