Introduction
in modern telecommunications with the rising up competition among service providers, and customer acquisition and retention is a big challenge. For newcomers, and get new customers is the top priority, while the occupants, and to keep revenues win customers is essential.
telecommunications companies can increase profitability by creating a predictive modeling to identify potential candidates froth and does not seek to profit and gain customers. It can increase revenues and profitability through targeted campaigns and promotions that these customers will not only retain but also convert revenue is to win customers in a revenue gain profitable customers.
This article highlights the need to churn and management of campaigns and the use of SAS - intelligence communications program (TIS) for this purpose. It also includes the various challenges of the implementation of the SAS - TIS in the scenario in real time
churn management
customer acquisition and retention is a big challenge in all industries. In the telecommunications industry because it affects the profitability of the company if the client Limoges before the company can invest incurred in obtaining the customer spent. Therefore, it is very important to identify profitable customers and keep them.
with the telecommunications market is becoming more competitive, and to identify the customer left the service of the company increasingly difficult reasons. In this circumstance, it is even difficult to predict the likelihood of the customer to drop in the near future. It is increasingly difficult to develop incentives cost effect to target the right customers to persuade him to stay with the company.
aims predictive modeling to analyze the froth and management to generate tens to imagine the possibility of customer churn in the future. This takes into account the different aspects of the sensitivity customer churn, including the history of the people are those who are churning in the past, and build a data model that generates reference numbers easy to understand (TENS) allocated to each customer. Then they are targeting those customers with incentives to deter canceled. In other words, the analysis determines the froth possible reasons for the abolition of the future based on the past records of the companies that will help to customize the display. For example: If the analysis reveals that many customers and deterrence of a specific area in the past month and further investigation identified that there is a frequent call drops (a defect in the service) in this exchange (or BTS) area. It can be concluded that due to the lack of technical adequacy of this exchange, in particular, experienced frequent call drops, which contributed to customer dissatisfaction and their transition out of the company. Even more technical solution to this exchange can prevent potential flared in the future.
Business definition of churn management
definition of churn is the first and most important activity in the froth management design. Different companies define froth according to the experiences of their business.
definition of churn differs from prepaid to post-paid scenario.
in the prepayment scenario, can be considered customers as churning in the following cases: can
a) If the client comes out of the network (inactivated)
b) if the customer is not active user (ANU)
ane client considered in the following cases:
i. The customer has no use for incoming and outgoing recent days (X) rolling
II. Customer has only use inbound and friendly but not out of the past (X) rolling a third day. In the case of customer use is less than the amount specified in advance (for work decided) than last (X) days rolling.
in a scenario after payment, and the customer pays rent on a monthly basis. Even if you do not use or use less, the company earns a fixed revenue from each customer after payment. Therefore, the client is also churning only when he / she comes out of the network (deactivated).
froth parameters to analyze the business
After selecting the foam, the next activity and determine the correct standards to contribute to froth. The possibility of foam or froth dozens of individual customers can be generated on the basis of the following details conclusive:
(1). And it used the demographics of the customer demographics of customers related to the division of the customer base the entire data depending on:
a) Age
b) Sex
c) Income
d) the customer's account information
cycle e) participate life
(2). Invoices and use:
billing information and the use of relevant and which is obtained from the switch (data call records) is mainly used to detect the likelihood of churn. Use the following details:
a. Price Plan
b. Monthly usage summary (accused number of the call, the volume of data charged, free speech and the amount of data)
c. Monthly subscription profit
d. Pay wore
e. Channel management information
and. Nutrition information channel
g. Product Information Network (voice, messaging and data)
(3). Technical quality:
quality of service is the engine churn potential, where the proportion of calls or poor quality of service goes down increases customer dissatisfaction, and thus violently possibilities. In the case of CDMA, as the client is coupled closely with the phones, and the effects of aging telephone likelihood of a customer churn
and use the following details:
a. Charges dropped call
b. Quality of Service
c. Omar equipment (phone age in the case of CDMA)
(4). Details of the contract: at the end of the contract period, or grace period, and the potential customer to leave high-touch, and therefore it has a great influence in determining the froth. Use the following details:
a. Commitment period
b. Number of renewal of the contract
c. The current contract end date
(5). Related event:
loyalty scheme or loyalty benefits to keep the main engines. The use of loyalty relevant data program to churn scoring
to identify the source systems:
After deciding the parameters froth, the next step is to identify the systems source from where they will be data extraction
For example:
cusomer details for customer-relationship management system
use and details related to the bills of the billing system
technical quality of the exchange and cellular sites
activation details of the supply system
data management
data management is the basis for business analysis. You must correct data are present in the right place
data management of three parts:
Extraction: involves the extraction of data from the source and load system layer data exchange
Transformation: includes verification from data extracted Health (for example: validate unique keys of its kind), and create join conditions between tables, clean data is invalid etc.
DOWNLOAD: involves downloading data in the data business intelligence warehouse
data modeling and foam generation result
once authentication is available in the data warehouse data, data modeling is performed. It is an iterative process. The access to the quality of the model is the model that returns the best business value. This model provides results in the form of foam result of individual customers and which can be used to determine the objectives of the campaign.
by dozens of foam to keep campaigns
data model generates a result customers wildly individual, which ranges from 0 to 1.
0 - indicates less likelihood for the customer to churn
1 - indicates a higher likelihood of the customer to churn
[1945001مكونات] are weighted the scores of various parameters, such asusage information
balance information
Shipping Information
decreasing (promotional and Core) Information
feature phone
network coverage
quality of service
Customer service / complaints
price sensitivity plan
business decision needs to be taken to determine the upper threshold of the result froth. You need to analyze more customers above this threshold (for example: Customers with a score of 0.7 and above). The top two parameters contributing to the result that the foam is created on the individual customer level (for customers and tens of greater violence than the threshold). Depending on these parameters to keep the campaign can be carried out. The parameters can be as follows:
usage statistics: You can derive the behavior of the use of a combination of attrition (promo and core), balance and recharge information. The client who has the highest score in the "use less" can be targeted with promotional price plan offers to promote his / her use and convert this client of graft revenue to earn revenues
higher outside the net use: higher on the "outside the net use "means that a particular client usually very released to other networks. The campaign can be performed with a plan useful price to connect to other networks. Further called net outside the numbers can lead to identify so-called often outside the net numbers that can be targeted campaigns as a candidate for the acquisition of analysis
Handset Features: phone used by the client can be old and be lacking in features modern. In this case, the likelihood of the customer to change to a newer phone is high, and there is a great affinity of this client to move to another existence bundled service offer phone provider. Retention campaign can be targeted (for this category of customers having high handset degree butter) with a new service with one phone
customers / Complaints Service: The highest score in customer / complaints service means that the client has called the customer service in many often, and the likelihood that customers are dissatisfied with the highest service. Further investigation to call the customer interaction can reveal details about the reason for his call repeatedly for customer service. After the implementation of campaigns on the basis of the result of drivers froth and foam, you need a campaign response to be captured and entered into the database for analysis of the terms of the success of the campaigns.
implementation froth implementation steps management solutions
involvednext stages in the implementation of a solution churn management:
(1). Analysis of the condition: at this stage, and the gathering of business requirements, analysis and decided to work definitions of butter
(2). Rating Solution: In this phase is evaluated BI solutions with a high level requirements of the executing company. And the feasibility of testing depending on business demands a high level of data availability.
(3). Detailed analysis / detailed design: In this stage, the analysis of business requirements for project management in the froth depth to the design, development and promotion of the project. The implementation of an exercise to understand the availability / non-availability of the necessary information to implement business requirements and mapping data from the source system.
(4). Data analysis - ETL: At this stage, data is extracted from the source system, turned (Cleaning / modification of the fields are analyzed and the quality of the missing data) and then loaded into the data warehouse of business intelligence tool
5. Data Modeling: at this stage, the creation of analytical data models statistical methods. (For example: logistic regression method) on historical data to predict the outcome of froth analytical tables populated by data base
(6). Reports Result froth (0-1: 0 - means less likelihood of churn 0.1 - maximum likelihood of churn) is generated in each / account / level of the customer's subscription is created corresponding report
(7). User acceptance testing and roll out: Upon successful completion Against Torture, the program returns out of business users
challenges the implementation of
There are many challenges when. It is implemented business intelligence solutions in a wide range of millions of customers.
time-consuming key to the implementation of the pre-data management. Data management uses 75% of the time the full implementation. Data management the following:
determine the source systems in terms of data to be extracted needs:
Due to the involvement of multiple source systems (CRM, supply system, billing systems, and brokerage etc.), it becomes difficult for the increasingly system to determine the proper source for various data fields. Select the correct data source and mapping fields DIL consumes most of the time of implementation. If you set the data source is wrong, then the next steps for the implementation of the (modeling and analysis) will be wrong, too. So, you need special care to be taken during the data collection process
data quality: in need of data obtained from the source systems to be of high quality and free of errors. The main challenge in implementing the solution business analytics and access to high-quality data. Clean up your data and fill in missing fields consume a great deal of time implementation of
Change Management: With the implementation of the BI solution, users need to change the way we used to make a prediction violently and campaign management. Therefore, the ability to adapt and educate users user needs to be built up through the appropriate training courses
to make smarter operational business system: After the implementation, organizational structure specific to deal with BI processes require planning and need to be trained in the areas required resources .
SAS in Business Analysis
SAS is a leading business analytics software and service provider in the field of business intelligence companies. It has delivered proven solutions to gain access to reliable and consistent and relevant information across organizations to help them make the right decisions and achieve sustainable performance improvement as well as risk mitigation.
SAS has a long ability of data to deal with a large scale, and (with the help of SAS-SPDS - scalable performance data server). This combined with a powerful programming language and a rich graphical interface and differentiated it from other analytical tools available in the market. This makes SAS is well-suited for use as the company calls dealing with massive data stores
SAS - Intelligence solution Telecommunication (TIS)
SAS has several specific industy solutions. SAS has packaged business analysis knowledge in the form of models, processes and business logic, queries, reports and analyzes.
TIS is the communications industry specific analytical solution business that has been built for the specific needs of the telecommunications sector. This solution helps communications with specific units of service providers, for example:
Campaign Management SAS for telecommunications
SAS customers of the telecommunications retailer
SAS Customer Retention for Telecommunications
performance management strategy SAS for telecommunications
SAS cross selling and up selling of telecommunications
SAS risk of payment for telecommunications includes
SAS management churn management campaigns to resolve the division of the entire customer base
disclosure of the reasons for churn
scoring individual customers based on the prospect violently
usedresult froth this is also an entry point for the management of the campaign.
SAS data flow (Architecture)
requires data to be collected from various sources systems
System CRM: customer / account / subscription related data
supply system: the date of activation, and equipment (telephone) bills old system: billing statements
mediation system: call details record
and data are collected in a data exchange layer (DIL ). Then the data extract, transform and load in the detailed data storage (DDS)
data is used for:
(1). Dimensional data modeling: This is used to query, reporting and the OLAP (online analytical processing)
(2). ABT (analytical table base): This is a model specifically developed a solution that can be used for a specific analysis. For example: The ABT model froth
(3). Mart campaign data: and use this data to target specific segments of customers for a campaign targeting
conclusion
Therefore, it is imperative that churn management is a fundamental challenge in. Modern telecommunications Indian industry era. It can detect the correct cause of froth and foam to predict in advance to save the company from a significant loss of income.
business intelligence tools to help telecom service providers to perform data analysis and forecasting the possibility of foam from a particular client. Apart from predictive churn analysis, and tools that can be used to analyze various other to help the business decisions.
SAS has the capacity to deal with the vast amount of data. As a tool for business intelligence, SAS authorizes action to handle efficiently the sheer volume of data and analysis on the information available to millions of customers. Moreover, SAS with a particular telecommunications solution (TIS - Telecom Intelligence solution) helps in building a data warehouse to conduct the required transactions for further analysis
Therefore, SAS-TIS can be an effective tool for the activities of business intelligence. In the telecommunications industry
link :. SAS company details: http://www.sas.com/
link: File Arindam in: HTTP: / /in.linkedin.com/in/arinmukh
0 Komentar