When your business sells to both everyday consumers and trade buyers like pharmacies and wholesalers, you need to know which group is responding to your advertising. Without that, you're splitting your budget blind. Here's how we gave this client complete visibility — and what they did with it.
Real-Time
Customer Segmentation
+35%
B2B ROAS Improvement
1 Dashboard
All Segments, All Channels
The Problem
This client ran a busy e-commerce store that sold to two very different groups of people. One group was everyday consumers buying for personal use. The other was trade buyers — pharmacies, wholesalers, healthcare businesses — buying in larger quantities on account.
Both types of customer were going through the same website. Both were generating revenue. But inside Google Analytics, all purchases looked identical. There was no way to tell a retail consumer from a pharmacy placing a bulk order.
This created a serious blind spot. When they looked at their Google Ads performance, they could see total sales and total revenue — but they couldn't see who was buying. A campaign might appear to be performing well, but if it was only attracting low-value retail buyers and missing the high-value trade accounts, they'd never know.
They also had no insight into which industries their B2B customers came from. Knowing that a segment of customers is "business buyers" is useful. Knowing that pharmacies specifically account for a disproportionate share of your revenue — that's actionable.
"They were running paid ads across multiple channels but had no way to know whether the buyers converting were their most valuable trade customers or one-time retail shoppers. Every decision about ad spend was a guess."
Our Solution
The information we needed was already in the system — the website knew exactly who each customer was. The challenge was getting that information out and into a place where the analytics tools could use it. Here's how we did it.
Modern e-commerce platforms like this client's NetSuite store carry a lot of data about each customer session — who's logged in, what kind of account they have, what their customer classification is. This data often exists on the website but isn't automatically shared with analytics tools.
We went through the website's data layer — the behind-the-scenes stream of information that flows as customers browse and buy — to locate the fields that described the customer type. Some of them weren't being made available at all initially. We worked with the site configuration to surface those fields so they could actually be read and used.
Once we knew where the data lived, we set up Google Tag Manager to read it every time a customer interacted with the site. We captured four key pieces of information:
In Google Analytics 4, you can attach properties to a user that persist across all their sessions. We used this to pass the customer type as a "user-scoped dimension" — meaning once GA4 knows a user is a B2B pharmacy account, it remembers that across every visit and applies it to all their historical data too.
This is what makes the segmentation powerful. Every report in GA4 — ad performance, source and medium breakdowns, conversion rates, revenue — can now be filtered by customer type. Suddenly, the client could answer questions they'd never been able to ask before.
Data sitting inside GA4 is only useful if you can read it easily. We built a custom dashboard in Google Looker Studio (formerly Google Data Studio) that connected directly to the GA4 data and presented it in a way the client's team could use without any technical knowledge.
The dashboard showed revenue, conversion rates, and ad performance broken down by customer segment — B2B vs B2C, industry type, new vs returning — alongside the source and medium data showing exactly which advertising channels were driving each type of customer. Everything in one screen.
The Results
Real-Time
Segmentation
Every customer tagged the moment they interact with the site — no manual work, no delay.
+35%
B2B ROAS
Once B2B revenue was visible separately, the client could shift budget to the channels that were driving it.
1-Click
Reporting
All segments, all channels, all time periods — in a single Looker Studio dashboard anyone can use.
This solution is relevant if your business does any of the following:
You sell to both businesses and consumers through the same website
Your analytics shows combined revenue figures but you can't split them by customer type
You suspect your trade or B2B customers are more valuable but can't prove it with data
You're running Google Ads but can't segment campaign results by customer profile
Your customer data lives in your website or CRM but doesn't flow through to your analytics
You have a logged-in account system and account types but they're invisible in GA4
This approach works for any e-commerce platform that stores customer account information — NetSuite SuiteCommerce, Shopify Plus, Magento, WooCommerce, or custom-built stores. If your platform knows who a customer is when they log in, we can get that information into GA4.
B2B (business-to-business) customers typically have higher order values, longer decision cycles, and much higher lifetime value than B2C (business-to-consumer) retail buyers. If you're running paid ads and can't see which type of customer each campaign is attracting, you might be spending heavily to acquire low-value retail shoppers while your most profitable trade accounts are coming through organic search for free. Segmenting properly means you can see this, and reallocate accordingly — which is exactly what happened with this client.
A user-scoped dimension in GA4 is a property attached to a specific user that persists across all their sessions. Standard event tracking only captures what happened in a single visit. A user-scoped dimension means that once GA4 knows a user is a trade buyer — or a pharmacy, or a returning customer — it applies that label to every session they've ever had and every one they'll have in future. This is far more powerful for reporting because you can analyse long-term behaviour and revenue by customer type, not just single visits.
Guest shoppers are tagged as guests — which is itself a valuable data point. When you can see what proportion of your revenue comes from guests versus account holders, you can make informed decisions about login incentives, loyalty programmes, and how aggressively to promote account creation. For B2B customers specifically, they almost always use a trade account, so guest vs logged-in is a strong early signal of customer type even before the account classification is read.
Yes. Any e-commerce platform that supports customer accounts and stores customer classification data can be set up this way — Shopify Plus, Magento, WooCommerce, BigCommerce, and custom-built stores all support it. The approach may differ slightly (the data layer structure varies by platform) but the outcome is the same: customer type passed to GA4 as a persistent user property, available in all your reports and Google Ads audiences.
The dashboard we built for this client showed revenue, transactions, conversion rate, and average order value — all filterable by customer segment (B2B vs B2C, industry type, new vs returning). It also showed source and medium data alongside each segment, so you could see at a glance which advertising channels were driving which types of customer. It was designed so that a marketing manager or business owner with no technical background could use it without training — one screen, all the answers.
We'll review your current analytics setup and tell you exactly what's missing — and what we'd build to give you the full picture. No jargon, no commitment.