BRIDGEi2i - #CustomerAnalytics Conference, Chicago 2014


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This presentation was presented at #CustomerAnalytics Conference, Chicago 2014 by Maruti Peri, VP Sales.

BRIDGEi2i helps businesses extract each ounce of loyalty in today's “Age of the Customers” as customer loyalty keeps fighting an uphill battle with increased product choices and proliferation of prospective client information. To know more about BRIDGEi2i Customer Intelligence Solutions, visit

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BRIDGEi2i - #CustomerAnalytics Conference, Chicago 2014

  1. 1. © 2014 BRIDGEi2i Analytics Solutions Pvt. Ltd. All rights reserved Prithvijit Roy CEO & Co-founder #CustomerAnalytics Summit Maruti Peri VP, Business Development
  2. 2. 2 “We see our customers as invited guests to a party, and we are the hosts. It’s our job every day to make every important aspect of the customer experience a little bit better.” Jeff Bezos “ It is not the employer who pays the wages. Employers only handle the money. It is the customer who pays the wages.” Henry Ford In a world of constant change…there is one tenet which hasn’t…Customer Focus
  3. 3. A Customer Centric Organizational Approach 3 Marketing Sales Operations Finance Product Development Customer Centricity CUSTOMER CENTRICITY ACROSS BUSINESS FUNCTIONS Product Profitability Current Sales Brand Equity Customer Equity Market Share Customer Equity Share Product NVP Customer NPS Product Life-cycle Customer- lifecycle Strategy driven by Products Strategy driven by Customer needs Incentives at product level Incentives at customer level METRICS THAT MATTER Customer Lifetime value Customer Profitability
  4. 4. 4 Customer Profile Segment Profile Web Profile CRM Profile Social Profile Market Research Data Web Data CRM Data Social Data Data is key to a Customer Centric Approach
  5. 5. 5 Customer Analytics Journey 360 degree customer data view to understand customers Target-marketing models and personalization opportunities Drive personalized recommendations, operationalize campaigns
  6. 6. Customer Analytics : The Evolution Market Research Transactional Data INFORMATION Offline Sales Insights IMPACT Purchase Propensity Models INSIGHT Segmentation Social / Unstructured Data Micro-segmentation focus Lifetime Value Real-time recommendations on cloud/mobile/web
  7. 7. Operationalize impact Develop actionable insights Diverse Applications of Personalization 7 Pervasive Customer Experience Analytics Customer Lifetime Value Channel Recommendation Engine Case StudyIndustry Function Build customer knowledge Focus Information Technology- B2B Customer Service Insight Ecommerce- B2C Marketing Impact CPG Sales
  8. 8. 1. Pervasive Customer Experience Analytics (1/2) 8 • Business: Global Provider of IT services to other enterprises. • Challenges : • Declining Contract renewals • Sliding Premium / Margins • Clueless about what was driving this. Disparate Data Survey Data Customer support data Social data • Why are Customer Satisfaction metrics not reflecting the slide? • Are we measuring our performance right? • What do we do to reverse the slide? Business Questions? Rich incidence as well as account level satisfaction scores All transcribed customer support data across calls/email/chats Reviews/ Blogs/ Opinions/ Expert Analysis
  9. 9. 1. Pervasive Customer Experience Analytics (2/2) 9 Query across 360 degree customer data view Identify drivers of customer experience from customer interactions Prioiritize key actions to focus on Data Integration Platform 360 degree Customer View Key Driver Analysis Insights and Recommendations Incidence rate 10% Adoption Rate 10% Support Satisfaction 14%
  10. 10. 10 • Who will be my most valuable customer in the future? • How do I focus my investments on potential High value Customers? • How do I build Loyalty and move away from deep discounting? 2. Customer Lifetime Value (1/2) Demographics Past purchases Typical promotions Marketing Costs Frequency of purchases Offline to online transactions Data Considered for calculating LTV Business : Global technology B2C ecommerce site. Challenges: • Repeat Purchase rates declining. • Discount seeking customers eroding margin. • Acquisition quality suspected to be lower. Business Challenges
  11. 11. 2. Customer Lifetime Value (2/2) 11 • Estimation of an appropriate “future period” • Capture typical “pathways” to value for different customers • Statistical models to predict “High Value” segment and non transactors • Rank order customers from 1- 10 on the basis of future value potential next 2 years • Ascribe expected value to each LTV segment • Design loyalty programs to connect with best customers • Overlaid with current propensity models to assess and refine % • marketing spend on high revenue customers High Med Low LTV based Persona New Customer Or Prospect SCORING Modelling Approach Strategy Design Implementation Target : 5% increase in Repeat Purchase rates. $25 increase in Average Ticket Size
  12. 12. Business : A CPG Giant in ASIA . Sells to 1.5+ M stores through about 50 + sole distributors spread across 1000+ branches Challenges : • High turnover in Stores and shelf space. • Intense Competition from a transforming market place. 3. Channel Recommendation Engine (1/2) Data Available Store level sales data Store Panel Data Promotion SKUs Product Rates Business Questions • How do we help stores increase their revenues? • How do we capture shelf space to keep competition out? • How do I use distributors and wholesalers to build loyalty for the brand
  13. 13. 3. Channel Recommendation Engine (2/2) 13 Segmentation of stores based on extent and mix of purchases Identify stores similar to a given store based on purchase pattern Define expected purchase behaviour and potential cross sells High Level Segmentation Define Neighborhood Build Recommendation Rules Recommendation Hit-rate 45% Revenue uplift 10%
  14. 14. For the Business 14 More Customers More Revenue from Customer Add Customer at a Lower Cost For the Customer A better and more personalized Experience Evaluate Purchase Install Usage Marketing Support Disposal Interact …to enhance customer experience and business impact
  15. 15. 15 INFORMATION INSIGHT IMPACT Valueforbusiness Actionability BRIDGEi2i bridges the gap in customer understanding from INFORMATION to IMPACT through INSIGHTS. BRIDGEi2i solves unstructured problems by using multiple data sources, leveraging technology and operationalizing the solution for clients How BRIDGEi2i transforms the Customer Journey
  16. 16. CUSTOMER INTELLIGENCE Customer Experience Management Analytics | Personalized Lifecycle Marketing Analytics : BRIDGEi2i
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