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Bots & Machine Learning Change Customer Interactions - Connected Brains 2018

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The future of work is strongly influenced by technology and new ways of working. We are eager to share the results of our
hackathon with business-oriented cases to give you an idea of what that conversational future with (chat)bots, AI, and Machine Learning looks like.

Published in: Data & Analytics
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Bots & Machine Learning Change Customer Interactions - Connected Brains 2018

  1. 1. Learn from our experiments how bots and machine learning change your interactions with customers and employees
  2. 2. We speak your language Supported by:
  3. 3. Some of us have an addiction
  4. 4. Our Journey What are Bots and Machine Learning?01 Why Bots?02 Bot Design Considerations03 Getting Started04 Our Experiments05
  5. 5. What is Machine Learning? Intrusion detection Image recognition Digital Assistants Self-driving vehicles
  6. 6. Personal Assistants (VPA) Employee Assistants (VEA) Customer Assistants (VCA) What are Bots? Bots are just part of the conversational puzzle Chat bot Chat bot Chat bot Chat bot Chat bot Chat bot Chat bot Chat bot
  7. 7. Content Engine: - Context - Analytics - Exceptions Under the Hood Chat UI Natural Language Processing (NLP) Intent Handling Response Generation text intent + entities text User structured content & follow-up actions Integration CRM ERP API’s FAQ/Wiki/Office365 ML ML
  8. 8. Tools Providers Brands Channels
  9. 9. Our Journey What are Bots and Machine Learning?01 Why Bots?02 Bot Design Considerations03 Getting Started04 Our Experiments05
  10. 10. Why Bots? Low waiting times Fast response High availability (24/7) Personal and context-aware Stable cost (savings) Data provided from multiple data sources
  11. 11. Our Journey What are Bots and Machine Learning?01 Why Bots?02 Bot Design Considerations03 Getting Started04 Our Experiments05
  12. 12. Essential Considerations for Bots Graphical Botflow Rich & Interactive Natural Language Human Handover API Integration Language Support Business Model Message Interface Fluid Conversations PL Supervised Learning
  13. 13. Where do Bots Fit in for Customers? Analytics & Insights Security & Privacy Integration ERP LOB IoT … Legacy Public website Portal Mobile app API & Social media Communication Customer Experience Omni-channel Customer Engagement Platforms Structure & Navigation Enterprise Search Community management Analytics dashboardsCustomer MDM Conversational
  14. 14. Where do Bots Fit in for Employees? BYOx Portal Apps & Wearables Communities Communication New World of Work: Channels Integration: B2E API ERP LOB IoT … Legacy Knowledge Management Platforms Structure & Navigation Enterprise Search Community & Gamification Analytics Dashboards LifecycleDigital Assets DMS/CMS Workflow Analytics & Insights Security & Privacy
  15. 15. Our Journey What are Bots and Machine Learning?01 Why Bots?02 Bot Design Considerations03 Getting Started04 Our Experiments05
  16. 16. How to StartYour First Bot BUSINESS FIRST - Chatbot Canvas User Focus Integrations Functional Design • The Problem • How it’s solved • Exist already? • Internal • External • Channel • Functionalities • Personality Performance Organization • KPI’s • Measure ROI? • Impact • Stakeholders • Strategy • Partner needs
  17. 17. How to StartYour First Bot •Think about the bot flow Identify account 0 … Consultants Competition scan Financial overview Projects Recent visits Sales activity Location 1 Basic account info SalesForce info Public (Google) info Account Manager Customer site on SharePoint
  18. 18. Our Journey What are Bots and Machine Learning?01 Why Bots?02 Bot Design Considerations03 Getting Started04 Our Experiments05
  19. 19. Our Experiments
  20. 20. Welcome Bot Welcome visitors at the door Audience: B2B B2C B2E Functions: Knowledge finding Process automation Level 0 support
  21. 21. Barry, the Bebat Bot Facilitate collection process & FAQ Audience: B2B B2C B2E Functions: Knowledge finding Process automation Level 0 support
  22. 22. Timesheet Bot Asks people to submit/correct timesheet entries Audience: B2B B2C B2E Functions: Knowledge finding Process automation Level 0 support
  23. 23. Lola Bot Live Online Learning Assitant helps solve complex case questions Audience: B2B B2C B2E Functions: Knowledge finding Process automation Level 0 support
  24. 24. Website Bot Guides website visitors with no clicks Audience: B2B B2C B2E Functions: Knowledge finding Process automation Level 0 support
  25. 25. Botler Bot Prepares (pre)sales team for customer contact Audience: B2B B2C B2E Functions: Knowledge finding Process automation Level 0 support
  26. 26. Custorina Bot Provides (pre)sales team customer org chart insight Audience: B2B B2C B2E Functions: Knowledge finding Process automation Level 0 support
  27. 27. Eloquent Estimates chance of sales deal close, analyses SalesForce data and follows deal evolution Audience: B2B B2C B2E Functions: Knowledge finding Process automation Level 0 support
  28. 28. Live Demo! •Botler, customer insights bot •Live LoQutus data (financials randomized, no NLP) Framework / platform: Channel: Web Services hosted on: Integrates with:
  29. 29. Wrap up What are Bots and Machine Learning?01 Why Bots?02 Bot Design Considerations03 Getting Started04 Our Experiments05
  30. 30. Key Takeaways •The bot landscape is still very scattered (hype) •Don’t code everything, try combining drag&drop frameworks with custom REST APIs •Start with your FAQ top 10% and consider making that a bot •Easy to integrate on a public website •Chat conversation of 5’ x 100 chats = 1 FTE that can specialize in training bot/complex cases •Avoid Kleurenwiezen at all times
  31. 31. Questions? Sebastiaan Mindreau Lead Strategist “Digital” LoQutus

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