Customer Success (CS) is evolving rapidly. This has been true for a while, thanks to complex market dynamics and fast product developments. But the pace is accelerating with AI. To explore these trends, Statisfy brought together senior industry leaders to discuss AI in CS. Our primary goal was to discuss how to build an “AI-infused” 2025 plan that your C-suite loves.
In this post, we share key insights from the session: Building AI As An Integral Part Of Your CS Technology Stack. [Read our 2nd session summary here: Why CS Leaders Use A Bottom-up Approach To Build The Right CSM Capacity Model]
In this post, we share a summary of a fireside chat between Nadav Shem-Tov (Founder of NST Success Consulting) and Whitney Littman (VP of CS at ZoomInfo). Nadav and Whitney provide insights on how AI is reshaping CS operations. And they discuss how other CS leaders can seamlessly adopt AI.
Let’s get to it!
In 2023, McKinsey showed where to expect a big impact from generative AI. And no surprise, there are big expectations for Customer Operations.
Bain takes this further and shows that a common use case already for AI is to "create recurring customers".
And Forrester adds to this by sharing that CS Leaders plan to invest in new technologies rather than personnel.
Given how hot AI is at the moment, none of this is too surprising. Yet, rather than blindly adopting a new technology, Whitney and Nadav discussed the importance of being deliberate and strategic with this investment.
As the VP of CS at Zoominfo, Whitney shared how they use their ZoomInfo AI Copilot.
This helps them in a number of ways. First, it highlights insights from both first-party and third-party data. Second, it provides CSMs a more comprehensive view of customer health and opportunities. Third, it enables CSMs to prioritize high-impact activities and minimize repetitive tasks.
Although improving CSM productivity is a leading use case, we’re starting to see potential in four more use cases:
These new uses cases are possible because of two important advancements in AI:
In the future, AI won’t just help CSMs understand what’s happening with their clients. Very soon, AI will actually implement changes, initiate follow-ups, and resolve issues. Every CSM will be a bigger, more capable version of their current self. Generative AI will help CSMs by proactively driving workflows, making decisions, and taking actions based on real-time data and customer needs.
This shift will fundamentally change how we approach CS – elevating CS teams from being reactive to strategically driving customer outcomes.
To maximize the impact of generative AI, it’s crucial to first clearly define the problem you’re trying to solve.
It’s possible that different customers have different needs. Some may prioritize health and avoiding unpleasant surprises along their journey. Others might prioritize productivity, seeking ways to streamline operations and free up time. This means the tools you choose may need to account for a wide variance in needs.
In practice, this means:
Second, CS leaders should proactively create psychological safety. There will likely be concerns about automation and potential headcount reductions. This requires proactive, transparent communication about AI’s value in enhancing, not replacing, human efforts.
Third, update ROI impact expectations. The expectation should be for AI tools to provide value faster than traditional platforms.
For instance, historically, creating a health score metric could take months or even years. But with AI, you can pull insights from data almost immediately. This reduces the time it takes to implement systems and see notable impact.
The promise is clear. It’s possible to better serve customers with tailored, responsive solutions provided by AI agents. This approach enables CSMs to focus on high-value interactions. And it asks technology to handle repetitive tasks.
As you plan for 2025, consider how to leverage new generative AI capabilities in your strategy.
At a minimum, you’ll see this investment boost your everyday tools like health scores and customer assessments. And you should expect AI to notably enhance the customer experience with more dynamic and actionable insights.
So, how do you make sure you have AI tools that will deliver these promises? The proper evaluation helps…
While many offerings are branded as AI today, there's a clear distinction between legacy players bolting on a superficial AI layer and true AI-first technology solutions (i.e. Native AI).
Here are a few important things to assess:
Assessing Homegrown AI Tools
Another key decision you’ll face is whether to build or buy AI solutions.
For example, companies like Klarna have successfully moved away from platforms like Salesforce and Workday in favor of custom-built tools. With the advancement of Native AI CS tools, it may be more practical to adopt existing solutions rather than build custom ones from scratch.
That said, there isn’t a one-size-fits-all solution. What’s more important is to move quickly, stay ambitious, and embrace AI where it can deliver the greatest impact.
This is what you can expect with Statisfy: the ability to create healthy, growing customers with the only GenAI Native Customer Success Platform.
Statisfy connects the dots across all your customer touch points, product usage, and external news so your CSMs know exactly what to do next for every customer. Statisfy’s AI Agents Automate Work And Make Customer Health Truly Actionable
Talk to us to see how Statisfy can help you build AI as an integral part of your CS technology stack.
