As technology progresses, more products and systems rely on AI and machine learning to improve processes. AI has come a long way and has separated itself from sci-fi notions to become a superb asset to provide value. Here’s where data-driven companies take the spotlight. Let’s take a closer look at it.
A data-driven company is a company that bases its decisions and model on data and analytics. Following data, these businesses are able to improve processes, have better decision-making, and predict trends in the market and the target audience.
The critical differentiator between data-driven companies and the rest is the variety of improvements that can be made thanks to the insights gathered by data. In this article, you will learn more about data-driven companies and the role of machine learning in their success.
What Are Data-Driven Companies?
Imagine you have a company that sells shoes through an online platform. Your company is working effectively, the sales are coming in, and the number of customers continues to grow. The problem is that you don’t know from where those customers come. Hence, you cannot improve that channel to increase sales.
Imagine you are not following the data to analyze trends within your audience. For six months, your customers have been buying a specific pair of shoes over the rest. What does this mean for your company? Should you act on it? Do you even know what that pair of shoes is or why it sells with more prominence?
Data-driven companies are businesses that take all of the data into consideration to make informed decisions, improve processes, predict trends, and enhance their operations overall. These companies apply machine learning features to their products in order to establish data extraction and processing protocols.
Once the data has been processed, every action the company takes is based on the insights and information that comes from it. Instead of guessing whether a business idea will work, data allows companies to predict the outcome and tailor strategies instead of shooting in the dark.
Examples of Data-Driven Companies
Some of the most important companies in the world are data-driven companies. Here are a few examples.
This streaming company uses data to decide the next blockbuster idea. Following the preferences of the users, the trends, and every insight the company can get from user activity, a new idea for a series or movie is born.
With this method, it is possible to anticipate the audience’s likes and create something that will be a success.
Among the many ways in which Amazon has implemented data into its operations, we find pricing optimization one of the smartest. Instead of manually following trends on its users, Amazon uses machine learning to extract data and thus optimize the prices of the products based on activity, interest, revisits, and more.
With this strategy, Amazon is able to offer discounts or increase the price depending on the insights provided by the data. Moreover, the process is completely automated!
Uber uses data to predict busy areas and send more drivers to those locations. That way, the app offers a fast and efficient service to users who want to grab a cab in minutes. By analyzing recent ride requests, Uber is able to control the offer and demand in a specific area with an automated system.
What Is AI Transformation?
AI transformation is the process of improving, enhancing, and automating processes and discovering new information through data. Once the digital transformation has been done, the next step is to integrate AI in order to improve the intelligence of the solution with data.
By improving the information and data collected, the system can learn from it and continue enhancing the value proposed by the digital solution. Businesses that integrate machine learning into their processes to access high-end analytics and thus better decision-making.
This integration is recommended as early as the discovery phase of a product or business. Integrating a data-driven functionality into the discovery process can help minimize the cost and maximize the effectiveness.
AI transformation seeks to discover hidden patterns within your data and create a more precise business model and help make informed decisions. With these patterns, efficiency is improved and the value is maximized.
This improved efficiency comes from the avoidance or modification of any processes when trying to integrate artificial intelligence or machine learning afterward. Since the technology has already been implemented, there is no risk of affecting the product.
Benefits of Data-Driven Companies
Being data-driven can offer many advantages for a business. Here are the most important benefits of data:
- Improved decision-making
- Optimization of operations
- Reduced headcount through automation
- Improved performance of the product
AI transformation allows businesses to gather data and apply it to the business model in order to make informed decisions. This process helps make decisions that are supported by information. Making informed decisions paves the way for better courses of action overall.
Optimization of operations
When you have all the information needed, you can improve the efficiency of the company’s operations. From the team’s performance to the effective use of time, any COO would be content to have data to help optimize processes.
Reduced headcount through automation
Reducing roles in a company can be of great benefit to the finances of a business. Through data and automation, companies can have a lower headcount.
Improved performance of the product
The valuable data extracted thanks to AI transformation can help improve the performance of the product. Just as the decision-making improves, so does the course of action, features, and solutions the product offers.
As you have seen, data can be a powerful tool to improve a business. Being able to make decisions backed by data is an advantage that could give the edge over competitors. Want to become a data-driven company? Let’s start implementing AI and machine learning into your business today.