The customer is always right.
At the face, the rules of business have not changed. Whoever provides more value to the customer, wins. Similar to how it has always been, whether through a price or premium service strategy.
What has changed is the ability of businesses to know the customer and the willingness to use that knowledge to improve the customer experience. The best businesses of today know their customers, even better than the customers know themselves. Amazon knows which items you might like. Netflix recommends movies you will most likely enjoy. Facebook serves you the ads that you will not dislike… or at least they try to.
What these companies have in common is a good understanding of who their customer is, and it’s made possible through the data that we continuously and willingly provide them through the use of apps, social media platforms or even our web activity. The lowering cost of technology has allowed more and more data to be captured and stored, ripe for data mining and insight extraction. Data Science, Artificial Intelligence, Machine Learning… these are buzzwords of today’s businesses globally. Even local companies in the Philippines are starting to assemble their own data, teams, and tools, for this new wave of competition. Data science is not new. It is just more powerful and accessible.
Business managers have always attempted to use data points to predict or forecast future states— guessing the next trends, mostly using experience and intuition. Today, data science allows companies to make better predictions using as many data points as possible. Companies are able to segment their customers better not only based on what customers say they actually like on focused group discussions or interviews but also based on how similar they are to other customer profiles. Data science is about uncovering relationships, predictors, and trends between a customer’s set of characteristics and actual behavior.
What good is data… if you’re not going to use it?
Data, unless it has been analyzed, is just data. Although data collection is important, data itself does not provide any business impact until it improves the customer experience or it makes the business process more efficient. This is where the execution of business intelligence differentiates a mediocre company from a winning one.
Business intelligence is a team effort. It requires the willingness of top management to change based on a data-driven approach, having the technical skill to extract information from data and having middle management pivot operations based on the knowledge extracted. Data science does not have to be fancy; it has to be useful. It is not just about programming languages, although these are the important tools to achieve the end goal. It should not start from the data and algorithms available, but instead, should begin with the end in mind: the customer.
Data science adoption is underway for most local companies, and business leaders must not forget that to solve the right problems, what is most important is to ask the right questions. Fundamentally, businesses are the same. The need to problem solve has not changed, but we are now lucky enough to be equipped with the processing power of machines. Before diving into a data science project, I always ask, “What problem are we trying to solve?”
