# Lytics 101 ### About this export | Field | Value | | --- | --- | | **content_type** | course | | **platform** | contentstack-academy | | **source_url** | https://www.contentstack.com/academy/courses/lytics-101 | | **language** | en | | **product_area** | Contentstack Academy | | **learning_path** | standalone | | **course_id** | lytics-101 | | **slug** | lytics-101 | | **version** | 2026-03-01 | | **last_updated** | 2026-05-08 | | **status** | published | | **keywords** | ["Contentstack Academy"] | | **summary_one_line** | Welcome to Lytics 101! This course is your starting point for mastering the fundamentals of customer data and profiles in Lytics. We’ll explore how to build rich, real-time profiles, uncover actionable insights, and leve… | | **total_duration_minutes** | 16 | | **lessons_count** | 7 | | **video_lessons_count** | 7 | | **text_lessons_count** | 0 | | **linked_learning_path** | standalone | | **linked_assessment_ref** | LMS_UNCONFIGURED_COURSE_ASSESSMENT | | **markdown_file_url** | /academy/md/courses/lytics-101.md | | **generated_at** | 2026-05-08T12:23:55.612Z | | **intended_audience** | [] | | **prerequisites** | [] | | **related_courses** | [] | > **Academy MD v3** — companion `.md` for Ask AI. Quizzes and graded assessments are **LMS-only**; this file never contains answer keys. ## Course Overview | Metadata | Value | | --- | --- | | Catalog duration | 15m 40s | | Released (if known) | 2026-03-01 | | Product area | Contentstack Academy | ### Description Welcome to Lytics 101! This course is your starting point for mastering the fundamentals of customer data and profiles in Lytics. We’ll explore how to build rich, real-time profiles, uncover actionable insights, and leverage powerful tools like behavioral scores, interest signals, and dynamic audiences. By the end of this course, you’ll have the foundation needed to personalize engagement and make data-driven decisions with confidence. Let’s get started! ### Learning objectives 1. Follow each lesson in order. 2. Practice in a training stack using placeholders **YOUR_STACK_API_KEY** and **YOUR_DELIVERY_TOKEN** in local `.env` files only. 3. Validate API responses against the official documentation. ### Topics covered Contentstack Academy ## Course structure ```text lytics-101/ ├── 01-the-profile · video · 85s ├── 02-common-schema · video · 137s ├── 03-scoring-intro · video · 117s ├── 04-behavioral-scores · video · 160s ├── 05-interest-scores · video · 113s ├── 06-audience-membership · video · 190s ├── 07-custom-modeling · video · 138s ``` ## Lessons ### Lesson 01 — The Profile #### Video details #### At a glance - **Title:** Lytics 101 01 The Profile - **Duration:** 1m 25s - **Media link:** https://cdn.jwplayer.com/previews/nMhJ5ymm - **Publish date (unix):** 1741199457 #### Streaming renditions - application/vnd.apple.mpegurl - audio/mp4 · AAC Audio · 114457 kbps - video/mp4 · 180p · 180p · 177889 kbps - video/mp4 · 270p · 270p · 228512 kbps - video/mp4 · 360p · 360p · 244067 kbps - video/mp4 · 406p · 406p · 271481 kbps - video/mp4 · 540p · 540p · 369040 kbps - video/mp4 · 720p · 720p · 509353 kbps - video/mp4 · 1080p · 1080p · 822065 kbps #### Timed text tracks (delivery) - **thumbnails:** `https://cdn.jwplayer.com/strips/nMhJ5ymm-120.vtt` #### Video transcript At the heart of Lytx is the customer profile. We help brands like yours build the most comprehensive custom data asset possible right out of the box. Because this occurs in real time, you never run the risk of missing the key engagement opportunity, even when the window for that engagement is small. This of course is often the case with anonymous site traffic. The real magic rests with our proprietary identity graph, allowing individual interactions across any number of channels to be associated with a single consumer and how we can effectively associate an individual's interactions from different channels such as clicking an email and making a purchase. This, along with our common schema, integrations, proprietary enrichments and profile management toolkit called Schema Studio result in tremendous opportunity with unbelievably low lift right out of the box. Over the next several videos, we'll examine every aspect of the Lytx profile, ensuring you have the knowledge and expertise necessary to maximize the impact. #### Key takeaways - Connect **The Profile** 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. ### Lesson 02 — Common Schema #### Video details #### At a glance - **Title:** Lytics 101 02 Common Schema - **Duration:** 2m 17s - **Media link:** https://cdn.jwplayer.com/previews/GA9O7eHQ - **Publish date (unix):** 1741199475 #### Streaming renditions - application/vnd.apple.mpegurl - audio/mp4 · AAC Audio · 114288 kbps - video/mp4 · 180p · 180p · 197313 kbps - video/mp4 · 270p · 270p · 259822 kbps - video/mp4 · 360p · 360p · 243985 kbps - video/mp4 · 406p · 406p · 269823 kbps - video/mp4 · 540p · 540p · 351553 kbps - video/mp4 · 720p · 720p · 488099 kbps - video/mp4 · 1080p · 1080p · 920937 kbps #### Timed text tracks (delivery) - **thumbnails:** `https://cdn.jwplayer.com/strips/GA9O7eHQ-120.vtt` #### Video transcript The Lytx Schema Studio represents a set of tools and automated intelligence to aid the curation and enrichment of your customer profiles effortlessly. It starts with our robust common schema, allowing you to quickly implement high-value use cases in just minutes. The predefined customer attributes streamline data mapping, letting you focus on results while fully supporting custom solutions as your needs evolve. Our common schema focuses on the following key categories. Identity. Predefined identifiers have been hand-curated to seamlessly aggregate data across all key engagement channels, ensuring native support and minimal maintenance. Associating a customer's email and web activity into a unified profile has never been easier. Consent and governance. Understanding and enforcing customer consent continues to be a critical investment. Lytx provides a means to gather consent preferences with little lift, also enabling adherence to those preferences through our automated segmentation and downstream syncs capabilities. Demographic and geographic. Of course, there is a dedicated home for general customer information such as name, address and location, along with customizable attributes to maintain first-party data such as account type or status. Activity. Build and maintain a comprehensive catalogue of user activity across channels, devices and campaigns. In addition, we'll automatically generate summary attributes, allowing you to easily access insights such as the first UTN collected or the last page visited. Intelligence. Lytx provides valuable out-of-the-box signals and insights related to customer interests and behaviours. These intelligence-based attributes are among the most powerful and actionable features of the platform. In the next video, we'll explore each of these attributes in more detail. Thank you for watching. For more information, visit us at www.lytx.com. #### Key takeaways - Connect **Common Schema** 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. ### Lesson 03 — Scoring Intro #### Video details #### At a glance - **Title:** Lytics 101 03 Scoring Intro - **Duration:** 1m 57s - **Media link:** https://cdn.jwplayer.com/previews/yZLfIbvJ - **Publish date (unix):** 1741199323 #### Streaming renditions - application/vnd.apple.mpegurl - audio/mp4 · AAC Audio · 114294 kbps - video/mp4 · 180p · 180p · 239764 kbps - video/mp4 · 270p · 270p · 338455 kbps - video/mp4 · 360p · 360p · 347606 kbps - video/mp4 · 406p · 406p · 391335 kbps - video/mp4 · 540p · 540p · 522846 kbps - video/mp4 · 720p · 720p · 728343 kbps - video/mp4 · 1080p · 1080p · 1323233 kbps #### Timed text tracks (delivery) - **thumbnails:** `https://cdn.jwplayer.com/strips/yZLfIbvJ-120.vtt` #### Video transcript Understanding behavioral and interest patterns has always been challenging, especially when faced with the complexity of raw data. For marketers, applying one-size-fits-all rules across channels simply doesn't cut it. The key is recognizing individual patterns. How do you know if someone consumes more or less content than usual? Consider return visitors. Instead of arbitrarily assigning significance to a specific number of page views, like five, how can you determine if they're engaging more or less than expected? Will they return, and when? These are the essential signals marketers need to engage effectively and maximize their investments. This is where Lytx proprietary profile intelligence comes into play. Each time an event, such as a page view or button click, is collected, a series of calculations occur. In this processing pipeline, we determine what profile to associate the event with, how it impacts the profile definition itself, and what actions should be triggered, such as a sync to your ad campaign audience. Most importantly, Lytx enriches each profile during that process with tangible signals that make activation a breeze. We call these our intelligence-based attributes. Within this category, you'll find our proprietary behavioral scores, interest scores, audience membership, predictive attributes, and custom model-based attributes. In the following modules, we'll cover the basics of each of our intelligence-based attributes and introduce some examples of how brands like yours are completely revolutionizing their marketing approach. #### Key takeaways - Connect **Scoring Intro** 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. ### Lesson 04 — Behavioral Scores #### Video details #### At a glance - **Title:** Lytics 101 04 Behavioral Scores - **Duration:** 2m 40s - **Media link:** https://cdn.jwplayer.com/previews/UQiop4I5 - **Publish date (unix):** 1741199436 #### Streaming renditions - application/vnd.apple.mpegurl - audio/mp4 · AAC Audio · 113622 kbps - video/mp4 · 180p · 180p · 161044 kbps - video/mp4 · 270p · 270p · 192898 kbps - video/mp4 · 360p · 360p · 192100 kbps - video/mp4 · 406p · 406p · 206567 kbps - video/mp4 · 540p · 540p · 253011 kbps - video/mp4 · 720p · 720p · 330596 kbps - video/mp4 · 1080p · 1080p · 552444 kbps #### Timed text tracks (delivery) - **thumbnails:** `https://cdn.jwplayer.com/strips/UQiop4I5-120.vtt` #### Video transcript Each time an event, such as a page view or button click, gets collected, a series of calculations take place. This processing pipeline is where we determine what user to associate an event with, how it impacts a common schema or custom schema, and most importantly, all of that user's individual intelligence-based attributes. Lytx automatically surfaces nine dynamic scores on every profile, unique to each individual and reflective of their cross-channel engagement. These scores are updated in real-time for each individual user. Here's how these scores work. Frequency measures a visitor's cumulative activity with your brand. The more active the user is, the higher the score is comparing each user to the rest. Frequency tracks how consistently a visitor interacts with your brand. More frequent engagement results in a higher score, benchmarking users against all others. Recency – this measure focuses on how recently the user has engaged. More recent activity leads to a higher score, comparing the user's present engagement to past engagement. Intensity assesses the depth of interaction. The more intense or sustained the engagement, the higher the score measuring depth relative to other users. Momentum tracks the rate of engagement. Users increasing their activity with your brand will have a higher score comparing their recent and past behaviors. Propensity predicts the likelihood of a user returning. Positive patterns of interaction lead to higher scores, measured relative to all users. Consistency measures the regularity of user engagement. Consistent behaviors, such as interacting every 7 or 30 days, lead to higher scores while inconsistent behavior reduces the score. Maturity – this measure reflects how long a user has been engaged with your brand. Long-term users have higher scores while users with significant engagement gaps will have lower scores. Volatility measures how stable or sporadic the user's engagement is. This score reflects the stability of interaction patterns, offering a more nuanced version of intensity. #### Key takeaways - Connect **Behavioral Scores** 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. ### Lesson 05 — Interest Scores #### Video details #### At a glance - **Title:** Lytics 101 05 Interest Scores - **Duration:** 1m 53s - **Media link:** https://cdn.jwplayer.com/previews/zlMVZoe4 - **Publish date (unix):** 1741199415 #### Streaming renditions - application/vnd.apple.mpegurl - audio/mp4 · AAC Audio · 113983 kbps - video/mp4 · 180p · 180p · 177279 kbps - video/mp4 · 270p · 270p · 224904 kbps - video/mp4 · 360p · 360p · 225735 kbps - video/mp4 · 406p · 406p · 248610 kbps - video/mp4 · 540p · 540p · 325791 kbps - video/mp4 · 720p · 720p · 441739 kbps - video/mp4 · 1080p · 1080p · 764287 kbps #### Timed text tracks (delivery) - **thumbnails:** `https://cdn.jwplayer.com/strips/zlMVZoe4-120.vtt` #### Video transcript If behavioral signals, as covered in the previous module, represent one side of the coin, understanding interest levels in content and products is the other. This is where Lytics interest scores come into play. The process begins automatically. Based on your account's configuration, Lytics' classification service proactively analyzes content and products across your site, using natural language processing and image analysis. As a result, we'll build a rich taxonomy for each piece of content, a set of topics that describe the content. Each topic within the taxonomy helps identify precisely what exactly is driving that customer's interest. As customers engage with your content, such as reading a product description, Lytics tracks their interactions and builds a set of scores representing their relative interest in the topics associated with that content. This means you'll gain immediate insights into what each customer is interested in and the extent of that interest, and those insights are represented by topic-level scores available on each customer profile. The best part – this process is fully automated. As customers interact with your site, their interest scores are continually updated to reflect their most recent behaviors, without any additional effort from you. These insights help drive content strategies, personalize ad creative for specific interest cohorts, and enhance engagement with intelligent content recommendations, delivering exactly what each user wants when they want it. www.microsoft.com www.microsoft.com #### Key takeaways - Connect **Interest Scores** 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. ### Lesson 06 — Audience Membership #### Video details #### At a glance - **Title:** Lytics 101 06 Audience Membership - **Duration:** 3m 10s - **Media link:** https://cdn.jwplayer.com/previews/ewEKIyEs - **Publish date (unix):** 1741199388 #### Streaming renditions - application/vnd.apple.mpegurl - audio/mp4 · AAC Audio · 113681 kbps - video/mp4 · 180p · 180p · 165635 kbps - video/mp4 · 270p · 270p · 202901 kbps - video/mp4 · 360p · 360p · 206386 kbps - video/mp4 · 406p · 406p · 224863 kbps - video/mp4 · 540p · 540p · 285927 kbps - video/mp4 · 720p · 720p · 380206 kbps - video/mp4 · 1080p · 1080p · 671725 kbps #### Timed text tracks (delivery) - **thumbnails:** `https://cdn.jwplayer.com/strips/ewEKIyEs-120.vtt` #### Video transcript Audiences within Lytx are unique. In many regards, you can think of a Lytx audience as more of a computed attribute, one that has customers entering and exiting in real time based on the defined set of rules. Much different than a traditional static marketing audience where the members do not change after the initial creation. This means that just like a behavioral score, audience membership becomes a key part of every single profile. The membership represents the audiences that that customer meets the criteria of at that very moment. For example, if a collected event contains a valid email address, that user will automatically exit the anonymous user's audience and enter the known user's audience. Later on, as we explore all of the aspects of building and using profiles in Lytx, we will dive much deeper into our powerful segmentation engine, learning how you can leverage membership triggers to sync data when a customer enters or exits a segment. For now, however, we want to cover the basics. How an audience can be built and ultimately how that will be surfaced on the profile to power personalization and decision making. It starts with our powerful segmentation engine. This rules builder allows you to create virtually any combination of rules, from specific attribute values to the level of interest in a specific topic, if they are currently a member of another audience, and more. As an example, maybe we want to easily know when a customer has a high momentum but a low frequency. This might signal that you have a short window of opportunity with a customer who is interested but is not likely to visit again. To build an audience we'll first access audiences from using profile section of the main navigation. Choose custom rule to leverage any of the available attributes. We'll search for score momentum and say the value should be above 50. Now, let's add another rule including anyone with a frequency score below 25. Last, we'll label and save our audience. Membership is calculated and updated in real time. As you can see, if we view a customer's profile that falls into this audience we'll see that membership directly as a native part of the profile, the same profile that can be synced and leveraged across your engagement tools and channels. #### Key takeaways - Connect **Audience Membership** 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. ### Lesson 07 — Custom Modeling #### Video details #### At a glance - **Title:** Lytics 101 07 Modeling - **Duration:** 2m 18s - **Media link:** https://cdn.jwplayer.com/previews/f6o8ZZX7 - **Publish date (unix):** 1741199365 #### Streaming renditions - application/vnd.apple.mpegurl - audio/mp4 · AAC Audio · 113956 kbps - video/mp4 · 180p · 180p · 181770 kbps - video/mp4 · 270p · 270p · 227805 kbps - video/mp4 · 360p · 360p · 225225 kbps - video/mp4 · 406p · 406p · 245455 kbps - video/mp4 · 540p · 540p · 311597 kbps - video/mp4 · 720p · 720p · 421627 kbps - video/mp4 · 1080p · 1080p · 737033 kbps #### Timed text tracks (delivery) - **thumbnails:** `https://cdn.jwplayer.com/strips/f6o8ZZX7-120.vtt` #### Video transcript As marketers, we know that data isn't always readily available. For example, using an account-based marketing tool like Sixth Sense gives us insights into only a small portion of our audience. And while we can be confident that the matched customers fit our ideal customer profile, what about the other 90% of visitors who aren't matched? Lytx makes it easy to leverage the data you do have to uncover customers who behave similarly. Building on our previous example, we can take the 10% of our audience we know and find customers who resemble the ideal profile from that group. We do this using Lytx Lookalike Modeling, a fully automated and highly configurable engine that surfaces the insights you need to engage your audience. To get started, navigate to Lookalike Models under the Using Profiles section in the main menu and choose Create New Model. From there, select the audience you want to analyze, in this case, customers without Sixth Sense data. Next, choose the audience you'd like to compare them to. Finally, Lytx will analyze all available data, including behavioral and interest signals, to determine how closely the customers in your source audience resemble those in your target audience. Next, we'll activate our model at the top of the screen. This will start the analysis process. Finally, we can choose to create a new audience using this model. It will take you directly to the audience builder with an initial definition in place. Customize it to your liking and sync the resulting audience. It's that easy. Under the hood, the result is a score between 0 and 1, 0 being a very low level of similarity, while 1 represents a high level of similarity. These scores exist independently on every user profile. #### Key takeaways - Connect **Custom Modeling** 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. ## Resources & references | Page | Companion Markdown | | --- | --- | | /courses/lytics-101/the-profile | /academy/md/courses/lytics-101/the-profile.md | | /courses/lytics-101/common-schema | /academy/md/courses/lytics-101/common-schema.md | | /courses/lytics-101/scoring-intro | /academy/md/courses/lytics-101/scoring-intro.md | | /courses/lytics-101/behavioral-scores | /academy/md/courses/lytics-101/behavioral-scores.md | | /courses/lytics-101/interest-scores | /academy/md/courses/lytics-101/interest-scores.md | | /courses/lytics-101/audience-membership | /academy/md/courses/lytics-101/audience-membership.md | | /courses/lytics-101/custom-modeling | /academy/md/courses/lytics-101/custom-modeling.md | ## Supplement for indexing ### Content summary Welcome to Lytics 101! This course is your starting point for mastering the fundamentals of customer data and profiles in Lytics. We’ll explore how to build rich, real-time profiles, uncover actionable insights, and leve… Welcome to Lytics 101! This course is your starting point for mastering the fundamentals of customer data and profiles in Lytics. We’ll explore how to build rich, real-time profiles, uncover actionable insights, and leverage powerful tools like behavioral scores, interest signals, and dynamic audiences. By the end of this course, you’ll have the foundation needed to personalize engagement and make data-driven decisions with confidence. Let’s get started! ### Retrieval tags - Contentstack Academy - lytics-101 - The - Profile - Common - Schema - Scoring - Intro - Behavioral - Scores - Interest - Audience - Membership - Custom ### Indexing notes Chunk at each "### Lesson NN — Title" heading; copy lesson_id and topics from the preceding HTML comment into chunk metadata for RAG filters. Course slug: lytics-101. Union of lesson topic tokens: The, Profile, Common, Schema, Scoring, Intro, Behavioral, Scores, Interest, Audience, Membership, Custom, Modeling. Do not embed or retrieve LMS-only quiz items or mastery exam answer keys from this export. ### Asset references | Label | URL | | --- | --- | | Video thumbnail: The Profile | `https://cdn.jwplayer.com/v2/media/nMhJ5ymm/poster.jpg?width=720` | | Video thumbnail: Common Schema | `https://cdn.jwplayer.com/v2/media/GA9O7eHQ/poster.jpg?width=720` | | Video thumbnail: Scoring Intro | `https://cdn.jwplayer.com/v2/media/yZLfIbvJ/poster.jpg?width=720` | | Video thumbnail: Behavioral Scores | `https://cdn.jwplayer.com/v2/media/UQiop4I5/poster.jpg?width=720` | | Video thumbnail: Interest Scores | `https://cdn.jwplayer.com/v2/media/zlMVZoe4/poster.jpg?width=720` | | Video thumbnail: Audience Membership | `https://cdn.jwplayer.com/v2/media/ewEKIyEs/poster.jpg?width=720` | | Video thumbnail: Custom Modeling | `https://cdn.jwplayer.com/v2/media/f6o8ZZX7/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/` |