Information is the new currency. How is that? Let me illustrate. You have worked for decades, saved for retirement and it’s time to invest. What comes to your mind when you think of ways to invest? What do you even know about financial investment? Except you have decades of years of financial investment experience, the basic financial knowledge from high school or retail banking would not do the trick. So, what do you do? You turn to an expert in financial investment – a financial advisor. Why? That’s because you are confident any advice recommended will be well-informed.
Think of the wealth of experience of that financial advisor as a collection of data. It can be historical or real-time. Big data is not just about collecting data from market research or sensors. It is about exploring data collected and stored and gaining insight from it.
I am going to describe herein the practical applications of data collection, analysis, and interpretation. Let me begin by defining big data.
Forbes defines big data as “essentially just a compilation of a large amount of information coming from multiple sources…”. The large amount of information collected is stored in databases from which data cleansing – removing errors and duplicates – is done. Thereafter, data visualization – graphical representation of data on dashboards – takes place. Next, is the fun part. This is the most vital part of big data analysis. I am talking about exploring, looking through, analyzing; call it whatever name you think is the fanciest, it’s all about searching for gainful insight.
The gainful insight will supply the confidence required to make those big business decisions. The type of decisions that will maximize profit, reduce cost, grow market share and gain a competitive advantage. Let me describe these benefits under the following subheadings: eCommerce, customer targeting, and sales and marketing forecast.
eCommerce
With Artificial Intelligence (AI) – the ability for a computer to think like a human – companies can increase their product advertisement ratings seamlessly by leveraging the insights from big data while they use AI marketing techniques. For marketing companies, Machine Learning – the ability for a computer to learn using mathematical and statistical models – can be useful in spotting trends and generating insightful data which when applied, can perform root cause and probability analysis.
Customer Targeting
Increasing market share in businesses is critical to the survival of the business. Companies seek new ways to increase their market share through customer targeting. How can big data and AI be leveraged in this regard? AI can be used to explore customer historical data then model Machine Learning algorithms after generally acceptable training sets to identify regular characteristics of customers. These characteristics can be age, location, buying habits, and gender.
Sales and Marketing Forecast
One of the many benefits of big data is predictive analysis – data visualization for prediction. When applied to sales and marketing, AI can be useful in predicting the success of a product launch. The training set for the Machine Learning algorithm can come from clicks from online shoppers, purchase history, marketing email responses, and time spent surfing the internet. Sales performance prediction can go a long way in cutting costs as it can prevent companies from bad investments. Big data collection, analysis, and interpretation change not just the way we live but more importantly, the way we make decisions – intelligent decisions. Many companies including Netflix, YouTube, and Spotify leverage big data. They have seen how this innovative concept will keep them in business. If you will like to leverage Big Data, then contact us, and let’s work with you on this.
