Can Service Organizations Drive Corporate Growth?

Transcription

1 Can Service Organizations Drive Corporate Growth? October 8 th, 2008 Dr. Vince Nowinski Director of Methodology Satmetrix

2 Satmetrix mission: to create loyal customers with the world s leading companies Co-developer of Net Promoter Technology and expertise Ten years linking loyalty to financial results Global deployments with Fortune 1000 clients

3 Introduction What role do service and support organizations play in driving the corporate bottom line? Study 1: Can service and support drive customer loyalty? If so, how? Study 2: Can we quantify the value of investing in support & service in order to optimize customer satisfaction and loyalty?

4 Study 1: Connecting Transactional Service Experiences and Customer Loyalty Does transactional support experience influence customer loyalty? Four companies from four different industries were selected Questions: Does transactional support experience influence broader perceptions of support and the company? Does its influence extend beyond support recipients? What aspects of transactional support can be leveraged to create a more customer-centric organization? Can the support organization contribute to overall customer loyalty, and thus help drive business growth? If so, how? TSE OSE REC

5 Study 1: Connecting Transactional Service Experiences and Customer Loyalty Does transactional support experience influence customer loyalty? Four companies from four different industries were selected Questions: Does transactional support experience influence broader perceptions of support and the company? Does its influence extend beyond support recipients? What aspects of transactional support can be leveraged to create a more customer-centric organization? Can the support organization contribute to overall customer loyalty, and thus help drive business growth? If so, how? TSE OSE REC

6 Transactional Support Leads Likelihood to Recommend by One Quarter Company A r = Company B r = T0 T2 T10 TSE T0 TSE 8 REC REC T1 T3 7 T1 T Company B r = 0.72 Company D r = T0 T12 T1 TSE T3 8 REC T0 REC T2 TSE T13 7 T1 6 TSE: Transactional Support REC: Likelihood to Recommend All 4 companies show a similar pattern Transactional support scores are generally higher than recommend scores Recommend scores move in sympathy with changes in transactional support scores Transactional support changes lead recommend by one quarter

7 Executive Recommend Sensitive to Changes in Transactional Support Satisfaction Average Score T0 T1 T2 T3 T4 T5 T6 T7 T8 T9 T10 Company B r = 0.91 TSE T1 T2 T3 T4 T5 T6 T7 T8 T9 T10 T11 Time (measured in quarters) REC (Execs) A quarterly decline or improvement in Transactional Support is typically followed by a more extreme pattern of declines or improvements in executive recommend Internal / organizational influencers exert an impact on executive perceptions TSE: Transactional Support REC: Likelihood to Recommend

8 Identifying Support Levers What levers can be pulled to improve transactional support and drive a more customer-centric organization? Common levers that can drive transactional support include rep knowledge level, ability to solve problems effectively and on time, and understanding of the business problem/impact Implications for training/coaching and balancing resolution quality with speed Knowledge/Expertise Resolution Effectiveness Resolution Timeliness Responsiveness Understands Business Problem TSE OSE REC

9 Summary of Findings Service experiences do exert an impact on overall customer loyalty Changes in customer perceptions of services execution is an early warning of changes in loyalty Effect can be seen in as little as 3 months The influence of support crosses the boundary from the frontline to executives Support organizations can improve the transaction experience, and thus impact loyalty, by concentrating on those areas that maximize support satisfaction

10 Striking a New Balance Optimize Customer Experience & Loyalty CEM Optimize Operational Metrics CRM Optimize service levels Increase customer retention Enhance growth Reduce costs Maximize return on customer Customer

11 Study 2: Linking Services, Loyalty, and Financial Impact Objectives: Develop a quantitative model to capture the full economic benefits of maintenance & support Provide a model approach for service and support organizations seeking to build a business case for investment in services Steps: Validate the connection between customer loyalty and financial outcomes Determine the strength of the relationship between transactional support satisfaction and overall customer loyalty Identify key drivers of support satisfaction to prioritize opportunities for greatest financial impact

12 Partner Profile: Novell Global B2B Software and Services Company 52,000 customers 4,700 employees $1B revenue

13 Novell Technical Services 9 Global Support Centers 70,000 Incidents Annually Capelle Nurnberg 700+ trained Support Engineers on Linux & Open Source technologies Provo Waltham Sao Paulo Mumbai Shenzhen Tokyo Sydney On-site and dedicated support engineers

14 Linking Support Experience, Loyalty, and Financial Outcomes Case Handling Customer Satisfaction Operational Performance 3 Overall Support Experience 2 Customer Loyalty 1 $ Economic Benefit $

15 Linking Customer Loyalty and Economic Benefit Case Handling Customer Satisfaction Operational Performance Overall Support Experience Customer Loyalty 1 $ Economic Benefit $

16 Establishing ROI: Approach Sample Mix of key and regional, premium and non-premium support accounts Method Loyalty metric used as a leading indicator (1 quarter lag) Financial growth averaged over 4 quarters to produce annual averages Customer Loyalty 1 $ Economic Benefit $ Segmented accounts by average loyalty score, mapped segments to financial growth

17 What is Net Promoter? How likely are you to recommend to a colleague or friend? Not at all likely Neutral Extremely likely Detractors Promoters Open standard Ease of adoption Actionable Proven correlation to growth - = % of 9s and 10s % of 0 through 6 Net Promoter %

18 Customer Loyalty and Economic Value Promoter 50% 11% 10 percent decrease Accounts Passive 38% 1% Detractor 12% -6% 7 percent decrease

19 Scenario Planning Economic Impact of Improving Loyalty Average Revenue Growth 8% 7% 6% 5% Promoter Passive Detractor Current (5.3%) $9.6M 50 $20.4M Scenario 1 (6.1%) Scenario 2 (7.0%) Maximizing Promoter and minimizing Detractor segments has demonstrable economic benefits First step in driving improvement is to identify performance areas which most impact loyalty 4% Loyalty Score

20 Linking Overall Support Experience to Customer Loyalty Case Handling Customer Satisfaction Operational Performance Overall Support Experience 2 Customer Loyalty $ Economic Benefit $

21 Approach Sample Premium Support customers Method Created satisfaction indices for Marketing, Sales, Product, Consulting, Training, Overall Support Experience Linked indices to loyalty via regression Overall Support Experience 2 Customer Loyalty Selected final model elements based on significance of relationship with loyalty

22 Identifying Key Drivers of Loyalty Drivers of Loyalty include Product, Support and Sales Satisfaction Product Satisfaction has the greatest impact on Loyalty, followed closely by Support Satisfaction Sales more weakly associated with loyalty Other touch points Marketing, Design and Implementation, Training were not significant Overall Product Satisfaction Overall Support Satisfaction Overall Sales Satisfaction Customer Loyalty

23 Scenario Planning Impact of Improving Overall Support Experience on Loyalty Increasing Overall Support Experience by approximately 3% results in a 1% increase in Customer Loyalty Loyalty % 3% Support Satisfaction

24 Linking Case Handling to Overall Support Experience Case Handling Customer Satisfaction Operational Performance 3 Overall Support Experience Customer Loyalty $ Economic Benefit $

25 Approach Sample Premium Support customers Case Handling Method Customer Satisfaction Operational Performance 3 Overall Support Experience Case Handling metrics used as a leading indicator (1 quarter lag) Linked case handling metrics to overall support experience via regression Selected final model elements based on significance of relationship with overall support experience

26 Uncovering Overall Support Satisfaction Drivers Case Handling Overall Support Experience is most impacted by overall incident satisfaction and engineer professionalism. Overall Incident Satisfaction Engineer Professionalism 1 2 Overall Support Experience Overall incident Satisfaction may be a catch-all category for other elements in model, as well as areas not explicitly evaluated (e.g., communication, speed of resolution).

27 Role of Operational Performance in Overall Incident Satisfaction 100% 80% 60% 40% 67% Resolution Rate 87% 99% Overall Incident Satisfaction may act as a proxy for operational metrics (e.g., Resolution Rate, Resolution Time). 20% 0% Low Med High Resolution Time (Days) Avg=15 days* Customers with low Overall Support Experience Satisfaction show lower resolution rates and higher resolution times Customers with high Overall Support Experience show extremely high resolution rates and below average resolution times 0 Low Med High

28 Scenario Planning Impact of Improving Case Handling on Overall Support Experience Overall Support Exp Increasing both Overall Incident Satisfaction and Professionalism Satisfaction by 3% results in roughly a 2.25% increase in Overall Support Experience % 2.25% Sat w. Transaction & Professionalism

29 Linking Support Experience, Loyalty, and Financial Outcomes Case Handling Customer Satisfaction Operational Performance Overall Support Experience Customer Loyalty $ Economic Benefit $

30 Demonstrating Value: Linking Support Performance and Revenue Case Handling Incident Satisfaction 5% Professionalism 5% Overall Support Experience 3.8% Customer Loyalty 1% $3.8M

31 Summary of Findings Customer loyalty contributes directly to revenue growth Overall Support Experience second only to Product Experience plays a key role in shaping customer loyalty Incident experience exerts a significant impact on Overall Support Experience Investing judiciously to optimize operational processes can have a cascading effect on value creation which reaches beyond the services organization

32 Q&A

33 Thank You Headquarters New York London Paris India Development Center 2755 Campus Dr., Suite Seventh Avenue 3 rd Floor, Colet Court 112, avenue Kléber G1, Tejaswini, Technopark San Mateo, CA Suite Hammersmith Rd Paris cedex 16 Campus Phone: New York, NY London W6 7JP Direct : Trivandrum, Kerala Toll Free: Phone: Phone: +44 (0) Switchboard: Phone : Fax: Fax: Fax: +44 (0) Fax : Fax : Satmetrix and the Satmetrix logo are registered trademarks of Satmetrix Systems, Inc. Net Promoter, NPS and Net Promoter Score are trademarks of Satmetrix Systems, Inc., Bain & Company, and Fred Reichheld.

34 Next Steps: Key Ingredients for Linking Support and Value Start with demonstrable ROI Corporate financial outcomes, not simply support and services P/L Revenue by category, total revenue, growth Assess loyalty on an ongoing basis Target executives, key decision makers, budget holders Include overall relationship (loyalty) and performance along key touch points Assess post-incident satisfaction continuously Target direct recipients of support Integrate operational metrics and customer perceptions

35 Next Steps: Measurement Window Target all metrics by account, by quarter Change over time in incident satisfaction, in loyalty, in financial outcomes is key Case Handling (Satisfaction) Overall Relationship (Loyalty) Revenue Growth (%) Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 FY2004 FY2005 FY2006

36 Next Steps: the Enterprise View NPS Loyalty Linkage to Financial Metrics Overall Experience (Relationship) Broad assessment across brand, key touch points Satisfaction with Touch Point (Transactional) Business Processes Feedback triggered by a specific event (e.g., support incident) Ongoing initiatives to improve processes