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Welcome to the latest edition of our weekly newsletter. This week we talk about:
The explosion of AI in CS
What if there was more than LLMs
AI should be used for more than personal efficiency
Let’s get into it…
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How much AI are you using?
AI continues to be a hot topic in Customer Success, and I doubt it will cool down anytime soon. My LinkedIn feed is full of other CS pros sharing new techniques they've discovered or tools they're using to become more efficient. And I welcome all of this. It's encouraging to see CS leaning in hard to take advantage of what AI can offer. When Revenue Per Head is such an important metric for most start-ups, being able to do more with less is such a crucial aspect of running a profitable company in the post-zirp era.
However, if there is one trend I've noted, it’s that many of the conversations appear to be focused on personal efficiencies, with use cases along the lines of automated email replies, presentation generation, ideation, and research. There is nothing wrong with that (I'm using Grammarly to help draft this), but AI is so much more than what recent large language models (LLMs) offer us.
AI makes an ideal assistant
AI is more than just LLMs
I've yet to see many people discuss using AI to provide better insights, more accurate forecasting, or segmenting customers in other ways beyond ARR size. We've jumped into generative AI as if our lives depend on it (perhaps our very jobs do), but we are overlooking what more traditional AI methods can do for our business. For example, Machine Learning (ML) has been around for a very long time, and most of us have interacted with it, possibly unknowingly. We're all no doubt familiar with Amazon's and Netflix's recommendation systems; well, that's AI. Have you gone through a credit card application and received a credit limit? That's AI.
We should be using AI more in our operations
It begs the question, why not use some of these ML solutions for our business? There are many suitable use cases, and just off the top of my head, I can already think of these examples:
Having a dynamic knowledge base that surfaces personalised content based on your previous interactions.
Automated emails that suggest specific actions based on the behaviour of successful customers in your particular cluster?
Forecasting churn and providing next-best actions to pre-emptively retain accounts.
The examples are plentiful, and businesses will truly become AI mature when they adopt these systemised solutions as an embedded part of their core operations, not just personal time savers.
At this point, I break AI usage into two themes:
Personal AI: Productivity hacks to gain personal efficiencies
Operational AI: Corporate solutions that drive better insights and decision-making
If you're in the very early stages of building out your Customer Success organisation, I recommend investing time in both of these areas.
Yes, Customer Success Managers should utilise AI to make their working day as efficient as possible. Still, as a business, you also need to examine AI and how it can enhance your operational intelligence.
I'd love to hear how you're currently using AI in your workflows today. Have you started? Beyond personal efficiency, what other use cases are you using AI for?
And that’s it for this edition. See you again next week!
Simon.
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