1. © Dr V.Kumar V. Kumar PROFITABLE CUSTOMER ENGAGEMENT Concepts, Metrics & Strategies

2. Chapter 9 Managing Customers in a Multi-Dimensional World Chapter 9 Managing Customers in a Multi-Dimensional World Instructor’s Presentation Slides 2

3. © Dr V.Kumar www.drvkumar.com Introduction  Profitably managing customers is a multidimensional task  Several key CEV elements need to be managed simultaneously  Firms might face organizational or database problems while trying to manage several CEV elements  Firms will have to prioritize which CEV metrics they use for managing customer profitably  Firms will have to start collecting individual level data for calculating several CEV metrics 3

4. © Dr V.Kumar www.drvkumar.com Implementing the CEV Framework Define firm objectives Align objectives with CEV metrics Decide which CEV metric you want to prioritize Decide which metric can be measured with your data Begin building your data towards the CEV metrics for future analysis 4

5. © Dr V.Kumar www.drvkumar.com Managing the CEV framework  Customer Brand Value (CBV), Customer Lifetime Value (CLV), Customer Influence Value (CIV), Customer Referral Value (CRV), Customer Knowledge Value (CKV) are interrelated  Firms need to prioritize the management of these metrics  The choice of metric for a business has everything to do with the type of business implementing the framework 5

6. © Dr V.Kumar www.drvkumar.com Customer Brand Value  A strong brand is the core of any customer engagement  Brands need to be seen as viable, before customers can work their way through CBV framework  The CBV metric is closely related to the CLV metric  Once brand advocacy and premium brand behavior is optimized, CLV can be maximized 6

7. © Dr V.Kumar www.drvkumar.com Customer Lifetime Value  Once a strong brand is build, firm should focus on managing CLV as it directly contributes to profits  In order to calculate CLV, customer transaction level data is needed  Statistical modeling will aid marketers in optimally allocating resources across customer segments  Wheel of fortune strategies can be used to maximize CLV  CLV is not the only factor that can determine a customer’s profitability 7

8. © Dr V.Kumar www.drvkumar.com Customer Referral Value  Current customers indirectly contribute to the profits of the firm by referring new customers to the firm  Customers act like non-employee salesperson who are compensated for contributing towards the firms profits  A firm can maximize CRV by identifying the right customer who can refer profitable customers  CRV is used in the B2C setting while BRV is used in the B2B setting 8

9. © Dr V.Kumar www.drvkumar.com Customer Influence Value  A firm can attempt to capitalize on CIV only if its customers are present on social media platforms  Influencers need not be famous spokespersons; they can be individuals with a broad social media network and considerable clout  By choosing the right influencer and by offering the right tangible and intangible benefits, companies can try and maximize CIV 9

10. © Dr V.Kumar www.drvkumar.com Customer Knowledge Value  CKV focuses on capitalizing on information customers provide to the firm, in order to improve customer satisfaction and thereby increase buying behavior  By encouraging customer feedback, firms increase the number of customer interactions which will lead to higher profits  Having a streamlined process and system to manage customer feedback helps firms in keeping customers happy and loyal  CKV can be maximized when firm makes communication with customers easy, provides them with incentives to give feedback and encourage customers to collaborate with the firm 10

11. © Dr V.Kumar www.drvkumar.com Note on managing the framework  CLV is a crucial metric to any organization which wants to understand the true value of its customers  However of the indirect CEV concepts, CRV can be easily quantifiable and can easily be maximized  Tracking CIV would be more difficult than tracking CRV as software to track social media needs to be in place  CKV is the most difficult to maximize, especially if a firm does not have a streamlined process of tracking and managing customer feedback. 11

12. © Dr V.Kumar www.drvkumar.com Organizational Challenges CMO/CEO Chooses appropriate projects and allocate projects accordingly Also decides how involved customers will be in new product development process “Who Does What” When integrating customer feedback into the new product and service development process Knowledge manager Analyzes summarized customer reports according to “3P” approach Summarizes analysis and potential strategies in new report for upper management Project managers Develop new products and involve customers in process according to upper management guidelines Launch product Customers Provide feedback to the firm about existing products and ideas for new products via social media New product/service Launch product Let customers know their input helped create a new product Knowledge team Gathers customer insights and summarizes in reports Implements strategies to encourage customer feedback 12

13. © Dr V.Kumar www.drvkumar.com Database Management 13

14. © Dr V.Kumar www.drvkumar.com Database Management  To implement CEV framework, firms need to store historical data. Data availability is essential to implement CEV framework  Exponential growth in need to store big data has significant impact on database management  Key issues regarding database management are: (i) data integrity (ii) data accessibility (iii) data security (iv) disaster recovery (v) change management 14

15. © Dr V.Kumar www.drvkumar.com Database Management  Data Integrity – ensures that the data is of high quality, consistent and accessible.  Threat to data integrity can be minimized by  Backing up data regularly and storing in an alternate location  Controlling access to data through read/write privileges  Designing user interfaces that prevent input of invalid data  Using error detection and correction while transmitting data  By encrypting data 15

16. © Dr V.Kumar www.drvkumar.com Database Management  Data Accessibility - is an increasingly important data quality dimension for firms.  Data accessibility ensures users can read/ update for business processes  As data becomes more accessible, there is a need to maintain data that is understandable and documented  Data Security - address the issues of data loss and theft  Data security can be achieved by restricting user access to data through user profiles  Encryption is another way to protect data  Security risks can be minimized by using security software 16

17. © Dr V.Kumar www.drvkumar.com Database Management  Disaster Recovery - involves the steps taken to recover data upon the occurrence of a breach or compromise  Data needs to be covered with an insurance policy  Disaster recovery measures needs to be in place. Disaster recovery measures can be classified into three groups  Preventive measures  Detective measures  Corrective measures  Change Management - is the process of determining which changes need to be made to a database, evaluating the effects of those changes, and then implementing the changes.  Change management is an necessary evil in maintaining the integrity and accessibility of a company’s data  Growing company needs would call for changes in database. Managing all these changes well would impact the IT related costs 17

18. © Dr V.Kumar www.drvkumar.com Future of Customer Engagement  Big Data – can be sourced from many channels – RFID, sensors, geolocation, audio visual streaming and through social media  It covers many type of data like demographics, transactional  Understanding and categorizing big data is relatively new  High Velocity – The speed with which big data is collected is high. Information is collected at a rate like never before  High Volume – Big data has been defined as data sets that are too large to be analyzed by traditional software. Actual sizes could vary from terabytes to exabytes  High Variety – Big data comes from countless unique sources and has many dimensions  Analyzing big data would require advanced software. Managers have to decide when their companies would be ready to mine Big data 18

19. © Dr V.Kumar www.drvkumar.com Future of Customer Engagement Type of Data Transactional Data Customer Level Services Marketing Metrics - Profit - Time of Purchase - Frequency - Emails - Direct mails - Promotions Marketing Data Firm DataDemographicsAttitude - Organizational Investments - Marketing Spending - Market Share - Digital data - Neuro- physiological data - Age - Income - Employment Firm Level Services Marketing Metrics Customer Engagement Value - CLV - CRV/BRV - CKV - CIV - CBV Expected Churn Rate Expected Share of Wallet Expected Service Failure and Recovery rates HR/ Employee Engagement metric Operational metric 19

20. © Dr V.Kumar www.drvkumar.com Future of Customer Engagement 20

21. © Dr V.Kumar www.drvkumar.com Future of Customer Engagement  SoLoMo – Convergence of social media, location based services and mobile based services  SoLoMo changes the way marketers engage with customers  Location details help social media players to personalize recommendations  SoLoMo provides marketers the ability to pinpoint customers location and sent relevant offers  As these technologies become more refined, CLV, CIV, CRV metrics can be maximized based on data gathered from SoLoMo 21

22. © Dr V.Kumar www.drvkumar.com End of Chapter 9 22