Over the past few years, the growing volume of data, coupled with increased computing power, has propelled us deep into the data economy.
Being data-driven equals good decisions and better business outcomes. According to an IDC report, the worldwide revenue for big data and analytics are expected to reach $260 billion by 2022.
As big data and analytics gained root, there hardly remained any aspect of the enterprise untouched by its influence – revenue management included.
So how has big data and analytics impacted revenue management?
Gain a 360-degree view of the customer
The customer is no longer king. The customer is the Emperor….one who must always be pleased. The consumerization of software and the growing influence of digital experiences in the customer’s vocabulary have led us to a place where the customer wants meaningful, relevant, easy, contextual, and personalized experiences. To deliver this, businesses need a 360-degree view of the customer.
Further, organizations are also coming under pressure to drive elevated customer experiences, personalize customer journeys, and enable price personalization. A revenue management system can help organizations achieve this by leveraging big data and analytics.
With the power of data and analytics, revenue management systems can gain a comprehensive 360-degree view of the customer and identify the influencers that drive enhanced customer experiences. This consequently helps organizations make more customer-centric decisions and improve revenue management and business outcomes.
Streamline and enhance internal processes
One of the key functions of a revenue management platform is to identify the revenue management needs of each department of the organization. Revenue management is moving away from manual processes and paper trails. But it can be complicated to identify which processes need automation, and which ones are complicated and time-consuming. Revenue management teams also have to ensure that these processes are simple, fast, transparent, error-free, and streamlined.
To remove the guesswork from the equation, revenue management teams now leverage big data and advanced analytics. Analytics uses both historical and real-time data to determine the best cases for automation and process improvements. Data from these workflows and processes can be mined and analyzed continuously to identify process improvement opportunities.
Improved segmentation, targeting, and improved revenue projection capabilities
Enabling the right segmentation and targeting capabilities is a crucial function of revenue management systems. While the revenue management system can host a lot of data such as buying information, demographic information, product purchase information, and the like, this data is useless unless put to work.
By leveraging rich business intelligence that comes from examining all the connected and influencing data points, organizations can gain deep insights into customer information, market trends, demographic information, etc. This helps them improve their segmentation, targeting, and revenue projection capabilities.
Identify revenue leaks
Billing and revenue management today is no longer only about generating invoices. With things like subscription billing, multi-parameter-based pricing, etc. becoming a mainstay, revenue management systems have had to increase their billing capabilities. However, as billing cycles and patterns change, and elements like event-based fees, interest calculations, and recurring fees become a reality, so do the chances of revenue leakage.
Using automation, big data, and analytics, revenue management teams can plug the leaks effectively. By leveraging analytics, organizations can effectively pinpoint exactly where the revenue leaks occur by taking into account product and revenue KPIs and proactively identifying anomalies in the billing cycles.
Making audits hassle-free
The volume of input data into revenue management systems is growing exponentially. These systems have to accept data from disparate sources as well. The rise of data has also made data privacy and the regulatory landscape quite the minefield. Changing legislation, a growing variety of products, and market evolution only increased the pressure on revenue management systems.
With big data and analytics capabilities in place, however, revenue management systems can help organizations navigate the complex audit landscape by capably stopping accounting irregularities and fraud.
Better pricing decisions
As customers get used to personalization, many organizations look towards revenue management systems to enable multi-parameter-based pricing. These systems help manage deal pricings across customer types, products, business lines and also enable multi-currency money exchange across locations while capably navigating the compliance landscape. Revenue management teams also have to conduct ‘what-if’ pricing analysis against numerous data points to set pricing parameters. Then there are pricing decisions to be made based on channel characteristics, customer profile, tiering, promotional price lists, and accounting level exceptions.
A revenue management system can capably handle all these pricing functions and more by leveraging big data and analytics. Using current, historical, and real-time data, revenue management systems can help organizations make better pricing decisions by taking into consideration all the relevant data points and their variables.
As the complexities in business functions increase, the role of revenue management becomes all the more relevant as an enabler of efficiencies and better decision making. However, it is with big data and analytics that revenue management has now grown from being just an invoicing and billing department to one that contributes significantly to organizational and business success.
