Data driven financial decisions

In this blog post I want to share with you a recent study that we have done to help us on global investment decisions. We are by no means experts when it comes to investment strategies but don't have the budget to hire external help. Thus, we had to work with what we have and our own skills; using the data.

We decided to analyse our global B2C customer base and see where we should focus on. We decided to look into 2 parameters, total volume and revenue per customer. Another decision we made was to convert local currencies into US dollars in order to compare one region with another.

We started by studying the normalised average revenue per customer. We have filtered the countries to have at least 10 customers per month so that the data is meaningful. Countries that are not a part of this chart had less than 10 customers per month.

This graph is showing us how important the currency is when it comes to global investment decisions. However, as you can see from the graph above, there are countries with weaker currencies but high average revenue per user even when converted to US dollars.

However, this wasn't the only data we needed in order to make decisions. The average income per user might be low but you might have a huge base in a country with significant revenue stream from that country. We had to look at the total revenue per country.

This chart looks difficult to read because of the high difference between the top 4 revenue generators and the rest of the world. However, the important thing is the order from highest to lowest; USA, EU, India, UK, Singapore, South Africa, Japan, Canada and the others.

After looking at these two data points, we decided to look into one other thing which is quite important for us, which is the engagement factor. We decided to count the number of social media shares, comments and reviews to measure the Engagement factor. The following graph shows the engagement factor.

From these three data points, we planned the allocation of marketing investment per geography by looking at the chart below. This chart combines the total reach we can have in the country and the average revenue we may generate from this total reach.

When we look at the first chart, Japan seems to be the winner and that graph suggests us to invest more in Japan. When we look at the second graph, USA looks like the winner.

However, when we combine all of the three data points, it is obvious for us to invest in India the most as it is the most promising country where we have the biggest opportunity.

This is a very simple way of using data in order to make financial decisions. We are working with large enterprises where we use 20+ different parameters in order to make data centric financial decisions. Drop us an email to info@icangroup.co.uk if you want to find out more about how we are using data science and machine learning for better decision making and forecasting purposes.

Let us know in the comments below how you use data in your decisions. If this post catches attraction, we will post another one about how these charts evolved YoY, in the last 3 years. So, don't forget to subscribe and follow this blog.