Can AI truly enhance Customer Success, or are we chasing a fantasy?
Despite all the social media excitement, many CS leaders are still unsure of how AI can truly transform their teams and how they deliver value for customers.
The skepticism isn’t unfounded. AI in Customer Success brings with it a host of challenges:
- Understanding the use-cases: Where can AI make a tangible difference in the customer journey?
- Choosing the right technologies: With so many AI tools available, which ones should you invest in?
- Mitigating the security and data risks: How can you mitigate concerns over data privacy and security, especially in industries with strict regulations?
- Getting over the "our data isn't clean" roadblock: This obstacle is a roadblock for many organizations to get started, slowing down AI deployment.
While these questions are big, the opportunities are even bigger.
The promise of AI is to make our teams: better, faster and more scalable, all while delivering a better and more personalised customer experience. If that's not the dream, I don't know what is.
In this edition of the newsletter, I’m thrilled to dive into the insightful content from Matik’s recent CS + AI Summit. Their sessions provided a wealth of knowledge on AI use cases tailored for Customer Success, making it clear that AI isn’t just hype—it’s a game-changer waiting to be unleashed.
Understanding AI and Its Impact on Customer Success
First, let’s tackle the big picture.
AI’s influence on Customer Success goes beyond automation and chatbots. It’s about:
- Enabling a more proactive and personalised approach to customer engagement. This is something we've all been trying to do (and falling short of) for a very long time!
- Predicting behaviour at scale. Or as a mentor used to say "seeing around corners". AI can forecast customer behaviour, helping teams anticipate needs before they arise.
- Improving decision-making with better and more comprehensive insights, directly impacting customer satisfaction and retention.
These 3 use cases have serious bottom-line impact.
- Better Experiences = Better Usage
- Better Usage = Better Results
- Better Results = Better NRR
If you want to learn more about how to communicate the impact to your business, I recommend you dive into the “How AI will Transform Customer Success” Session, as Rod Sherkas (CEO at HelloCCO) and Mary Poppen (President at HRIZONS EX; former CCO at SAP & LinkedIn) laid the groundwork for why AI isn’t just another tech buzzword but a fundamental shift in how we approach customer relationships.
Integrating AI: Practical Steps to Get Started
Transitioning from theory to action, many leaders wonder where to start.
The session “Integrating AI Into the Customer Success Tech Stack” by Bo Sun - Head of Customer Success - North America at LinkedIn and Andrew Lefevre - Head of Talent Insights at LinkedIn offered a ton of actionable insights into how you can embed AI into your existing workflows to make them better.
- Customer Health and Journey Mapping with AI: Most of us already have health scores and journey maps, AI can help us significantly enhance these tools. Churn prediction is an easy place to sell this to your leadership team, and has a simple and measurable impact on the bottom line.
- Efficiency Gains: CSMs do a huge amount of admin and toggling between systems to deliver a great customer experience. AI can help take away some of those simple tasks such as history summaries, call prep, call notes, follow-up emails etc. But don't go buying new tools just for ths. Your Call System, CRM or CSP should be the place where those features live because it's where your team works.
- Tailoring The Customer Journey: The reason why we tend to have cookie-cutter customer journeys is because it's hard to personalise at scale. But AI can help you do just that. Data questions aside, there are a bunch of low hanging fruit options. For example, Matik also has this incredible AI-powered QBR one-pager creator that can help your team create these often time consuming presentations in one click.
- Digital Customer Success: Many companies are investing in their digital segment as a bet to scale better. AI should be part of that strategy, making experiences less cookie-cutter and complementing human-led interactions. This can help drive faster customer outcomes, improve adoption of key features, and support multi-product strategies, ultimately enhancing overall customer satisfaction. Leveraging AI to automate value and usage and ROI reviews is already a great first step, as most people are not being proactive with the long-tail (I wrote an entire newsletter on this).
Whether it’s leveraging AI to analyse customer data or adopting AI-driven tools to personalise outreach, this session underscored that starting small, with clear goals, is key.
TL'DR
AI’s impact on Customer Success can be transformative. The potential is huge:
- Better and more personalised customer experiences
- Predicting customer behaviour at scale
- Improving CSM productivity and scaling better
- Enhancing decision-making
These drive significant business outcomes, enhancing customer experiences, usage, and results—ultimately boosting NRR.
For those looking to integrate AI, start with practical steps. Ask yourself 2 questions:
- What are you doing today that can be enhanced by AI?
- What strategies are you betting on, that can be delivered faster/better with AI?
My key takeaway was: Begin small, focus on clear goals.
A simple place to start might be with AI-generated QBRs.
Want to deep dive into the incredible sessions and learn how other CS businesses are using AI?
Watch some of the top CS leaders share their thoughts on AI in these incredible and completely free 'AI+CS Summit' sessions.