Discover practical AI strategies that scale customer success across diverse business segments, from startups to enterprises. This session showcases how AI tools and techniques can optimize resources and enhance customer interactions, providing a roadmap for growth and efficiency.

Speaker:

Chad Rosh - Manager of Customer Success at GaggleAMP

‍

Link to presentation: https://gamma.app/docs/Scaling-Customer-Success-with-AI-A-Practical-Approach-or8qdrnf4otlth0

Q&A

Are people using an AI tool with their CS platform or one that's built into their platform?

Both scenarios are common. Integrated AI tools provide seamless functionality within the CS platform, while standalone AI tools offer more flexibility and customization for specific workflows. You'll find a lot more flexibility in conforming AI to your use case with a model outside of your CS platform.

I'm curious, other than Salesforce, if other platforms have AI tools to scrape the data Chad is talking about.

Yes, there are many other platforms and tools like Salesforce, LinkedIn Sales Navigator, HubSpot (ChatSpot), Agent.ai, and Gainsight also have AI capabilities for customer insights. But there are many custom use cases you can leverage with deep insights. For example, you can use AI to layer in a value alignment framework from current customer goals to write intro emails for a new CSM taking over an account, demonstrating a deep understanding of the company, goals, and industry. This helps build credibility and elevate the relationship instantly.

Does anyone know if certain CRM systems i.e., Gainsight, ChurnZero, HubSpot, etc., are more advanced with their AI embedded features?

Gainsight, HubSpot, and Salesforce are particularly advanced in leveraging embedded AI features for customer insights and predictive analytics. These platforms use AI to automate tasks, provide personalized recommendations, and enhance decision-making processes. ChurnZero is also making significant strides in this area, quickly catching up with its robust AI capabilities. Other platforms are continuously evolving, integrating AI to improve customer engagement, streamline workflows, and drive better outcomes.

Curious, how do folks think about the ROI case for AI solutions today and expectation on delivery? Is it time savings and efficiency for the existing team? Does it have to show direct NRR/GRR impact in a shorter time frame, or something else?

In my experience, evaluating the ROI of AI involves assessing immediate benefits like time savings and efficiency, alongside the direct impact on NRR/GRR. However, I don't believe we're fully equipped yet to calculate the entire ROI of AI. It's not just about the immediate gains. Long-term advantages, such as enhancing customer satisfaction and improving decision-making, are crucial but harder to quantify. Striking the right balance between these short-term wins and the strategic, long-term goals is essential to grasp the comprehensive value of our AI investments.