foto van Erwin van Oosten
Erwin van Oosten
Data translator

June 16th, 2016

How can data science help us to know, understand, and satisfy the customers?

The world is changing rapidly, both people’s lives and businesses are increasingly shifting towards digital channels. This trend alters the customer – vendor relationship significantly. Do you remember the last time you went to a local travel agency to book your favourite holiday? With sincere interest your personal agent asked you in detail what kind of holiday you were looking for. With your input he evaluated the offers of different suppliers and then booked suitable flights, hotels, and even a rental car. All of this matching perfectly with your preferred level of luxury, interests, and family size. Nowadays, we often book our holidays ourselves. On our favourite comparison website, we compare different flights, hotels, and rental cars, and then choose the most attractive alternative. In this process none of the vendors ever sees our face. Nevertheless, our demand for personalized service has not decreased. We want the perfect tailor made vacation, for the lowest price, and with our privacy intact. So the question is: how can vendors satisfy their client’s personal needs in an environment with little personal interaction? A question I will discuss in this article.


The changing world, from past to present

Vast amounts of data give rise to new possibilities

Luckily, the digitalization of markets brings new opportunities as well. People constantly share data about who they are, what they are doing, and what their interests are. For example: when shopping in the Albert Heijn XL people use their bonus cards and when they shop online they leave a digital footprint with every click they make. This digital behaviour results in a lot of data. On the internet we produce over 1,826,000,000 GB of data every day! At the time you are reading this, this number is not even accurate anymore since this increases rapidly. 

Different data scources


These new data sources can be used to know and understand customers. Instead of the personal agent, the data can be used to help the customers successfully! In this article I will set the scene of this modern environment and discuss how data science can help to satisfy the customers' needs and deliver them the tailor made offer they are looking for!

Understand your customers with data science

The first goal is to get to know the physical customer through online channels. In the world of data science, we refer to this as customer profiling. If you are able to see the differences in needs, characteristics, interests, and values of customers, you will be able to increase service levels and better satisfy their needs. Without data science, this would not be possible, since the human brain is not capable of processing every bit of information in the data rationally. In the figure below some techniques are described that can be used to know and understand the customers.


Data Science techniques to understand the customer




Understand your products with Data Science

Secondly, you need to know the products (known as product profiling). Of course vendors are aware of the products they are selling, but how are their products perceived by the customers and how do they relate to each other? Which products are bought simultaneously? And how do customers make choices between their products and those of their competitors?

Data Science techniques to understand your products


The next step is to combine the customer and product knowledge. If you are able to do this right, you can connect them optimally. With data science you gain insight in what kind of person buys which kind of products, the amount they desire, how much they are willing to pay for it and when and how they want to be addressed. It gets even better when you realize that data science is objective and unbiased, isn’t that exactly what you want?


Combine customer profiling and product profiling


Applying the presented solutions separately is useful. However, if you are able to combine them, the added value will be even greater! Doing this accurately brings a lot of complexity. That challenge is why I enjoy doing it every day!

Now we have set the scene and know the basics, we can dive deeper into these solutions, describe their business value and discuss some of the data science techniques I use to implement them. I will discuss this in future articles. Moreover, I will show what happens if you combine these solutions and how to solve the difficulties with these techniques. Together, let’s help the customers get what they want!