Customer Experience Management (CEM) has been described in various ways from the broader aspect of ordering, billing and B2B/B2C relationships to the technology experience with the actual services delivered by a communication service provider (CSP). In this blog series we will look at CEM and the actual customer experience with the service technology.
- How does a CSP monitor and measure true customer experience of the services delivered? - Today a bottom-up network to service model does not capture the experience of individual customers.
- How does a CSP plan and model individual customers? - Modeling customers can require millions if not ten's of millions of managed objects in a database. This may take hours to model and hours to load into any runtime system.
- How does a CSP monitor and measure customer service usage data which requires a huge amount of processing power? Solutions for service usage data processing requires tremendous scalability and throughput.
Different Customer Experience Data Sources:
Disclaimer: Monitoring the Customer Experience of your service is often bordering upon privacy issues. Each CSP must take this into account based upon their internal policies and set clear rules to ensure privacy is maintained. Approaches below describe how the customer experience data can be gathered. OSSera's position is that we have the platform to process the data whatever the source, however we either partner or work with your service usage data sources to process and analyze it against your service models.
- Agent Approach - Some vendors offer an agent which resides upon the set-top-box (STB), smartphone, or broadband laptop. These agents provide a view into what are the KPI's upon that device. Metrics are collected and stored in a database and thresholds can be set against KPI/KQI's. The challenge is the agents are only running when the device is being used, and therefore data is intermittant. It provides a good set of data for Customer Care to spotlight the problem but usually does not give the root cause.
- Call Usage Data Approach - Call Detail Records (CDR) or SMDR (Station Management Detail Records) are generated for each telephone call from the switch and pieced together to form a billing record. CDR/SMDR records contain the originating, terminating Telephone Number (TN), duration, and any information that may be used for billing (i.e.: Telephone Card usage, Long Distance, Inter/Intra-exchange). CDR/SMDR can be used to look at Service Usage. The challenge is this typically looks at voice call service and only calls that are completed. Calls that did not complete may be thrown away during processing if analysis takes place after the billing record is created.
- Signaling Usage Data Approach - xDR's are captured and correlated by signaling probes. Various signaling probe vendors have probes which capture the protocol stack (i.e.: GSM, GPRS, UMTS, PSTN, VoIP, NGN, CDMA, and W-LAN) signaling data. The xDR has a wealth of condition codes that can be leveraged to analyze network, service, and customer quality. The challenge is the cost of probes can be high and also the volume of signaling records may be hundreds of times greater than Call Detail Records. xDR's will include SMS, MMS, and the individual set-up communication signals.
OSSera's solution encompasses the OSS explorer platform and its symmetrically distributed architecture to be able to process data at high volumes. It also involves the Data Mediation Platform which can process the incoming data records. Let's look at the three main questions discussed earlier.
How does a CSP monitor and measure true customer experience of the services delivered?
As noted above the the OSSera OSS Explorer CEM solution requires data from an agent, switch, or probe. Each has its pros and cons however the data can be processed and analyzed.
How does a CSP plan and model individual customers?
With OSSera you do not need to model every single customer but has a feature which allows a single managed object to represent millions of customer nodes or node groups. This way the model is much simpler to model and much quicker to start and load. This is a unique feature of our Service Planning and Modeling tools which are extended up to model the customer device.
The OSSera platform does however allow you to model individual customers if you choose to because of its flexible data model. Business customers can be modeled. For example we are working on leased line services and these services can be modeled with a direct one to one link to business customers.
How does a CSP monitor and measure customer service usage data which requires a huge amount of processing power?
To date our xDR processing and data mining benchmarks have been extremely well received.
"Real-time applications are supported by the high performance and symmetrically distributed nature of the platform. When the data volume is relatively low, a single instance of the platform and application logic can handle the load. When the data volume is higher than what a single instance can handle, it can be handled by simply running another instance. Data sources can be split based upon the application logic and processed data can be re-joined later such as through a correlation. Application components/objects are inserted at any point to meet the needs. The flexibility of the process flow tool and execution environment makes it easy to do.
High volume data applications need the help of data warehousing algorithms to quickly generate dynamic user reports. Again the flexibility of the platform is a tremendous help.
Benchmarks show that the throughput of OSSera's CEM system can handle more than 4K data records in less than 300 ms on a linux machine (duo 2 core - AMD Opteron 2212 at 2.0G, 2.4T 7KRPM Sata II, 4G memory)." David Deng, CTO and co-founder, OSSera, Inc.
If you are looking at an end-to-end CEM and SQM solution, please contact us
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