# What are behavioral scores? ### About this export | Field | Value | | --- | --- | | **content_type** | lesson | | **platform** | contentstack-academy | | **source_url** | https://www.contentstack.com/academy/courses/data-insights-core-concepts-capabilities/data-insights-course-2--what-are-behavioral-scores | | **course_slug** | data-insights-core-concepts-capabilities | | **lesson_slug** | data-insights-course-2--what-are-behavioral-scores | | **markdown_file_url** | /academy/md/courses/data-insights-core-concepts-capabilities/data-insights-course-2--what-are-behavioral-scores.md | | **generated_at** | 2026-05-04T05:36:51.607Z | > Part of **[Core Concepts & Capabilities](https://www.contentstack.com/academy/courses/data-insights-core-concepts-capabilities)** on Contentstack Academy. **Academy MD v3** — structured for retrieval; no quiz or assessment keys. #### Video details #### At a glance - **Title:** data-insights__core_concepts__behavioral-scores - **Duration:** 2m 40s - **Media link:** https://cdn.jwplayer.com/previews/8I7tQlvF - **Publish date (unix):** 1752797058 #### Streaming renditions - application/vnd.apple.mpegurl - audio/mp4 · AAC Audio · 113622 kbps - video/mp4 · 180p · 180p · 161033 kbps - video/mp4 · 270p · 270p · 192964 kbps - video/mp4 · 360p · 360p · 192398 kbps - video/mp4 · 406p · 406p · 206608 kbps - video/mp4 · 540p · 540p · 253002 kbps - video/mp4 · 720p · 720p · 331136 kbps - video/mp4 · 1080p · 1080p · 551882 kbps #### Timed text tracks (delivery) - **thumbnails:** `https://cdn.jwplayer.com/strips/8I7tQlvF-120.vtt` #### 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. #### Subtitles (WebVTT) ```webvtt WEBVTT 1 00:00:00.000 --> 00:00:21.040 Each time an event, such as a page view or button click, gets collected, a series of 2 00:00:21.040 --> 00:00:26.560 calculations take place. This processing pipeline is where we determine what user to associate 3 00:00:26.560 --> 00:00:32.440 an event with, how it impacts a common schema or custom schema, and most importantly, all 4 00:00:32.440 --> 00:00:36.440 of that user's individual intelligence-based attributes. 5 00:00:36.440 --> 00:00:41.620 Lytx automatically surfaces nine dynamic scores on every profile, unique to each individual 6 00:00:41.620 --> 00:00:47.040 and reflective of their cross-channel engagement. These scores are updated in real-time for 7 00:00:47.040 --> 00:00:53.920 each individual user. Here's how these scores work. 8 00:00:53.920 --> 00:00:58.480 Frequency measures a visitor's cumulative activity with your brand. The more active 9 00:00:58.480 --> 00:01:04.560 the user is, the higher the score is comparing each user to the rest. 10 00:01:04.560 --> 00:01:09.760 Frequency tracks how consistently a visitor interacts with your brand. More frequent engagement 11 00:01:09.760 --> 00:01:15.440 results in a higher score, benchmarking users against all others. 12 00:01:15.440 --> 00:01:20.800 Recency – this measure focuses on how recently the user has engaged. More recent activity 13 00:01:20.800 --> 00:01:27.320 leads to a higher score, comparing the user's present engagement to past engagement. 14 00:01:27.320 --> 00:01:32.800 Intensity assesses the depth of interaction. The more intense or sustained the engagement, 15 00:01:32.800 --> 00:01:37.200 the higher the score measuring depth relative to other users. 16 00:01:37.200 --> 00:01:41.960 Momentum tracks the rate of engagement. Users increasing their activity with your brand 17 00:01:41.960 --> 00:01:46.800 will have a higher score comparing their recent and past behaviors. 18 00:01:46.800 --> 00:01:51.800 Propensity predicts the likelihood of a user returning. Positive patterns of interaction 19 00:01:51.800 --> 00:01:56.760 lead to higher scores, measured relative to all users. 20 00:01:56.760 --> 00:02:01.400 Consistency measures the regularity of user engagement. Consistent behaviors, such as 21 00:02:01.400 --> 00:02:07.160 interacting every 7 or 30 days, lead to higher scores while inconsistent behavior reduces 22 00:02:07.160 --> 00:02:11.480 the score. Maturity – this measure reflects how long 23 00:02:11.480 --> 00:02:16.680 a user has been engaged with your brand. Long-term users have higher scores while users 24 00:02:16.680 --> 00:02:20.440 with significant engagement gaps will have lower scores. 25 00:02:20.440 --> 00:02:26.200 Volatility measures how stable or sporadic the user's engagement is. This score reflects 26 00:02:26.200 --> 00:02:30.600 the stability of interaction patterns, offering a more nuanced version of intensity. ``` ```transcript [00:00] Each time an event, such as a page view or button click, gets collected, a series of [00:21] calculations take place. This processing pipeline is where we determine what user to associate [00:26] an event with, how it impacts a common schema or custom schema, and most importantly, all [00:32] of that user's individual intelligence-based attributes. [00:36] Lytx automatically surfaces nine dynamic scores on every profile, unique to each individual [00:41] and reflective of their cross-channel engagement. These scores are updated in real-time for [00:47] each individual user. Here's how these scores work. [00:53] Frequency measures a visitor's cumulative activity with your brand. The more active [00:58] the user is, the higher the score is comparing each user to the rest. [01:04] Frequency tracks how consistently a visitor interacts with your brand. More frequent engagement [01:09] results in a higher score, benchmarking users against all others. [01:15] Recency – this measure focuses on how recently the user has engaged. More recent activity [01:20] leads to a higher score, comparing the user's present engagement to past engagement. [01:27] Intensity assesses the depth of interaction. The more intense or sustained the engagement, [01:32] the higher the score measuring depth relative to other users. [01:37] Momentum tracks the rate of engagement. Users increasing their activity with your brand [01:41] will have a higher score comparing their recent and past behaviors. [01:46] Propensity predicts the likelihood of a user returning. Positive patterns of interaction [01:51] lead to higher scores, measured relative to all users. [01:56] Consistency measures the regularity of user engagement. Consistent behaviors, such as [02:01] interacting every 7 or 30 days, lead to higher scores while inconsistent behavior reduces [02:07] the score. Maturity – this measure reflects how long [02:11] a user has been engaged with your brand. Long-term users have higher scores while users [02:16] with significant engagement gaps will have lower scores. [02:20] Volatility measures how stable or sporadic the user's engagement is. This score reflects [02:26] the stability of interaction patterns, offering a more nuanced version of intensity. ``` #### Key takeaways - Connect **What are 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. ## Supplement for indexing ### Content summary What are behavioral scores?. What are behavioral scores? in Core Concepts & Capabilities (data-insights-core-concepts-capabilities). ### Retrieval tags - What - are - behavioral - scores - data-insights-core-concepts-capabilities - lesson 04 - What are behavioral scores? - data-insights-core-concepts-capabilities lesson ### Indexing notes Index this lesson as a primary chunk tagged with lesson_id "04" and topics: [What, are, behavioral, scores]. Parent course slug: data-insights-core-concepts-capabilities. 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: What are behavioral scores? | `https://cdn.jwplayer.com/v2/media/8I7tQlvF/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/` |