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Personalization starts with a simple question: who is on the page right now? Personyze answers it by assembling a unified visitor profile from many first-party signals, then letting you turn the traits in that profile into audiences. This post is a technical tour of what gets tracked, how it’s gathered, and how you put it to work in behavioral targeting, segmentation, and on-site targeting.
When a visitor loads a page that’s running Personyze, the request itself already carries a lot. From the user-agent string, Personyze reads the device type, browser, operating system, and language; from the request headers it sees the referrer and any campaign parameters. None of this needs extra setup — it’s present on the very first pageview.
Next comes IP enrichment. From the visitor’s IP address, Personyze derives geo-location (country, region, city), and can go further: deduce the company behind the visit via reverse-IP lookup — the basis for B2B and account-based marketing — and even pull the local weather at the visitor’s location, which is genuinely useful for some retail and travel use cases.
Then Personyze sets a first-party cookie — a persistent visitor identifier on your own domain. That cookie is what turns a single pageview into a profile: instead of starting from scratch each time, Personyze keeps building the same visitor’s profile across the session and from one session to the next — and across devices when identity can be linked (cross-device tracking).
Everything Personyze collects rolls up into a handful of categories — and each one is something you can segment on:
Here’s the fuller library of what you can target on — most conditions accept operators, ranges, and time windows, so you can be as precise as you need:
Every condition can be set to include or exclude and combined with AND / OR / XOR, nested into groups — the full reference lives in the targeting rules guide.
The categories above work out of the box. For anything specific to your site, you can tell Personyze to extract values from the page and turn them into custom profile attributes — first-class traits you can target on exactly like the built-in ones. Personyze can read from:
dataLayer
Each extracted value becomes an attribute in the visitor profile, available in any targeting rule or segment. The full setup is documented in the Personyze knowledge base.
First-party site signals describe the session; your own systems describe the customer. Personyze gives you several ways to push that data into the same profile:
However it arrives, the data joins the on-site traits in one profile — so you can combine “subscribed customer on the enterprise plan” with “currently viewing the pricing page” in a single rule.
With the profile assembled, segmentation is just combining those traits into audiences. The targeting builder lets you mix any of them — system, location, company, behavior, source, CRM, and your custom attributes — with include / exclude conditions and AND / OR / XOR logic, nested as deeply as the audience needs. Because the profile updates in real time as the session unfolds, the audience does too — which is exactly what makes on-site targeting possible: the page can respond the moment someone enters a campaign, views a key page, or matches a target account.
Prefer not to build the tree by hand? Describe the audience in plain English — “Dutch mobile visitors who haven’t subscribed” — and the built-in AI assistant turns that natural-language description into the rule for you to keep or fine-tune. Build an audience here:
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Individually the conditions are simple; the value is in combining them. A few practical recipes — each is a compound rule plus what you’d show the audience it matches:
spring_sale
/sale
For finished, real-world inspiration, browse the website personalization examples — each one starts with a targeted audience like these.
An audience on its own doesn’t do anything — you point it at an experience. Because targeting and personalization share one profile, a segment you define here works everywhere: recommendations, popups and banners, A/B tests, or a fully personalized page. Define who once; reuse it across every channel.
For the technical details — tracking setup, custom attributes, integrations, and cross-device tracking — see the Personyze knowledge base, or read the behavioral targeting overview.
Related reading: see how an offline touchpoint carries its campaign context into a personalized session in our offline-to-online QR code personalization post.
Personyze builds a unified profile from first-party signals: system and device (from the user-agent), location and local weather (from the IP), company and firmographics (reverse-IP lookup), on-site behavior (pages, products, events, recency), traffic source and campaign, and any CRM data you sync. You can also extract custom values from the page.
Personyze sets a first-party cookie on your own domain as a persistent visitor identifier. That cookie is what lets the profile build across sessions — and across devices when identity can be linked — rather than resetting on every pageview.
Yes. From the visitor’s IP address Personyze can deduce the company, industry, and size via reverse-IP lookup, which is the foundation for B2B and account-based marketing targeting. You can enrich this further with CRM or CDP data.
You can tell Personyze to extract values from page inputs, your own cookies, meta tags, JavaScript variables, DOM containers, or the Google Tag Manager data layer. Each becomes a custom profile attribute you can use in any targeting rule or segment, just like the built-in traits.
Beyond on-site tracking, you can upload a user list from a file, sync your CRM or CDP through a native integration, and push events or profile attributes from your backend or mobile app via the Personyze REST API and SDK. Everything lands in the same unified profile you target on.
Yes. CRM and CDP data synced through the API or a native integration (HubSpot, Salesforce, Segment, and others) lands in the same profile as on-site signals, so a single rule can combine something like ‘enterprise-plan customer’ with ‘currently viewing pricing.’
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