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How do I make my chatbot aware of the page a user is on?

To build a page-aware chatbot, pass page URL/metadata from the browser (or data layer) into the widget, use your platform’s URL targeting rules, and enable Webpage Awareness plus optional custom context in CustomGPT.ai when you embed the agent. Scope: Last updated – November 2025. Applies globally; ensure page-aware chatbots respect existing site permissions and cookie/analytics consent under laws like GDPR and CCPA/CPRA when tracking URLs and user behavior.

Use the current page URL as chatbot context

Many chat widgets can accept extra parameters when you embed them. The simplest signal to send is the current page URL. That alone lets you change behavior or at least see where conversations started.

Reading the URL with JavaScript

In the browser you can read the active page with standard JavaScript:
const pageUrl = window.location.href;       // full URL const pagePath = window.location.pathname; // path, e.g. /pricing
You can also derive simple “page type” flags from the URL or path:
const isPricingPage = pagePath.includes(‘/pricing’); const isBlogPost = pagePath.startsWith(‘/blog/’);
These values can be passed into your chat widget snippet (or into your data layer/analytics tags) so both your bot and your reporting know which page started the conversation.

Passing the URL into your chatbot widget

Here’s a generic pattern you can adapt to most widgets:
  1. Grab the URL or path (window.location.href or window.location.pathname).
  2. Build a small config object, e.g. { pageUrl, pagePath }.
  3. When you initialize the widget, pass that object into its config or init function (often a global like window.chatConfig or a JS tag’s init call).
  4. In your bot platform, read that field as a custom attribute/parameter and:
    • Route to different flows, or
    • Insert it into the system prompt (“User is on: /pricing”).
  5. Store the URL in your analytics event for that chat session.
Most platforms don’t care what you call the field (for example page_url), as long as you pass it consistently.

Pass page IDs, categories, or custom attributes

Raw URLs can be messy (query strings, tracking parameters, language codes). Often it’s more stable to pass a normalized value like a page ID or category.

Using data attributes and global variables

A simple pattern is to encode page info in HTML:
<body data–page-id=“product-123” data–page-category=“product”>
Then in JavaScript:
const body = document.body; const pageId = body.dataset.pageId; const pageCategory = body.dataset.pageCategory;
You can forward these values when you bootstrap the chat widget. This lets your bot logic branch on things like:
  • pageCategory === ‘pricing’
  • pageId === ‘product-123’
Because the values come from your CMS or template, they don’t break when you adjust the URL structure.

Using Google Tag Manager or a data layer

For more complex sites, it’s cleaner to use a data layer and Google Tag Manager (GTM):
  1. Declare a dataLayer object on each page and push page info into it (ID, category, content type).
  2. In GTM, create Data Layer Variables for pageCategory, pageId, etc.
  3. Use those variables in tags that initialize your chat widget (or in custom HTML tags that call its API).
  4. Optionally, also send them to analytics tools (e.g. GA4) as event parameters.
Using the data layer keeps your chat integration in sync with your broader tracking strategy.

Configure page-based behavior in chatbot platforms

Most modern chat platforms let you change where and how the bot appears based on URL rules.

Page targeting and display rules

In tools like HubSpot, you can define targeting rules so a chatflow only shows specific URLs or URL patterns. Typical options include:
  • “Website URL is /pricing”
  • “Website URL contains /blog/”
  • “Website URL matches a regex pattern”
This means you can:
  1. Show bot A on all pages.
  2. Show bot B only on /pricing or /demo.
  3. Prioritize certain chatflows when multiple rules match the same page.
Even without extra context parameters, this gives you basic page awareness at the visibility level.

Page-specific greetings and playbooks

Once you have URL-based targeting, you can tailor:
  • Opening greetings (“Need help choosing a plan?” on /pricing).
  • Playbooks or flows (e.g., a “book a demo” flow only on product or comparison pages).
  • Embedded knowledge (“FAQ: refunds” on post-purchase pages).
Most platforms let you configure separate greetings and starting questions per chatflow. Because each chatflow is attached to one or more URLs, the bot effectively “knows” what kind of page it’s on, even if you aren’t passing extra metadata.

How to do it with CustomGPT.ai

With CustomGPT.ai you get two key tools for page awareness:
  1. Webpage Awareness – automatically summarizes the page the agent is embedded on and feeds that into the agent.
  2. Custom Context – lets you pass extra text parameters with each embed or call, like page type or user segment.
Together, they let your agent understand where it is and what else it should know.

Enable Webpage Awareness for your agent

To make a CustomGPT.ai agent aware of the page it’s on:
  1. In the CustomGPT.ai dashboard, open your agent.
  2. Click the three-dot (⋮) menu and choose Actions.
  3. Find Webpage Awareness in the list of agentic actions.
  4. Toggle it On.
  5. Deploy the agent on your site using the standard embed or live chat snippet.
  6. When users chat, CustomGPT.ai:
    • Fetches and summarizes roughly the first chunk of page content,
    • Stores that page summary, and
    • Inject it into the agent’s system prompt so it can reference that page directly.
You can then optionally use features like context-rich starter questions, which auto-generate prompts based on the current page content.

Pass extra page context with Custom Context

Sometimes page content alone isn’t enough. For example, you may want the agent to know:
  • “This is a product page for SKU-123 in the ‘Enterprise’ plan.”
  • “This page is part of the onboarding flow.”
Use Custom Context to pass extra text parameters to the agent at deployment time:
  1. Open your agent and go to the deployment settings (embed/live chat).
  2. In the embed configuration, add a custom_context field with a short description, like:
“custom_context”: “Page type: pricing. Audience: prospects evaluating Enterprise plan.”
  1. If you deploy on multiple templates, have each template output a tailored custom_context string.
  2. For API-based or advanced integrations, include the same field when you call the CustomGPT.ai API.
Custom Context is merged with Webpage Awareness, giving your agent both page content and structured hints about how to respond.

Track page-aware conversations in analytics

Once your bot is page-aware, you’ll probably want to see which pages drive the most engagement and what users ask on each one.

Sending page info into chat events

There are two main streams of analytics:
  1. Platform-native analytics
    • With Webpage Awareness, CustomGPT.ai tracks which pages are summarized and how often page context is used across queries.
  2. External analytics (e.g., GA4)
    • Use your data layer or widget events to send:
      • page_path or pageCategory
      • chat_open, chat_message_sent, chat_conversation_resolved
    • Guides from chat vendors and analytics practitioners show how to push chat events into GA4 using GTM.
In both cases, the key is to include page identifiers in the event payload.

Reporting on pages that drive conversations

Once events contain page data, you can:
  • Build reports showing which URLs generate the most chats.
  • Compare conversion rates with and without chat on certain pages.
  • Cluster common questions by page type (e.g., “shipping questions on /checkout”).
In GA4 or other BI tools, you’d typically break down chat events by page_path, pageCategory, or your own ID, then drill into the conversation summaries from CustomGPT.ai for deeper qualitative insights.

Example — Product page support chatbot

Imagine you run a SaaS product with /features, /pricing, and individual /product/* pages. You embed a CustomGPT.ai agent as a floating live chat. For this deployment:
  • Webpage Awareness is turned on, so the agent automatically reads and summarizes whichever product page it’s on.
  • Each template also passes a custom_context string like: “This page describes Product X. Priority: highlight key benefits, integrations, and pricing FAQs.”
On a product page:
  • The greeting becomes: “Have questions about Product X or choosing a plan?”
  • If the user asks “Does this integrate with Slack?”, the agent answers using that product’s docs, not a generic answer.
  • In analytics, you can see that /product-x generates more “ready-to-buy” conversations than /product-y, and tweak your content accordingly.

Conclusion

Generic chatbots often frustrate users by forcing them to explain context that should be obvious from the page they are viewing. CustomGPT.ai solves this disconnect with native Webpage Awareness and Custom Context features that instantly ground your agent in the user’s current environment. Instead of complex JavaScript routing or manual rule sets, you get a system that automatically adapts its answers and behavior to the specific content of any page. Deliver smarter, context-aware support without the development headache. Activate Webpage Awareness for your agent and start driving more relevant conversations today.

FAQs

How can I make my chatbot aware of which page a user is on?

You make a chatbot page-aware by passing the current page URL or metadata from the browser into the chat widget when it initializes. That URL or a normalized page ID can then be used in your bot platform to tailor greetings, flows, and routing logic—for example, showing different playbooks on /pricing versus /blog pages and logging which page each conversation started from.

How does CustomGPT.ai use Webpage Awareness and custom context for page-aware chatbots?

CustomGPT.ai’s Webpage Awareness action automatically fetches and summarizes the page where the agent is embedded and injects that summary into the prompt. You can also pass a custom_context string—such as page type or audience—alongside the embed or API call, so the agent combines live page content with structured hints to give responses tailored to each template or section of your site.

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