Mobile Social Network Analysis – The Next Big Thing in Telecom Analytics

TELECOMS

|
Image: By BiztechAfrica
Mobile Social Network Analysis – The Next Big Thing in Telecom Analytics

By Dr. Jay B. Simha, Chief Technology Officer, ABIBA Systems

WAR in Telecom

Wallet share, Acquisition and Retention, commonly called as WAR, form the basis of major revenue generation activities in telecom.

Providing only one service for a fixed rate is not profitable unless the usage trend is increased across the subscriber base. It is easier to predict marginal utility of such commodity services and it is more likely to reduce when the competition offers a similar service at a cheaper rate.

This requires having a set of services and products, which can be cross sold to the subscriber base. Further a subset of the customer base may be prone to increased usage of the same service, which requires identification of such subscribers and executing an upsell campaign.

Churn and customer value are critical to telecom. If a customer spends (ARPU) $50/month and an operator has 5M subscribers, then 0.5% churn is equivalent to a dent of $1.25M/month, which results in a cumulative loss year on year. Annual churn rates in the prepaid segment average between a significant 50 to70 per cent. Lowering this churn percentage has a large effect on the bottom line. 

Even a small reduction in churn can mean big savings – the cost of retaining a client is estimated to be only one-fifth of acquiring one. And these consumers could ultimately help decrease the churn within their own social circles, amounting to even more potential savings.

Mobile SNA

Mobile Social Network Analytics can help operators to reduce churn by studying the social behaviour of their subscribers. Mobile Network Analytics is hidden cousin of social network analytics. There are two types of MSNA:

  • Based on the voice connectivity network within an operator’s customer base
  • Social network on internet through mobile/smart phones

Voice based MSNA is a big data opportunity, hitherto was difficult to tackle. With the innovation and adoption of Hadoop based technologies, it is becoming a reality to add crowd/social information from the network in predicting the subscriber behaviour.

Mobile usage data available in CDRs will contain wealth of information. Mobile social networks (unlike other social communities), is mostly virtual community latent in the data. Each person can participate in multiple communities, creating a handful of opportunities for innovation for growth.

Table 1: Frequency of calls to groups (in percent) 

Reference: Sadie Plant, 2001. “On the mobile: The effect of mobile telephones in social and individual life”Frequency of calls to groups

It is a common sense that every individual has his own personal, professional and social networks. This creates a different set of behaviours in different networks. Identifying these subgroup activities will provide multiple channels for revenue enhancement activities.

A typical distribution of type of interactions among the subscriber groups is shown in Table 1. This indicates that the cross sell and acquisition is well suited problems to be tackled by MSNA.

How MSNA is different from Statistical Modelling

Table 2: Difference between profiling based on domain expertise, statistical modelling and MSNA

Profiling differences

MSNA is based on the social relations than just individual behaviour as studied in statistical modelling or the selective profiling based on domain expertise. The following are the basic differences in the approaches:

How MSNA is different from SNA

Though MSNA has origins in SNA, the depth of coverage and amount of data crunching makes MSNA to be an independent method compared to SNA.

Table 3: SNA vs MSNA

Table 3 compares the two methods.

Extracting the Influence

A profile of each user in the network called social proximity index can be used to drive lot of activities for campaigns. A social proximity index is a composite index which contains multiple measures combined in a weighted sum or some other proprietary form to maximize the information utility. 

Addition of the social network metrics in the behavioural modelling not only improves the accuracy of prediction, but also improves the homogeneity of the social network identities. This homogenisation of the subgroups will result in better information for predictive modelling than just behavioural data from aggregates. The most important metrics derived from the social groups, which can be used independently or in predictive modelling are:

Centrality: It has been observed that the subscribers who are in periphery of the network are least connected and are not useful in conducting any experiments.

Influence: It is often sufficient to condition the influencers, who in turn will effectively influence the connected subscribers in their immediate network.

Duality: Most subscribers have different behaviour in different networks as a group or as an individual. This helps to identify the cross sell/up sell opportunities.

MSNA in Campaign Analytics

MSNA in campaign analytics

A recent research has indicated that certain types of behaviour exist in a social network. For example, the survey results in Table 4* show that the ringtone recommendations are predominant with both friends and acquaintances. This is a good starting point to identify the potentials in the social subgroups for cross selling/up selling specific ring tones within the social networks.

In addition, this helps in identifying the psychographic profiles of both the individual and groups, which can be extracted from a combination of behavioural modelling and social network modelling.

An interesting input for campaign design can come from the evolution of the social network over a period of time. When the social metric for each subscriber is scored periodically and analysed, it throws light on the influencing behaviour of the few subscribers within the network causing the growth or shrinkage of network. Such analysis can be used for early intervention and targeted campaign for retention or X-sell or acquisition for revenue enhancement.

*Reference: Giuseppe Lugano and Pertti Saariluoma, 2007. “To Share or not to share: Supporting the user decision in Mobile Social Software applications,” Proceedings of the International User Modelling conference (UM 2007; Corfu, Greece, 25–29 July). 

MSNA Architecture

MSNA Architecture

MSNA requires massive storage and processing power for a short period. It is ideally suited to be deployed in elastic cloud. However, due to privacy restrictions, the CDRs cannot be processed over cloud.

Hence it requires massive infrastructure investments to handle the BIG CDR data. This inhibited the use of MSNA in telecom for a long time, though CDRs were available for long. However, the introduction of distributed computing technologies using commodity hardware has ushered new era in MSNA.

At present, MSNA solution providers use a Hadoop based stack for MSNA. The architecture is shown above. The CDR data will be pre-processed by a Hadoop-Hive based pre-processing engine, which provides the multiple flavours of data like, network, individual and aggregate for modelling. The network models are then developed using MSNA engine. Subsequently the scoring and visualization of the derived networks and its properties will be done by the scoring and visualization components of the solution. The entire stack is configured for quick deployment.

MSNA Methodology

MSNA Methodology

Unlike the behavioural modelling, which uses aggregated data or social network analysis, which uses small world/sample/survey data, Mobile social network analysis requires detailed to data to build and analyse the network models. The process starts with pre-processing the CDR data to the required format.

Once the network models are built, the different social metrics are attached to individual subscribers, which can be further analysed using visualization or other applications or can be used for enriching the predictive models based on behavioural data.

Conclusion

Mobile Social Network Analysis is a powerful tool that should be there in every Telco’s arsenal. It provides a different and enriched view of the customer base in addition to domain based and statistical modelling approaches. MSNA requires careful selection of the hardware and software to implement. The recent advances in Hadoop based solutions have sparked new interest in MSNA. This paper has highlighted how MSNA can be used for increasing the WAR effectiveness in telecom. Further it has provided the architecture and approach for MSNA with typical applications in campaigns.

About the Author

Dr. Jay B.Simha is Chief Technology Officer, ABIBA Systems, a telecom BI & Analytics company based out of Bangalore. He has about 15 years of experience in R&D, Business Intelligence and Analytics consulting. He has implemented large scale systems for telecom, BFSI and manufacturing industries in Business Intelligence and analytics. Dr. Simha holds a Doctoral degree in Data Mining and Decision Support and Post Doctoral from Louisiana State University, USA. He is active in research and has interests in business visualization, predictive analytics and decision support. He has so far published about 40 papers in international journals and conferences in the areas of business intelligence and analytics. 



Share the News

Get Daily Newsletter

comments powered by Disqus

MORE TELECOMS NEWS

TeliaSonera International Carrier strengthens connectivity in Western Africa

TeliaSonera International Carrier (TSIC) and Angola Cables have announced an IP Transit agreement that will enhance regional connectivity to TSIC’s customer base along the West African coast using Angola Cables’ significant submarine cable assets. Read More

We’ve built West Africa's strongest aerial fibre, says Phase 3 chief

The Chief Executive Officer of Phase 3 Telecom, Mr. Stanley Jegede, says the firm has invested massively in building a very robust aerial fibre network to improve connectivity across the country and the entire West African sub-region. Read More

Orange launches reward scheme for corporate clients

Orange has introduced a loyalty programme for its corporate clients, dubbed Corporate Ziada. Read More

MTN Ghana launches fixed wireless phones for SMEs

MTN Ghana has launched the Eazifon fixed wireless phone as an alternative to the traditional landline fixed phone for Small and Medium-sized Enterprises (SMEs).  Read More

Cameroon to increase telephone digits in November

The number of telephone digits in Cameroon will be increased from eight to nine come 21 November 2014, the telecoms regulator, l’Agence de Régulation des Télécommunications (ART), announced recently at a press briefing. Read More

“Colossal disparity” between fixed, mobile penetration in Africa

There is a “colossal disparity” between fixed and mobile communication penetration rates in Africa, according to analyst firm Frost & Sullivan. Read More

Preparing for the next evolution in the telecoms landscape

Change is coming to the telecoms market, as increased competition, reduced cost of services and changing business models pave the way for new services, new solutions and more pervasive communication to connect more users, more affordably, says Jasco. Read More

MTN notes ruling by International Arbitration Panel

MTN Group has noted that a tribunal of independent arbitrators has ruled against Turkish mobile operator Turkcell, in the investor-state arbitration under a bilateral investment treaty case held in terms of the rules of the United Nations Commission on International Trade Law (UNCITRAL). Read More

Vodacom enhances enterprise voice suite

Vodacom Business Nigeria’s Vernon Van Rooyen; Coca-Cola Nigeria’s Titilayo Oyebolu and PZ Cussons’ Serge Yao Vodacom Business Nigeria has enhanced its enterprise voice suite with the launch of two new solutions, Business Connect and Business Express.  Read More

Telecom Namibia receives NTA certification

Telecom Namibia Training Centre has been endorsed by the Namibia Training Authority (NTA), the national body responsible for the registration of vocational training centres and institutes, to deliver a wide range of general IP/IT training programmes. Read More

PRESS OFFICES

Sage ERP AfricaSAP AfricaSage Pastel AccountingTrust PayVMWareSamsung ElectronicsMitsumi DistributionPhoenix DistributionSage HR AfricaMTN BusinessSchneider ElectricMultichoice

FEATURED STORY

Growing African focus on data securityGrowing African focus on data security

Beachhead Solutions’ new SA and Mauritius country manager explains the challenges and solutions around securing customer data and compliance with new personal information legislation.

IN DEPTH

Africa lags on digital migration Africa lags on digital migration

Only three African countries have so far completed the digital migration process, and serious issues are hampering the migration in other nations.  

COMPANY NEWS

VMware reports third quarter 2014 results

VMware, the global leader in virtualization and cloud infrastructure, today announced Year-over-Year Revenue Growth of 18% to $1.52 Billion in its financial results for the third quarter ...

CNN, MultiChoice name top African Journalist 2014

Kenyan journalist Joseph Mathenge has been awarded the top prize at this year’s CNN MultiChoice African Journalist 2014 Awards Ceremony.