Applying Sonamine Social Network Analysis To Telecommunications Marketing An introductory whitepaper
Introduction Social network analysis (SNA) uses information about the relationships between customers in order to make better marketing predictions. Common SNA techniques include finding communities, simulating word-of-mouth and influence modeling. Such techniques provide a different view of the vast amount of data that is captured within companies. Within telecommunications firms, the phone calls and messages among 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 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 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 interactions. ions. Traditional 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 of data. 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-of-mouth phenomenon. enon. Whether you call it gossip or networking or just complaining, people share their experiences with their friends and families. When 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. 1 Sonamine LLC Confidential
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 of 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. Leaders have the power to influence decisions within groups. This influence could be based on knowledge or other more subtle social cues such as family connections. Quite often, these roles change in different contexts: 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 context dependency is the reason why SNA has to be tailored to 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 social networks tend to exhibit a very stable group of friends and family, and a more transient set of acquaintances. The stable group constitutes a long-lived lived social network. This concept of stable social networks is the basis of Sonamine algorithms that t measure vertex similarity. SNA improves churn prediction and retention marketing 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 prediction. Sonamine uses the 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 ecommunications companies already have existing churn prediction systems that use demographic, usage and calling-plan data to generate subscribers who are likely to churn. Sonamine 2 Sonamine LLC Confidential
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. 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. 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 3 Sonamine LLC Confidential
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 studies i 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-getmember 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. 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. Sonamine LLC Confidential 4
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. Research ii 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. 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. 5 Sonamine LLC Confidential
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. Sonamine software Sonamine results Data mining predictive analytics Data warehouse Segmentation CRM BI, Reporting, Query 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 LLC Confidential 6
Applying Sonamine SNA to Telco Marketing 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 introduces a new tariff targeted to night-time night 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 night-time time social network, followed byy 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 have, e, learning a brand new tool and user interface presents 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 management, 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 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 ownership owners is lower and the return on investment is much higher than comparable products. Sonamine LLC Confidential 7
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 info@sonamine.com 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. Sonamine LLC Confidential 8