Companies are aware with the importance of digital data in businesses. All organizations had already started to understand and identify what valuable data they can possess. So they are collecting it, analyzing it and using it to improve their business and operations. They are leveraging machine learning applications that help them in solving complex hurdles.
The two important ways for companies to commercialize data are:
- Data is collected and evaluated for product development purposes, used to create better products, which are then to customers. This results in increased sales, products with higher added value or more closed deals.
- Data is used to categorize problems and bottlenecks in internal processes, which are then eliminated to improve business efficiency and profitability.
Above two ways are important for companies to know the opportunities via digital data. They typically master the structured engineering-like process of data collection and analysis, but fail in the innovative and commercial side of thing. They fail to make use of and commercialize all the data they have.
Following are the ways how companies can make money from their data:
Delivering right insights to customers:
Considering existing data and aggregating, enriching, and then selling it to customers as new valuable insights makes money for the business. Reports, online dashboards and indexes can be standalone products bundled with the company's existing offering, helping increase the price of the bundle that is sold to customers. User interfaces can be augmented with machine learning applications to help customers get what they need or interact with the brand.
Allow Data for Sales Team:
A sales organization's role in a company is to maximize sales. Data can be a highly effective tool in reaching that target. Smart companies empower their sales force with rich customer data sets that help them easily identify customer problems, potentially churning customers and sales leads. With data, the sales force can give better product presentations, improve customer service and use more tailored sales argumentation when meeting customers. Smart companies position themselves as outstanding data leaders, and sales people play an important role in delivering that message to customers.
Data used in marketing:
Data that tells us something about consumers and their interests can be used to create marketing and advertising solutions. You have two options: either the company uses its data to optimize its own marketing and advertising or sells its data to other companies, so they can do it.
Data is important in asset optimizing and operational activities:
Companies often view their business as a ├??├?┬ó??silo├??├?┬ó?? and the data they have, they've derived from their own operations and own customer interactions. They use it for their own purposes only. The reality is that they've been operating in network environments and value chains where the final customer delivery is the result of the joint effort of several collaborative companies. In recent years many companies have woken up to the fact that these networked business environments create opportunities for sharing and capitalizing data from company to company. Data can be an important asset in optimizing the operations and cooperation of the players in the value chain. Companies can monetize their data by selling it to their suppliers and vendors down the value chain or by selling it to retailers, resellers and other sales-related partners up the value chain or both.
Marketing of Data outside Organization:
An opportunity to monetize data is to look outside the company's industry or value chain. There might be a number of players interested in insights on economic activity, consumer behavior or other relevant topics. These players might be found in surprising fields. Companies should actively seek out these players and explore innovative joint opportunities.
Data adds Value to companies:
The ultimate way to make money with data is to consider data as an asset in the company├???├??├?┬┤s balance sheet and sell the entire company to a buyer who desperately needs the data. In this case, the data is considered valuable, because it can help the buyer to grow or improve its business. The data is sold as a full package, as part of the rest of the company assets.
Hence, advancement is machine learning technology and with the help of above explained ways companies make money from the data. Partnerships with players in and outside industries are instigated with the aim of combining data from different sources to enrich it into valuable, new insights.