Data-Driven Metrics That Interest Telecom Operators for Business Monitoring

Telecom network elements logs like CDR, UDR, and EDR are a goldmine of subscriber data. It is estimated that by 2050, telecom companies will be collecting data from 95% of the world’s population. When harnessed correctly, telecom operators can improve business monitoring and increase overall revenue.

However, this data comes in huge numbers. A significant reason is the expansion of the smartphone market. The global smartphone market size is expected to reach $520.7 billion by 2030, compared to $273.9 billion in 2021. In addition, advancements in 4G and 5G technology have accelerated data influx, making it hard for telecom operators to process customer information.

Telcos require constant innovation and extensive planning to manage their operations. They leverage data from network elements logs to monitor subscriber activities. This includes tracking critical telecom metrics, which allows them to measure their overall performance and make informed decisions in the future.

In this article, we’ll discuss various network element logs like CDR, UDR, and EDR. Additionally, we’ll talk about the challenges the telecommunication industry faces when it comes to business monitoring. And we’ll share important data-driven telecom metrics that operators use for robust business monitoring using network elements logs.

Telecom Network Elements Logs–CDR, UDR, and EDR

Customers use telecom services to make voice calls, send text messages, and use mobile internet data. Every time they use any telecom service, the operator generates usage data using different network elements. These network elements allow telecom operators to collect and validate subscriber data, filter or identify irrelevant or suspicious activity and determine accurate subscriber billing.

Let’s discuss three of these network elements logs below.

1) CDR–Call Detail Record

Sample CDR log

Call Detail Record (CDR) is a network element that generates a detailed record of all the telecom traffic events or transactions, such as voice calls and SMS, to gain insights into the telecom subscriber’s usage patterns and behaviors. Telecom data analysts process CDR records to provide various analytics that allows operators to make informed decisions. A CDR record contains details such as:

Call timestamp
Call duration
Sender or source number
Receiver or destination number
Billing information for each call
Call completion status
Unique record identifier
Type (voice or SMS)
IMEI
IMSI

A CDR data source serves as the basis of many telecommunication operations. For instance, CDR determines subscriber billing, which is valuable for the telecom operator’s revenue generation. Moreover, CDR records are critical for law enforcement agencies to identify suspicious activity and uncover communication patterns during criminal investigations. It is important to note that the CDR does not record the contents of the call or SMS.

2) UDR–Usage Detail Record

Sample UDR log

Usage Detail Record (UDR) is another network element log that tracks information like balance refills, deductions, and data charges. Similar to CDR, UDR data is logged for each telecom subscriber in the form of tables. It also plays a key role in determining subscriber billing. UDR tracks data attributes like caller party, called party, type (MOC/MTC), unique identifier, call duration, revenue amount, etc.

3) EDR–Event Data/Detail Record

Event Data Record (EDR) usually tracks attributes related to 3G and 4G internet data. It can also include records for other telecom content and services like buying ringtones, call recording charges, and other value-added services offered by the telecommunication operator.

Challenges in Telecom Data Analytics

Due to the massive influx of telecom data, operators find it challenging to process data, which reduces operational efficiencies and makes business monitoring more difficult. Telecom data is categorized as big data, which presents the following characteristics:

Data Volume: Due to 4G and 5G access, telecom data volume is increasing at an unprecedented rate. Telecom operators require distributed big data storage to manage massive amounts of data.
Data Variety: Today, data is highly diverse, i.e., structured, semi-structured, and unstructured. Traditional data warehouses cannot manage or integrate well with different data sources. This is where big data systems are helpful.
Data Velocity: The speed at which data is generated, collected, and distributed has increased immensely, requiring telecom operators to develop real-time big data analytics systems.

These big data characteristics collectively present telecom operators with the following challenges:

Data Quality Issues: The sheer volume of data coming from different sources requires rigorous processing to make it digestible for business monitoring. Analysts spend 70% of their time ensuring data quality.
High Data Dimensionality: Telecom operators track hundreds of data attributes using CDR, UDR, and EDR network elements logs. That makes it difficult to determine correlations and patterns in telecom data.
Data Compliance: Telecom operators need to ensure that they are following data compliance standards like GDPR and CCPA.

5 Powerful Data-Driven Metrics Derived From Telecom Network Elements Logs

Telecom metrics quantify business goals. They allow telecom operators to measure network performance and access subscribers’ activities, allowing them to make data-informed decisions. Let’s discuss some of the most important telecom metrics that we can derive from network elements logs like CDR, UDR, and EDR.

Metric 1: ARPU–Average Revenue Per User

ARPU measures how much income telecom operators generate from each user or subscriber on average. It is formulated as:

ARPU = Total operator income in a specific duration / Number of active subscribers in a specific duration.

The time duration can be weekly, monthly, quarterly, or yearly. Some operators prefer calculating ARPU on every month because it presents a large enough sample of subscriber data points that enable operators to make efficient decisions. ARPU depicts a telecom operator’s operational performance, allowing them to analyze their overall expenditure and profits.

Telcos that offer bundled services often have higher ARPU metrics. Besides the time of the year, the ARPU metric can be tracked for individual service types like voice calls or internet data. It allows operators to analyze their pricing models for each service. By maximizing ARPU, the telecom operator can minimize business costs.

Metric 2: Number of Minutes Used by Subscriber

Also defined as Minutes of Usage (MOU), the number of minutes used by a subscriber directly informs the operator about how much time a user is spending on using their service. This metric is simply formulated as:

MOU = Total minutes used in a specific duration per customer

Like ARPU, the MOU metric can be calculated for incoming and outgoing calls or prepaid and postpaid services. It can be calculated based on week, month, quarter, or year. Telecom operators that use bundled voice packages need to keep a close eye on this metric to maintain a balance between benefitting the user and their company. They can adjust their pricing model for calls or introduce new promotional packages.

Metric 3: Number of SMS per Subscriber

Similar to the MOU, the number of SMS per subscriber metric analyzes SMS bundles offered by the telecom operator. A high SMS count determines that the subscribers are enjoying this service and willing to pay the required charges. In case of a low SMS count, the operator can adjust their promotional offers and bundled packages to align user interest with business goals. This metric can also be tracked based on a specific time of the year. It uses CDR records to calculate the total number of SMS sent per user.

Metric 4: Number of MB per Subscriber

The number of MB per subscriber metric leverages EDR records to find internet data usage for each customer. This metric can also be calculated based on a specific time of the year. Some operators may track daily internet data usage. Data rates differ for 4G and 5G services. Operators may track this data consumption separately.

Metric 5: Churn Rate

Subscriber churn is one of the most important metrics that telecom operators track to monitor the overall performance of their business. Churn refers to how many subscribers are leaving the service and opting to use a competitor service. This metric can be tracked for a specific time of the year and for individual services.

For instance, some subscribers may use the voice call service of one operator and the internet data service of another operator. In the end, it all comes down to which operator is offering better rates and bundled packages. By tracking this metric, operators can adjust their marketing strategies to ensure greater customer retention.

Benefits of Analyzing Network Elements Logs for Telecom Operators

Telecom operators and their subscribers can benefit greatly by analyzing the data available in network elements logs like CDR, UDR, and EDR. Let’s look at some of these benefits below:

Price Optimization: By tracking different telecom metrics to analyze subscriber behavior, operators can offer improved bundled packages to their customers.
Customer Segmentation: By tracking area-wise usage, operators can gather insights into regional customer patterns.
Prediction For Customer Retention and Churn: By analyzing historical log data, operators can predict retention and churn percentages beforehand, allowing them to intervene as early as possible.
New Product Offerings: Based on subscribers’ feedback and usage patterns, telecom operators can offer various value-added services, increasing overall revenue.
Network Traffic Management & Optimization: High-traffic areas can be managed using real-time log analytics. Traffic can be redirected to optimize the telecom network.
Fraud Detection: Network elements logs allow operators and law enforcement agencies to identify fraudulent activities.

Robust Telecom Business Monitoring With S-One Analytics at Scale

At Synaptique, we offer easy integration and transformation of telecom data. Our S-One Analytic big data platform can integrate data from 50 telecom connectors. It can transform raw demographic data, call record data, trace data, and more into curated data, readily available for analytics. Operators can visualize active/inactive subscribers, view subscriber locations, and monitor their average revenue and churn rate by tracking various telecom metrics.

Book a demo today to discover how we are helping telecom operators achieve operational excellence.

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Posted on May 19, 2022 by Yassine, LASRI