AI for customer success (CS), as well as AI for customer service, customer education, and customer relationship management (CRM)—and virtually every area of business—is evolving at a remarkable pace. This evolution is not just a tech upgrade; it’s a paradigm shift that promises to redefine interactions between Software-as-a-Service (SaaS) companies and their customers.
According to a 2024 Forbes Advisor survey, a staggering 64% of respondents in SaaS believe AI will enhance customer relations and productivity. With 55% already deploying AI for more personalized services, the future of AI in Customer Success isn’t some distant reality—it’s unfolding right now. At Gainsight, we believe AI will make us better at our jobs, and it’ll even make us better humans by freeing up time for what matters most: each other. We’re already seeing that CS leaders embracing the change now are positioning their businesses, their teams, and their customers for a brighter future built on a foundation of AI-powered productivity and fast customer data insights. That’s why we put together the Essential Guide for How to Leverage AI as a CS Leader. Here are our top takeaways for CS leaders beginning their AI adoption journey.
The Accelerating Adoption of AI in Customer Success
According to Gartner, companies deploying AI as a business tool are projected to surpass 60% by the end of 2024. And that’s just the start of a new era: The age of AI has impacted every aspect of how we do business.
AI’s potential in customer success is multifaceted. It can handle vast datasets to anticipate customer needs, automate routine tasks, generate personalized communications, and even predict churn with high accuracy. Gainsight CEO Nick Mehta eloquently captures the essence of AI’s impact: “We know that AI can make your job easier and better. It helps you make better decisions with better insights about your client. AI is going to radically make customers and customer success better.”
AI: The Strategic Asset for Human-First Customer Success
Customer expectations are evolving rapidly, especially within the SaaS sector. Customers now demand immediate responses, hyper-personalized interactions, and proactive service. Meeting these demands in real time is challenging but achievable with the right AI tools. AI’s capabilities in customer success range from automating customer interactions to harnessing predictive analytics to foresee and address issues before they escalate.
In Gainsight’s State of AI in 2023 report, over 85% of Customer Success and Customer Support teams reported “enthusiastic” adoption of Generative AI. Additionally, 47% of those utilizing AI believe their teams will save time and enhance efficiency by automating redundant tasks. In our State of AI in 2024 report, we found the majority of respondents (52%) have already adopted AI into their workflows. The integration of AI in CS is more than a technological enhancement; it’s a transformation leading to improved customer experiences, early detection of churn risks, and newfound internal efficiencies.
All of these efficiency gains allow your team to spend more time being present for face-to-face client interactions, which are the moments that matter most. In that way, AI enables a Human-First approach to customer success.
How Harri Gained Deeper Customer Insights With Gainsight AI
Harri is the all-in-one human capital management platform for the hospitality industry. Harri uses Gainsight AI to make CSMs’ lives easier by delivering deep dive information on customers. “Gainsight AI was really powerful for us to really understand what’s going on with our customers,” says Dan Maimone, Head of Customer Success and Global Director of Customer Success Operations at Harri. “Even when a CSM thinks they know everything about the account, Gainsight’s AI tools tell them more.”
Implementing AI in Customer Success: Best Practices
The successful integration of AI into customer success requires a strategic approach. Here are some best practices:
- Align AI with CS Objectives: AI should complement your existing customer programs without disrupting them. Clearly define how AI will enhance customer experiences and align with specific CS goals, identifying key performance indicators (KPIs) such as customer satisfaction scores, churn rate, and time to first value.
- Select the Right AI Tools: With numerous AI tools available, choosing the right ones is crucial. Evaluate tools based on their ability to meet your specific needs, integration capabilities, scalability, and vendor support. Ensure your chosen vendor has strong security and privacy measures to protect customer data.
- Build a Skilled Team: Implementing AI is a cultural shift as much as it is a technological one. Develop a team skilled in both customer success principles and AI technologies. This might involve training existing staff, hiring new talent, or both.
Brady Bluhm, CS Manager, Innovation & Enablement, Gainsight, is leading change management on the Gainsight CS team when it comes to all things AI. Blumn says:
“At Gainsight, we’re setting the stage for a transformative shift within our organization with weekly co-working enablement sessions named “AI for ALL.” We are working to ensure every teammate is not just aware of, but also comfortable and skilled in harnessing the power of AI. This initiative is rooted in a hands-on, experimental approach, where learning by doing becomes the cornerstone of our strategy.
By creating a culture that encourages curiosity and practical application, we are paving the way for our teammates to not only adopt AI technologies but to lead with them and, in so doing, also help lead our products toward the most powerful AI integrations.”
Ultimately, AI can enable teams to expand their capabilities, but leaders have to make time to build a culture where teammates can grow their skills with AI.
How Menlo Security Uses Gainsight AI to Automate and Optimize Customer Success
Gainsight’s AI Scorecard functionality has been a game-changer for browser security leader Menlo Security. Using this tool, the team can get AI-recommended measures and measure weights for their scorecard. This helps the team better capture and understand customer usage and gives them a clearer picture of the customer.
“The AI Scorecard is like AI wizardry for our health scores,” says Ben Wanless, Customer Success Operations Lead, Menlo Security. “Optimizing my scorecards with AI helped demystify what metrics to include to accurately see a customer’s health by recommending data points that weren’t currently included in the scorecard; for example, support ticket creation. These recommendations took the guesswork out of what to include, and enabled us to have quality health data.”
Navigating AI Adoption Challenges
Implementing AI in customer success comes with its set of challenges. Key strategies to overcome these include:
- Technical Compatibility: Ensure that AI solutions integrate seamlessly with existing systems. This may require backend work and collaboration with IT departments or external vendors.
- Data Quality: AI’s efficacy depends on the quality of data it processes. Invest in data cleansing and enrichment processes and establish robust data governance frameworks to maintain high data quality over time.
- Change Management: Engage teams early in the AI adoption process, highlight the benefits, and provide comprehensive training to mitigate resistance.
How PopMenu Improves Team Efficiency and Customer Experience with Gainsight AI
Restaurant technology platform Popmenu was looking to improve the efficiency of their Customer Success team. They also wanted to gain better visibility into customer health, make health scores more actionable, and maximize the value of their customer usage data. With Gainsight, PopMenu doubled productivity, nearly tripled NPS scores, and achieved a coverage model that supports customers with fewer CSMs.
How did they do it? AI for customer success, along with Gainsight’s Product Experience offering.
Gainsight’s Text Analytics feature makes it easier for Popmenu to collect and analyze written feedback and content from within the platform. Once the data is collected, it automatically provides advanced analytics to help identify churn and improve product usability. “I love the text analytics from Gainsight—that’s my favorite,” says Tori Dailey, Director of Client Strategy and Retention at Popmenu. “That’s been really, really helpful and insightful.”
Gainsight’s AI-powered customer summary feature, AI Cheat Sheet, provides the team with a quick snapshot of a customer’s biggest risks, goals, business needs, and more to help them prepare for customer engagements. “AI Cheat Sheet does a nice job of looking at the milestones and the CTAs,” says Carie Buchanan, Chief Experience Officer, Popmenu. “As a leader, being able to dig into customer information without having to spend a lot of time is key.”
The Future of AI in Customer Success
The trajectory of AI in Customer Success is incredibly promising. AI’s potential goes beyond operational efficiency and predictive analytics; it encompasses creating engaging, interactive experiences that foster deeper connections between customers and brands. By understanding AI’s capabilities and integrating them thoughtfully into their strategies, CS leaders can elevate customer experiences, drive loyalty, and propel their businesses into a new era of growth and innovation.
Learn More
To learn more, read our Essential Guide: How to Leverage AI as a CS Leader.
