AI & CS: Innovate or stagnate

Some believe AI is overhyped. Others think we are already in the midst of transformation. The reality is that most of us sit in the middle. A recent poll taken during the Higher Logic Super Forum SPARK conference in April says  61% of CS professionals sometimes use AI platforms alongside other systems, while 11% always leverage AI in various instances and workflows. Nearly 30% are not using AI at all, but they’re excited about new ideas for usage. CS professionals have a choice: Embrace AI and harness its potential to drive innovation and growth, or remain hesitant and risk falling behind in a rapidly evolving landscape. 

Economic pressures are compelling companies to rethink their strategies, with a heightened focus on both acquiring new business and nurturing existing customer relationships to drive revenue growth. Unsurprisingly, a similar echo was heard at TSIA World INTERACT in May—doubling down on the fact that CS lags behind other customer-facing functions like support and service when it comes to AI adoption and innovation. This juncture is a serendipitous moment for AI to take a prominent role in how businesses drive growth and accelerate impact for customers.

Embracing AI presents challenges and some uncertainties with regard to optimal data consolidation, ubiquitous governance and regulation, and succinct experimentation and process updates. But there are proven, compliant ways to drive impact with AI today. By prioritizing data privacy, security, and ethical practices, businesses can safely leverage AI tools to optimize processes, automate tasks, and uncover new opportunities for improving effectiveness and efficiency. Leading companies and CS teams are paving the way by providing innovative solutions that leverage AI technologies to accelerate impact and drive customer retention and growth.


Tackling everyday customer experience challenges with AI

I’m a CS leader for a CS company, so I know the everyday challenges and opportunities that come with the function’s territory, such as:

  • Tier 1 support overload: CSMs are often inundated with basic support inquiries and unnecessary escalations, taking time away from more strategic tasks.
  • Slow support response times: When support teams are slow to respond, customers escalate concerns to CSMs, leading to increased workload and decreased efficiency.
  • Cumbersome executive summaries: Preparing comprehensive account summaries for executives is time-consuming and challenging, especially when data must be gathered from multiple sources.
  • Inconsistent post-call follow-up: According to a recent Deloitte report, one-third (35%) of a CSM’s time is spent driving follow-ups and pulling materials post-customer meetings. This time drain causes them to struggle to consistently provide high-quality, actionable recap emails to customers after calls, potentially impacting customer communication and satisfaction.


So, what can CS teams do today? Let’s explore four ways AI can help address these challenges to improve CS impact.

  1. Reduce support tickets

    A quarter (25%) of support cases are opened for topics already addressed in the support site and/or knowledge base. Leveraging AI in customer support can significantly reduce customer effort. AI-powered chatbots, automated tasks, and workflows from tools like Help Scout, Custify, and Zendesk can streamline support processes. Integrations from Totango + Catalyst further enhance these capabilities.

  2. Make customer account insights actionable

    The Deloitte report also highlighted that three-quarters (75%) of CS teams struggle to successfully integrate multiple data sources into a unified, consolidated tool. As a result, CSMs spend a staggering 35% of their time compiling details on customer accounts using various tools. Ella Dillon, the CCO at Conversica, found that a typical CSM would need around 80 hours a week — or 5,000 hours annually — to complete all the demands placed on them.A solution can be as easy as consolidating your sales and customer success information. Tools like Totango + Catalyst are purpose-built to aggregate data in a view that can be actioned either automatically or by the CSM. AI applied in the platform provides automated account summary insights, saving valuable time and effort.

  3. Connect engagement to communications

    Record your calls! Tools like Chorus and provide transcription and summary actions from call recordings to streamline communication, capture valuable insights, and enhance team collaboration. Leverage recording integrations to simplify account summary workflows, then use generative AI tools to craft summaries of the output. As your team and customer base grow, AI-powered tools can help maintain personalization at scale while saving time and effort. At Totango + Catalyst, we apply this approach to customer calls, webinars, podcasts, and other recordings we use in our marketing efforts.

  4. Up-level strategic planning and actions

    Imagine having a customer at the top end of your digital segment with reasonable revenue but no named CSM. If the customer starts exhibiting signs of risk, such as early indicators in sentiment response and trends, a finely tuned AI engine can detect these issues, call out the risk, explain why it’s a concern, and provide guidance on mitigation strategies based on historical actions. This sequence could trigger a campaign and series of automated workflows to get the customer back on track, all without requiring significant effort from a CSM.The ultimate goal is to help customers realize higher value more quickly, which is the holy grail of CS and AI infusion. With AI, CS teams can proactively address potential issues, identify growth opportunities, and develop targeted strategies to drive CS. To achieve this level of strategic planning and action, start with unified data and a robust CS platform that integrates AI capabilities (because bad data leads to bad signals!).


Take the next step in AI innovation 

AI will evolve the opportunity and potential impact for customer success, but immediate opportunities demand a mindset shift in how teams think about experimentation, optimization and processes for learnings. To get started, focus on easy and fast wins like call recording. Take a quick inventory of your best data sources, then identify the main snags in your CS/CSM workflow and prioritize those with readily available solutions.

When leveraging community programs and industry resources as data inputs for AI, establish clear protocols to protect privacy, ensure accuracy, and maintain consistency. With a solid foundation in place, set up a test-and-learn plan to experiment with AI-powered solutions and iterate based on your findings. Staying adaptable, informed, and collaborative will be key to harnessing AI’s full potential to propel CS and business growth. Follow along Totango + Catalyst as we continue our journey to deliver the most powerful customer growth platform on the market, or connect with us now for a discussion and demo.

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