IT and Telecom
Telecom companies are thriving to be innovative and maximize their revenue by implementing right tools at the right place to harness massive volume, type, format, and velocity of data in order to leverage on actionable insights from that data. Telecommunication companies are managing terabytes of data stored in silos and scattered across the organization. Thus, for faster and easier processing of useful data, telcos are searching for a driven data advanced analytics solution to achieve accurate real-time insights through data mining and predictive analytics. The IT and telecommunications sector has witnessed rapid growth in the past decade, and it is undergoing various transformations. With its large size, the industry exhibits complex contracts, interdependencies of services, disparate spends, and minimal resources and time.
The major advantages of predictive analytics to a telecom company is a rise in sales, improved risk management, a decrease in the operational cost, and analysis of customer behavior. The latest predictions from CFCA 2015 Industry Survey reveals that the telecom operators globally incur an average loss of 13% or USD 294 billion due to the numerous uncollected revenue and frauds prevailing in this industry. This predictive analytics tools can help in identifying the potential threats that are prevailing in the industry to avoid losses.
Additionally, predictive analytics is being utilized across all the telecommunication enterprise to smoothen the supply chain, to understand targets and craft marketing campaign accordingly. For instance, network optimization has become an essential part of the telecommunications industry. Predictive analytics is facilitating the user a better customer experience. Optimizing a cellular network involves making numerous decisions, which are supported by predictive analytics based on analysis of historical data making the business stronger, prone to lower risk, and to achieve better outcomes.
COMPETITIVE LEADERSHIP MAPPING TERMINOLOGY
The vendors of predictive analytics software in IT and Telecom are placed into 4 categories based on their performance in each criterion: “visionary leaders,” “innovators,” “dynamic differentiators,” and “emerging companies.” The top 25 vendors evaluated in the data quality tools market include Agilone, Alteryx, Inc, Angoss Software Corporation, Dataiku, Domino Data Lab, Exago, Inc., Fair Isaac Corporation (Fico), Good Data, Greenwave Systems, Inc, IBM Corporation, Information Builders, Inc., Knime Ag, Kognitio, Microsoft Corporation, Microstrategy Incorporated, NTT Data Corporation, Oracle Corporation, Qliktech, Inc., Rapidminer, Inc, SAP SE, SAS Institute Inc, Sisense, Tableau Software Inc, Tibco Software and Teradata Corporation
USE CASES of Predictive Analytics in IT and Telecom
- Customer Relationship Management: Predictive analytics would help companies to monitor and analyze actions, behavior and habits of existing and potential customers such as their demands, usage pattern, etc. and analyze these vital insights for effective customer relationship management.
- Customer Churn Rate Optimization: Churn rate usually happens when customers stop using company’s product and services, preferably known as customer attrition. Predictive analytics tools help company to study factors such as customer usage, understanding their sentiments, and conduct behavioral analysis to design predictive model for customer retention.
- Fraud Analytics: Predictive analytics tools enables organization to analyze complex datasets and events to discover the situations and triggers that can cause fraudulent activity related to payments, identity, and other misconducts.
- Marketing & Sales Analytics: Predictive analytics is used in marketing to identity and analyze the potential customers as to what products and services could be suitable as per their buying patterns for cross selling.
- Revenue Assurance: Predictive analytics helps the company to conduct a real-time revenue monitoring to predict and address the revenue loss associated with customer attrition, frauds or any kind of misconduct, to safeguard revenue across all channels.
- Quality Assurance: Predictive analytics is used to validate business requirements and predict the issue impacting the quality of services, by optimizing testing to critical functions for improved business performance.
- Price Optimization: Predictive analytics is used to analyze the pricing management model by taking into account all the variables impacting the pricing to calculate profit margin.
Case Studies of Predictive Analytics Software in IT and Telecom
IBM Corporation
Case Study: IBM helped eircom to improve customer churn rate
IBM helped Ireland-based telecommunications service provider “eircom” to improve customer experience using predictive analytics to reduce customer churn rate by automating churn prediction alerts. eircom implemented IBM SPSS analytics solution to gain actionable insights about customer’s journey to predict the churn outcome.
Business Outcome:
- Reduction of data processing time by 75% through automation
- Reduction in customer churn rate by 6%
Lavastorm Analytics
Case Study: Lavastorm Analytics helped Mobistar to combat frauds
Lavastorm Analytics helped Mobistar, one of the major mobile operators in Belgium, to implement Lavastrom’s Analytics-driven fraud solution, to prioritize and investigate multiple type of frauds related to payments, identity, dealer and communication frauds.
Business Outcome:
- Accuracy rate for fraud threat detection increased by more than 60%
- Reduction in fraud detection time from 24 hours to nearly 5 minutes
Versium Analytics
Case Study: Versium helped major software company to extend digital campaign
Versium Analytics helped major software company in extending the reach for their digital campaign and generate more leads cost effectively. Versium helped them in mapping consumer attributes of business decision makers using their LifeData warehouse and proprietary matching technology.
Business Outcome:
- 320% increase in online campaign reach
- The number of emails and phone numbers used for matching its customer has increased by 80%
- Increased audience reach with reducing 75% of cost per sales on approved leads
Qlik Technologies
Case Study: Qlik helped Qualcomm in streamlining reporting and operation processes
Qlik enabled Qualcomm to optimize and streamline reporting and operation dashboards by deploying QlikView across their 15 business units, for real-time process analysis and improvement of workforce throughput time.
Business Outcome:
- Saving staff time for reporting process up to 20 hours per month via automation
- Efficiency of Qualcomm’s ASIC System Test group increased for chip testing lifecycle, saving a day’s time each month
TIBCO
Case Study: TIBCO assisted inQuba for enhanced customer experience
TIBCO helped inQuba, a customer experience software provider, in integrating their client’s data with their hosted services for embedded business intelligence and building data visualization reports, to drive improved performance.
Business Outcome:
- Improved customer experience orchestration
- Efficient embedded BI and reporting
Vizualytics
Case Study: Vizualytics helped Mahindra Comviva for telecom revenue assurance
Vizualytics implemented SMS Hub reporting for Mahindra Comviva, a value-added services provider for mobile operators, with the use of custom visualizations tool, for automating SMS delivery based on route cost, which would help source mobile operators to take low-cost route for message delivery for high profitability and revenue assurance.
Business Outcome:
- Improved processing for several terabytes of messages logs within 2-3 hours, to boost profitability
- Maximizing SMS delivery route profitability by identifying low-cost route
RapidMiner
Case Study: RapidMiner helped Mobilkom Austria to optimize customer support
RapidMiner used their Data Science platform to help Mobilkom Austria to analyze the incoming customer requests and automatically categorize them into different categories and forward them to concerned support analysts, using text mining technology.
Business Outcome:
- The customer request categorization time reduced by 70%, for improved ROI
- Minimized the error rate by 5%, for more than 50 different customer request categories
11Ants Analytics
Case Study: 11Ants Analytics helped 2degrees for customer churn rate optimization
2degrees, a mobile telecommunications company in New Zealand implemented 11Ants Analytics solution to identify customers who are at risk of churning, by monitoring various attributes such as time spent on network, customer usage activities and their behavior.
Business Outcome:
- Boost in customer churn rate identification process by 1275%
SAS
Case Study: SAS helped Orange Business Services to improve customer relationship management
Orange Business Services implemented SAS analytics solution to build an improved and effective customer relationship management (CRM) strategy, via tracking sales and marketing campaign effectiveness.
Business Outcome:
- 30% boost in productivity
- Improvement in multi-channel sales and marketing efforts
SAP SE
Case Study: SAP helped Swisscom AG for next-generation data warehouse management
Swisscom AG implemented SAP BW/4HANA solution for faster reporting and interoperability for their new data warehouse landscape with more than 15,000 users, with self-service analytics capabilities.
Business Outcome:
- Report execution time improved by a factor of 100.
- Boost in IT productivity
Dataiku
Case Study: Dataiku helped LINK Mobility Group for revenue optimization
LINK Mobility implemented Dataiku’s data science platform to support their revenue monitoring services with capabilities such as self-documentation, technical and business collaboration, and improved customer dashboards.
Business Outcome:
- 2X times increase in revenue generation
- Improved collaboration between various processes
Hortonworks
Case Study: Hortonworks helped O2 for managing financial reporting and compliance
O2, a brand of Telefónica UK Limited implemented Hortonworks Data Platform (HDP) and Hortonworks Data Flow (HDF), for analytics of various business datasets within Q2 warehouses, to manage and mitigate financial and security risks, to meet International Financial Reporting Standards (IFRS).
Business Outcome:
- Dataset analytics reduced to days from weeks, with almost 20 million records processed daily
- 9% daily accuracy was achieved to meet IFRS 15’s compliance
Qlik Technologies
Case Study: Qlik helped Qualcomm in streamlining reporting and operation processes
Qlik enabled Qualcomm to optimize and streamline reporting and operation dashboards by deploying QlikView across their 15 business units, for real-time process analysis and improvement of workforce throughput time.
Business Outcome:
- Saving staff time for reporting process up to 20 hours per month via automation
- Efficiency of Qualcomm’s ASIC System Test group increased for chip testing lifecycle, saving a day’s time each month
Vizualytics
Case Study: Vizualytics helped Mahindra Comviva for telecom revenue assurance
Vizualytics implemented SMS Hub reporting for Mahindra Comviva, a value-added services provider for mobile operators, with the use of custom visualizations tool, for automating SMS delivery based on route cost, which would help source mobile operators to take low-cost route for message delivery for high profitability and revenue assurance.
Business Outcome:
- Improved processing for several terabytes of messages logs within 2-3 hours, to boost profitability
- Maximizing SMS delivery route profitability by identifying low-cost route
Dataiku
Case Study: Dataiku helped LINK Mobility Group for revenue optimization
LINK Mobility implemented Dataiku’s data science platform to support their revenue monitoring services with capabilities such as self-documentation, technical and business collaboration, and improved customer dashboards.
Business Outcome:
- 2X times increase in revenue generation
- Improved collaboration between various processes