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James Sanders:
Alright. Welcome everyone to another deep dive.

Michelle Carter:
Yeah. Excited for this one.

James Sanders:
Me too. This is, this is gonna be a lot of fun.

Michelle Carter:
Absolutely. For

James Sanders:
those of you who haven't joined us before, I'm James Sanders. I'm an AI implementation strategist.

Michelle Carter:
And I'm Michelle Carter, a customer success innovation lead.

James Sanders:
And we are here to dive deep into the world of AI and generative AI.

Michelle Carter:
Yes. Specifically, we're looking at its impact on customer success roles.

James Sanders:
Yeah. How it's changing things.

Michelle Carter:
Within software companies?

James Sanders:
Exactly. If you're in a software company or you're working customer success, this is really the place to be because we're gonna be talking about how AI is already changing things, what's coming up in the future, and really try to give you that insight so you can identify those opportunities and understand these technologies.

Michelle Carter:
Absolutely. And all of this is based on some really cool industry analysis and trends that we've been looking at.

James Sanders:
Yeah. We've been diving deep into the data.

Michelle Carter:
Absolutely.

James Sanders:
Alright. So let's get started. AI, especially generative AI. You know, it's it's kind of moved beyond just the talk. It's actually becoming a practical tool.

Michelle Carter:
It is. It's so exciting.

James Sanders:
I mean, if you look at the numbers, over 75% of workers are using AI in some way.

Michelle Carter:
It's amazing.

James Sanders:
And if you look at customer success, over half of the companies out there, 52%, are already integrating AI into their workflows. That's huge. That's a lot. And I think what's even more interesting is 87% of CS teams are either using or planning to use AI, but only about 21% are actually using purpose built tools.

Michelle Carter:
Yeah. So there's a lot of interest.

James Sanders:
There's a huge amount of interest. There's a huge opportunity.

Michelle Carter:
It's a journey. Right? Like, we're seeing teams experimenting, seeing the benefits. Yeah. But we're still early in that adoption of, like, specialized AI for customer success.

James Sanders:
Yeah. That gap is where things are gonna get really interesting.

Michelle Carter:
Absolutely.

James Sanders:
So let's talk about, you know, how is AI actually helping customer success managers like yourself?

Michelle Carter:
Yeah. How is it actually making their lives easier?

James Sanders:
So one of the biggest areas is in call summaries and follow-up generation.

Michelle Carter:
This is a lifesaver.

James Sanders:
Right. We're seeing AI tools and these conversation intelligence tools. They can transcribe those calls

Michelle Carter:
Yeah.

James Sanders:
Summarize them, even pull out those action items.

Michelle Carter:
It's like magic.

James Sanders:
I mean, some platforms are claiming a 90% reduction in prep time for meetings.

Michelle Carter:
No way.

James Sanders:
They're actually using those call notes to draft those follow-up emails. It's incredible. I mean, think about the time savings there.

Michelle Carter:
It's huge.

James Sanders:
We're talking about tools like Gong and Chorus that can do this kind of analysis.

Michelle Carter:
And it frees up the CSMs

James Sanders:
Exactly.

Michelle Carter:
To actually have those strategic conversations.

James Sanders:
They can focus on engaging with the customer.

Michelle Carter:
Right. Building relationships.

James Sanders:
And, you know, it also ensures that nothing falls through the cracks.

Michelle Carter:
Exactly. Because you have those action items captured.

James Sanders:
Another key area is sentiment analysis, understanding the voice of the customer.

Michelle Carter:
Yes. That's

James Sanders:
crucial. So these AI tools can go through all sorts of communication, emails, support tickets, chat transcripts, even survey responses.

Michelle Carter:
What's your name? And

James Sanders:
they can detect that sentiment. What is the customer actually feeling?

Michelle Carter:
Are they happy? Are they frustrated?

James Sanders:
Exactly. And they can identify those recurring themes.

Michelle Carter:
Yeah. What are the common pain points?

James Sanders:
Imagine you're a CSM and you get an email flagged as negative.

Michelle Carter:
Yeah. That's a heads up.

James Sanders:
You know right away there's a potential problem.

Michelle Carter:
Before it escalates.

James Sanders:
And there are platforms out there specifically designed to aggregate that feedback

Michelle Carter:
Yes.

James Sanders:
And surface those common pain points across multiple accounts.

Michelle Carter:
Absolutely.

James Sanders:
That gives your team the data to actually go back to the product team and say, hey. We need to improve this.

Michelle Carter:
It's data backed insights.

James Sanders:
It's not just anecdotal.

Michelle Carter:
Right.

James Sanders:
And this goes beyond just reacting to negative feedback.

Michelle Carter:
Absolutely. It's about understanding the bigger picture.

James Sanders:
Right. You can tailor your communication

Michelle Carter:
Yes.

James Sanders:
Identify opportunities to provide more value.

Michelle Carter:
Exactly.

James Sanders:
And speaking of being proactive, predictive analytics for churn and upsell.

Michelle Carter:
Oh, that's a big one.

James Sanders:
This is where AI algorithms are looking at your historical data, your usage patterns.

Michelle Carter:
Your port history, demographics.

James Sanders:
All of that to predict who's at risk of leaving.

Michelle Carter:
Yeah. And who might be ready for an upgrade.

James Sanders:
Exactly. And this is like an early warning system.

Michelle Carter:
It is. It gives you time to intervene.

James Sanders:
And we're seeing some really impressive results.

Michelle Carter:
Oh, yeah.

James Sanders:
One company reported a 25% reduction in CSM workload.

Michelle Carter:
That's significant.

James Sanders:
And on average, CS teams are saving over ten hours per week.

Michelle Carter:
Just from automating that churn detection.

James Sanders:
This is huge. It's all about moving from reactive to proactive churn management.

Michelle Carter:
It is.

James Sanders:
And that's powered by AI.

Michelle Carter:
And it's not just about saving customers.

James Sanders:
Right. It's about resource allocation.

Michelle Carter:
Exactly.

James Sanders:
You know, where do you put your resources?

Michelle Carter:
Where do you focus your efforts?

James Sanders:
And then you've got customer health scoring.

Michelle Carter:
So important. A lot of

James Sanders:
the platforms now are using AI to compute these dynamic health scores.

Michelle Carter:
In real time.

James Sanders:
They're pulling in all sorts of metrics.

Michelle Carter:
Product usage, feature adoption.

James Sanders:
Support tickets, NPS score.

Michelle Carter:
And it gives you that single indicator.

James Sanders:
How healthy is this account?

Michelle Carter:
Exact

James Sanders:
The AI is constantly updating these scores.

Michelle Carter:
Yeah.

James Sanders:
It can trigger alerts when things start to go south.

Michelle Carter:
Before it's too late.

James Sanders:
And this allows CSMs to manage by exception.

Michelle Carter:
Yes. Focus on the accounts that need it most.

James Sanders:
You can't keep an eye on every single customer all the time.

Michelle Carter:
You can't.

James Sanders:
So this gives you that extra help.

Michelle Carter:
It's like having an extra set of eyes.

James Sanders:
Now let's talk about task automation and workflow orchestration.

Michelle Carter:
Well, this is where things get really efficient.

James Sanders:
CSMs spend a lot of time coordinating those routine touch points.

Michelle Carter:
Sending emails, scheduling check ins.

James Sanders:
Renewal reminders, updating those CRM notes.

Michelle Carter:
It never ends.

James Sanders:
AI and automation are really helping to streamline these tasks.

Michelle Carter:
Yes. They are.

James Sanders:
You've got these workflow automation tools Yeah. That let you set up rules or playbooks.

Michelle Carter:
Like, if this, then that.

James Sanders:
Exactly. So for example, when a new customer signs up

Michelle Carter:
Yeah.

James Sanders:
The system can automatically send a welcome email series

Michelle Carter:
With content tailored to their use case.

James Sanders:
And then maybe if they haven't logged in after a wink, it schedules a follow-up task for the CSM.

Michelle Carter:
That's amazing.

James Sanders:
And this is really driving the rise of digital customer success.

Michelle Carter:
It

James Sanders:
is. It's enabling that one to many engaged

Michelle Carter:
Without having to hire a ton of people.

James Sanders:
And, again, it's not about replacing the human touch.

Michelle Carter:
No. It's about freeing up the CSMs.

James Sanders:
So they can focus on those complex relationship driven aspects.

Michelle Carter:
Exactly. It's about maximizing the impact of human interaction.

James Sanders:
And then you've got chatbots and self-service AI.

Michelle Carter:
This is a game changer.

James Sanders:
It is. And we often associate them with customer support, but they're playing a growing role in customer success.

Michelle Carter:
They are. They're handling those common inquiries.

James Sanders:
Providing that twenty four seven support.

Michelle Carter:
That's what customers expect now.

James Sanders:
Exactly. And you can embed these chatbots on your website or in your application. Yeah. And they can answer those routine questions.

Michelle Carter:
Guide users through basic troubleshooting.

James Sanders:
And if something more complex comes up

Michelle Carter:
Yeah.

James Sanders:
They can seamlessly hand off that conversation to a human CSM.

Michelle Carter:
With all the context.

James Sanders:
Exactly. And then you've got those AI driven knowledge bases.

Michelle Carter:
Oh, yeah. Those are great.

James Sanders:
They can provide customers with personalized how to content.

Michelle Carter:
Based on their usage patterns.

James Sanders:
This self-service aspect empowers the customer.

Michelle Carter:
Yes. They can find answers quickly.

James Sanders:
And it frees up the CSMs

Michelle Carter:
Exactly.

James Sanders:
To have those higher level strategic conversations.

Michelle Carter:
It's a win win.

James Sanders:
And finally, personalized content and recommendations.

Michelle Carter:
Oh, everyone loves personalized experiences.

James Sanders:
Customers expect it. In fact, over 70% of consumers say that they expect personalized treatment.

Michelle Carter:
Wow.

James Sanders:
And AI is making it possible to deliver this at scale.

Michelle Carter:
That's the key.

James Sanders:
By analyzing each customer's context, AI can recommend the next best action.

Michelle Carter:
What training module should they take?

James Sanders:
Maybe it automatically compiles a quarterly business review report.

Michelle Carter:
Highlighting the metrics that matter to them.

James Sanders:
Or maybe it even auto generates a personalized video update.

Michelle Carter:
It's incredible.

James Sanders:
This level of customization wasn't possible before AI.

Michelle Carter:
No. It wasn't.

James Sanders:
And this level of personalization really builds loyalty

Michelle Carter:
It does.

James Sanders:
Because it makes the customer feel understood.

Michelle Carter:
Yeah. They feel valued.

James Sanders:
So to recap, all these AI tools are really acting as assistants.

Michelle Carter:
They are.

James Sanders:
They're freeing up CSMs from those routine data heavy tasks.

Michelle Carter:
Yes. So

James Sanders:
they can focus on the strategy and building relationships.

Michelle Carter:
And that leads to greater efficiency.

James Sanders:
And improve customer retention.

Michelle Carter:
Absolutely.

James Sanders:
And as we look to the future, the next one to two years Yeah.

Michelle Carter:
What's coming up?

James Sanders:
We anticipate even more significant transformations.

Michelle Carter:
Oh, yeah. AI is just getting started.

James Sanders:
We're moving beyond basic automation to AI that's really augmenting strategy.

Michelle Carter:
It's getting exciting.

James Sanders:
So first up, we're expecting more sophisticated proactive retention alerts.

Michelle Carter:
So, like, even earlier warnings.

James Sanders:
Driven by what we call multi signal AI.

Michelle Carter:
Okay.

James Sanders:
Instead of relying on those lagging health scores

Michelle Carter:
Right.

James Sanders:
These predictive models are gonna synthesize data from the entire customer journey.

Michelle Carter:
The whole thing.

James Sanders:
Product usage, support interactions, financial data, even the sentiment from calls.

Michelle Carter:
Wow.

James Sanders:
The goal is to create these early warning systems that can flag an account as at risk months before you see any trouble.

Michelle Carter:
That's incredible.

James Sanders:
And these systems can pinpoint the specific factors.

Michelle Carter:
So you know exactly what to address.

James Sanders:
It's not just, oh, they're at risk. It's, oh, they're at risk because of this.

Michelle Carter:
That's so helpful.

James Sanders:
It's gonna be a huge step forward.

Michelle Carter:
It is.

James Sanders:
It's not just about identifying at risk accounts.

Michelle Carter:
Right.

James Sanders:
It's about understanding why they're at risk Uh-huh. And suggesting specific interventions.

Michelle Carter:
So much more actionable.

James Sanders:
We're also expecting to see the widespread adoption of what we're calling embedded co pilots.

Michelle Carter:
Co pilots. What does that even mean?

James Sanders:
It's like an AI assistant

Michelle Carter:
Okay.

James Sanders:
That's integrated into the tools that CSMs use every day.

Michelle Carter:
That's right there with them.

James Sanders:
And these copilots are powered by large language models

Michelle Carter:
Cool.

James Sanders:
So they can answer questions Okay. Generate content tailored to specific customers. On the fly. Imagine asking your AI copilot why a customer's health score is dropping,

Michelle Carter:
and

James Sanders:
it gives you an instant analysis.

Michelle Carter:
That would be amazing.

James Sanders:
Or maybe you prompted to draft a reengagement email.

Michelle Carter:
Okay.

James Sanders:
And it generates a first draft in seconds.

Michelle Carter:
That's so efficient.

James Sanders:
We're seeing early examples of this.

Michelle Carter:
Yeah.

James Sanders:
And we expect this to become a standard feature.

Michelle Carter:
So every CSM will have one.

James Sanders:
It's like having a GPS for a driver.

Michelle Carter:
I like that analogy.

James Sanders:
It's not replacing the CSM. It's providing guidance and

Michelle Carter:
Helping them navigate those complex situations.

James Sanders:
And as these copilots learn from your best practices Yeah. They'll ensure consistency and expertise across your entire team

Michelle Carter:
That's a huge benefit.

James Sanders:
AI is also going to start acting as a conductor for multichannel customer orchestration.

Michelle Carter:
Orchestration? That sounds fancy.

James Sanders:
It is. So today, a lot of automation is based on rigid rules. Yeah. But in the future, we expect AI to enable these adaptive engagement plans

Michelle Carter:
Okay.

James Sanders:
The tailor not just the content, but the timing in the channel.

Michelle Carter:
Based on the customer's behavior.

James Sanders:
So for example, if a customer ignores your emails

Michelle Carter:
Yeah.

James Sanders:
But they're active on Slack Okay. The AI might automatically shift the communication to Slack.

Michelle Carter:
That's smart.

James Sanders:
And maybe even adjust the tone.

Michelle Carter:
Make it more casual.

James Sanders:
This kind of orchestration is gonna lead to more personalized and impactful interactions.

Michelle Carter:
Absolutely. It's about meeting the customer where they are.

James Sanders:
And then there's customer success operations, CS ops.

Michelle Carter:
What about them?

James Sanders:
This is where AI is gonna be used to optimize data management, identify bottlenecks.

Michelle Carter:
And forecast outcomes.

James Sanders:
Imagine AI analyzing those past customer journeys to figure out which onboarding steps lead to the best retention.

Michelle Carter:
Wow.

James Sanders:
It can help you redesign your playbooks for better results.

Michelle Carter:
That's incredible.

James Sanders:
This behind the scenes optimization is crucial

Michelle Carter:
It is.

James Sanders:
Because it ensures the efficiency and effectiveness of your entire customer success organization.

Michelle Carter:
It's like a secret weapon.

James Sanders:
And then we have the even greater levels of personalization and value delivery.

Michelle Carter:
We were talking about that earlier.

James Sanders:
Right. But AI is going to enable these hyper personalized success programs

Michelle Carter:
Okay.

James Sanders:
That adapt to each customer's definition of value.

Michelle Carter:
So it's not one size fits all?

James Sanders:
No. So for example, one customer might prioritize usage depth in a specific module.

Michelle Carter:
Okay.

James Sanders:
So all their metrics and reports will revolve around that.

Michelle Carter:
Makes sense.

James Sanders:
But another customer might be focused on ROI.

Michelle Carter:
Okay.

James Sanders:
So AI is gonna help quantify and communicate that value.

Michelle Carter:
That's powerful.

James Sanders:
And we'll likely see generative AI playing a bigger role in creating unique content.

Michelle Carter:
Like those QBR

James Sanders:
Exactly. Tailored to each account.

Michelle Carter:
That's the future.

James Sanders:
And the bottom line is leveraging AI is probably gonna become a necessity for staying competitive. I

Michelle Carter:
think you're right.

James Sanders:
So as we move into 2025 and beyond Yeah. AI and customer success is evolving from just automating tasks to becoming a strategic partner.

Michelle Carter:
It's elevating the role of the CSM.

James Sanders:
It is. It's making them more strategic.

Michelle Carter:
Absolutely.

James Sanders:
So let's break down the actual solution category.

Michelle Carter:
Yeah. Let's get specific.

James Sanders:
So first up, we have conversation intelligence and call analysis tools.

Michelle Carter:
Okay.

James Sanders:
These solutions are all about capturing and analyzing those customer conversations.

Michelle Carter:
So transcribing, identifying topics.

James Sanders:
Sentiment, generating summaries, and action items.

Michelle Carter:
It's like having a note taker in every meeting.

James Sanders:
We're talking about companies like Gong and Chorus

Michelle Carter:
The big name.

James Sanders:
And even more focused solutions like Fireflies.ai and Zoom IQ.

Michelle Carter:
Okay.

James Sanders:
Imagine prepping for a UBR in minutes because the AI has already summarized all the key points.

Michelle Carter:
That would be a dream.

James Sanders:
This category helps you listen at scale Yeah. Identify those trends and insights

Michelle Carter:
that you might miss otherwise.

James Sanders:
It allows for better coaching, better understanding of those pain points.

Michelle Carter:
And more effective follow-up.

James Sanders:
Next, we have customer workflow automation and digital engagement platforms. Okay. These tools automate those customer touchpoints and playbooks.

Michelle Carter:
So like Gainsight, Tatango

James Sanders:
Client success, Catalyst.

Michelle Carter:
Usual suspects.

James Sanders:
Imagine a new customer signs up

Michelle Carter:
Okay.

James Sanders:
And the system automatically triggers those personalized onboarding emails

Michelle Carter:
Okay.

James Sanders:
And in app messages.

Michelle Carter:
Based on their use case.

James Sanders:
And then if they haven't logged in after a week, it schedules that follow-up for the CSM.

Michelle Carter:
That's so smart.

James Sanders:
This automation ensures consistent and timely engagement.

Michelle Carter:
Across the entire life cycle.

James Sanders:
It frees up the CSMs to focus on those strategic interactions.

Michelle Carter:
It's all about working smarter, not harder.

James Sanders:
And then we have predictive health scoring and risk analytics.

Michelle Carter:
Another big one.

James Sanders:
This is where AI is analyzing data to predict health, churn risk, and expansion opportunities.

Michelle Carter:
So companies like Gainsight again.

James Sanders:
Planhat, Tatango, and even newer players like Lantern. Imagine you're a CSM and you get an alert because a customer's health score just dropped. Uh-oh. Maybe they're using the product list. Maybe they have more support tickets.

Michelle Carter:
That's a red flag.

James Sanders:
This early warning allows you to reach out and address those issues.

Michelle Carter:
Before it's too late.

James Sanders:
These predictive capabilities are so valuable. They are? They help you prioritize your efforts.

Michelle Carter:
Focus on the accounts that need it most.

James Sanders:
And, ultimately, improve those retention rates and drive revenue.

Michelle Carter:
That's the goal.

James Sanders:
Then we have customer feedback and sentiment AI.

Michelle Carter:
Okay.

James Sanders:
These tools are designed to analyze all that unstructured feedback.

Michelle Carter:
Surveys, support tickets.

James Sanders:
Social media mentions.

Michelle Carter:
Good stuff. All the good stuff.

James Sanders:
And they extract those key insights on topics and sentiment.

Michelle Carter:
So companies like Interpret, Thematic

James Sanders:
Qualtrics, XM Discovery. Okay. Imagine you're a CSM and you're looking at hundreds of MPS responses.

Michelle Carter:
Okay.

James Sanders:
And you can quickly identify that a lot of the detractors are confused about a new feature.

Michelle Carter:
That's actionable feedback.

James Sanders:
It is. It helps you understand those concerns.

Michelle Carter:
And it gives the product team something to work with.

James Sanders:
Understanding the voice of the customer is crucial for improvement.

Michelle Carter:
Absolutely.

James Sanders:
And these AI tools help you tap into that wealth of information.

Michelle Carter:
At scale.

James Sanders:
And finally, we have generative AI for content and training.

Michelle Carter:
This is a hot topic.

James Sanders:
It is. It's all about using AI to create custom content

Michelle Carter:
Okay.

James Sanders:
Or even simulate interactions for training.

Michelle Carter:
So, like, role playing within AI?

James Sanders:
We're talking about companies like cast dot app, Hejin.

Michelle Carter:
And Berry AI CSM.

James Sanders:
Imagine needing to create a personalized QBR deck for a client. Yeah. Instead of spending hours on it, you use a generative AI tool to create a first draft.

Michelle Carter:
That's so much faster.

James Sanders:
And it can pull in those relevant metrics and insights.

Michelle Carter:
It's like having a personal assistant.

James Sanders:
The potential here is huge.

Michelle Carter:
It is.

James Sanders:
It can significantly reduce the time and effort involved in creating content.

Michelle Carter:
Allowing CSMs to engage in more meaningful ways.

James Sanders:
And it's important to note that these categories often overlap. Yeah. Many companies are using a toolkit approach.

Michelle Carter:
They're using multiple solutions.

James Sanders:
The goal is to offload those tasks to AI.

Michelle Carter:
So CSMs can focus on relationships and insights.

James Sanders:
Exactly.

Michelle Carter:
And speaking of AI, let's do a quick glossary of terms.

James Sanders:
Yeah. Let's demystify some of this stuff.

Michelle Carter:
So first up, we have LLMs, large language models.

James Sanders:
These are those powerful models trained on massive amounts of text data.

Michelle Carter:
They can understand and generate human like language.

James Sanders:
Think chat GPT.

Michelle Carter:
Exactly. That's an LLM.

James Sanders:
So when you see AI drafting emails or providing those natural language responses There's

Michelle Carter:
probably an LLM at work.

James Sanders:
Then we have embeddings.

Michelle Carter:
Okay.

James Sanders:
This is a way to represent information as numbers that capture its meaning.

Michelle Carter:
So, like, words or sentences turned into numbers.

James Sanders:
That allows the AI to understand the relationships between different pieces of information.

Michelle Carter:
That's cool. And then we have vector search. Instead of keyword search.

James Sanders:
Right. Vector search uses those embeddings to find information based on meaning.

Michelle Carter:
Even if the wording is different.

James Sanders:
This is also known as semantic search.

Michelle Carter:
Okay.

James Sanders:
And it can really improve the accuracy of your knowledge based searches.

Michelle Carter:
That's helpful.

James Sanders:
Then we have fine tuning. This is where you take a pretrained model like an LLM

Michelle Carter:
Okay.

James Sanders:
And you train it further on specific data.

Michelle Carter:
To make it even better at a specific task.

James Sanders:
It's like customizing it to be an expert in your domain.

Michelle Carter:
I like that.

James Sanders:
And finally, RRAG, retrieval augmented generation.

Michelle Carter:
What a mouthful.

James Sanders:
It is, but it's basically combining a generative AI like an LLM with an external knowledge source.

Michelle Carter:
Okay.

James Sanders:
So the AI can retrieve relevant information before generating a response.

Michelle Carter:
Making the answers more accurate.

James Sanders:
It's all about reducing those errors.

Michelle Carter:
That's important.

James Sanders:
So understanding these core terms gives you a foundation for understanding how these tools work.

Michelle Carter:
It's like peeking under the hood.

James Sanders:
So to wrap things up, AI is a powerful amplifier for customer success. It is. And the best results come from humans and AI working together.

Michelle Carter:
It's a partnership.

James Sanders:
We're seeing real benefits in efficiency and customer satisfaction.

Michelle Carter:
And it's only gonna get better.

James Sanders:
It's crucial to invest in these skills and explore these technologies.

Michelle Carter:
Don't fall behind.

James Sanders:
Keep an eye out for new capabilities.

Michelle Carter:
K. Consider running pilot programs.

James Sanders:
AI is helping us strike that balance between high touch and high-tech.

Michelle Carter:
It's enabling us to deliver more personalized, proactive, and impactful customer success at scale.

James Sanders:
It's an exciting time to be in customer success. It is. Thank you for joining us for this deep dive.

Michelle Carter:
We hope you found these insights valuable.

James Sanders:
We hope you'll join us for our next deep dive.

Michelle Carter:
We'll see you then.

James Sanders:
Take care.

Michelle Carter:
Bye.