A deeper look at how you can bridge the gap between experimentation and customer expectation when thinking about using AI based support. If you'd like to read about our latest offerings in the AI space, have a look at our blogpost - https://blog.freshdesk.com/social-signals-ai/

1. The AI Dilemma
Bridging Experimentation and Expectation
Presented by
Girish Shenoy

2. Creating moments of wow

3. Freshworks in numbers
$149M in
funding
7
Years
Old
150+
Countries
5
Global
offices
9
Acquisitions
7
Products
150k+
Happy
Customers

4. Our Products

5. Office
Data Centre
General Data Protection Regulation
(GDPR), compliant by May 2018Global Presence

6. 150,000+ customers from 150+ countries

7. Our experiments with AI

8. Artificial Intelligence
Learns
Understands
Responds

9. Three Questions

10. Three questions led us
Where can AI help in a customer support environment?
Will AI replace an agent or assist them?
Is AI good enough for customer support?
1
2
3

11. Where can AI help?

12. Our Support Framework
Avoidance Routing ResolutionDeflection

13. AI for
Avoidance

14. “Where is my cab?”
Uber wants to prevent this question from
reaching their support
Arrival Time
Cab Location
Pick-up Point

15. AI for
Deflection

16. AI can suggest solutions

17. Chatbots can initiate and deflect

18. AI for
Routing

19. Skill-Based Routing
AI can intelligently assign tickets to the best agent available

20. Noise Cancellation
AI can filter the noise from social media

21. AI for
Resolution

22. Direct Responses
AI will be able to respond to customers directly and solve problems

23. Better Context
AI can provide better context and recommend responses to agents

24. Replace or Assist?

25. Intelligent. Helpful. Economical.
● B2B Chatbots can respond to about 40% of the questions
● Accuracy of answers are between 8% and 25%
● The more questions AI tackles, the better it becomes
● AI can help businesses save a lot of money as well as time

26. Is AI good enough?

27. Microsoft Tay soon after launch

28. 12 hours after launch

29. 14 hours after launch

30. Two Methods of Learning
● AI can learn from any source
● This is how humans learn
● Skynet Google Assistant, Microsoft Cortana
Free-Form Learning
● AI needs specific sources to learn from
● This is how most bots are learning
● Your local chatbot
Curated Learning

31. ● Comprehensive self-help articles, or other content will be a necessity
● A dedicated curator might be required to teach the AI the right answers
Curated AI For Deflection

32. Curate what your AI learns

33. ● Free-form learning AI will be better suited for resolving tickets quickly
● Need to teach right from wrong, to prevent another Microsoft Tay
Free-Form AI For Resolution

34. ● Free-form AI needs constraints and safeguards
● Free-form AI needs to be taught how to differentiate right from wrong
● Free-form AI is not ready for customer-facing role. Yet.
What can we learn from Tay?

35. The places AI can help in a customer support environment
AI entities right now are capable of assisting agents
AI and business should be ready for each other
1
2
3
So far we’ve seen

36. Should you use AI?

37. 1. What problem in your support do you want to solve with AI?
2. How “controllable” is your AI going to be?
3. How open is your support to experimentation?
Ask yourself this

38. Bridging the Gap

39. Here’s how we bridged the gap
● AI should not stop a customer from contacting an agent
● AI should provide extra value without compromising core support experience
● Experimentation is fine, if the customer is aware that they are talking to an AI

40. Is your support ready for AI?