Big data drives pricing strategies for today’s digital services
A time for change
A famous Charles Darwin quote says, “It is not the strongest or the most intelligent who will survive but those who can best manage change”. This is particularly applicable to service providers delivering services in today’s digital economy, primarily because of constantly evolving business models, diversity in service choices, and competitive threats. The pricing and bundling of digital services is necessarily in a state of dynamic tension because each model attracts a given segment of customers with specific service consumption needs. As customer service consumption patterns change or as competitors offer different bundled services, the service provider must react quickly in order to combat customer attrition. To be successful, service providers must prepare to constantly tailor, evolve and adapt their pricing strategies to meet customers’ specific needs in order to remain competitive and successful.
Formulate a strategy
The author of the acclaimed book: “The Art of Pricing”; Rafi Mohammed explains, “Pricing is not just about setting a numerical price, but its more about creating a set of strategies to maximize a company’s profit”.
The word of emphasis in the above quote is “Strategy”, because this is where many fall short in their quest to monetize their products and services. Pricing strategy is much more than just identifying and aiming for target revenues, or underpricing your competitors to gain market share. It is primarily about constantly finding and exploiting hidden value. By hidden value, I mean the ability to find hidden profit that allows you to win market share and maintain sustainable business growth well beyond the initially identified target business objectives.
So how does a service provider formulate and execute a winning pricing strategy? The value of the service delivered must match the demands of the target customers and the pricing strategy must clearly reflect and communicate the perceived value of the product or service to its target market.
Big-data in today’s hyper-connected world
For service providers delivering services in today’s digital economy, the big data explosion created by the hyper-connected world we live in (see Monetizing Services in the Hyper-Connected) exacerbates the pricing challenge even further. A restaurant looking to price a lunch or dinner menu can perform some standard research into the number of daily visitors, spending patterns, preferred menu choices of their customers, building costs, employee salaries, cost of food and storage and energy costs. The restaurant owner can then price their menu accordingly based on their revenue targets.
However the volume of big data generated from selling digital services makes finding the right pricing strategy for digital services many magnitudes more challenging than pricing a restaurant menu. Instead of analyzing a few hundred or thousand customers, the scope and variety of data to be analyzed increases daily into millions or billions of records. The frequency of service consumption fluctuates by the second and is affected by a multitude of factors from network availability and quality, bundled or packaged services, special events like holidays or sporting events, trending content, social media, and a host of other factors. The speed to insight and ability for timely and accurate execution is critical to delivering a successful pricing strategy, because the rate of generation and evolution of business relevant data is continuous and ever changing.
Empower business users with accelerated time to insight
Service providers looking to determine the optimal pricing strategy for digital services must embrace a big-data philosophy as part of their overall pricing strategy. Key decision makers and business users need immediate insight into ongoing business activity, so they can monitor business performance, identify evolving trends, and quickly address potential issues. The scope of data to be analyzed at any time must be both broad and deep, so strategic and tactical decisions can be taken quickly based on the latest information available. The time to insight must be measured in seconds, minutes or hours, instead of days or weeks.
However all too often, many service providers simply lack the right solutions they need in order to quickly gain and leverage insight into generated big-data. Key business users and decision makers have to rely on archaic and complicated processes that aggregate big data into pre-defined cubes which often overlook important details that might uncover hidden value or expose potential issues. Solutions that can quickly derive the right questions from insight into ongoing business activity are a necessity for service providers, to enable them to find the right answers that can help to truly exploit hidden value in their market opportunities to contribute to sustained business growth.
See here for an example of using analytics on big data to gain insights into customer consumption of services.
Exploit opportunity with innovative and flexible pricing and bundling
In order to maximize revenue potential with innovative pricing strategies, it is also important to react quickly to evolving market trends. Service providers must have the ability to implement customer-centric, adaptive and flexible pricing and bundling strategies that can be tailored if necessary to each customer needs. This allows the service provider to not only react quickly to competitive pricing threats that threaten market share, but also find pricing strategies that can help to build long lasting relationships that resonate with customers by enhancing the perceived value of your service, and enable continuous and profitable growth.
Using simulation and predictive tools to fine-tune pricing strategies
Developing innovative pricing strategies is of little use if you do not know where or when to use it. Service providers need to identify when pricing strategies need to be applied, which customers will benefit most from certain strategies, and understand the potential effect a pricing change can have on the business, based on historical trends. This is where simulation and predictive analysis tools can help test various strategies on actual historical data, compare strategies with competitor offerings, or look into evolving market trends over the last few months and years. The optimal pricing strategy can be derived from understanding historical precedent and implementing lessons learned in future pricing strategies.
Pricing and monetizing services in today’s digital world is a continuous process that requires constant evolution and adaptation of pricing strategies to match market requirements and find and exploit hidden opportunities for growth. It entails a big-data strategy for deep insights into ongoing business activity so the right decision makers can ask the right questions quickly. It needs the ability to discover and execute the right pricing strategy for evolving market conditions; leveraging simulation and predictive tools that can help discover the optimal pricing strategy for specific scenarios. And it requires flexible pricing and bundling solutions that allow pricing strategies to be implemented and launched quickly and at a low cost and risk, taking advantage of evolving opportunities for growth.
Service providers that can best exploit their big-data when implementing their pricing strategies are ideally placed to thrive in today’s digital economy.
Authored by Charles Vogt.
Learn about SAP’s Convergent Pricing Simulation solution.