Lucas Skoczkowski is CEO of billing and charging solutions firm Redknee. For more information visit www.redknee.com
Removing the guesswork from price plans
The explosion in demand for data services has led to many well-documented consequences to the network and customer experience. It has also led to a revolution of pricing plans that sees service providers use them as a key way to differentiate rather than create price wars.
As we see a proliferation of new players to the market, increased pressure on margins, churn, and competition for high value customers, greater scrutiny is focused on how pricing plans are driving profitability for communication service providers.
Developing a profitable price plan now crosses multiple business units and is connected to myriad of internal demands.
Marketing is continuously designing new and more complex products while battling margin, product pricing and time to market pressures. Finance is under further pressure to contain margins, responding with demands for pre- and post-launch analysis of new services, in-depth analysis of margin per service, and trend analysis of usage and subscriber behavior per service offering. Large account sales teams are pushing to be able to attract new large customer accounts with value-driven price plans, and the Customer Care unit is desperate for better business intelligence data to develop anti-churn campaigns and offers.
All of those business units have become key stakeholders, each with specific needs and demands on how pricing plans are constructed. So how do pricing specialists balance the complex and sometimes contradictory requirements of all those stakeholders? To put it mildly, the success key performance indicators of a price plan have become increasingly complex to develop and evaluate.
To keep all those business units happy, pricing specialists need to provide solid answers to the following questions:
What is the expected adoption rate?
What is the profit margin?
How will it impact ARPU?
Will this reduce churn, and by how much?
Will it result in new subscriber add-ons?
What length of time should the promotion run?
Yet, for even the largest operators, it is a major struggle to perform a simple analysis on product lifecycle, profitability, or customer buying behavior. Today, many operators are still stymied by manual analysis, so when business units call for analysis on the macro and micro levels, it becomes almost impossible to deliver precise reports that take in all the dynamics in a timely manner.
As the dynamics of the industry change on a week-to-week basis, operators can no longer afford the months of labor-intensive ad hoc pricing scenarios that are needed. The analyses are costly and are also proving inaccurate due to small sample sizes and unreliable data.
So, while operators are desperate for the full picture of how their customers and competitors will respond to changes in price plans, they’re relying on too much guesswork to plug the gaps.
To get any meaningful answers to the core questions requires a new generation of integrated pricing simulation tools that enable service providers to launch new pricing plans and bundles with optimal forecasting precision of customer adoption, projected revenue and ARPU. With event-driven tools to calculate every possible new tariff structure and deliver fast and meaningful output to support and validate the entire decision making process from concept to operation, complex pricing scenarios and impact studies that once required weeks or months to perform can now can be completed in just a few minutes.
With business intelligence based on data analyzed through real-time pricing simulation tools, operators have a clearer understanding of their markets, identifying high-value customers, and the historical view that contributes towards precise forecasting.
To succeed in today’s market, profitability, revenue and margins need to be part of the discussion from the very beginning. Marketing teams will continue to build forecasts and revenue projections, but the systematic application of quality data is empowering them to improve the odds of making better decisions.