#TDSU Episode 210:

⏱️ Timestamps:

00:00:00 - Intro

00:02:03 - The Lego analogy for data mastery

00:05:58 - Why data is non-negotiable in 2025

00:06:37 - The human touch in data analysis

00:08:30 - Building a smarter data model

00:09:52 - Overcoming data roadblocks

00:11:02 - Creating a culture of data excellence

00:12:30 - Wrapping up

📺 Lifetime Value: Your Destination for GTM content

Website: https://www.lifetimevaluemedia.com

🤝 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 Mohammed Alqaq:

Mohammed's LinkedIn: https://www.linkedin.com/in/mohammedalqaq/

[Mohammed] (0:00 - 0:15)

Always thinking about data. For me, it is the backbone of customer engagement or strategic customer engagement, because if you don't have the data, you have no story to tell your customer, and you have no story to build.

[Dillon] (0:25 - 0:45)

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 JP here. JP, can you say hi?

How's it going, people? And we have Rob with us from the cockpit of his convertible.

[Rob] (0:46 - 0:47)

My rental.

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

Rob, can you say hi?

[Rob] (0:48 - 0:52)

My rental convertible.

I'm on vacation, baby. Mo' money, mo' problems.

[Dillon] (0:52 - 0:58)

All right. Mo' money, mo' problems.

And we have Mo with us. Mo, can you say hi, please?

[Mohammed] (0:59 - 1:00)

Hey.

Hello, everyone.

[Dillon] (1:00 - 1:09)

Hello, hello. And I am your host.

My name is Dillon Young. Mo, thank you so much for being here. Second time back.

Can you please introduce yourself?

[Mohammed] (1:10 - 1:49)

Thank you, Dillon. Thank you all for having me. It's always a pleasure to be with you.

It's always a pleasure to have this conversation. So my name is Mohamed Alqaq. I'm from Jordan.

I'm a strategic customer success manager at Oracle, and I'm the founder of Customer Success Middle East Community. I've been in this customer-facing role for the last 20 years. I've done it locally, regionally, and globally.

I've been involved in so many practices and industries in the past 20 years. And here I am. I'm trying to give back as much as I can.

[Dillon] (1:50 - 2:02)

I love it. I love it, Mo. And you do know exactly what we do here.

We ask every single guest one simple question. Yep. And that is, what is on your mind when it comes to customer success?

So can you tell us what that is for you?

[Mohammed] (2:03 - 5:58)

Data. Always thinking about data. To me, it is the backbone of customer engagement or strategic customer engagement because if you don't have the data, you have no story to tell your customer, and you have no story to build.

We all, in a certain time, played Lego. I'm a big fan of Lego bricks. So imagine you have 1,000 pieces of Lego bricks, different colors, different shapes, all together in a pile.

It doesn't mean anything. You cannot figure any opportunity what you want to build with those bricks. Now, if you start to sort those bricks by color, that gives you an understanding how many pieces of each color you have.

Then you start to arrange those colors into shapes. So each color, you arrange them into different shapes. Organize them, put them in a way that you can visualize all the pieces.

That's an organized or arranged bricks. Those arranged bricks will give you an opportunity to understand the trend. Common pieces, missing, repeated, unique, all sorts of things you can understand from those arranged pieces.

Now, this will give you an understanding of what a potential model you can build in the future from those bricks because now you understand what you have. This is exactly how we should treat data. We collect data from all over.

They are everywhere. Now, if we don't sort the data, if we don't arrange it, if we don't build a relation, it means nothing. If we collect, sort, arrange, build relation, build predictions, regressions, slice it into a way that it can become an information, that we can take it and start to build our story to engage with the customer.

This is how I think about data. And this is how I treat my data, to optimize your engagement and your customer experience. So how we do this?

By establishing our objectives and define what success looks like to us and understand the customer objectives, start to align those two objectives and build our data model. Collect the data, collect all data from any and every, every and each touchpoint you have with the customer. That will help you to understand all the trends, all the customer behavior, and it allows you to predict what might happen in the future.

This will help you also to build a very creative success journey, the customer, because you understand from their behavior, you can understand what might come in the future and you start to build your plan accordingly. It will help you to predict any problem might happen and you'll be more proactive to solve those problems before it happens. It allows you to improve the customer retention because you understand the customer needs, you have a good understanding of what has happened in the past, so you can build and improve the understanding of the customer needs and start to work accordingly or proactively to deliver more success to your customer.

[Dillon] (5:58 - 6:36)

I want to jump in here and just say, I love the analogy of the Lego bricks. I think it's fantastic. And the go so far as to how you sort it and then categorize it.

I love it. I will say you probably are in an enviable position working for Oracle. You probably have fantastic data.

The last thing I'll say is that I would argue, though, that in 2025, if you're a customer success professional of any variety and you're not working with data, you are destined to fail. And I'm sorry to be so pessimistic. JP, why don't you jump in here?

[JP] (6:37 - 8:30)

I think that the context, being able to contextualize data is one of those things that I like to bring up because sometimes you start talking about data, you start inevitably talking about AI, and sometimes people start to get worried about their jobs. It's sort of like that entry point. But I think us humans can do something really great.

What we have the ability to do is we can actually process things pretty fast, right there, maybe even from one call. Like I had a call earlier today where just while I was giving my introduction to a customer, I was able to read their disposition, right? I don't know if there's something that can read someone's disposition.

So I was able to tell, hmm, this person seems a little upset or something like that because here I am. I'm just giving my sort of spiel, and I can see the tension. I can see the body language, right?

And so once we go around and he gets to talk, he lets out why he's upset, right? And now I am able to address him not just from a data point, which is like, oh, this concern X addressed with solution Y. I'm able to actually hear and say, this person needs to be able to talk.

They need to be able to get things out. They need some reassurance, right? There are different touch points that I have that come from the human interaction that make me able to take in maybe some immediate data and act on it.

And so I just bring this up because, yes, like Dillon said, you're at Oracle. You probably have like a lot of great data, but I think we can even think about data even in the sense of like a very immediate encounter, which is the information that we're being fed.

[Mohammed] (8:30 - 9:52)

Data doesn't have to be – comes from systems. Me as a person, I can create the data from my interaction with the customer. We all have this kind of like sentiments we put towards our relation with the customer.

And we can build a new data model based on our interaction as a human. And we start to gauge those interactions and build the data. And for data accuracy, it doesn't have to be accurate at the first time.

But if you don't collect, if you don't sort, if you don't organize and analyze, you will not understand that this is not an accurate data. So we need to collect from every and each touch point. And then go through, sort, arrange, analyze, or visualize, analyze, and then build relation.

If it doesn't work, we remove it. We don't collect it in the future. So this is how we build our data collection model is by trying to collect everything, analyze it.

If it doesn't work, if it has no value, then we don't collect it in the future. And the human interaction is very important to build another level of data. That second level of data will help you to understand the customer behavior.

And then you build your relation with the customer based on that.

[Dillon] (9:52 - 9:53)

Rob, take us out of here.

[Rob] (9:54 - 10:44)

Yeah, I want to bring this home for some of the guests listening. Mo, I think you bring up a super important topic. I imagine there's a lot of the guests who will listen to this and say, I agree with everything I heard, but I still feel blocked.

And why? Maybe I lack the time to analyze data. Maybe I lack the interest.

I don't like looking at a spreadsheet. It doesn't feel exciting to me. Maybe I lack the skill set.

And maybe I feel like I need to take a course on this, which, by the way, I would actually recommend. I was thinking about pursuing a certification, at least, in data science myself. I feel like that would really level up my skill set.

And maybe I lack even access to the data. I mean, I love my people in RevOps, but I got to admit, some of them are a little protective of the data that they have access to from the systems.

[Mohammed] (10:46 - 11:01)

I've seen some cases where, you know, even the customer success manager, they have no access to the data. But, again, then you play with whatever you have in hand. And then you start to build your own data.

[Rob] (11:02 - 12:29)

And I love that you include that advice. I'm thinking about, there's a meeting recording tool that I started using called Spiky, which I really like, future potential sponsor Spiky, maybe. And it's cool because, you know, you can sign up for a free trial, and I'm not really trying to promote them here necessarily, but what you can do is you get tons of sentiment data from the call.

It's best in class, best I've seen across any meeting recording tool. And so you can start to enable yourself by finding places where you can create your own data story. I like the Lego analogy.

I'll close out with that. I mean, I feel like there are times in my past where, like, I'm trying to put together something with Legos, but I have, like, mixed in with my Legos. I have, like, some Lincoln Logs and some Play-Doh.

And it's just, like, and then I'm, like, missing pieces. And I'm trying to create this thing. I'm trying to create a cathedral out of my Legos, but I can't do it.

I can't do it. But I do think at the very least, like, if people listening to this leave with a re-inspired spirit to explore the data, to close, to use your Lego analogy, there's a parable that I heard once. It's, like, there's three brick layers.

The first, you ask them each what they're doing. The first one says, I'm putting, I'm laying bricks. The second one says, I'm building a wall.

The third one says, I'm building a cathedral. And if you can, in your company, create a culture where you're, like, we are building a cathedral of data, then it can be the most exciting, inspiring, unlocking thing that you do as a company to master your data.

[Dillon] (12:30 - 12:45)

Mo, that is our time. I love the analogies. The cathedral of, that might be a little bit grandiose, Rob, so let's stick with Legos.

But, Mo, thank you so much. Come back again. Please, love having you here.

But until then, we've got to say goodbye.

[Mohammed] (12:45 - 12:49)

Thank you so much. Thank you for having me, and hopefully we'll be in touch again.

[VO] (12:55 - 13:25)

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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