Leveraging AI In Customer Success Management To Boost Efficiency

Published on September 10th, 2024

When I first started in Customer Success (CS), it was all about building relationships one conversation at a time. But as technology advanced and customer expectations grew, my role became more complex.

The challenge now is maintaining those personal connections at scale, all while juggling countless tasks with limited time.

Initially, I was skeptical about using AI. I worried it might distance me from my customers, making interactions feel less personal. But as I explored AI tools, I realized they’re not here to replace the human touch – they’re here to enhance it.

AI hasn’t replaced my ability to think critically or reach solutions myself. Instead, it’s become a tool that helps me manage my workload and gives me more time to focus on my customers.

With that, let’s get into some of the ways I’ve successfully integrated AI into my work as a Customer Success Manager (CSM).

6 Ways To Use AI In Your CSM Strategy

As I’ve incorporated AI into my work as a CSM, I’ve discovered several ways it can significantly improve how we manage our CS strategies. Below are some of the most effective applications of AI that have helped me save time and be more efficient:

1. Suggesting Next Steps

One of the biggest benefits of AI is its ability to craft messages that are not only personalized but also aligned with the customer’s previous interactions and current needs – ensuring my communication remains consistent and relevant even when I’m working at scale.

For example, I use a CS tool called Velaris that has an in-built AI writing assistant to automate the creation of follow-up emails. Since my emails are already linked to the platform, the tool is able to read through all of them and tell me how to respond.

Now you could use tools like ChatGPT for this as well, but this is easier for me since it’s already a part of my CS workflows. Plus, it has preset tones so I don’t have to spend a lot of time finding the right prompt.

2. Flagging Customer Sentiment

I like to think I’m pretty good at reading people’s emotions, but this can be very hard to do over email. However, I realized that tools like Velaris with well-trained AI can use its knowledge on past interactions to flag sentiment itself – like happy, sad, or empathetic.

Again, ChatGPT could be great for this but it’s a bit time-consuming to train it myself. With Velaris it was already done for me.

Regardless, using AI to read emotions reduces the element of human error and overall just helps me spend less time decoding messages.

3. Predicting Churn

Keeping track of customer health metrics is crucial for preventing churn, but unless you watch your metrics like a hawk – you’re bound to miss something. As a CSM, nothing feels worse than realizing you could have prevented a customer from churning.

I’ve found that AI tools can help me monitor these indicators and alert me when something needs attention. This gives me the opportunity to address concerns before they become bigger problems.

These are just a few ways I’ve found AI to be valuable in my role as a CSM. By leveraging AI effectively, I’ve been able to manage my workload more efficiently while still maintaining the personal touch that’s so important in customer success.

4. Streamlining Processes By Identifying Missing Steps

As a CSM, ensuring that processes run smoothly is always top of mind, especially when it comes to onboarding new customers.

I’ve always believed we had a solid process in place, but after putting it through ChatGPT for a breakdown, I quickly realized some key steps were missing. It allowed me to map out every stage of our onboarding and highlight areas we hadn’t been covering thoroughly.

For example, I discovered that while we were doing a great job introducing customers to our platform, we were missing an important post-onboarding check-in step. This helped me see that we weren’t following up as consistently as we should have been.

What’s great about tools like ChatGPT is that they give you a clear skeleton to work with, and this can apply to any process. Once I had an outline, it became much easier to tweak and perfect.

5. Optimizing Customer Support Responses

Customer support can be a tricky area to navigate, especially when tickets are piling up, and each issue requires a unique response. AI has been invaluable in helping me handle the volume and complexity of support tickets.

One of the standout benefits I’ve experienced is the way AI analyzes past resolved tickets to suggest the most relevant solutions for current issues.

Before using AI, I’d often rely on my own memory or notes to address customer problems. This led to longer response times and sometimes missing key details. But with AI suggesting solutions based on similar past cases, I’m able to respond faster and more accurately.

It’s like having a personal assistant that combs through all the support data for me, pulling out the most relevant insights.

6. Customizing Learning Resources

Discovering how to use AI for learning resources has been incredibly useful. Note that I’m not talking about writing content for your learning resources, but customizing them.

Every customer learns differently, and while we’ve always had plenty of resources available, figuring out what each customer needs at the right time was a challenge.

So what I started doing was using AI to track what areas of the platform a customer is engaging with – or struggling with – and customize resources accordingly. Instead of sending a general tutorial or guide, the AI flags which features the customer has yet to fully adopt or understand. This way, I’m able to offer them specific resources or training that address their unique needs, ensuring they get the most value out of the product.

For instance, I had a customer who was really struggling with a particular integration feature. AI helped me identify the issue before they even brought it up, allowing me to proactively send a personalized tutorial specific to that feature.

It felt like a small gesture, but the impact was huge – they were able to resolve the issue on their own, which built their confidence and strengthened our relationship.

These are just a few ways AI has made things more convenient for me. Of course, while it can do these things, it’s still no substitute for genuine human interaction.

There’s a fine line between using AI to enhance interactions and using AI to replace them. That’s why it’s crucial to find the right mix.

Here are a few tips I’ve found helpful in maintaining a human-centric approach while leveraging AI:

• Use AI as a guide, not the final word: AI can provide valuable insights, but I always review and personalize these recommendations based on my understanding of the customer.
• Keep communication genuine: Even if AI drafts an email, I add a personal touch, whether it’s a handwritten note or a follow-up call.
• Stay involved in the customer journey: While AI can track progress and suggest next steps, I ensure every interaction aligns with the customer’s unique needs and goals.

For example, this one time AI flagged a customer’s dissatisfaction and suggested a specific follow-up. While the suggestion was helpful, I knew this customer preferred face-to-face interaction. Instead of just sending an email, I scheduled a video call to discuss their issues personally. It’s all about being able to discern AI’s recommendations with your own intuition.

In addition to that, I also learned that AI is only as good as the data it processes. Clean, accurate data is crucial for AI to provide meaningful insights. If the data isn’t reliable, the AI’s recommendations won’t be either.

Once you’ve got the right balance and information in place, AI can become an incredible tool for Customer Success – not by replacing CSMs, but by equipping them.

Embracing The Future Of AI In Customer Success

Looking back, integrating AI into my work as a CSM has been a practical and valuable addition. It hasn’t taken away the personal touch that’s so essential to Customer Success – instead, it’s enhanced my ability to manage more efficiently.

The key takeaway for me has been finding that balance between AI and human interaction. AI can provide helpful insights, but at the end of the day, it’s up to us as CSMs to use our judgment, experience, and intuition to ensure those customer connections remain personal and genuine.

By maintaining clean data, being selective with AI’s recommendations, and staying involved in the customer journey, AI becomes a tool that supports, rather than replaces, our role. There’s a lot of potential here, and I’m excited to see how AI continues to evolve and support us in this field.

If you’ve started using AI in your CS strategy, what’s one way it’s helped you streamline your processes or improve customer relationships? Feel free to leave a comment – I’d love to hear your experiences.