Big Data for Telcos – How Big Data can Renew Revenue and Reduce Costs

Categories: Big Data, Data Storage and Management, Telecommunications and Computing

Price: $3,740


This report is dedicated to the analysis of Big Data opportunities for telecom operators:

- What applications can be developed with telcos data?
- What kind of new revenues can be generated?
- What cost savings can be done thanks to Big Data techniques?

The study provides business cases for each application of analytics that can be done by telcos, for internal and external purposes. Specific figures are provided to estimate the financial benefits of each big data application on the global telecom services market and the report especially ranks the most valuable opportunities for telcos.

Table of Contents

1. Executive summary
1.1. With big data, telcos can generate new revenues and to make savings
1.1.1. A developing big data environment
1.1.2. Strong potential savings and limited new revenues
1.2. Main potential benefits can be achieved from internal data and internal applications
1.2.1. Various sources of data
1.2.2. Applications for internal and external purposes
1.3. Telcos helped by big data players and pure players to provide new services
1.3.1. Big data players
1.3.2. Pure players
1.3.3. A need to raise awareness of telcos
1.3.4. Various levels of competition

2. Methodology

3. Main concepts
3.1. Big data
3.1.1. Definition
3.1.2. Background
3.1.3. Technical aspects and key technologies
3.1.4. The ecosystem
3.1.5. Sizing the market
3.1.6. Drivers
3.1.7. Barriers

4. Telcos and big data
4.1. Main activities of a telco: network, products and services, and customers .
4.2. Internal and external data
4.2.1. Main associated internal data
4.2.2. Main potential external data
4.2.3. Focus on external data providers
4.3. Telco costs breakdown

5. Major telco initiatives
5.1. Internal use of data
5.1.1. For network and infrastructure purposes
5.1.2. For product and service purposes
5.1.3. For customer purposes
5.2. Intermediation for third parties
5.2.1. For network and infrastructure purposes
5.2.2. For products and service purposes
5.2.3. For customer purposes
5.3. Sales to third parties

6. Conclusion
6.1. Internal purpose services
6.1.1. Optimisation of network and real-time DPI
6.1.2. Improvement of products
6.1.3. CRM and Sales
6.1.4. Churn prevention
6.1.5. Fraud detection
6.2. External purpose services
6.2.1. Insights
6.2.2. Audience measurement
6.2.3. Raw data sales
6.2.4. Ad networks
6.2.5. Recommendations
6.2.6. APIs
6.3. Global overview of telco opportunities

Big Data for Telcos: How big data can get new revenue and reduce costs


Table 1 : Potential benefits of big data applications for telcos in terms of new revenues and potential savings, based on telcos revenues and costs in 2012
Table 2: Major big data players
Table 3: Main uses of big data by telcos, by type of players involved and type of target
Table 4: Potential benefits of big data applications for telcos in terms of new revenues and
potential savings, based on telco revenues and costs in 2012


Figure 1 : Main usages of big data by telcos, by type of players involved and type of target
Figure 2: Variety of data sources
Figure 3: Stages in data treatment process
Figure 4: Breakdown of structured and unstructured data according to type of application .
Figure 5: How MapReduce works
Figure 6: Big data value chain
Figure 7: Worldwide big data revenue forecasts – 2012-2015
Figure 8: The main activities of a telco
Figure 9: The concept of crossing data from various sources for more complete set of data
Figure 10: ‘Blind matching’ for political campaigns
Figure 11: Yahoo! privacy statement indicates use of external data
Figure 12: Yahoo! Ad Interest Manager page
Figure 13: Experian cross-channel marketing platform, including data integration
Figure 14: Acxiom Website
Figure 15: comScore Subscriber Analytix for mobile operator data
Figure 16: The Tesco Clubcard TV is free for all members, in exchange for personalised ads
Figure 17: Telco costs breakdown
Figure 18: Telco network costs breakdown – In blue, costs sensitive to big data applications
Figure 19: Telco sales costs breakdown - In blue, costs sensitive to big data applications
Figure 20: Example of an overview provided by Allot – here, the most active subscribers
Figure 21: Allot real-time bandwidth utilisation monitoring
Figure 22: Aito Customer Experience Analytics data processing and analysis cycle
Figure 23: Sample chart measuring process cycle time, analysed by Software AG platform
Figure 24: Oracle real-time decision process
Figure 25: Breakdown of losses related to fraud, by communication services and products
Figure 26: Cedexis network performance alert and report
Figure 27: Charge to Mobile API by BlueVia
Figure 28: Direct-to-bill on Facebook: some operators offer easy two-click process
Figure 29: Telefónica UNICA APIs
Figure 30: i-concier service by NTT DOCOMO
Figure 31: Mobile spatial statistics, by NTT DOCOMO
Figure 32: Examples of analyses by Verizon Precision Marketing Insights
Figure 33: Screenshot of a Smart Steps insight result
Figure 34: AT&T AdWorks TV Blueprint
Figure 35: Amobee refers to SingTel just like any other operator, as a partner
Figure 36: Orange TraficZen