Big Data and the Telecom Industry
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This whitepaper discusses the transformative potential of big data in the telecom industry, highlighting its ability to enhance customer insights, operational efficiency, and revenue generation. It identifies key areas where big data strategies can be implemented, such as customer retention, network optimization, and targeted marketing. However, many telecom companies remain underutilized in their data capabilities and must evolve their strategies to fully leverage the wealth of information at their disposal.
Big Data and the Telecom Industry
- 1. WHITEPAPER BIG DATA AND THE TELECOM INDUSTRY. THE POTENTIAL OF BIG INSIGHTS THROUGH DEEP DATA ANALYSIS.
- 2. Introduction WHITEPAPER We are progressing towards an era of information which can and must be converted into real time actionable acumen, to enable the companies respond in real-time to behavioral changes in the customer mindset or to swiftly respond to threats from the market competition.ThisisexactlywheretheBigDataanditsanalysiscanwinthebattleagainstthetraditionalBItools. Meanwhile, Telecom companies are unaware about the volume of data which could, on proper analysis can get deeper insights into customerbehavior,preferences,interestsandtheirserviceusagepatterns.ThisiswhatBigDataisforTelcos. With the increasing adoption of smartphones and growth in mobile internet, Telcos today have access to exceptional amounts of data sources including – customer pro les, device data, network data, customer usage patterns, location data, apps downloaded, etc.. All this datacombinedtogetherbecomestheBigData. Big data has the potential to place the telcos in a position to win the battle to earn more customers and create new revenue streams. It provides them with a wealth of information about their customers’behaviors, preferences and movements.Yet, many telcos still struggle tofullyderivethegreatestvalueofbigdata. How much can companies in the telecommunicationsindustry bene t from“big data”?That’s a critical question. Most operators conduct analytic programs which enable them to use their internal data and boost the efficiency of their networks and drive pro tability with somesuccess.Thepotentialofbigdataalsocomeswithadifferentchallengeofcombininglargeramountsofinformationsoastoincrease revenues and pro ts across the entire telecom value chain - from network operations to product development to marketing, sales, and customerservice. Finding big bene ts in The more you know your data, the more you can use it to your advantage How much? bytes of data are created everyday (that’s 2,500,000,000, 000,000,000 bytes.) The volume of business data doubles every year. This year + 1.2 years By 2020, the digital universe will equal 1 Zettabyte = 1 Billion TB (1,000,000, 000 TB) Thats 5,247 GB of machine-generated data for every person on the planet WhiletalkingabouttheBigDatastrategy,thetelecomindustryhasanadvantageduetotheabsolutebreadthanddepthofdataitcollects in the course of normal business. A telco serving 8 million prepaid mobile subscribers generates approximate 30 million CDRs daily, amounting to 11 billion records annually. If the same operator also provides postpaid and xed lines services, then there is even more volumeandvarietyofdataattheready. Data is de nitely one of the most strategic assets for a telco today.With an treasure of data at their ngertips, telcos are practically sitting onagoldmineofinformationandhaveanimmenseopportunitytocapitalizeonthesevaluabledatasets. There are various types of information that can be enhanced with a sound Big Data strategy. So what could an operator do? Based on a Telecoms.comindustrysurvey,bigdataispoisedtobringmostvaluetotelcosintheareasofcustomerretention,customersegmentation, network optimization&planninganddelivering upsell/crosssellopportunities.LookingatBigDatathroughacustomerperspectivefour strongopportunitiesappear. Probable Bene ts From Big Data
- 3. WHITEPAPER Customer Experience Network Optimization Operations Analysis Data Monetization Targeted Marketing Predictive Churn Analysis Customer Life Cycle Analysis Proactive Support Capacity Planning Investment Planning Real-time Traffic Analysis Revenue Leakage Network Security Data Analysis as a Service Data Monetization Customer Experience Telcos today are re ning & optimizing the customer experience which is a key to sustaining a market differentiation and reducing churn. Telcos are leveraging Hadoop and big data analytics to gain a true 360-degree view of their customers along with their lifecycle. Basis the detailed customer pro les, Telcos would then do targeted micro-segmentation of their consumer base, offer a compelling customer experience,developpersonalizedofferrecommendationsandpredict/preventchurn.Exampleofthesameisasbelow: Targeted Marketing Customized product offerings basis the characteristics like –usage patterns, billing data, support requests, purchase history, service preferences demographic information, location, etc.This also enables a telco to proactively present the right offer at the right time, in the rightcontexttotherightcustomerinordertoimproveconversionrates.Examples–offertop-upplansorup-sellrecommendationsbased ondatausage,discountsoroffersbasedonrecentpurchasesorenquiriesorcallsintothecallcenter. Predictive Churn Given the impact of customer churn affecting the Telco industry today, they are effectively using big data analytics to bring together various data points including – quality of service, network performance, subscriber billing information, details on calls to the customer care centers centers, and social media sentiment analysis to build an effective model to predict and prevent churn. For example telcos would be able to proactively reach out to high value customers, who have experienced a series of Quality of Service (QoS) issues or who shared a negative sentimentregarding the service in social media, and address those issues and offer them discountsor service credits to preventcustomersfromdefecting.
- 4. WHITEPAPER Customer Lifecycle Real-timeanalyticsthatmaptheuserjourneyandgeneratesactionableinsightsthatcanallowTelcostorespondquicklywitha“next-best offer”and convert interested prospects into customers. Data such as customer demographics, purchasing behavior and clickstreams are being combined with attributes such as location and content preferences to for next best offers.This also enables telcos to map speci c customer’sinteractionswiththeTelcoatvariousstagesofthelifecycletopromotetailoredofferingsandcampaigns. Proactive Support Using big data,Telcos are building intelligence and analytics tools so as to proactively identify issues and x it or offer a solution before it impacts the customer. Based on a recent survey conducted by Coleman Parkes focused on theTelco industry it found that 84 percent of respondents were more likely to recommend their service provider if the provider was able to identify and pre-emptively resolve potential issues affecting them. Given the impacts,ServiceProvidersareproactively xingissuesorreachingouttocustomerstohelpresolveissuesbeforetheynegativelyimpacttheexperience. Network Optimization Network capacity is a highly valuable resource andTelcos are starting to leverage big data & analytics to effectively monitor and manage networkcapacity,buildpredictivecapacitymodelsanduseitforprioritizingandplanningnetworkexpansiondecisions. Capacity Planning By correlating network usage and using real-time capacity data highly congested areas can be pinpointed where network usage is nearing itscapacitythresholds,inordertoprioritizeexpansionfornewcapacityrollout.Forareaswithexcessnetworkcapacity,theycanrunspeci c customer campaigns or promotions to increase usage. Based on real-time analytics and traffic, they can also develop predictive capacity forecastingmodels,trackactualversusforecastedtrafficto ne-tunethemodelandplanforsupplementalcapacityincaseofoutages. Investment Planning Withsomanyconsiderations,telcosneedtobeabletoeffectivelyprioritizetheirinvestmentsandresourcesbasedon–futureconnectivity needs,strategicobjectives,projectedRoI,forecastedtraffic,customerexperienceetc.allwhileensuringthatthehighestvaluedcustomers get to bene tfrom theseinvestments as well. Hence the needto be ableto effectively combinenetwork traffic data, customerexperience metrics,revenuepotentialandlocationdataalongwithcustomervaluedatatoensuretheyareinvestingtheirCAPEXintherightspots.
- 5. WHITEPAPER Real-time Analytics Telcosusedtorelyonhistoricaldatafortheirnetworkmanagementalthoughtheyhavenowstartedusingbigdataandanalyticaltoolsto build real time capacity heatmaps to monitor the quality of user experience and send alerts on network congestion or potentialoutages. Big data analytics can enhance these processes by enabling real-time processing of network data to continuously monitor and manage thenetwork andhelpthemmodelnetwork activityandmapfuturedemand.Telcoscannowmodelthepotentialimpact,inreal-time,ofa particular cell site goes down based on the number of subscriber and capacity in the adjacent sites. Similarly based on real-time data collected from the cell towers, engineers can monitor any drop in service performance at a speci c location and send in crews, if need be, foraproactiveresolution. Operational Analysis Telcos use the big data around driving internal efficiencies, process improvements and cost savings around the core Telco operations. They are starting to adopt big data solutions powered by Hadoop for everything from plugging and minimizing revenue leakage, managing network and cyber security, driving down order-to-activation lead-times to proactively identifying and xing customer issues inordertominimizetruckrolls. Revenue leakage Based on industry estimates, telcos lose approx. 2.8% of their revenues to leakage & fraud annually – costing the industry approximately US $40 Billion every year, which meansTelcos could be adding $ 40 Billion to their bottom-line without selling any additional products or services. Hadoop based solutions can help telcos process and analyze both structured & unstructured data going back several years, ratherthanjustafewmonths,enablingthemtogainabetterunderstandingofthebehaviorofcustomers. Network / Cyber Security Telcos need to ensure their networks and associated systems are secure from malicious attacks. Legacy event detection capabilities are unable to analyze all the data sources necessary for identifying & responding to advanced threats due to the sheer cost & complexity. Security professionals need to be able to access and analyze an avalanche of data (including logs, events, packets, ow data, asset data, con gurationdataetc.)inreal-timeinordertomitigaterisk,detectincidents,andrespondtobreaches.
- 6. WHITEPAPER Data Monetization Telcos have unique advantage about having access to subscriber demographics, subscriber location, network usage, devise, application usage, preferences etc. Given all the data telcos are starting to mine, model, aggregate and anonymize these data sets to create powerful statisticsthatcanbeofsigni cantvaluetootherbusinessesandverticals. Data Analysis By combining the customer location information with customer demographics and preferences, telcos are starting to provide Data Analytics as a Service (DAaaS) to other key verticals including: retail, nancial services, advertising, healthcare, public services and other customer-facing businesses.There is a wide variety of applicationand use cases for datacentric analytics ranging from - customer footfall analyticstoassistingcitiesunderstandtheirtrafficpatternsandbottlenecks. Even though the data analytics market opportunities are still in a nascent stage, telcos are looking to accelerate their revenue share from analytics services in the future. Though privacy is still a concern, if executed right, telcos have an opportunity to effectively monetize customerinsightsbymakingitrelevanttootherbusinessesandverticalswithoutcompromisingonsubscriberprivacyandrights. IoT / M2M Analytics Telcos are trying to leverage the IoT opportunity to move up the value chain from providing just connectivity services, to providing end- to-end M2M solutions.Telcos have the ability to add locationbased and geo-spatialelementsto the streaming datato enrich the insights ofthedatacomingsothatitcanprovidevaluableinsightstotheenterpriseverticals.Withpetabytesofdatastreaminginmultipleformats inreal-timefromsensorsacrossmultiplegeographies,telcosareleveragingHadoopastheidealplatformtocollect,store,secure,manage andanalyzethesedatasetsinreal-time. Today customers want aggressive pricing, value for money and a high quality service.They don’t hesitate to switch between providers if theydon’tgetwhatthey’relookingfor.Soparticularlyindevelopedmarketsitisabsolutelycrucialtoputinplaceasustainableandrobust strategyforcustomerretentiontopreservecustomerlifetimevalue. The telecom market today knows why the high acquisition costs and slim pro t margins for each customer make churn analysis vital to helpcompaniesidentifyandretainthemostpro tableamongthem.
- 7. WHITEPAPER Potential Data Availability & Use Bigdatapromisestostimulategrowthandincreaseefficiency&pro tabilityacrosstheentiretelecomvaluechain. •EnhancingroutingandQoSbyanalyzingnetworktrafficinrealtime •Analyzingcallrecordsinrealtimetoidentifyfraudulentbehaviorimmediately •Allowingcallcenteragentsto exibly&pro tablymodifysubscriberplansimmediately •Customizingmarketingcampaignstoindividualcustomersbylocation-basedandsocialnetworkingtechnologies •Usinginsightsintocustomerbehavior&usagetodevelopnewproducts Big data can even open up new sources of revenue, such as selling insights about customers to third parties.The analysis of Big Data also contributestodecreasetheCAPEXorOPEXassociatedwiththebusinessoperations. Network Infrastructure Product Marketing & Sales Customer Care Billing RoI Of Big Data Peppers & Rogers Group recently worked with a mobile operator to improve its marketing effectiveness and ROI.The client did not have detailed data for its mobile subscribers, and the average time to market for a targeted marketing campaign was one month. It was simply notinteractingwithcustomersfastenoughorwiththerightmessages. The team constructed a data mart containing a summary of all detailed international usage information for each mobile subscriber and used this data mart to determine target subscriber groups. The team then designed and launched several below-the-line campaign waves based on best practices in the industry to the relevant customer groups. For example, some campaigns were designed to boost revenuesbyadjustingproductofferingsbasedoncustomerusagepatternsbycountry. Over the course of one year, the operator launched more than 250 targeted outreach campaigns, which achieved a 33-percent response rate, on average.The time to market for those campaigns dropped from 30 days to one week. And the biggest improvement was seen in customer interactions. Network traffic increased by 64 percent, daily active subscribers jumped by 17 percent, and revenues grew by 2 percent. These results are not unusual for companies with a keen balance of data strategy and the customer experience.Yet many operators are at differentpointsalongthedatamaturityspectrum.Inourexperience,mostoperatorsfallintooneofthreedataenvironments: • Network events • Call records (on and off network) • Number of text and multimedia messages • Volume of data traffic • Location-speci c data • User handset data • Technical fault data • Product catalog • Product life-cycle data • Product and platform costs • Innovation road map • Product usage • Critical products • Product delivery management • Customer devices • Option preferences • Sales channel data • ARPU classi cation • Response rate of marketing campaigns • Segmentation data • Usage patterns • Subsidy levels • Order data • Contact data • Fault handling data - Problem type - Resolution time and rates - Repeated faults • Call center logs • Termination reasons • Call duration records • Tariff data • Usage history • Customer account data
- 8. •Info-archive:OperatorsthathaveyettostartinitiativestoleverageBigData.Theyhavelimitedornoanalyticscapabilities. • Info-familiar: Those who have already embarked on the data journey but have not implemented a full- edged solution. Any analytics theydohavearead-hocandnotcoordinated. • Info-smart: Operators that have created a robust Big Data environment.Customer information is aligned and shared across the business andadvancedanalyticsareused. The concluding goal is to combine and correlate every information source to generate a complete and transparent view of all the interactions every customer has with the operator. But to really utilize big data, telcos must radically change how they compile and make useoftheinformationattheirdisposal. “Operators should realize from companies such as Google and Facebook, where data is king and virtually every product decision ows fromwhattheavailabledatasaysaboutcustomersandhowitcanbeused.”-PwC Big data poses a real opportunity to gain much more of a Telco operation and its customers and to add to their innovation efforts. The industry as a whole spends too less on R&D than any other technology-oriented industry and its efforts to change its ways have not yet provensuccessful. The operators that can incorporate new agile strategies into their organizational DNA fastest will gain a real competitive advantage over theirslowerrivals. Tata Teleservices Ltd. | Registered Office Address: Tower 1, Jeevan Bharati, 124, 10th Floor, Connaught Circus, New Delhi - 110 001 | Corporate Identity Number: U74899DL1995PLC066685 | Tata Teleservices (Maharashtra) Ltd. Registered Office Address: D-26, TTC Industrial Area, MIDC Sanpada P. O. Turbhe, Navi Mumbai - 400 703. Corporate Identity Number: L64200MH1995PLC086354 Tel No: 1800 266 1515 | email id: [email protected] WHITEPAPER Data Maturity Return On Information Info Archive Operator > Data sits in the source system > Very limited analysis & reports > No analytics Info Familiar Operator > Data structure is dispersed > Ad-hoc analysis & reporting > Basic analytics Info Smart Operator Integrated Customer Information > Advanced analysis & reports > Smart targeting basis customer > Information