#TDSU Episode 137:

⏱️ Timestamps:

00:00:00 - Intro

00:00:54 - A customer experience nerd

00:01:31 - Struggling with retention forecasting

00:02:50 - Trust no health score

00:03:10 - Health scores: More of a guessing game?

00:04:36 - Keep sentiment and health scores separate

00:05:56 - Can AI solve the accuracy gap?

00:06:23 - The risk of equating happiness with renewal

00:09:00 - Blind spots in customer predictions

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🤝 Connect with the hosts:

Dillon's LinkedIn: https://www.linkedin.com/in/dillonryoung

JP's LinkedIn: https://www.linkedin.com/in/jeanpierrefrost/

Rob's LinkedIn: https://www.linkedin.com/in/rob-zambito/

👋 Connect with Diane Gordon: Diane's LinkedIn: https://www.linkedin.com/in/gordondiane/

[Diane] (0:00 - 0:14)

I'm pretty religious about it that the sentiment should live separately from the health score that the thing about the health scores is purely machine generated. There's no way a human can mess with it. And the minute you put the human sentiment in there, you kind of mess with the purity of it.

[Dillon] (0:22 - 0:33)

What's up lifers and welcome to The Daily Standup with lifetime value where we're giving you fresh new customer success ideas every single day. I got my man Rob here. Rob, do you want to say hi?

[Rob] (0:33 - 0:34)

What's up people?

[Dillon] (0:35 - 0:39)

And we've got JP here. JP, do you want to say hi?

[JP] (0:40 - 0:41)

How's it going lovely folks?

[Dillon] (0:42 - 0:45)

And we have Diane with us. Diane, do you want to say hi?

[Diane] (0:46 - 0:46)

Hello.

[Dillon] (0:47 - 0:54)

Thank you so much for being here, Diane. And I am your host. My name is Dillon Young.

Diane, can you introduce yourself please?

[Diane] (0:54 - 1:17)

Yes, of course. I am a customer experience nerd. I've been working on post-sales SaaS organizations for my whole career, about 35 years now, building out and running post-sales teams that maximize retention and all the things that go with that value, frameworks, metrics, health scores, you name it.

I love it. I'm passionate about it. And it's how I've spent pretty much my whole life.

[Dillon] (1:18 - 1:31)

Love it. Love it. Diane, you know what we're doing here?

We ask every single guest one simple question, and that is, what is on your mind when it comes to customer success? Why don't you tell us what that is?

[Diane] (1:31 - 2:47)

I'm consulting with a number of customers now that are using different CSPs. Some of them are homegrown and in Salesforce. And so the thing I'm struggling a little bit with, and I've never found a solution to this, is how to really know what's going on with the customer.

So you have your machine-generated health scores, which are incredibly valuable. Look at things like usage, and are they using the licenses they paid for? Are they using sneaky features?

All those things. And then you have a CSM sentiment. If I asked the customer today, would they renew?

And then there's this other kind of murky stuff, right? Like the CSM isn't necessarily talking to the executive buyer. I find myself as a consultant constantly being asked by CFOs to help them do a better job of retention forecasting.

And I feel like the tools that we have at our disposal, the health score, the CSM sentiment, if you're in a company that doesn't have an account manager, it's also gauging the buyer sentiment. That's a missing piece. I feel like we could do better.

And I'm sure AI can play a role in this somewhere, but it still feels like we're pretty good at it. But I feel like the margin of error is still too great. And one company I'm working with now, that margin of error is in the millions.

And so it's really significant. So that's the thing that I'm continuing to tune. After all this time, I still don't have a great answer.

[Dillon] (2:50 - 3:08)

Rob, I'm sure you have a lot of the same conversations, and I know you know Diane personally, but I'd love to hear your perspective on this. And maybe, I don't want to challenge that we could do better. Of course, we could always do better.

But what does better look like to you, Rob? If somebody challenged you today, what would better be?

[Rob] (3:10 - 4:35)

That's a really good question. It's a good topic, Diane. It's one that Diane and I have thought about and talked about a bit in the past.

So I appreciate you bringing it up. I think it does still continue to be this mystery. I was talking with some friends at Vitaly, and they gave me a hat that says, trust no health score.

I wish I had it with me. I'll wear it next time. But it is baffling that it's still a mystery, right?

It seems like very few people actually trust their health scores. I don't personally know hardly anybody who does. And it's because of those nuances, like CSM is not talking to their economic buyers, for example.

So the CSM sentiment is way off. Oh, they're totally good to renew. They're going to be fine.

Come to find out they got a new CFO. Nobody was tracking that. So for me, what I noticed is most health scores that I deal with, they're initially based on conjecture and a guessing game.

We would venture to guess that CSM sentiment should be worth like 20%. And we'll venture to guess that this one usage metric is worth like 20%. But what I don't see is regular enough updating of health score methodologies and doing so in a scientifically rigorous way, where I think there's room, not to get too technical here, but I think there's room to do some really advanced statistical analyses and utilize data science to retroactively look back and say, okay, to what extent did this health score actually predict the outcome that we were trying to predict? But I haven't seen that yet. Not commonly.

[Diane] (4:36 - 5:54)

So A, I'm of the school of thought, pretty religious about it, that the sentiment should live separately from the health score, that the thing about the health scores is purely machine generated. There's no way a human can mess with it. And the minute you put the human sentiment in there, you kind of mess with the purity of it.

And so whether or not it says you've got this machine generated cold clinical score, you hold that up against your human sentiment, which I think should be both the sentiment of your champion, as well as the buyer. And that second one is the one that usually gets lost somewhere in the fray. The champion's all like, we're awesome.

And then the buyer, whoever's signing is like, I don't know, wait. So I do think that to the extent possible, if you have data that you can use to create, if you have any years of just smart data, which a number of my customers do, they're startups, but older startups. So you can actually look at churn data and dig in and see what features were people not using or using when they turned.

So we can get pretty close, I think, on the health score. So I do trust what the health score is saying, but it doesn't tell the human side of the story. And that human side is where things get murky, right?

You've got your champion sounding really positive. And then next week, you get an email from the CFO saying, hey, we're going to cancel. Everything was green.

What happened? But anyway, I'm a believer in keeping those things separate.

[Dillon] (5:56 - 6:22)

I have nothing to add. The one thing I wanted to say right after Rob was talking about scientifically rigorous methods for updating your score, that's where AI comes in, is the ability to analyze that with no emotion whatsoever, and particularly to bump it up against sentiment and to help you understand where that may have diverged, so on and so forth. But JP, why don't you jump in?

[JP] (6:23 - 8:58)

Yeah, this thing about separating what the machines can do for us and what we as humans can do for us. And I like the way you're stating it because it doesn't sound like you're necessarily placing an emphasis of one over the other, which is sometimes where I feel like these discussions that involve AI or other things tend to go. And so we're just saying, hey, let's keep these things separate, but they're both still very useful.

One of the things that I was thinking about as we were discussing this is what are some of the blockers that I've experienced in getting information so that there's less guesswork, right? The more information I have, the better. Of course, the more accurate information I have, the better.

And so that's where things go, right? Because I've heard in the short time that I've been in customer success, at this point, I've only had about maybe three years in this customer success space. One of the things that I feel like I've seen that's a little bit of a change is, how do I put this?

People used to talk about customer obsess, and there's some sort of fluffy language that I felt was an overblown sentiment, maybe, in a way, that like, oh, the customers, they're really happy. Of course, they're going to renew. It was equating the sentiment that you observed and interpreted as positive from the customer, meaning that they were going to renew.

When in fact, if we look at that information, I think someone mentioned the executive buyer. And so we know if that customer who we're talking to, if they're not showing the value of that product to that executive buyer, to the person who's signing off, then there's no renewal, no matter how happy they are. Because I've heard of instances where there's tools that I've known of internally, I won't say where, but tools that people really liked internally, but got totally shuttered, but they didn't really get any input from the people who were actually using it, because sometimes that's the way decisions are made.

They're not always going to say, oh, wow, we're thinking about cutting something. We should talk to the people in customer success, especially if they're not maybe investing a lot in them, then why would they even initiate that discussion? So part of me thinks in this effort to get more information to the customer, it's like, yeah, how do I have conversations with people where I can really thread the value to the renewal happening?

So how do I talk with someone so they understand and can communicate that with that executive buyer, so that we actually get that renewal, as opposed to, oh, I talked to them the other day, they're happy.

[Dillon] (9:00 - 9:25)

Diane, that is our time. I think we could talk about this for a lot longer, and maybe we should, maybe you should come back. I think at the very least, it's a great reminder about blind spots.

And the many, many variables that we're dealing with when we're trying to predict certain things with our customers. Thank you so much for bringing this to our attention. We'd love to have you back in the future.

But for now, we've got to say goodbye.

[Diane] (9:25 - 9:27)

Okay, thanks for having me.

[Voiceover] (9:31 - 10:02)

You've been listening to The Daily Standup by Lifetime Value. Please note that the views expressed in these conversations are attributed only to those individuals on this recording, and do not necessarily reflect the views and opinions of their respective employers. For all inquiries, please reach out via email to Dillon at lifetimevaluemedia.com.

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