Sweating Digital Assets Analytics Way

Agenda Growth isn t growth anymore! MNOs continues to be relevant The power of analytics The new age assets Digital Getting the best out Mahindra Comviva s Revenue+ Solution 2

Growth isn t growth anymore! Declining mobile base growth Africa - SIM per subscriber Number of connections outnumber the unique users Dropping ARPU SIM per subscriber 2.10 2.05 2.00 1.95 1.90 1.85 1.80 2.03 2.05 2.00 1.96 1.91 2011 2012 2103E 2014E 2015E Markets maturing, customers spreading spend across multiple networks Source: GSMA Intelligence 3

The new world order-rules have changed! Mass marketing Batch & blast Aligned to campaign calendar One-way communication Business & channel silos Manual/semi-automated Periodic Contextual Communication Aligned to customer lifecycle Dialogue/interactive Integrated & informed Fully automated Real-time/ near-real time Segment of one marketing 4

Digital assets are evolving Have you identified right assets? Subscribers Subscriber profile Ability to reach out on SMS, USSD, Email, Bill, Portal New age assets: Transaction data, Usage patterns, Social data => Context Identify the right customer and serve contextually relevant offers 5

How do we get more from existing subscriber base? Do we have right product mix? Ability to discover the products? Can we improve campaign efficiency? When and how you reach out to subscriber? 6

Customer-side engagement is the key Who is the customer Demographic information, life stage, transactional patterns, device type, social group Where is the customer present Location & network environment When a would a person take an action Real-time information, Operators have large volumes of customer data Power of analytics to understand and bring context to engagement Potentially treat each subscriber as unique 7

Power of Analytics - The paradigm Analytics to micro-segment (even N=1) based on behavior and profiles Cross-product into matching products with micro-segments Reach via more than one touch point: Average is for marketers who don t have enough information to be accurate --Seth Godin 8

Deploy a multidimensional approach to arrive at granular customer insights Analysis based on tariff profile Value based analysis Multi-dimensional analysis Platinum RFM score Interactions Gold Recency Location Demography Frequency Transactions Silver Monetary value Attitude Defines broad segments based on class of service Ranks customers on recency, frequency & monetary value to create segments Leverages demographic, transaction, location, interaction & social media data to identify and address each customer uniquely 9

Deepen engagement over the lifecycle of the customer Acquire Grow Retain Winback Pricing Incentives for the first top-up Discount on VAS trials Bundled pricing plans Location based pricing Use cases Real-time Offers Churn control Personalized real time offers Next best offers Data/VAS/mMoney promotions Location based offers Churn propensity scoring Customer experience optimization Winback campaigns Recommendation Service/content recommendations Rewards Loyalty programs Tenure based personalized rewards 10

Transforming customer context insight Into value requires more than technology Generate big ideas, and innovate Elevate information to the status of a corporate asset Find untapped sources of data Hire new skills /choose right partners Build trust and an analytical culture Profiling basis history Traditional Analytics History will repeat itself! Most of us do this! Profiling basis history & right now context Consumer Behaviour understanding History may not repeat itself! Mahindra Comviva s solution does this! 11

Mahindra Comviva s RevenuePlus 12

Need to address the 3V challenge The 3V challenge Magnitude of challenge Use analytical tools to gain insight into customer data and drive business decisions and action in real/ near-real time Data velocity 5mn x Number of mobile customers GB TB PB Data volume Use open source framework to process and store large datasets 20 = Number of CDRs generated per person per day Data variety 100mn CDRs processes Analyze both structured data (transactional data) and unstructured data (data from social networks, customers feedback) to develop deep insights into consumer behavior 13

Mahindra Comviva s Revenue Plus Data sources Transactional data Analytics layer RFM segmentation Custom micro-segmentation using customer s 360 profile parameters Campaign manager, scheduler and executor Multi-channel Campaign delivery Subscriber profile Location Social media Data visualization layer Reports 14

Case: Analytics driven improvement in Wallet share Operator Leading Nigerian operator with 40 million connections Each customer owns 2.4 SIMs 20% inactive base: US$ 581 mn is the approx. annual opportunity loss from inactive users Deployed winback solution provides retention offer when customer switches-on mobile phone Results Customer data Inactivity patterns Silent period during a day Device type (multi-sim) Service usage pattern Variance in recharge pattern Potential to generate USD 26 mn in annual revenue Analyze customer data patterns to identify multi-sim customers Scientific algorithms Discount Multi-SIM on customer calls during 1: Active day-time: during night Get from 50% 8pm discount to 2am on all calls from 8:00 am to 8:00 pm Send personalized campaigns to multi-sim users Voice Multi-SIM and data customer bundle: 2: Get Uses 1GB data data usage service and only 50 free voice minutes for a month Discount Multi-SIM on off-net customer calls: Same 3: charge for Makes off-net onnet calls calls and on-net only 2.14% growth in market share from Dec 12 to Mar 13 $25,00,000 Monthly net revenue (USD) $20,00,000 $15,00,000 Net revenue 50% 49% 48% 47% 46% Operator's market share 49.3% 49.7% 48.8% 47.9% 48.1% 47.8% 47.6% Winback Launch Sep'12 Oct'12 Nov'12 Dec'12 Jan'13 Feb'13 Mar'13 Operator's market share 15

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