# Demonstration: Real-time Profiles ### About this export | Field | Value | | --- | --- | | **content_type** | lesson | | **platform** | contentstack-academy | | **source_url** | https://www.contentstack.com/academy/courses/getting-started-with-data-insights/data-insights-course-1--demonstration-real-time-profiles | | **course_slug** | getting-started-with-data-insights | | **lesson_slug** | data-insights-course-1--demonstration-real-time-profiles | | **markdown_file_url** | /academy/md/courses/getting-started-with-data-insights/data-insights-course-1--demonstration-real-time-profiles.md | | **generated_at** | 2026-05-22T14:37:28.616Z | > Part of **[Getting Started with Data and Insights](https://www.contentstack.com/academy/courses/getting-started-with-data-insights)** on Contentstack Academy. **Academy MD v3** — structured for retrieval; no quiz or assessment keys. #### Video details #### At a glance - **Title:** 3-data-insights-demo-real-time-profiles - **Duration:** 8m 29s - **Media link:** https://cdn.jwplayer.com/previews/ZgOtsMdH - **Publish date (unix):** 1752807640 #### Streaming renditions - application/vnd.apple.mpegurl - audio/mp4 · AAC Audio · 113589 kbps - video/mp4 · 180p · 180p · 140595 kbps - video/mp4 · 270p · 270p · 159797 kbps - video/mp4 · 360p · 360p · 177409 kbps - video/mp4 · 406p · 406p · 190323 kbps - video/mp4 · 540p · 540p · 228708 kbps - video/mp4 · 720p · 720p · 288340 kbps - video/mp4 · 1080p · 1080p · 464689 kbps #### Timed text tracks (delivery) - **thumbnails:** `https://cdn.jwplayer.com/strips/ZgOtsMdH-120.vtt` #### Video transcript So first and foremost, if we just jump into an account, I guess maybe a quick overview of just the structure at a super high level. On the left hand side, you'll have the nav. Like I mentioned, the navigation is structured in the same way that we structured these sessions and that there's one all about data pipeline. This is how you get data analytics. And then there's a section for building profiles, which is all of your schema management, your identity controls, which we'll go through in great detail. Using profiles is then all of your modeling, your reporting, your experiences, which is our own personalization, web personalization tool. And then content has its own section for classification and customization and recommendations and all the stuff that you can do there. But to get started, first and foremost, it's super easy. You can either hit install from the dashboard or you can go over here to the different SDKs. But the easiest way to kind of just understand how to install Linux is to go to the JavaScript snippet. So for anybody that's installed Google Analytics or Google Tag Manager or any other sort of client side software, it's as simple as just copying and pasting this JavaScript snippet into the site. So you can do that in Google Tag Manager. You can drop it natively into the header, which is going to have an integration, already has an integration where you can just toggle it on and install it. So there's lots of ways to get started. But the more important thing to understand is what the tag does. So one in this initialization payload, and we can share some documentation on the different options and we can come back to all the different ways that you can configure it. But one important thing to know is that in this init call, there's a lot of different options of things that you can turn on. So in our demo that we walked through, it'll show like how to push data to Google Analytics as an example, which is a client side integration and a server side integration, or Google DFP, which is their ad manager platform. It's a client side and a server side integration. So there's lots of things that you can actually toggle on and off in this init call. The net result when you install the Lytx tag is kind of twofold. So on one hand, it gives you the mechanism to collect the data from the web. So I can just, and we'll go through and kind of show an example of this. You can fire events just like any other sort of analytics platform to collect page view data, to collect custom events, to collect any information really that you want that you want to fire from JavaScript. So the collection mechanism is part of it. And then on the other hand, it's also the personalization mechanism. So to kind of showcase that, if I go to one of our sandbox sites, just petsy.lytx.com, this will also work on any site that Lytx is installed on. So I know there's like Red Panda is out there. I'm not sure what the kind of current URL is that the ContentCon demo folks are using, but we have this Chrome extension that you can find in the Chrome store. It's just called Lytx DevTools that makes it super easy to see the profile. I'll show you also how to pull all this information from the console that our tag is surfacing. But in the case of this Petsy site, if I just turn the Chrome extension on, our tag is already installed. So what it's going to do, but at the bottom of this Chrome extension, you can, once you turn it on and pin to the URL, you can click the Profile tab, and this is going to actually show you a real-time view of this particular user's profile. So if I were to open, for instance, an incognito window and go to Petsy.com, so this is the first time that this user's ever visited this page in this context. There's no cookie, there's no session, and pull up my profile. There's not going to be a lot of information, right? Like we haven't calculated interest yet because the user hasn't browsed the site. We have some super basic scores based on one single page view. But as I browse the site, the scores are going to be calculated in real time. So we're collecting a page view event. That data is being sent to Lytx for every single event that gets processed. We actually update the scores, update the interest scores. As I continue to click around, you'll see those scores adjust. So you'll see as I browse, like this particular user has some basic topics. So I'm interested in dogs, I'm interested in dog fashion. As I browse around, you'll actually see those interest scores adjust. There's no smoke and mirrors here. What Lytx is doing is we're collecting information about the page view. We'll talk a lot about content and what it does, but at a high level we actually go out, we scrape the content, we classify it to understand the topics that that particular URL is about. And then because we know what pages that a user is visiting and what that URL in particular represents, we can associate those in the form of interest scores for a particular user. This is one of the aspects that we'll cover in the kind of deeper dive on the Lytx plus content stack story that is super unique and interesting. And that with content stack, obviously as a CMS, we have much greater access to the content and the topics and whatnot. And then really the magic that's happening if you click on the person or if you click on the details tab, it shows the full profile that's being returned. So just by installing the tag, by doing nothing else, Lytx is already going to start to build these very high value profiles that have a series of scores that will cover how these are getting calculated and what they represent, a number of interest scores, which should be in here. I think so a question just came in the chat I think is worthy of actually speaking out loud, which is, are the interests dynamically depending on the page or the site or are they predetermined? Yeah. So the interests are calculated. So interests are made up of topics and scores. The topics are related to the pages in aggregate. So if you have a hundred pages on your website, we'll actually go out and scrape every single one of those and classify all of those to generate a bank of topics. So your corpus of topics across your domain. And then for a particular user, when I visit a page, there might be three or 15 topics associated with that page. That topic sort of existence will impact my individual score. So when I browse the site and you can, it's probably a little bit small on the big screen. I don't think I can make it bigger either. You can see here, these are my initial interest scores. So obviously it's a sandbox site. So the topics are pretty limited to not very useful necessarily, but there's a score from zero to one that represents my particular level of interest in that topic based on my global activity across your domain. So we don't share any information across different accounts. So it's like, if it's, they don't get visibility into the interest scores, like it's all sandboxed to a particular Linux instance. But it is global across all of the pages in aggregate, if that makes sense. Does that answer the question? Hopefully. Yeah, I think so. I think one thing that an analogy I like to give is like, for the topics and affinities is if you're a cashier and you see someone come in with a basket of candles and balloons and cake mix, you probably can use those as to extract that they're probably going to throw a birthday party. So that's like the topics are the things in the basket. You bring those together and you can put together what their interests are, which in this case would be a birthday party. Yep. Yeah. And we'll definitely in one of the follow-up sessions, we'll spend a lot more time on content and talk about interest engines and configuration and how the scores actually work. This is just to introduce the idea that based on any channel, and this one in particular, it's web, we're building in real time, these very, very robust profiles that contain all of this contextual information that can power experiences, that can power agents and AI, that can power kind of anything that you want to do. Yeah. #### Key takeaways - Connect **Demonstration: Real-time Profiles** back to your stack configuration before moving to the next module. - Capture one concrete artifact (screenshot, Postman call, or code snippet) that proves the step works in your environment. - Re-read the delivery versus management boundary for anything you changed in the entry model. ## Supplement for indexing ### Content summary Demonstration: Real-time Profiles. Demonstration: Real-time Profiles in Getting Started with Data and Insights (getting-started-with-data-insights). ### Retrieval tags - Demonstration - Real - time - Profiles - getting-started-with-data-insights - lesson 03 - Demonstration: Real-time Profiles - getting-started-with-data-insights lesson ### Indexing notes Index this lesson as a primary chunk tagged with lesson_id "03" and topics: [Demonstration, Real, time, Profiles]. Parent course slug: getting-started-with-data-insights. Use asset_references URLs as thumbnail hints in search results when present. Never surface LMS quiz content or assessment answers from this file. ### Asset references | Label | URL | | --- | --- | | Video thumbnail: Demonstration: Real-time Profiles | `https://cdn.jwplayer.com/v2/media/ZgOtsMdH/poster.jpg?width=720` | ### External links | Label | URL | | --- | --- | | Contentstack Academy home | `https://www.contentstack.com/academy/` | | Training instance setup | `https://www.contentstack.com/academy/training-instance` | | Academy playground (GitHub) | `https://github.com/contentstack/contentstack-academy-playground` | | Contentstack documentation | `https://www.contentstack.com/docs/` |