Targeting Rules in Personyze

Targeting rules in Personyze allow you to precisely control which visitors see specific campaigns, banners, popups, or personalized content. These rules leverage real-time user behavior, demographics, CRM data, device attributes,…

Targeting rules decide which visitors a campaign applies to. Personyze tracks 70+ real-time signals about every visitor — behavior, location, device, profile and CRM data, and signals from your connected tools — and evaluates your rules on the fly, so a matching visitor sees the personalized experience the moment they qualify.

A new campaign’s audience starts empty (it would match everyone until you narrow it). You build it by clicking Add targeting rule and choosing from the categories in the picker. Each category you add becomes a rule group on the screen, and you combine the groups however you need.

The Add-targeting-rule picker with categories under three tabs. — Adding a rule opens the category picker. Rules are organized under three tabs — Visitor context, Behavior, and Integrations — so you can jump straight to the signal you want. Click to enlarge.

How rules combine

Each condition supports include or exclude. Parentheses nest logic, and rule groups combine with AND, OR, or XOR. A rule can be as simple as “is on the pricing page” or as layered as “viewed the pricing page in the last 14 days AND is on a paid plan AND NOT opened a support ticket in the last 7 days.”

An example audience with several rule groups added and configured, combined with AND/OR/XOR. — An example of a more complex audience: several rule groups added and combined with AND / OR / XOR, with include/exclude per condition. Your own campaign will contain whatever groups you choose. Click to enlarge.

Many rules also carry a scope: “on the current page” checks the page the visitor is on right now, while “anywhere in this session” checks everything they’ve done this visit.

A page/session targeting rule with its scope selector and related rules. — Page & session rules use a scope selector — “On current page” vs. “Anywhere in this session.” The first checks only the page they’re on now; the second checks their whole visit. Click to enlarge.

Visitor context & attributes

Who and where the visitor is, right now:

Pages Visited — match on the full URL, a path, or a query parameter, scoped to the current page or the whole session. Example: on any /pricing URL this session.
Number of Page Views — how many pages the visitor has seen this session. Example: viewed 5+ pages.
Most-popular Page — the page (or page type) a visitor spends the most time on or returns to most. Example: frequent visitors of a specific product category.
Countries / Cities — geo-location down to city level from the visitor’s IP. Example: visitors in Canada.
User / CRM / ABM data — known-visitor profile fields synced from your CRM or CDP: lifecycle stage, plan tier, lifetime value, industry, custom fields. Example: lifecycle stage = SQL.
Device & System — device type, operating system, browser, screen size, and browser language. Example: mobile visitors with a small screen, or visitors whose browser language is French.
Visitor Type — new vs. returning, plus session count. Example: returning visitors on their 3rd+ session.
User Lists — match against a spreadsheet/CSV of users you upload. Example: a list of trial accounts.
Date & Time — a date range, day of week, or hour of day. Example: only during a weekend sale.
IP Addresses — specific IPs or CIDR ranges. Example: exclude your office IP from a promo.
Weather — the visitor’s local conditions by IP or GPS. Example: show umbrellas when it’s raining.

Behavior & engagement

What the visitor has actually done, this session or over time:

E-commerce — products viewed, added to cart, or purchased, with finer filters for cart value, number of products purchased, total purchased value, and filters by brand or price range. Example: cart value over $100 containing a specific brand.
Product Interactions — counts across products (distinct, same, or total). Example: viewed 3+ different products.
Last Product Interaction — the most recent shown / cart / purchase event, for “pick up where you left off.” Example: last added a specific SKU to cart.
Content Interaction — article views, favorites, subscriptions, and reading depth. You can also target by the content’s attributes — author, tags, category, or topic — pulled from your content feed. Example: read 2+ articles tagged “pricing.”
Session Attributes — cookies, JavaScript variables, form/input values, meta tags, DOM values, and your Google Tag Manager data layer — any client-side data you expose. Example: a dataLayer value your site pushes.
Time on Site — total time in the current session. Example: engaged for 2+ minutes.
Landing Page — the first (entry) page of the session. Example: entered on a campaign landing page.
Traffic Source — referrer, search engine, social network, or campaign. Example: arrived from a paid ad (UTM).
Search Keywords — the terms a visitor searched to arrive, or searched in your on-site search. Example: searched for “noise-cancelling headphones.”
Interests — topics Personyze infers from browsing behavior via AI topic tagging, each with a strength score, plus any explicit interests. Example: strong interest in “running shoes.”

Integrations

Signals pulled live from connected tools. Known-visitor data flows in through integrations with HubSpot, Salesforce, Pardot, Zoho, Tealium, Segment, and Zeotap; for anonymous B2B visitors, ABM and intent providers — such as 6sense, Clearbit, Leadfeeder, ZoomInfo, and Albacross — can infer company name, firmographics, and buying intent, so you can target by account before anyone fills out a form.

Build rules faster with the AI Targeting Assistant

If you already know the audience you want in plain English, describe it to the AI Targeting Assistant and it generates a matching rule set. You review, edit, and refine before saving — it’s a starting point, not a black box.

The AI Targeting Assistant generating rules from a plain-English description. — Describe an audience in plain English and the assistant builds the matching rule groups for you to review and adjust. Click to enlarge.

For example, typing “returning US visitors who viewed the pricing page but didn’t sign up in the last 30 days” produces a rule set like: Visitor Type is returning AND Countries is United States AND Pages Visited contains /pricing (this session) AND NOT a sign-up event in the last 30 days — each as an editable rule group.

The assistant has two modes: Append adds the generated rules to whatever you already have, while Replace swaps in a fresh rule set. Use Append to layer on an extra condition, Replace to start over from a description.

Preview the audience with the live forecast

As you edit rules, the audience forecast updates continuously, showing how much of a rolling sample of your recent traffic would match versus would not match. The counters are only the summary — the real value is opening the forecast to see the actual visitors behind the numbers.

Expand it and you get two lists: the visitors who would match your current rules and the ones who wouldn’t. Click into any visitor to see their attributes and exactly which conditions they pass or fail — so a surprising count (too high, too low, or zero) is quick to diagnose. The forecast also has a live-traffic mode that evaluates your rules against visitors arriving in real time, a final sanity check before you publish.

Audience persistence & frequency cap

Audience persistence controls how long a visitor stays in the audience after they first match. Options range from “just this page view” (re-evaluate on every page), to “this session,” to “for N hours,” to “for N sessions,” to “permanently once matched.”

Audience persistence options controlling how long a matched visitor stays in the audience. — Audience persistence — how long a matched visitor stays in the audience: every page, once per session, for N hours or sessions, or permanently. Click to enlarge.

For most acquisition campaigns, per-session persistence is right — the visitor is re-evaluated fresh each visit.
For retention or loyalty campaigns, permanent membership often makes sense so the experience follows the visitor across future sessions.

A frequency cap sits alongside persistence and limits how often the campaign shows — for example, at most three times per session, or once per visitor per day — so a matched visitor isn’t shown the same popup on every page.

Resolving overlaps between campaigns

When several campaigns can match the same visitor, Personyze doesn’t silently stack them. Add the overlapping audiences to a shared audience group and give each a priority; the group’s conflict-resolution rule then decides which one wins, so a shared visitor sees only the intended experience.

Real-world targeting examples

Most useful audiences combine a few rules. Here are common patterns and the rules behind them:

E-commerce & retail

Mobile shoppers on category pages — a sticky app-download bar only where it belongs. Device & System = mobile AND Pages Visited path contains /category.
Cart abandoners with a high-value cart — an exit-intent discount worth showing. E-commerce = added to cart, not purchased AND Cart value > $150.
Repeat buyers of one brand — cross-sell within that brand. E-commerce = purchased AND Filter by brand = Acme AND Number of products purchased ≥ 2.
Browsers who never bought — a first-order incentive. Product Interactions = viewed 3+ products AND NOT any purchase this session.
Price-sensitive shoppers — lead with deals. Filter by price range = under $50 OR Search Keywords contains “cheap” / “discount”.

B2B & SaaS

High-intent trial users on pricing — a “talk to sales” prompt. User / CRM data lifecycle = Trial AND Pages Visited = /pricing this session AND Visitor Type = returning.
Named accounts, still anonymous — an ABM banner before they ever fill a form. Integrations (6sense / Clearbit) company = target-account list.
Enterprise-sized visitors — route to the enterprise plan. User / CRM data company size > 500 OR lifetime value > $10k.
Engaged blog readers — a newsletter or demo CTA. Content Interaction = read 2+ posts AND Time on Site > 2 min.

Geo, timing & context

Weekend sale, one country — Date & Time = Sat–Sun AND Countries = Canada.
Rainy-day promo — Weather = raining AND Pages Visited = outerwear category.
Paid-traffic landing experience — match the ad’s message. Traffic Source = paid (UTM) AND Landing Page = the campaign page.
New vs. returning welcome — a first-time intro vs. a “welcome back.” Visitor Type = new for one campaign, returning for the other (use an audience group so they don’t collide).

Exclusions & QA

Exclude your own team — keep internal traffic out of stats. NOT IP Addresses = office range.
Exclude existing customers from an acquisition offer — NOT User Lists = current-customers CSV.
Desktop-only rich experience — a layout that needs the space. Device & System = desktop AND Screen size ≥ large.

Tips for accurate targeting

Start broad, then narrow. Add one rule, watch the audience forecast, then tighten — it’s easier than debugging a huge rule set at once.
Use the scope selector deliberately. “Current page” and “this session” answer different questions; mixing them up is the most common targeting mistake.
Verify with real visitors. The forecast and the QA Simulator let you confirm you’re catching the right people, not just the right number.

Targeting and Personalization — the full campaign lifecycle.
Resolve Audience Overlaps and Conflicts — when campaigns share visitors.
Page Groups — reusable groupings of URLs for rules.
Personyze QA Simulator — test targeting before launch.