Mark Tamis - Customer Experience - Día Mundial de la Caldiad - Asociación Española de la Calidad
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Presentación de Mark Tamis el Día Mundial de la Calidad sobre Customer Experience
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Mark Tamis - Customer Experience - Día Mundial de la Caldiad - Asociación Española de la Calidad
- 1. Linking Customer Journeys and Digital Transformation Mark Tamis
- 2. Stimulus
- 3. Touchpoint
- 4. Experience
- 9. Source :E&Y Consumers On Board, June 2014
- 13. Reduce Frictions in the Customer Flow
- 15. Touchpoints
- 18. Rich Profiles Through Big Data and Social Media Interaction
- 20. From Personas to Patterns
- 21. Website Session Website Session Website Session CallCenter Question LoyaltyCard PromoEmail LoyaltyCard SignUp MajorProduct PurchaseinStore Store all the detail, in time order Capture Events
- 24. Use Context and Behaviour Patterns to Anticipate Expectations
- 25. Optimize for Business Outcomes Get The Big Picture!
- 26. What Impact on the Organisation?
- 27. Touchpoint & Mapping Experience Analysis are your Journey GPS
- 28. Service-Design logic is driven by an innate purpose of doing something for and with another party, and is thus customer-centric and customer responsive
- 29. Why Does Digital Transformation Seem Mainly Internally Focused? Source PwC: The Cloud you don’t know
- 31. The impact of CJM and DT Source : HBR Putting the Service-Profit Chain to Work -1994
- 32. Business & Customer Intelligence Value Proposition Capabilities Customer and Business Outcomes Business Vision and Strategy Portfolio Service Feedback & analysis Organisational Capabilities
- 33. Conclusions • Understand Customer Needs & Expectations • Map Customer Journeys • Capture Events at Touchpoints • Complete Event Data with CRM Data • Use Patterns to Anticipate • Adapt your Service Portfolio • Use feedback loops to adapt and iteratively enhance Interactions & Experiences • Optimize for Business and Customer Outcomes
- 34. linkedin.com/in/marktamis @marktamis TouchFlows 64 rue Anatole France 92300 Levallois Perret France Mark Tamis Managing Partner
Editor's Notes
- So we assemble all the data, and reconstruct the chain of events Causes precede effects – necessary but not sufficient to understand causes What of these things influence the purchase? Do people with loyalty cards buy more, or do people who buy a lot take out loyalty cards
- You might focus on loyalty card – look at all the people who took out a loyalty card, and those that didn’t Or this might be offering someone a discount – does that make a difference? Most modelers spend 90% of their time on data wrangling Turn this very granular data and semi-structured data into something more tractable
- http://hbr.org/2008/07/putting-the-service-profit-chain-to-work/ar/1