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Return on Investment in Linking Content to CRM by Applying the Linked Data Stack

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Slides from the talk at the KESW2014 conference. The accepted paper will be published at Springer

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Return on Investment in Linking Content to CRM by Applying the Linked Data Stack

  1. 1. Return on Investment in Linking Content to CRM by Applying the Linked Data Stack Daniel Hladky, Martin Voigt and Svetlana Maltseva KESW 2014, September 2014 1 RDF RDBMS CSV Text CRM User CRM SYSTEM Extraction Storage & Querying Authoring Linking & Fusion Enrichment Quality Analysis Evolution & Repair Exploration & Analysis OntosLDIW
  2. 2. I speak about … … the use case and its problems, … our solution, … the estimated ROI, and … the main findings. 2
  3. 3. Use Case Customer Relationship Management (CRM) 3 http://blog.unisoft.net
  4. 4. Use Case: CRM Target group: sales employeewith multi-sides information needs 4
  5. 5. 23% accessibleas a Service Searchable Use Case: Data Dilemma 5 Structured40% Unstructured60% Enterprise Data Web & SN Source: TowerGroup, BearingPoint 40% 12%
  6. 6. Use Case: Required Data 6 Customer (Potential, New, Existing) Web Information Credit Risk News Press & Social Media Stock Market Order Products Revenue Activities (Call, Mail, Meeting) Support Case (Open, Closed) Contract Terms & Conditions Warranty has consists of
  7. 7. Use Case: Task Evaluation 7
  8. 8. Solution Ontos Linked Data Information Workbench (OntosLDIW) 8 ONTOS LINKED DATAINFORMATION WORKBENCH Extraction and LoadingLinking and FusionAuthoringEnrichmentVisualization and AnalyticsUser Storage Administrator Portal Text DocumentsSpreadsheets & CSVRelational DBsRDF Data
  9. 9. Solution: Overview RDF RDBMS CSV Text CRM User CRM SYSTEM Extraction Storage & Querying Authoring Linking & Fusion Enrichment Quality Analysis Evolution & Repair Exploration & Analysis OntosLDIW
  10. 10. Solution: OntosLDIW& OntoDix 10 Ontology •Common model Extraction •Mapping •Extraction Linking / Fusion •Linking model •Connect-Integrate Store •No-SQL “Graph” Consume •Reuse data
  11. 11. Solution: OntosLDIW& D2RQ 11 Ontology •Common model Extraction •Mapping •Extraction Linking / Fusion •Linking model •Connect-Integrate Store •No-SQL “Graph” Consume •Reuse data
  12. 12. Solution: OntosLDIW& LIMES 12 Ontology •Common model Extraction •Mapping •Extraction Linking / Fusion •Linking Models •Connect-Integrate Store •No-SQL “Graph” Consume •Reuse data
  13. 13. Solution: OntosLDIW& OntoQUAD 13 Ontology •Common model Extraction •Mapping •Extraction Linking / Fusion •Linking model •Connect-Integrate Store •No-SQL “Graph” DB Consume •Reuse data
  14. 14. Solution: OntosLDIW& CRM 14 Ontology •Common model Extraction •Mapping •Extraction Linking / Fusion •Linking model •Connect-Integrate Store •No-SQL “Graph” Consume •Reuse data
  15. 15. Solution: OntosLDIW& CRM 15 Ontology •Common model Extraction •Mapping •Extraction Linking / Fusion •Linking model •Connect-Integrate Store •No-SQL “Graph” Consume •Reuse data
  16. 16. Return on Investment OntosLDIW& CRM Integration 16 http://www.photocase.de/foto/18722
  17. 17. ROI: Costs
  18. 18. ROI: Benefit & ROI in 3 years ROI in 3 years: 186%
  19. 19. Sum it up… http://www.photocase.de/foto/18722
  20. 20. Sum it up CRM –Linked Data Integration All required data in CRM time and cost efficiency 1mininstead of 8min Up-to-date information enables ad-hoc customer queries Lessons Learned and ToDos Missing parts of LD lifecycle, e.g., InfoVis, quality Enterprise lack of knowledge about Semantic Web technologies and their benefits
  21. 21. Q&A Martin Voigt Ontos AG / GmbH Nidau(CH) / Leipzig (DE) T:+49 341 21559-10 M:+49 178 40 222 58 E: martin.voigt@ontos.com 21

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