You know this scenario? Your subscriber base is stable. Your customers make
calls in an unpredictable way but regardless, your income goes down. How
useful would it be if you could predict your customers’ behaviour and
influence it by making changes to your pricing models? Immensely. We cannot
predict the future but at least we can simulate it.
Predicting revenue is one of the most difficult challenges for a mobile
operator. You can derive it from past developments or you can guess it – there
are no more options. Except if you could simulate the customers’ behavior based
on real data; simulate their call patterns for changed parameters.
RMS
gives you this opportunity. You load your own call data and customer tariffs
into the simulation engine. You design your own scenarios, changing tariffs and
customer behavior as you want. And then you rerate the calls and compare the
results.
RMS
uses real calls from real customers and you real tariffs. For a simulation
scenario you select a group of customers based upon the criteria that you
choose. Now you apply modifications to the tariffs according to your marketing
target. And you set the parameters for the changes on call behavior that you
expect.
“Increasing the prices for
data traffic by 10% will lead to 5% less calls but 12% increased income in the
group of male business users under 40 years old.”
The
results can be viewed and compared in our own client application or exported to
Spreadsheet applications or databases for further analysis.
RMS
operates on Linux and uses an optimized version of the Billing Components™
Rating Engine, a proven and reliable software that has been in productive use
for many years.
RMS
uses powerful next generation database technologies. The call data is stored in
Mongo DB, a noSQL database and processed much faster than you are used to,
rerating a whole month of calls over night.
The
client application is browser based and uses JavaScript frameworks.
RMS
does not require investments in 3rd party software licenses. All components are
either made by us or are license-free open source products.