Communication service providers (CSPs), especially Tier 2 & 3, have a bit of an advantage over some of their larger competitors in that they are agile and nimble. This flexibility enables them to make decisions about launching new services that let them compete with their similarly agile and flexible competitors launching OTT applications.
On the other hand, any minor misstep can have a significant impact on a small provider’s day to day operations. For that reason, small organizations are turning to data analytics to help them identify new opportunities that are going to have the least capital and operational impacts, as well as the optimal ROI.
Today’s data analytics platforms generally are very niche in their capabilities. Their focus is limited: just the application on the device or the packet core or the IMS core or the Application Servers or…well…you get the picture.
It’s difficult for an organization of any size to deploy and correlate different analysis from different platforms to create an end to end picture of their service. It’s also difficult for each of these niche data analytics players to understand the end to end services, as they don’t necessarily have expertise in the vast arrays of data throughout the network that comprise the insight into the customer experience and performance of the components.
To understand the full customer experience, service providers must leverage a data analytics platform that is going to be robust enough to understand the following:
- Am I targeting the right market segment to launch a new service?
- Can I leverage my existing data sources (OSS, NEMS, etc.)?
- What value is my customer going to get from my new service?
- How well is my service working?
- What impact is the new service having on my network and applications?
- How is the application being used between the device and network application services?
- How quickly can I resolve any issues that impact my customer?
Leveraging existing data sources and being able to create service models on the fly using a single platform is no easy task. Your best bet is to partner with an organization that is familiar with telecom environments and data analysis. This will get you the answers you need to identify the value of the services as they are perceived by your customer. Fast.
How are you using data analytics to improve customer experience, business intelligence, and strategic decision making? Let me know in the comments below.
Interested in gaining intelligence that improves customer experience, reduces churn, streamlines operations and reveals innovative business models? Take a look at the Empirix IntelliSight brochure.
Want to gain more insight into predictive analytics? Check out Minimizing Subscriber Impacting Issues with Predictive Analytics.
Written by Jason Miller – Jason on Twitter | Posts by Jason
Jason is Empirix’s expert on predictive analytics, big data, and cutting edge technologies like WebRTC and VoLTE. He has lived on both the customer and the vendor side of things so he has a unique perspective of the market. In his free time he also coaches Little League.