Leveraging AI in Customer Support: Insights from Zapier's Director of Support

We recently hosted Lauren Fearn, a support leader with over 10 years of experience and the Director of Support at Zapier, in our fireside chat series.
Hritika Singh
November 23, 2023

Leveraging AI in Customer Support: Insights from Zapier's Director of Support

We recently hosted Lauren Fearn, a support leader with over 10 years of experience and the Director of Support at Zapier, in our fireside chat series.
Hritika Singh
November 23, 2023

Leveraging AI in Customer Support: Insights from Zapier's Director of Support

We recently hosted Lauren Fearn, a support leader with over 10 years of experience and the Director of Support at Zapier, in our fireside chat series.
Hritika Singh
November 23, 2023
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We recently hosted Lauren Fearn, a support leader with over 10 years of experience and the Director of Support at Zapier, in our fireside chat series. Lauren brings a wealth of experience from her tenure at various companies.

We delved into the fascinating role of AI in enhancing customer support.

Here are some key takeaways from this insightful conversation.

AI in Customer Support at Zapier:

1. Adopting AI at Zapier:

  • Zapier, known for enabling non-technical users to build automated processes, has been at the forefront of adopting AI in its operations. Lauren emphasized the company's approach to AI adoption: moving quickly, learning on the go, and not being bound by existing knowledge.

2. The Support Sidekick Tool:

  • A standout innovation at Zapier is the "Support Sidekick," an AI assistant for technical support specialists. This tool, originating from a Hack Week project, provides functionalities like creating note summaries, downloading ticket information, and categorizing tickets. It was designed to reduce the manual workload and enhance efficiency in handling customer queries.
  • Currently, the Support Sidekick is used in about 25% of tickets, particularly those that are less complex. Zapier aims to increase this percentage as the tool evolves.
  1. Challenges and Limitations:
  • One of the main challenges is the complexity of customer issues, especially with thousands of app integrations at Zapier. The current limitation of AI is its inability to match the personalized, conversational nature of human interactions, which is a hallmark of Zapier's customer support.
  1. Understanding AI Responses:
  • It's crucial to monitor the effectiveness of automated responses.
  • Analyzing customer reactions helps identify areas needing improvement and those where AI suffices, such as simple tasks like password resets.

Documentation in Customer Support teams

The Importance of Help Documentation:

  • Equally investing in help documentation as in AI tooling is vital.
  • Documentation should be comprehensive and reflect the bot's capabilities and tone.

Brand Consistency:

  • Consistency in communication across all customer-facing platforms, whether AI-driven or human, is key.
  • A mismatch in tones (formal vs. informal) across different service bots can lead to a disjointed customer experience.
  • Establishing and adhering to specific communication values for AI interactions aligns the customer experience with the brand's ethos.
  • Regularly revising these values ensures alignment with evolving customer expectations.

Leveraging Customer Feedback:

  • Customer interviews and research are instrumental in determining the effectiveness of both AI responses and documentation.
  • Feedback from new and long-term customers provides diverse insights for continual improvement.

How can companies integrate AI into their support teams?

  1. Customer-Centric AI Integration: Companies should be mindful of how AI impacts both agents and customers. The goal is to enhance the experience for both parties.
  2. Gradual Implementation: Implementing AI tools like ADA or Intercom must be a thought-out process, particularly for premium plans. Letting customers decide how they want to interact, whether through AI or human support, is key.
  3. Internal Team Dynamics: Rapid AI adoption can instil fear and uncertainty within support teams. Communication is vital. Teams should be kept in the loop about AI strategies and how they align with the company's goals.
  4. Focus on Efficiency: AI should be used to enhance efficiency, allowing support teams to explore new customer service channels. The emphasis should be on providing personalized service where AI cannot fully cater to customer needs.
  5. Strategic Financial Planning: Investing in AI is a long-term play. The initial costs are offset by long-term gains in efficiency and service improvement. It's crucial to present a clear financial narrative to stakeholders, highlighting how AI can reduce ticket volume and open new service channels.
  6. Problem-Solution Approach: Start discussions about AI by focusing on the problems it solves, not just the technology itself. Align AI strategies with overall business goals and assess the willingness of the business to invest in AI.
  7. AI in Customer Support: A Two-Pronged Approach
  8. Addressing a query about AI in customer support, Lauren recommends training AI for both redundant tasks and complex problem-solving. This dual approach allows for a deeper understanding of customer needs and helps in determining which issues should be automated and which require human intervention.
  9. Conclusion:
  10. Lauren's insights provide a valuable glimpse into the future of customer support, where AI plays a significant role in enhancing efficiency and handling a range of customer queries. However, the human touch remains crucial, especially in creating personalized customer experiences.
  11. As AI continues to evolve, companies like Zapier are at the forefront of exploring its potential to transform customer support. Stay tuned for more updates and insights from leaders in the field!

We recently hosted Lauren Fearn, a support leader with over 10 years of experience and the Director of Support at Zapier, in our fireside chat series. Lauren brings a wealth of experience from her tenure at various companies.

We delved into the fascinating role of AI in enhancing customer support.

Here are some key takeaways from this insightful conversation.

AI in Customer Support at Zapier:

1. Adopting AI at Zapier:

  • Zapier, known for enabling non-technical users to build automated processes, has been at the forefront of adopting AI in its operations. Lauren emphasized the company's approach to AI adoption: moving quickly, learning on the go, and not being bound by existing knowledge.

2. The Support Sidekick Tool:

  • A standout innovation at Zapier is the "Support Sidekick," an AI assistant for technical support specialists. This tool, originating from a Hack Week project, provides functionalities like creating note summaries, downloading ticket information, and categorizing tickets. It was designed to reduce the manual workload and enhance efficiency in handling customer queries.
  • Currently, the Support Sidekick is used in about 25% of tickets, particularly those that are less complex. Zapier aims to increase this percentage as the tool evolves.
  1. Challenges and Limitations:
  • One of the main challenges is the complexity of customer issues, especially with thousands of app integrations at Zapier. The current limitation of AI is its inability to match the personalized, conversational nature of human interactions, which is a hallmark of Zapier's customer support.
  1. Understanding AI Responses:
  • It's crucial to monitor the effectiveness of automated responses.
  • Analyzing customer reactions helps identify areas needing improvement and those where AI suffices, such as simple tasks like password resets.

Documentation in Customer Support teams

The Importance of Help Documentation:

  • Equally investing in help documentation as in AI tooling is vital.
  • Documentation should be comprehensive and reflect the bot's capabilities and tone.

Brand Consistency:

  • Consistency in communication across all customer-facing platforms, whether AI-driven or human, is key.
  • A mismatch in tones (formal vs. informal) across different service bots can lead to a disjointed customer experience.
  • Establishing and adhering to specific communication values for AI interactions aligns the customer experience with the brand's ethos.
  • Regularly revising these values ensures alignment with evolving customer expectations.

Leveraging Customer Feedback:

  • Customer interviews and research are instrumental in determining the effectiveness of both AI responses and documentation.
  • Feedback from new and long-term customers provides diverse insights for continual improvement.

How can companies integrate AI into their support teams?

  1. Customer-Centric AI Integration: Companies should be mindful of how AI impacts both agents and customers. The goal is to enhance the experience for both parties.
  2. Gradual Implementation: Implementing AI tools like ADA or Intercom must be a thought-out process, particularly for premium plans. Letting customers decide how they want to interact, whether through AI or human support, is key.
  3. Internal Team Dynamics: Rapid AI adoption can instil fear and uncertainty within support teams. Communication is vital. Teams should be kept in the loop about AI strategies and how they align with the company's goals.
  4. Focus on Efficiency: AI should be used to enhance efficiency, allowing support teams to explore new customer service channels. The emphasis should be on providing personalized service where AI cannot fully cater to customer needs.
  5. Strategic Financial Planning: Investing in AI is a long-term play. The initial costs are offset by long-term gains in efficiency and service improvement. It's crucial to present a clear financial narrative to stakeholders, highlighting how AI can reduce ticket volume and open new service channels.
  6. Problem-Solution Approach: Start discussions about AI by focusing on the problems it solves, not just the technology itself. Align AI strategies with overall business goals and assess the willingness of the business to invest in AI.
  7. AI in Customer Support: A Two-Pronged Approach
  8. Addressing a query about AI in customer support, Lauren recommends training AI for both redundant tasks and complex problem-solving. This dual approach allows for a deeper understanding of customer needs and helps in determining which issues should be automated and which require human intervention.
  9. Conclusion:
  10. Lauren's insights provide a valuable glimpse into the future of customer support, where AI plays a significant role in enhancing efficiency and handling a range of customer queries. However, the human touch remains crucial, especially in creating personalized customer experiences.
  11. As AI continues to evolve, companies like Zapier are at the forefront of exploring its potential to transform customer support. Stay tuned for more updates and insights from leaders in the field!
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