How You Can Make Smarter Decisions With Machine Learning and Big Data

Machine Learning and Big Data is a great way to make smarter decisions in life. These two technologies and innovations, have become ubiquitous in today’s day and age. There are so many business opportunities and revolutionary business operations are key to becoming successful. Sometimes, it’s the only way to stay relevant.

You need to keep innovating in your business practises to keep up with client demands and sometimes overshoot them. You need to look your best, feel your best and act your best when conducting business and sometimes you need some machine learning to help you make better decisions in this context.

AI:ML has come back in a big way, and now that there are so many companies invested in this technology, its created a wave that isn’t going anywhere. Companies can make better decisions using this technology in various ways, and not rely on human intuition or gut feeling to make a final call. It's all about understanding consumer behaviours and deriving patterns from purchases.

Machine Learning and Big Data comes in handy when it comes to unveiling hidden potentials, so that you can make better complex decisions in business.

1. Customer Segmentation

When its not clear about how you can segment customers into divisible chunks, you can use a range of options available through machine learning and big data. You can discover such groups and make a decision based on the data available.

The good thing is that ML clustering algos are excellent when we try to achieve this kind of segmentation. They don’t really require human direction to oversee and can quite literally see what we can’t see. They can come up with similarities and differences and create better customer segments than you and I could. That’s a good thing if you’re in the marketing department of a large organization and you’re sitting on millions of data points across 50 states.

Insights like Mac users spend 20% more on flight tickets, is a great one that can be substantiated across the board with testing and analysis. No human could have figured that out and its helping businesses across the world with their IT and customer segmentation problems.

Segmentation also helps refine your marketing budget. With programmatic ads becoming the trend of the year, there are more companies indulging in online advertising than ever before. The problem is that they don’t know who they’re targeting.

They may create one advert for 4 different groups who have different belief systems when it comes to how they view the brand. Machine Learning segmentation helps us make better decisions the next time we communicate with them.

2. Targeting, Analysis and Effectiveness

The other marketing and decision-making problem that we come across is related to effective targeting. We don’t really know who our target audience is, beyond an abstract or a consumer funnel report. You need to refine your customer targeting strategy and that is easily done by the help of Machine Learning and Big Data.

If you can target large chunks of customers on the basis of their gender and age, you may miss out on local trends that may shift or deviate from national ones. This real-time approach to targeting is one of the key tenets to decision making, and ML does a great job at that.

You can also compare preferences and user behaviour by targeting unique sections of customers. With ML and BD, you can refine your strategy further by comparing specific behaviour and patterns that multiple customers partake it. It's possible to do so in human scale in the hundreds, but when it comes to learning from millions of customers – the picture changes quite a bit with AI and ML.

We can also codify certain behaviours and trends that we will see in the near future. E.g. Machine learning can uncover new trends emerging from Milan that can affect the way consumers see cars. Therefore, you can run a targeting test and analyse which consumer sets were most attracted towards a certain car make and colour.

Some of the biggest companies in the world, including Apple and Google, are leveraging AI and ML for big decision-making processes. Their automated system hasn’t quite yet reached the state where they can replace humans, but they’re getting quite close.

3. Risk Analysis

Providing a foundation for risk analysis helps businesses to make better decisions. When it comes to understanding what amount of risk needs to be taken, Big Data and Machine learning can get quite good at that. They can create models and extensively analyse how much risk a customer, a sale or a new venture can provide through the first few years of existence.

Companies are even using it for fraud detection and analysing large sets of historical datasets. In fact, ML has become so much better in these last few years that they don’t require human intervention at all. These systems can predict risk and allow businesses to make calculative ROI decisions about what they can do to prevent the risk that they’re taking on.

You can check out your own financial sheet and use machine learning to understand the intricacies of where you might need it the most. Sometimes what happens is that we use our human eye over the data and think everything is fine because the numbers say so. However, there could be hidden correlations and causations that we might have missed because we didn’t match one data set with another properly.

Risk analysis is a huge area in which machine learning and big data are flourishing. They should be getting every bit of attention, as they are going to be game changers for business that work with multiple partners and large consumer data sets.

Conclusion

You can use Machine Learning and Big Data to make better informed decisions. The future is inevitable, and the more we can form our decisions on hard facts and figures, the better decision makers we become overall.