Published on September 9, 2015
1. Are you ready to engage? Total Customer Relationship with Informatica MDM Helsinki 3. September 2015
2. 2 Agenda 1. Why Customer MDM? 2. Some best practices 3. Informatica Total Customer Relationship 4. Examples
3. “By 2016, companies will compete primarily on the customer experiences they deliver.” Gartner The Vision: Customer Satisfaction
4. Customer Master Customer Experience ?
5. Not with the solution! 1. Start with the needs, pains or problems Sales/Service • Search, Create and Update • «Knowing» the customer • Tracing the customer across channels Marketing • Customer intimacy - Unable to create a message tailored to the individual customer • Cost of mass marketing BI/IM • Customer analytics across the organization IT • System integration
6. Identify current and planned initiatives relying on customer data 2. What is going to change? • New CRM solution • Digitalization • System integration or consolidation • Customer analytics • New customer facing apps
7. A single, cross organization, view of the customer? 3. What core capabilities do you need?
8. These questions can help you identify the capabilities you need Core capabilities • Where is the complete set of customer information? • How do I get the customer data when I need it? • What does the customer data mean? • Can I trust it? • Is it complete and correct? • How do I get it in the form I need? • How do I control it?
9. How do you value data management and infrastructure capabilities Value drivers • Customer satisfaction • Cost of marketing • Digitalization • Omi-channel • Customer analytics • System integration What will be the cost of operating without a consistent 360 view of your customer?
10. 10 Agenda 1. Why Customer MDM 2. Some best practices 3. Informatica Total Customer Relationship 4. Examples
11. Always remember that Customer data management is not all about technology! Gartner’s 7 building blocks for MDM Vision Strategy Metrics Governance Organization Process Technologyinfrastructure
12. From spaghetti to single source of integration …to process changes It’s all about reducing complexity Realize value: How can existing processes be simplified with a sentral customer data service?
13. Some best practises • Again: start with focus on needs, pains and problems, not the solution • Don’t underestimate change management • Be avare of dependencies • Start with only data you are able to define, but enough data to create value from first release • Data quality comes from enforcing a set of data policies and rules on your customer data. Your organization needs to be able to specify and agree on these guidelines.
14. 16 Agenda 1. Why Customer MDM 2. Some best practices 3. Informatica Total Customer Relationship 4. Examples
15. Informatica Total Customer Relationship Complete solution • Data integration • Data quality • Search • Business Process Management • Composite services • User interface • Security Products • Master Data Management (Multidomain) • Data Quality • PowerCenter • Address Doctor
16. 20 Agenda 1. Why Customer MDM? 2. Some best practices 3. Informatica Total Customer Relationship 4. Examples
17. DNV-GL • High rate of duplicate customer records after integrating multiple CRM systems and legacy systems • Incorrect addresses due to lack of definitions • Lengthy manual process to create customer. Have to apply to central office (minimum 24 hours) • No easy way to integrate customer information from M&A companies • Automatic detection of duplicates on entry. Automatic merging of duplicate records from new companies added. • Automatic address lookup and cleansing on entry and periodic to handle address changes. • Clear definition of address usage and only integrating systems with same address usage • Every user can create customers with high quality and confidence (available in all systems after 15 min) • Single point integration for new systems handling customer data and new companies
18. SpareBank 1 • No complete view of customers in local banks or at alliance level across product lines • No complete view of product uptake amongst customers • No common model for product pricing • Lack of consistent and complete customer and product views prevents IT modernization and multi channel sales • Single and complete view of customers across product lines, locally and alliance wide with all major systems integrated – single point of update for customer data. • Single point of integration for customer data. Reduces cost of integrating customer data into new systems • Enabling development of multi channel sales applications and alliance wide call-centers
19. Møller Group • Low data quality with large number of duplicates • Poor customer interaction • No defined ownership and governance of customer data • Low ROI on marketing activities • Increased customer satisfaction and loyalty • Common platform for customer data services • Single point of integration for customer data • Shared set of data quality rules enforced across applications
20. Thank you Informatica day, Helsinki 3. September 2015
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