Intent management application jan 2014
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Intent management application jan 2014 Intent management application jan 2014 Presentation Transcript

  • 1confidentialFlytxt. All rights reserved. 30 March 201430 March 2014© Personalized Intent Management Capture, Associate, Recommend
  • 2confidentialFlytxt. All rights reserved. 30 March 201430 March 2014© Flytxt Overview – About Us  200+ employees consisting of Marketing Consultants, Data Scientists & Analysts, R&D Experts, Software Engineers  Management team with 200+ years in Telecom  Dutch corporation with Global Development Centre at Trivandrum, India and offices at Dubai, Delhi, Mumbai, Dhaka, Lagos and Nairobi  Our vision is to create >10% measurable economic value for CSPs through Big Data Analytics  Flytxt solutions increase revenues, margins and customer experience for CSPs  Products based on patent pending DLU framework implementing complex analytics  Serving many small & large operators across continents totaling 500M+ subscribers, via a mature CTE model  Proven: 2% to 7% economic benefit to customers  Emerging market innovation that has high potential and relevance to the developed markets Vision, Mission & Impact Company Awards & Achievements Sample text IEEE Cloud Computing Challenge B.I.D International Quality Sample text Customers (50+ customers, 32 countries) Operators & SIs Brands
  • 3confidentialFlytxt. All rights reserved. 30 March 201430 March 2014© Big Data Opportunity for Telco’s Big Data: Creating economic-Value from high-Volume, high-Velocity, high-Variety information assets with high-Veracity using new techniques of information processing.  Creating transparency  Micro-segmentation  Enabling experimentation  Replacing/Supporting human decision making  Innovating new business models, products & services Enables Revenue Enhancement Customer Retention Intent Management Mobile Advertising Granular Margin Management* Current solutions from Flytxt The opportunity is to create an impact of well over $250 Billion p.a. by 2017 Flytxt current solutions’ scope is estimated at a third of this. * Roadmap Application
  • 4confidentialFlytxt. All rights reserved. 30 March 201430 March 2014© KPIs INSIGHTs RECOMMENDATIONs ACTIONs PREDICTIVE MODELS FILTERING STATISTICAL CLASSIFIERS SOFT CLUSTERING CORRESPONDENCE ANALYSIS TIME SERIES ANALYSIS AGGREGATION COVARIANCE TWO-PASS ALGORITHM K MEANS CLUSTERING SCORING ITERATED FILTERING NESTED SAMPLING EXPECTATION MAXIMIZATION SOCIAL NET MODELS PREDICTIVE MODELLING TIME SERIES ANALYSIS ANALOGICAL REASONING PREDICTIVE INFERENCING MATRIX REASONING GENERALIZATION STATISTICAL SYLLOGISM REDUCTIVE REASONING SET COVER ABDUCTION PROBABILISTIC ABDUCTION ABDUCTIVE VALIDATION ABDUCTIVE REASONING LOGIC BASED ABDUCTION INDUCTIVE REASONING BAYESIAN INFERENCE SUBJECTIVE LOGIC ABDUCTION Ad Network Insight Monetization Revenue Enhancer Intent Management Ad Market-placeCustomer Retention Faster, More efficient, Easier Full Service: Technology, Consulting , Execution
  • 5confidentialFlytxt. All rights reserved. 30 March 201430 March 2014© 500+ Million Subscribers Flytxt in Action 440 Million prepaid and 60 million postpaid customers 750 thousand customer segments  25 Million data products sold in 2012-13  0.3 Million mobile money transactions for a leading CSP  Products sold through 8 different touch points  2 multi-national group level framework agreements  3 out of global top 15 CSPs based on revenue (Q1 2013)  70% market share in Africa 50+ CSPs across 32 countries 300+ Million products sold in 2013 $250 Million Incremental Revenue till now 27 Billion customer offers made  33% usage enhancement for Kenyan CSP  Churn reduced by 25% for South Asian CSP  >300% ROI on mobile Ad campaign for handset upsell  3% average improvement in total MoU for African Tier 1 CSP  3 Billion data offers sent  3 Billion VAS offers sent  1 Billion annual personalized recommendations in one CSP
  • 6confidentialFlytxt. All rights reserved. 30 March 201430 March 2014© Real-time Visibility and Measurements KPI’s, Insights, Actions, Recommendations, Correlations, Multi-Dimensional Trending, Multi-granular segmentation, … 10s of 1000s, Micro- Segmented ,Multi wave, Recurring, Contextual, Control group, Best fit, Next-Best, … Managed Multi-Channel Communications Flexible Workflows, Comm. Policy, Traffic management, Prioritization Multi-channel Communication, … On-Screen Business Dashboard, Performance, Milestones Real-time Impact, … ROI Reporting, Impact Measurement, Experiment Results, Rating, Billing. … ANALYSIS PLANNING EXECUTION MEASURING Sample Actions: 1. As soon as a zero-usage subscriber activates send Best fit offer 2. Send two wheeler visual MMS to subscribers who are Commuters but not long distance travelers with free helmet offer on test drive. 3. Offer Best Fit Data Upgrade to CSP subscribers segmented on consumption , pocket size & Handset type Platforms: Real-Time, Integrated, Closed Loop Measurement and Reporting Real-time Analytics Real-time ActionsReal-time Visibility <90d 90-180d > 180d >=300 KES Diamond Top 1% Platinum Next 9% Gold Next 40% Silver Next 50% Ivory New Silver ARPU/ % of base AON Gold Ultra New T M
  • 7confidentialFlytxt. All rights reserved. 30 March 201430 March 2014© Enhances Customer Experience through personalizing services and content, with behavioural association and contextual recommendations NEON-Big Data Analytics Powered Platform
  • 8confidentialFlytxt. All rights reserved. 30 March 201430 March 2014© Functions of Intent Management Next Best Action Service Personalization Lost Intent Revival Touch point personalization Content personalization Proactive customer care Auto recommendation Experience optimization Offer discovery Lost intent capture and revival RFM based prioritization Contextual cross-sell offers
  • 9confidentialFlytxt. All rights reserved. 30 March 201430 March 2014© Why Service Personalization is Important? Food Air Shelter Esteem Self actualization Innovative Operators are striving to meet Service Personalization objectives for Self Actualization
  • 10confidentialFlytxt. All rights reserved. 30 March 201430 March 2014© What Goes Wrong? Untimely offer Inconsistent customer experience Bad experience Blanket offers Improper segmentation Operator Customer Irrelevant content “Frustration leads to opportunity loss and customer churn”
  • 11confidentialFlytxt. All rights reserved. 30 March 201430 March 2014© Approach Needs to Change Blanket recommendations Persona driven recommendations  "If we have 4.5 million customers, we shouldn't have one store, we should have 4.5 million stores." - Jeff Bezos, CEO, Amazon.com  “Event Triggered, real-time recommendations based on customer behavior have 10-15 times the response rate than mass marketing “ – Gartner Persona Driven Recommendations focusing on unique needs of individual customers Personas of same person
  • 12confidentialFlytxt. All rights reserved. 30 March 201430 March 2014© Flytxt Approach to Intent Management 1. Big Data Analytics 2. Creating subscriber personas 3. Personalized recommendations Service Personalization Next Best Action Lost Intent Revival 4. Business outcomes Personas of same person
  • 13confidentialFlytxt. All rights reserved. 30 March 201430 March 2014© Deriving Insights through Big Data Analytics Data Fusion Engine Continuous Insight Engine iTag Assembly Adapter Online Batch mode Supervised/ unsupervised learning Predictive modeling Statistical classifiers Soft clustering Correspondence Analysis Nested Sampling Iterated filtering Social net models Millionsofsubscribers Thousandsofproducts Hundredsofcontexts Insights Recommendations Actions Heavy international caller Provide value pack for international calling Offer international pack at 20% discount
  • 14confidentialFlytxt. All rights reserved. 30 March 201430 March 2014© Capturing Subscriber Personas Persona: Young subscriber High volume SMS usage Party enthusiast Persona: Professional Business content user High end handset user Persona: Young Subscriber Uses Social Networks & IM Sports enthusiast Personas of individual subscribers Different personas of same subscriber Persona: Professional Business content user Online money user Persona: Sports enthusiast Loves cycling Attends sports events Persona: Traveler Heavy roaming pack user
  • 15confidentialFlytxt. All rights reserved. 30 March 201430 March 2014© Personas Sports fan, celebrity fan, high tech lover, etc. Social models Top 10 friends, top 10 influencers, etc. Call/data models Heavy caller, International caller, night caller, etc. Location models Home location, frequent traveler etc. Custom models Any custom models on demand Usage models Minutes of usage, Local, international, GPRS, etc. Intent Management Personalized ads Best fit offers Personalized experience Personalized content and navigation Futuristic offers Dedicated customer service Creating Personalized Recommendations
  • 16confidentialFlytxt. All rights reserved. 30 March 201430 March 2014© Enhance Experience through Service Personalization Optimize Customer Experience at each touch points through Sequence Discovery (Perpetual Pull Campaign) Segment 2 Segment 3 Segment 1 Segments created from the full base using profile, metrics and event Information Offer A Offer B Offer C Segment 3 Each segment is mapped to one or multiple offers Rule based Offer Cascading SMS MMS OBD WAP WEB Email USSD Offers fetched through multiple communication channels
  • 17confidentialFlytxt. All rights reserved. 30 March 201430 March 2014© Recommending Services and Best-fit Offers Your Friend just tried to call you. Answer the calls while you are busy- subscribe to our automatic reply services Miss call alert  Use Social profile (top friends) and subscribers persona (frequent callers) High value subscriber, treat accordingly! Customer service  Treat subscribers more personally  Better recommendations  “Frequent customer care caller”  “Inbound calls only” You are a frequent SMS user. A 100 SMS pack for X would save you money! SMS package  “Best fit offers” based on usage personas  Not only “push”, but also pull, through retailers, etc... Sales and distribution  “Value conscious subscriber”  In store recommendations  Helping subscriber and outlets  SMS service “best offer” for retailer Another voucher will provide more value than the one you are just buying. Would you like it?
  • 18confidentialFlytxt. All rights reserved. 30 March 201430 March 2014© Content Discovery on Portal Content type Content structure  Customized content • Content itself can be highly personalized  Customized content structure • Content structure on subscriber preference
  • 19confidentialFlytxt. All rights reserved. 30 March 201430 March 2014© Next Best Actions through Contextual Grading Objective was to design an advisory system which aids the marketer in recommending most graded contextual offer to subscriber based on relevance & Objective An analytics technique that identifies packs which would be interesting to each user based on their historical usage behavior, spending patterns and current context Capability to tune the fairness of the algorithm (Subscriber Affinity vs. Correspondence Association vs. Contra Association) Fuzzy matching, Soft Clustering, Propensity deduction technics applied to create graded matching of subscribers into soft clusters. Graded Association of subscriber to each cluster is a powerful approach for automated decisioning (e.g. Automatic matching of relevant offers to Subscriber) The work got published in 19th National Conference on Communication at IIT Delhi - Thomas, Shyju et al. , available for download from IEEE Xplore Next best Offer Fairness tuning: Subscriber Affinity Correspondence Association Contra Association Revenue Objective Margin other
  • 20confidentialFlytxt. All rights reserved. 30 March 201430 March 2014© Contextual Grading Recommendation Example 0 2 4 6 8 10 12 14 16 18 20 Offer-1 Offer-2 Offer-3 Offer-4 Offer-5 ConversionRateinJul-2012 (in%) 0 5 10 15 20 25 AP AS BH CHN DL GJ KAR KL KOL MH MUM OR PUN RJ TN WB ConversionRatein Jul-2012(in%) Circles Rule-based campaign Best-fit recommendation (fair) Current Personas built: CLV (HVC, MVC, LVC), Volatile, Early Adopter, Frequent Handset Changer, Heavy Data user, Social Media Fan, Bollywood Fan, Music Fan, Sports Fan, potential ipad buyer, International Caller Etc……. Objectives: Cross sell, Upsell, Stimulate recharge/usage/Service adoption Etc… Offers: Data Plan, 3G plan, VAS usage, International Calling packs, Bundle offers, Recharge stimulation, Seeding, ebill subscription etc…… Channels: IVR, SMS insert, In store, Retailer, WAP portal, Customer care portal
  • 21confidentialFlytxt. All rights reserved. 30 March 201430 March 2014© Failed subscriptions/purchases CRBT packISD pack GPRS pack Subscriber Dear Customer, You have been successfully credited $50. Your purchase of ISD pack has failed before, would you like to purchase now? If yes reply ISD100 to 56363 Best match in value/recency/number of attempts Lost Intent Revival: Best Match Selection and Revival Recharge transaction Recharge success notification + intent marketing message Recharge value: $50
  • 22confidentialFlytxt. All rights reserved. 30 March 201430 March 2014© Definite Business Outcomes Correlation between high Customer Experience Index and three elements of loyalty Source: Customer Experience Boosts Revenue- Research note by Forrester NBA conversion is 1.6 times higher than manual 40% of subscribers decides to buy another transaction due to low balance 1% increase in Customer Satisfaction leads to 2.9% increase in ARPU Intent Management Enhances Customer Loyalty Intent Management Enhances Revenues Service/Content Personalization Next Best Actions Lost Intent Revival Source: Arthur D. Little Source: Flytxt Source: Flytxt
  • 23confidentialFlytxt. All rights reserved. 30 March 201430 March 2014© Case Study: Recommendations at an Indian Operator Subscriber Profile –67.53 Million base Total Rows Processed/Day -175 billion rows at a data integration frequency of 5 Minutes to 24 Hrs. Max. TPS Achieved – 1533 messages/sec Total 7 Touch Points Integrated – IVR, webPayment, Retailer, USSD, SOMA (prepaid system), ASCC, MBR, System Specifications Impact Generated 1185 MN Recommendations annually 8 touch-point personalized 12 MN Unique conversions obtained annually 1.4% incremental revenue generated annually
  • 24confidentialFlytxt. All rights reserved. 30 March 201430 March 2014© Sample text Advantages  Lower TCO  Enhanced marketing agility  Seamless Integration  Flexibility in defining marketing workflows  Comprehensive Analytics driven decisioning Sample text  Service and content personalization • Better touch point experience • Highly targeted marketing communication  Contextual auto recommendations • Highly relevant next best actions • High possibility of influence and conversion  Lost intent revival • Better use of lost opportunities to engage with customers • Increases ARPU and improves customer experience Intent Management Solution TM
  • 25confidentialFlytxt. All rights reserved. 30 March 201430 March 2014© Flytxt Proven & Differentiated Flytxt Big Data Solutions are Faster, More efficient and Easier Fully managed service with Consulting, Technology and Execution makes it Easy for CSPs to generate measurable economic value Proven to deliver 2%-7% economic value in some of the world’s toughest CSP markets Endorsed by Industry experts and thought leaders as an emerging market innovation that is relevant for mature market CSP’s Source: Cool Vendors in Emerging Markets, 2013. Published: 16 April 2013. Gartner.Source: Emerging Market analysis: CSP solutions for innovative solutions in Telecom services, 2013 and beyond. Published: 9 April 2013. Gartner.
  • 26confidentialFlytxt. All rights reserved. 30 March 201430 March 2014© Achievements and Recognitions 1. Recognized as ‘ Exemplar’ in Product Excellence Matrix for Marketing Analytics done with Frost & Sullivan 2. Featured in League of 10 Emerge Growth companies 2013 Won the 2011 IEEE Cloud Computing Challenge – C3 in recognition of its innovation in Mobile Subscriber Fingerprinting using Big Data Analytics. 1. Cool Vendors in Emerging Markets, APAC 2013 2. Featured in Analytics, Telecom, CSP Operations Hype Cycles, 2013 3. CSP Framework for Innovative Solutions in Telecom, 2013 Finalist among Top 5 in Asia Communication Awards under innovation category, 2013 1. How Can European Operators Make The Most Of Mobile Marketing & Advertising?, 2010 2. Mobile Messaging Vendor Overview., 2012
  • 27confidentialFlytxt. All rights reserved. 30 March 201430 March 2014© Thank You www.flytxt.com