Target Time: 15–20 minutes Each slide has an estimated time. Speak naturally — these are guides, not lines to memorize.
⏱ ~30 seconds
“Good [morning/afternoon], everyone. Today I’m walking you through a GA4 Segmentation Demo — specifically, how Google Analytics 4 uses segments to help marketers move beyond surface-level data and into real behavioral insights.
This is grounded in both hands-on GA4 practice and two peer-reviewed research articles that validate why segmentation is one of the most strategically important tools in modern digital marketing. Let’s get into it.”
⏱ ~45 seconds
“Here’s what we’re covering today. We’ll start with the basics — what a segment actually is — then move into the three types GA4 offers, how to build them, and some advanced features like sequences and exclusions.
I’ll wrap up with real use cases you can apply right away, and then connect everything back to the academic research. You’ll see the number 238 on this slide — that’s how many peer-reviewed articles were analyzed in one of our source studies on marketing analytics. Segmentation isn’t just a tool — it’s a discipline with serious academic backing.”
⏱ ~1 minute
“So what exactly is a segment? Simply put — it’s a filter that isolates a specific subset of your data so you can analyze it in isolation.
Instead of looking at your total users, a segment might let you look at only your US-based users, or only people who added something to their cart, or only people who came in from a paid ad.
Why does this matter? Three big reasons: First, you can identify your highest-value users — who’s actually driving revenue. Second, you can feed those segments directly into Google Ads to target people who behave a certain way. And third, you can compare groups side by side — mobile versus desktop, new visitors versus returning ones.
One important thing to know right away: in GA4, segments only work inside Exploration reports — the Explore section of the platform. If you’re in a Standard report, you’ll use something called Comparisons instead, which I’ll get to in a minute.”
⏱ ~1 minute
“Speaking of which — let me quickly clarify the difference, because this trips a lot of people up.
Segments live in Exploration reports only. But they’re incredibly powerful — you can create sequences, set multiple scope conditions, build audiences, and include or exclude specific behaviors.
Comparisons work everywhere — they persist across standard reports as you navigate — but they’re much more limited. No sequences, no advanced scoping, no audience building.
The way I think about it: use Comparisons for a quick filter while you’re browsing standard reports. Use Segments when you’re doing deep analysis in Explorations and you need precision.”
⏱ ~1.5 minutes
“Now here’s where it gets interesting. In GA4 there are three types of segments, and the type you choose determines not just who gets filtered — but how much data comes with them.
User Segments are the broadest. If a user meets your criteria at any point in their history, you get all of their events — every session, every interaction.
Session Segments are narrower. You only get the events from the specific sessions that matched — not other sessions by the same user.
Event Segments are the most granular. You get only the individual events that match — nothing else is pulled in.
Let me make this concrete on the next slide.”
⏱ ~1.5 minutes
“Let’s say we have one user who had two sessions on your website. Session 1 had a couple of page views and a click. Session 2 had a page view, an add_to_cart, and a checkout.
Now I build a segment around the ‘add_to_cart’ event. Here’s what happens depending on which segment type I choose:
User Segment — because this user did add_to_cart at some point, I get all six events. Everything. Both sessions. Their entire history in your date range.
Session Segment — I only get the three events from Session 2, because that’s the session where add_to_cart happened. Session 1 is excluded.
Event Segment — I get exactly one event: the add_to_cart itself. Nothing else.
Same user. Same criteria. Three completely different datasets depending on which type you pick. That’s why choosing the right segment type is one of the most important decisions you make before building.”
⏱ ~1 minute
“Let’s walk through how you actually build one of these. You go to Explore, open a Free Form report, and click the plus icon next to Segments. That opens the Segment Builder.
The interface is split: on the left, you define your conditions. On the right, GA4 gives you a live preview of how many users, sessions, or events your segment would capture.
You can add conditions by searching for any dimension or event name. Then you connect them with AND — meaning both must be true — or OR — meaning either one qualifies.
You can also group conditions into separate Condition Groups, which is where the real power comes in — because each group can have its own scope. And that’s our next slide.”
⏱ ~1.5 minutes
“Condition scoping is what separates basic GA4 users from advanced analysts. It controls when your conditions need to be met — not just what they are.
Across All Sessions means GA4 doesn’t care when the conditions happened. Condition A in January, Condition B in March — user still qualifies.
Within the Same Session means both conditions have to happen in a single visit. If they happen in different sessions, the user doesn’t qualify.
Within the Same Event is the tightest scope — all conditions must be satisfied by one individual event and its parameters.
Here’s a real-world example: say you want users who subscribed to your newsletter at any point, AND who viewed a promotion AND purchased in the same session. You’d need two separate condition groups — one set to ‘Across All Sessions’ for the newsletter, and one set to ‘Within the Same Session’ for the promo-to-purchase path. That’s a sophisticated, multi-touch segment that you simply cannot build any other way.”
⏱ ~1.5 minutes
“Building on that — sequence segments take it one step further. They’re only available in User segments, and they let you specify that events must happen in a particular order.
Here’s why that matters. If I just use AND conditions — ‘view_promotion AND purchase’ — GA4 will include anyone who did both, regardless of order. A user who purchased on Monday, then saw a promotion on Thursday? Still included.
But with a Sequence Segment, I can say: show me only users who saw the promotion first, and then purchased. Now I’m actually measuring whether the promotion drove the sale — not just that both events happened to a user.
And it gets more powerful. You can add time constraints — ‘view_promotion, then purchase, within 24 hours.’ That lets you test the urgency window of a promotion. Did your flash sale actually move people to buy faster?
You can also set different scopes on each sequence step — so Step 1 can happen in any session, but Step 2 must happen in the same session as Step 1.”
⏱ ~1 minute
“Just as important as including data — is knowing what to exclude. GA4 lets you add exclusion groups, highlighted in red in the builder.
There are two modes. Temporary Exclusion is date-range scoped. A user who purchased in the last 30 days gets excluded — but once those 30 days pass, they’re eligible to re-enter the audience. Great for retargeting: stop showing ads to recent buyers, but let them back in when they might be ready to repurchase.
Permanent Exclusion removes a user forever — even if you’re only analyzing a recent date range. If someone purchased 60 days ago, they’re out regardless.
The most practical use case here: cart abandoners. Build a segment that includes ‘add_to_cart’ and permanently excludes ‘purchase.’ Now you have a clean list of people who showed purchase intent but didn’t follow through — perfect for a Funnel Exploration to see exactly where they dropped off.”
⏱ ~1 minute
“GA4 also offers built-in starting points so you don’t have to build everything from scratch.
General segments like Purchasers or Non-Purchasers come pre-filled with basic conditions — useful as a starting point that you can customize.
Template segments give you a structured layout by category: Demographics, Geography, Technology, Acquisition. You fill in the values.
And then there are Predictive segments — these use machine learning to predict which users are likely to purchase or churn in the near future. This sounds exciting, and it is — but it requires significant data volume. Google’s threshold is at least 1,000 users who purchased in a 7-day period within the last 28 days. Most businesses won’t hit that. It’s something to work toward, but for most use cases you’ll be building custom segments.”
⏱ ~1.5 minutes
“Now let’s make this real. Here are six segment ideas that have immediate marketing value.
Cart Abandoners — include add_to_cart, exclude purchase. Run this in a Funnel Exploration to see exactly which checkout step loses the most people.
Mobile vs. Desktop — create two technology segments and compare conversion rate side by side. Most teams are shocked by the gap.
High-Engagement Users — users with more than five page views. Build an audience from this and retarget them in Google Ads — they’ve already shown serious interest.
Exclude Logged-In Users — permanently exclude your login event. This cleans your acquisition data so you’re not counting returning customers as new prospects.
Promo-Driven Buyers — sequence segment: view_promotion → purchase within 24 hours. Now you have a measurable number for promotional attribution.
Geographic Segments — US vs. non-US. Or any two regions. This tells you where to concentrate ad spend.”
⏱ ~1.5 minutes
“Everything I’ve shown you isn’t just a GA4 tutorial — it’s grounded in legitimate marketing research. Two peer-reviewed articles anchor this presentation.
The first is Ozcan’s 2026 study published in the Journal of Theoretical and Applied Electronic Commerce Research — which has an impact factor of 4.6, meaning it’s well-regarded in the field. Ozcan extended the traditional RFM model — Recency, Frequency, Monetary — by adding dimensions like basket depth, price sensitivity, and shopping regularity. He applied clustering algorithms — K-means, K-medoids, and Fuzzy C-means — to over 675,000 customer records and identified nine distinct customer segments: champions, at-risk customers, churners, promotion-sensitive buyers, and more. His core finding: richer behavioral dimensions produce more actionable segmentation.
The second is a bibliometric review by Gómez Pescador and colleagues, also published in 2026, which analyzed 238 academic articles spanning 2007 to 2023. Their conclusion: marketing analytics is now the core technological engine of data-driven market orientation. Companies that segment strategically — and act on those segments — consistently outperform those that don’t.”
⏱ ~1 minute
“So how does the research connect directly to what we’ve been doing in GA4?
Ozcan’s RFM dimensions map almost directly to GA4 user segment conditions. Recency? That’s your last_visit date parameter. Frequency? Session count. Monetary? Revenue events. His nine customer clusters — champions, at-risk, churners — are exactly the audiences you’d build in GA4 and activate in Google Ads.
And Gómez Pescador’s concept of Data-Driven Market Orientation? GA4 Explorations with well-built segments are the operational tool that makes that philosophy real. The research says companies should be using analytics to generate market intelligence and translate it into action — GA4 segmentation is the mechanism that makes it executable.”
⏱ ~1 minute
“Let me leave you with five things to take away from today.
One — there are three segment types in GA4, and the one you choose determines how much data comes with it. Match the type to the question you’re answering.
Two — segments live in Explorations, not standard reports. Use Comparisons for quick filters in standard reports.
Three — condition scoping is where the real power is. Use it to build multi-touch segments that capture complex user behaviors.
Four — sequence segments reveal intent by capturing the order events happen in — critical for attribution and promotional measurement.
Five — segmentation is strategic, not just technical. The research confirms it’s the core mechanism through which marketing analytics creates competitive advantage.
Thank you — I’m happy to take any questions.”
| Slide | Topic | Time |
|---|---|---|
| 1 | Title | 0:30 |
| 2 | Agenda | 0:45 |
| 3 | What Are Segments? | 1:00 |
| 4 | Segments vs. Comparisons | 1:00 |
| 5 | 3 Segment Types | 1:30 |
| 6 | Scope in Action | 1:30 |
| 7 | Segment Builder | 1:00 |
| 8 | Condition Scoping | 1:30 |
| 9 | Sequence Segments | 1:30 |
| 10 | Excluding Data | 1:00 |
| 11 | Suggested Segments | 1:00 |
| 12 | Practical Ideas | 1:30 |
| 13 | Academic Grounding | 1:30 |
| 14 | Research → Practice | 1:00 |
| 15 | Key Takeaways | 1:00 |
| Total | ~17 minutes |
Tip: If you’re running short on time, slides 4 and 11 are the easiest to condense. If you have extra time, expand on slide 12 by walking through how you’d actually build the cart abandoner segment step by step.