Progressive Rewards Deliver Maximum Returns
Upcoming SlideShare
Loading in...5
×
 

Like this? Share it with your network

Share

Progressive Rewards Deliver Maximum Returns

on

  • 949 views

 

Statistics

Views

Total Views
949
Views on SlideShare
949
Embed Views
0

Actions

Likes
0
Downloads
18
Comments
0

0 Embeds 0

No embeds

Accessibility

Categories

Upload Details

Uploaded via as Microsoft PowerPoint

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment

Progressive Rewards Deliver Maximum Returns Presentation Transcript

  • 1. Progressive Rewards Deliver Maximum Returns Turning Loyalty Programs Into Profit Centers Amit Shankardass & Channing Rollo amitsha@clientlogic.com [email_address] www.clientlogic.com
  • 2.
    • Loyalty Concepts
    • Program Types
    • Operationalizing Loyalty CRM
    • Case Study Examples
    Agenda
  • 3. The Problem U.S. enterprises spend more than $1.2 billion on customer loyalty programs that do not significantly increase profits . Companies must embrace a new generation of programs that broaden customer appeal and integrate with CRM . - Gartner
  • 4. Importance of Customer Loyalty
    • Increased longitudinal economic returns
    • Reflects the level of value a company delivers to customers
    • Enhanced reputation
    Beware the Satisfaction Trap Source: Gartner Optimize Yield (CRM) Revenue Cost
  • 5. Customer Loyalty Hierarchy Source: Gartner
  • 6. Types of Loyalty Programs
  • 7. Loyalty Tool: Clubs
    • Pros:
    • Target large interest group
    • Encourage purchasing behavior through bonuses and rewards
    • Provide steady, reliable revenue for company
    • Easily personalize customer interaction
    • Make loyalty convenient
    • Cons:
    • Limited product/service applicability
    • Non-exclusive merchandise
    • Require responsive customer care, fulfillment and CRM
    • Plans may mandate negative purchase option
  • 8. Loyalty Tool: Continuity
    • Pros:
    • Positive and flexible purchase option
    • Provide steady and reliable revenue for the company
    • Exclusive product offerings
    • Easily personalized for customer interaction
    • Allow customer to enjoy periodic opportunity to shop
    • Cons:
    • Target niche interest groups
    • Limited product/service applicability
    • Require highly responsive customer care, fulfillment and CRM
  • 9. Loyalty Tool: Private Label Exclusive Rewards Program
    • Pros:
    • Allow RFM targeting, segmenting and monitoring
    • Create brand loyalty
    • Ongoing communications allow familiarity, affinity and trust
    • Create an incentive to return
    • Ongoing return of value lessens the chance of defection
    • Cons:
    • Require extensive marketing and record keeping
    • Long-term costs to the company
    • Must be supported by effective CRM, or risk being seen as a bribe
  • 10. Acquisition Tools: Coalition Programs, Coupons, Prizes
    • Pros:
    • Drive customer traffic
    • Low-effort promotion
    • Broaden buyer spectrum
    • May assist in creating customer loyalty only if experience or product “delights”
    • Possible use for data collection and/or surveying
    • Cons:
    • One-time offers produce one-time shoppers
    • May attract primarily swing buyers
    • Spread thin customer attention and business across coalition merchants
    • Lack incentive for customers to remain vendor loyal
    • Increase market share only during promotion; may reduce gross revenues
    • Almost zero customer loyalty effect
  • 11. Operationalizing Loyalty CRM
  • 12. Segmentation is the Key Objectives High- Value Customers Samplers/Non-Loyal Moderate-Value Customers Conversion To High-Value Retention Reward Conversion To Moderate
  • 13. Loyalty Functionality Source: Gartner
  • 14. Required Components for CRM Marketing Database Customer Segmentation and Preferences Customer Data Collection Data Analysis Segmentation Value/Rank Objective Per Segment Technology (Channel & Infrastructure ) Channel Personalization Multi/Cross Channel Management Optimization Reporting Offer/Action Management Offer Analysis Customer Offer Design Channel Offer Design Offer Management
  • 15. Case Study Examples
  • 16. Case Study: Success With Retailer
    • Client:
    • Marketer of premium consumer perishables and related gourmet products
    • Direct mail marketing, outbound telemarketing, member-get-member, etc.
    • Client Came to ClientLogic for:
    • The ability to target specific communications and offers to specific customers
    • Convert multiple systems into one customer view
    • Buyer’s Choice Continuity
      • Represents 95% of client sales volume
      • Several different clubs
      • High member churn each year
      • Negative option for annual program
    • Catalog
      • One-time orders, 4th quarter peak
  • 17. Case Study: Customer Value Pyramid Total Revenue Customer Strategies Retention / Reward Call Center Routing Priority Call Handling Milestone Rewards Premium Loyalty Programs Conversion To Core Churn Reduction Pay Loyalty Program Up-Sells Cross-Sells Conversion To Moderate Recovery Programs Partnership Marketing List Rental $170MM (30%) $214MM (38%) $181MM (32%) Core Customers $1,000+ / 5% Samplers Up to $499 / 83% Moderate Shoppers $500-999 / 12%
  • 18. Case Study: Churn Reduction
    • Challenge
    • Critical business risk: out of business by 2007
    • Customer churn at 39.2% per year and increasing by 5.7 points/year
    • Acquisition stable at 21.8% per year
    • Solution
    • Risk model to classify every customer into a group based on his/her risk for canceling account
    • Specialized training programs for CSR - Risk Handling Certifications
    • Route “high risk” customers to certified CSRs
    • Results
    • Churn decreased 1.1 points/year vs. increasing by 5.7 points/year (approximately $8MM annualized in saved revenue)
    • Identified behaviors of high-risk customers -- enabled client to develop alternative product offerings for migration and further stabilization
  • 19. Conclusion
    • Loyalty programs must be data-driven, sustainable, progressive in reward giving and brand-centered
    • Regardless of the loyalty program tool, segmentation is essential
    • All initiatives must be personal and communicative
    Optimize Yield (CRM) Revenue Cost
  • 20. Progressive Rewards Deliver Maximum Returns Turning Loyalty Programs Into Profit Centers Amit Shankardass & Channing Rollo amitsha@clientlogic.com [email_address] www.clientlogic.com