Required Reading: AI Is Creating Support Experiences, Not Just Journeys
In his new book, Support Experience: How Innovative Companies Use Artificial Intelligence to Win the Hearts, Minds, and Wallets of Customers, Krishna Raj Raja, founder and CEO of SupportLogic, provides strategies for leveraging AI to gain a competitive edge by deeply understanding and meeting customer needs. He also reveals how AI is shifting customer support from reactive to proactive, predicting emotional escalations, and helping companies preemptively resolve issues. CRM editor Leonard Klie recently explored these points more deeply with him.
CRM: How is AI changing the current customer support landscape?
Raja: AI is not just enhancing customer support; it’s transforming it into an experience-driven growth engine. Historically, support was reactive, focused on resolving problems after the fact. AI flips this. By analyzing vast amounts of unstructured data, such as support tickets, emails, and chat transcripts, AI can extract actionable insights in real time, identify customer sentiment, predict escalations, and flag opportunities for upselling or engagement before they surface as issues.
Generative AI transforms customer support further. Imagine a support engineer equipped with a genAI agent that crafts nuanced, emotionally aware responses based on customer history, tone, and intent. This elevates the customer experience while freeing frontline support to focus on strategic issues.
AI’s true power lies in augmenting human capabilities, not replacing them. The voice of the customer is a treasure trove of insights. AI helps us listen better, act faster, and build lasting trust.
How can AI help companies understand and meet customer needs?
AI is like a spotlight in a sea of noise. It turns unstructured data from customer interactions into known, actionable insights. Sentiment analysis deciphers and tracks what customers are saying and how they feel. Predictive models identify patterns, whether it’s customers likely to churn or needing product upgrades.
This isn’t just about analysis; it’s about taking the right actions. AI can alert businesses to product issues or suggest the next best step for customers. These insights empower every team to align around customers’ evolving needs.
How can AI drive the shift from reactive to proactive and preemptive customer support?
Predictive AI uses historical and real-time data to foresee potential issues, allowing businesses to act before customers notice a problem. AI-driven systems might identify a drop in usage and initiate outreach to re-engage customers before they disengage entirely. Preemptive AI can even resolve issues autonomously, such as deploying a software patch for a flagged error without waiting for a support ticket.
This shift isn’t just operational; it’s cultural. It shows customers you value their time and satisfaction. Proactive support strengthens relationships and builds the foundation of trust and loyalty.
You say in the book that AI needs to go beyond chatbots. What else is there?
Chatbots are like the training wheels of AI in support: they’re useful but limited. The real magic happens when AI is embedded across the entire support ecosystem, helping support teams and customers with issues too complex for chatbots.
GenAI in particular enhances the human-agent experience by summarizing case histories, suggesting solutions, and ensuring responses are empathetic and relevant. Support isn’t a one-touch interaction; it’s a journey. AI’s role is to orchestrate that journey, ensuring consistency, empathy, and efficiency across channels. AI can help us maintain context and historical behavior so we can evolve how we support customers.
How should companies deploy AI? Should there be a different road map for startups and more established businesses?
AI deployment must align with company size and maturity. Startups should adopt lightweight, scalable solutions, such as automated ticket routing or generative AI, that deliver immediate ROI. For larger, established organizations, integration is key. These companies often possess legacy technology and siloed systems and require a phased approach, starting with operational efficiency tools and scaling to predictive and generative applications.
What’s universal is the need for clarity and focus. Deploy AI with specific goals, measure its impact, and iterate. Always prioritize the customer. AI should enhance, not diminish, the human touch.
What is the main message you want readers to take away from this book?
AI is a tool to deepen human connection, not replace it. Support isn’t about technology for technology’s sake. It’s about creating meaningful, trust-driven interactions at scale. AI allows companies to listen better, act faster, and show customers they care.
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