Applying sonamine social network analysis to telecommunications marketing

Applying Sonamine Social Network Analysis To Telecommunications Marketing An introductory whitepaper

Applying Sonamine SNA to Telco Marketing

Sonamine LLC

1

Introduction

Social network analysis (SNA) uses information about

make better marketing predictions.

word-of-mouth and influence modeling. Such techniques provide a different view of the vast

of data that is captured within companies.

Similar people form social groups

People who share the same interests and are simi

of “homophily”, a sociology concept that has been supported by 20 years of research. While we do not

know the reason behind this behavior, we can easily observe it in our daily interact

brand segmentation has been utilizing the basic concept that there are people with different

aspirations and needs. SNA can extend this segmentation by providing another way to empirically

understand your customer base, even if you only have a sample

This homophily concept is the basis of the Sonamine algorithms of collective inferencing, network

classification and community detection.

Information spreads through a social network

Another central principle in SNA is the word

networking or just complaining, people share their experiences with their friends and families.

people make decisions about purchasing or dining, they rely on the information they received from

their friends. Therefore understanding how information spreads through the social network can

provide insight into what types of decisions that your subscribers will make.


Sonamine LLC | Confidential

information about the relationships between customers in order to

make better marketing predictions. Common SNA techniques include finding communities, simulating

mouth and influence modeling. Such techniques provide a different view of the vast

of data that is captured within companies.

Within telecommunications firms, th

messages among the subscribers provide

into the social connections among the subscribers.

SNA provides a way to leverage this information

improve marketing effectiveness. This whitepaper

will describe the principles of Sonamine SNA,

different marketing applications and case studies of

Sonamine SNA tools.

Similar people form social groups

People who share the same interests and are similar tend to hang out together. This is the definition


know the reason behind this behavior, we can easily observe it in our daily interactions. Traditio



understand your customer base, even if you only have a sample of data.


classification and community detection.

formation spreads through a social network

Another central principle in SNA is the word-of-mouth phenomenon. Whether you call it gossip or

networking or just complaining, people share their experiences with their friends and families.


refore understanding how information spreads through the social network can

provide insight into what types of decisions that your subscribers will make.

the relationships between customers in order to

Common SNA techniques include finding communities, simulating

mouth and influence modeling. Such techniques provide a different view of the vast amount

Within telecommunications firms, the phone calls and

g the subscribers provide good insight

into the social connections among the subscribers.

SNA provides a way to leverage this information to

improve marketing effectiveness. This whitepaper

principles of Sonamine SNA,

marketing applications and case studies of

lar tend to hang out together. This is the definition


ions. Traditional




enon. Whether you call it gossip or

networking or just complaining, people share their experiences with their friends and families. When


refore understanding how information spreads through the social network can


If you think back to the last time you were going

to watch a movie or a new restaurant...very

likely you discussed it with some friends before

making your decision.

This word of mouth phenomenon is the basis

Sonamine algorithms of diffusion and

relationship strength modeling.

Different social roles within each context

Within the social groups, there are different roles such as leaders and followers.

power to influence decisions within groups. This influence could be based on knowledge or oth

subtle social cues such as family connections. Quite often, these roles

an influential leader in terms of which nightclubs to visit may not be the same leader when it comes to

selecting handsets for the group. This

each marketing objective.

This concept of roles is the basis of Sonamine algorithms of cascade scoring, eigenvector centralities

and pagerank.

People have relatively stable social networks

Life stage marketing refers to the idea that there are common stages in life that people progress

through. Within each stage the needs, wants and aspirations are common to everyone in that stage. In

SNA, the same concept is applied to the phenomenon that the

stable group of friends and family, and a more transient set of acquaintances. The stable group

constitutes a long-lived social network.

This concept of stable social networks is the basis of Sonamine algorithms tha

similarity.

SNA improves churn prediction

Since the cost of acquiring a new subscriber is high, it makes sense to start by retaining your existing

customers. One way to apply Sonamine SNA is to improve churn predic

diffusion, community detection and cascade scoring algorithms to pinpoint these “contagious

churners”. These are subscribers who have not churned yet, but are being influenced by their friends

and social group to churn.

Most telecommunications companies

demographic, usage and calling-plan data to generate subscribers who are likely to churn. Sonamine


Sonamine LLC | Confidential |

hink back to the last time you were going

to watch a movie or a new restaurant...very

likely you discussed it with some friends before

This word of mouth phenomenon is the basis of

diffusion and

roles within each context

Within the social groups, there are different roles such as leaders and followers. Leaders

uence decisions within groups. This influence could be based on knowledge or oth

subtle social cues such as family connections. Quite often, these roles change in different contexts:


selecting handsets for the group. This context dependency is the reason why SNA has to be tailored to


People have relatively stable social networks

stage marketing refers to the idea that there are common stages in life that people progress


SNA, the same concept is applied to the phenomenon that the social networks tend to exhibit a very


lived social network.

This concept of stable social networks is the basis of Sonamine algorithms that measure vertex

churn prediction and retention marketing


One way to apply Sonamine SNA is to improve churn prediction. Sonamine uses the



ecommunications companies already have existing churn prediction systems that use

plan data to generate subscribers who are likely to churn. Sonamine

2

Leaders have the

uence decisions within groups. This influence could be based on knowledge or other more

change in different contexts:


SNA has to be tailored to


stage marketing refers to the idea that there are common stages in life that people progress


social networks tend to exhibit a very


t measure vertex

retention marketing


tion. Sonamine uses the



already have existing churn prediction systems that use

plan data to generate subscribers who are likely to churn. Sonamine



3

Case study : Prepaid churn with European

mobile operator

Problem : Prepaid churn model was not accurate due to lack of

customer demographic information.

Results : Accurately predicted 25% of churners using 5% of

population. Lift of more than 5x.

SNA complements these existing churn prediction systems by providing Sonamine SNA variables that can

be used together with the demographic, usage and calling plan data. The benefit is that the prediction

model gets the best results from combining all the available data about subscribers.

By having a more accurate target list of potential churners, your retention campaigns will become

more effective. Not only will you save more potential churners, you will also reduce the “lost

revenue” by offering retention promotions to subscribers who were not going to churn.

Increase retention ROI by identifying spinners

One way to improve retention campaigns is to identify revolving spinners. These are subscribers who

continually switch numbers but remain loyal to one telecommunications company. They change

numbers to take advantage of better rates with new numbers. Sonamine SNA can accurately pinpoint

these spinners using the algorithm of vertex similarity because these spinners will have a stable social

network.

Since these spinners would seek out better rates but stay with the telecommunications company, it is

not necessary to send them retention campaigns. By removing these spinners from the retention

campaigns, loyalty managers can improve the effectiveness of their campaigns. The benefits could

come in the form of lower campaign costs and higher save rates.

Increase conversion rates of cross-sell and up-sell campaigns

Cross-sell and up-sell campaigns are key marketing initiatives because additional product purchases can

increase the ARPU of existing customers. Common practices include generating a target list of

subscribers for a product promotion. These products could include anything from games to music to

handsets to accessories like headsets.

Sonamine SNA can improve the target list of cross-sell and up-sell campaigns by using the diffusion and

relationship strength modeling algorithms. These algorithms simulate a word-of-mouth regarding the



4

Case study : Cross-sell promotion with US

telecommunications company

Problem : Needed to increase cross-sell of a new product.

Results : Target list generated by SNA had 340% higher conversion

rate than control group. Conversion rate is the percentage of the

target list that purchased the product.

product being promoted. The target list generated by Sonamine SNA include subscribers who are most

likely to have heard good things about the product through word-of-mouth, and therefore more likely

to respond to the product promotion.

Acquisition through SNA member-get-member campaigns

Recent studiesi have shown that a subscriber’s decision to switch to a different mobile operator is

highly affected by the social group. Specifically, when there are more social group members who use a

specific mobile operator, the subscriber is more likely to switch to that same mobile operator. This

social or peer pressure effect can be used by telecommunications marketers to improve their

subscriber acquisition campaigns.

Using both community detection and centrality algorithms, Sonamine SNA can pinpoint the subscribers

who can “get” new subscribers from their social group. Marketers can then design member-get-

member campaigns that target these subscribers. Member-get-member campaigns provide incentives

for the current subscriber to “sign-up” other people in their social group with your company.

Viral marketing by targeting influencers

Product promotions involve a cost in the form of subsidies. In the case of handset or accessories

promotions, these costs can be substantial. As a result, it would be beneficial to target these

promotions to the most valuable subscribers as a sign of recognition of their loyalty. Additionally it

would be very useful to target these promotions to subscribers who can influence other subscribers to

purchase the product. This combined target list achieves two objectives at the same time, providing a

retention effect to high value subscribers and a marketing effect via influential subscribers.

Sonamine SNA uses both the centrality and cascade scoring algorithms to identify the influential

members within your subscriber base. These influential subscribers may be different for different

contexts such as video products or handset accessories.



5

Case study : Age estimation at Asian mobile

operator

Problem : Needed to use subscriber age for product planning and

development.

Results : For the test group of 450,000 subscribers, accurately

predicted age for 73% with a +/- 1 year error margin.

Value segmentation using social network revenue

Common value segmentation methods in the telecommunications industry revolve around grouping

subscribers together based on their ARPU. Depending on the tariff plan, such a method may not

accurately reflect the value of each subscriber. For example, a low ARPU subscriber may be

generating a lot of revenue because her friends call her a lot. This associated revenue could be direct

mobile originated revenues from on-net friends or inter-connect fees from off-net friends. Since

telecommunications is a network-based service, by losing such a low ARPU subscriber, you also lose the

associated revenues of her friends.

Sonamine SNA allows you augment your existing value segmentation models by identifying such low

ARPU but high network revenue subscribers. These subscribers should be classified into the high value

segment. By highlighting the contribution of and catering to the needs of that these subscribers, you

do not cannibalize your own revenues.

Prepaid subscriber demographic profiling via SNA

The lack of subscriber demographics is a pervasive problem in prepaid telecommunications markets.

The ability to buy and start using a new account without providing accurate information limits a

marketer’s ability to understand and predict the behavior of the customer base. For example, in trying

to optimize the product mix, a marketer would want to make sure that all customer segments are

covered. Another example is using subscriber age to estimate their life-stage and hence the

appropriate marketing offers.

By leveraging the concept that similar people form social groups, Sonamine SNA can estimate the

demographic profiles of your prepaid subscribers. Researchii has shown that these techniques work

well even when only you have less than 10% of post-paid subscribers. You can then use these estimated

demographics in product planning and target list generation.



6

Sonamine software and services

Sonamine provides software that can be installed and operated by the Information Technology or

business intelligence departments of any telecommunications company. We specialize in very large

scale network mining and analytics.

Sonamine Graph Scoring Engine (SGSE) is a SNA software that you can install and run on a single server.

Depending on the server, the SGSE can support up to 10 million subscribers and 100 million

connections.

Sonamine Graph Analysis Engine (SGAS) is a SNA software that works on distributed servers. The SGAS

can handle unlimited amounts of data. One customer of Sonamine is using SGAS to analyze 150M

subscribers with 15 billion relevant connections.

Sonamine provides outsourced network analysis services. In cases where the customer does not want

to install the software, data can be safely transferred to Sonamine. The results of the analysis are sent

back to the customer.

Data security and privacy

Sonamine provides software that is installed and operated by business intelligence and data mining

departments. There is no requirement to transfer sensitive subscriber information outside of your

environment, thus minimizing the risks of any security breach and stolen data.

Streamlined integration with existing systems

The analysis results from Sonamine SNA can be used themselves or integrated into existing systems.

The diagram below shows how this integration would take place. From the left, it shows that Sonamine

software will generate SNA analysis. The SNA analysis results are then imported into existing data

warehouse and predictive analytics systems. With this process, the Sonamine analysis will be sent to

any reporting, segmentation, CRM or business intelligence systems that use the data warehouse.

The final SNA analysis can be stored within the data warehouse in a simple table. Consolidating the

results makes it available for other uses within the company such as fraud detection and customer

service.

Sonamine

software

Data mining

predictive

analytics

Data

warehouse

Segmentation

CRM

BI, Reporting,

Query

Sonamine results


Sonamine LLC

7

Agility in responding to market conditions

By integrating Sonamine SNA into existing systems, marketers can respond to changing market

conditions rapidly. For example, when a competitor

calls, you may want to respond by offering a retention incentive to your subscribers most likely to take

churn. You can immediately use Sonamine to create and analyze a “night

followed by predictive analysis and proactive campaign execution. This rapid response is one benefit of

using Sonamine software that is installed in your business intelligence department.

Minimum training and support costs

Given the busy schedules that marketers hav

significant adoption hurdles. Training sessions and the required help desk increase the cost of support.

Sonamine SNA tools avoid this problem by integrating directly with the existing campaign man

reporting and CRM systems. A marketing professional who wants to know the average community size

of the prepaid segment will use the existing reporting system to obtain this information.

Total cost of ownership

Sonamine utilizes its own data storage and analysis technology. As such there are no new databases to

manage or additional database license and hardware costs.

lower training, maintenance and support costs. Consequently, the overall cost of owners

and the return on investment is much higher than comparable products.



Agility in responding to market conditions


conditions rapidly. For example, when a competitor introduces a new tariff targeted to night


churn. You can immediately use Sonamine to create and analyze a “night-time” social network,

y predictive analysis and proactive campaign execution. This rapid response is one benefit of

using Sonamine software that is installed in your business intelligence department.

Minimum training and support costs

Given the busy schedules that marketers have, learning a brand new tool and user interface presents


Sonamine SNA tools avoid this problem by integrating directly with the existing campaign man



Total cost of ownership

orage and analysis technology. As such there are no new databases to

manage or additional database license and hardware costs. The streamlined integration results in

lower training, maintenance and support costs. Consequently, the overall cost of owners

and the return on investment is much higher than comparable products.


introduces a new tariff targeted to night-time


time” social network,

y predictive analysis and proactive campaign execution. This rapid response is one benefit of

e, learning a brand new tool and user interface presents


Sonamine SNA tools avoid this problem by integrating directly with the existing campaign management,



orage and analysis technology. As such there are no new databases to

The streamlined integration results in

lower training, maintenance and support costs. Consequently, the overall cost of ownership is lower



8

Proof of concept and evaluation

Sonamine offers the SGSE for free 30 day evaluation at http://www.sonamine.com

For larger subscriber populations, Sonamine offers a proof-of-concept (POC) package that includes data

transfer, analysis and results discussion. These POCs can be completed within 6 weeks. Please contact

us at [email protected]

Supported hardware configuration

Sonamine software runs on the following systems.

• Windows XP, Windows Vista and Windows 7, both 32- and 64-bit versions.

• Fedora, CentOS, Redhat Enterprise Linux.

• Amazon EC2 cloud supported including Double Extra Large Instance, Quadruple Extra Large

Instance.

Minimum 2GB of RAM and 50GB of disk space is recommended.

i The role of (personal) network effects and switching costs in determining mobile users’ choice. Juan

Pablo Maicas, Yolanda Polo, Francisco Javier Sese. Journal of Information Technology (2009) 24, 160–

171.

ii Classification in Networked Data: A Toolkit and a Univariate Case Study. Sofus A. Macskassy, Foster Provost. Journal of Machine Learning Research 8 (2007) 935-983.

Business

Applying sonamine social network analysis to telecommunications marketing