Sundar’s experiMENTAL
Hello experiMENTAList, it’s Sundar 👋
I’m a former Head of Marketing Science at Uber where I optimized $1Bn+ in spend across Brand, Performance, and Lifecycle.
Now, I share weekly playbooks top Marketers use to prove, optimize, and scale ROI.
Thank you for being a valuable part of this growing community of 2.6K+ marketing leaders from Uber, DoorDash, Google, Spotify, and many more.
Now let’s step into the lab!
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What we’ll dive into today
Everyone knows the benefits of segmentation:
stronger personalization
better customer experience
improved profitability.
But what most people don't recognize is that there are three types of segmentation, each with its own pros and cons.
Let's dive in.
The 3 types of segmentation
Demographic
Lifecycle + value
Algorithmic
All segmentation is based on data. Pretty obvious statement, but the data you have available determines the segmentation that you can build.
Let’s start with Demographic.
Demographic
Demographic is a wide-ranging segmentation system that uses demographic information. What constitutes demographic information is quite broad, but it's an attribute about the user themselves. It doesn't describe their actions; it simply describes the user.

The classic attributes are:
Age
Gender
Household income
What often happens with demographic segmentation is when we create personas. We use demographic information to create a structure or system that encompasses who a user is, to then represent what they'll do and why

Let’s take a quick look at the example above. Now what can you assume about Stacy?
She’s in her early 30s.
She’s female.
She’s got a bachelor’s degree and makes $75-100K.
Based on this you can likely make some inference about her lifestyle, her likes, dislikes, to a reasonable degree because we have lived experiences. We are likely able to articulate where she is in stage of life, what her experiences might be as a female, and what she can buy or not buy with $75,000 to $100,000. For example, we know she likely can't afford a Lamborghini, but she's also likely not buying a completely broken-down junk car.
“But Sundar, what if her parents are super wealthy and she drives a Lambo?!”
“Cool. That’s a hyper edge case.”
Pros
More personal information
More targetable with ads
Cons
Expensive data to acquire
Leads to normalizations not related to behavior

The meme above is a great example of where demographic segmentation can break down. Yes, it’s an edge case but it is reflective of the fact that it doesn’t say anything about behaviors.
Now, let’s move on to Lifecycle segmentation.
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