# What are "triggers"? ### About this export | Field | Value | | --- | --- | | **content_type** | lesson | | **platform** | contentstack-academy | | **source_url** | https://www.contentstack.com/academy/courses/data-insights-data-ingestion-profile-construction/data-insights-course-3--what-are-triggers | | **course_slug** | data-insights-data-ingestion-profile-construction | | **lesson_slug** | data-insights-course-3--what-are-triggers | | **markdown_file_url** | /academy/md/courses/data-insights-data-ingestion-profile-construction/data-insights-course-3--what-are-triggers.md | | **generated_at** | 2026-04-28T06:55:44.161Z | > Part of **[Data Ingestion & Profile Construction](https://www.contentstack.com/academy/courses/data-insights-data-ingestion-profile-construction)** on Contentstack Academy. **Academy MD v3** — structured for retrieval; no quiz or assessment keys. #### Video details #### At a glance - **Title:** 23-data-insights-trigger-basics - **Duration:** 3m 43s - **Media link:** https://cdn.jwplayer.com/previews/AW2Mx2Bb - **Publish date (unix):** 1752881258 #### Streaming renditions - application/vnd.apple.mpegurl - audio/mp4 · AAC Audio · 113752 kbps - video/mp4 · 180p · 180p · 130023 kbps - video/mp4 · 270p · 270p · 138491 kbps - video/mp4 · 360p · 360p · 145476 kbps - video/mp4 · 406p · 406p · 150625 kbps - video/mp4 · 540p · 540p · 166917 kbps - video/mp4 · 720p · 720p · 192897 kbps - video/mp4 · 1080p · 1080p · 263885 kbps #### Timed text tracks (delivery) - **thumbnails:** `https://cdn.jwplayer.com/strips/AW2Mx2Bb-120.vtt` #### Transcript Once you have a profile built and you start to build audiences, what's the actual mechanism to allow you to do something with that? How do we know somebody just entered an audience? How do we know they exited an audience? How do we know a value changed? How do the jobs that are real-time syncs even work at all? All of the answers to those questions are what we call triggers. So essentially, this is where I'm going to explain it like a noob. If we want to go into more detail, Eric can go into much more detail on the processing pipeline. But essentially, data comes into Lytx. You have raw events. It's the stuff that we're collecting. It's the stuff that we're pulling from systems. We do what I call enrichment. So that's where our behavioral scores are calculated. Audience memberships are calculated. The model scores are calculated. So there's a bunch of things that are happening to where we're improving, updating, and adding additional context onto the profile. Based on the results of that, it then can trigger things. Most of the triggers, certainly the most common triggers, are around segment membership. So at that point in the pipeline, once data has been collected, we've done all this analysis, now we understand all of the audiences that this user is either a member of and no longer a member of or isn't a member of and now will be a member of. At that point in time, you can essentially use what we call a trigger to say, Eric is now joining segment A. Because Eric's joining segment A, I want to fire off that information, that profile, in these 16 different systems, or I want to fire this webhook, or I want to do something downstream based on that specific signal. So segment entry is one of those. I'm now a member of a segment. Segment exit is one of those signals. So now I'm no longer a member of that segment. Yep. A new trigger, I guess, technically, is flows. We'll go through and talk about flows specifically, but flows is somewhere between segment and attribute. It's a little bit different than its own special thing, but sort of like flow, stage, step membership is also a trigger, but it's all contained kind of within flows, which is in a segment context. But yeah, the triggers are super important in that it's how data gets out of the system and kind of understanding what you can do and what you can't do with them is important. And then also for our jobs, you have the non-trigger base, which is sort of like on a cadence. We're going to go through and just do a scan of the users in that segment and pass it. That's still a possibility as well. But I think more and more, we try to do everything in that sort of real-time streaming system. Every time a trigger happens, it sends to the information. Yeah, the other thing that we probably won't get into very deep here is there are sort of like candidates to be triggered later. So it's the concept of like, maybe we need to look at this profile again in the future. And that's another thing that we look at during the same evaluation. So if one of these custom rules has been inactive for five days, that would be like, as soon as they have any activity, it would make them a candidate to be inactive five days in the future. And that's another thing that happens all at the same time that we're calculating these triggers. #### Subtitles (WebVTT) ```webvtt WEBVTT 1 00:00:00.000 --> 00:00:22.040 Once you have a profile built and you start to build audiences, what's the actual mechanism 2 00:00:22.040 --> 00:00:24.680 to allow you to do something with that? 3 00:00:24.680 --> 00:00:27.040 How do we know somebody just entered an audience? 4 00:00:27.040 --> 00:00:28.560 How do we know they exited an audience? 5 00:00:28.560 --> 00:00:30.520 How do we know a value changed? 6 00:00:30.520 --> 00:00:34.800 How do the jobs that are real-time syncs even work at all? 7 00:00:34.800 --> 00:00:37.360 All of the answers to those questions are what we call triggers. 8 00:00:37.360 --> 00:00:40.360 So essentially, this is where I'm going to explain it like a noob. 9 00:00:40.360 --> 00:00:43.360 If we want to go into more detail, Eric can go into much more detail on the processing 10 00:00:43.360 --> 00:00:44.360 pipeline. 11 00:00:44.360 --> 00:00:46.100 But essentially, data comes into Lytx. 12 00:00:46.100 --> 00:00:47.100 You have raw events. 13 00:00:47.100 --> 00:00:48.100 It's the stuff that we're collecting. 14 00:00:48.100 --> 00:00:50.280 It's the stuff that we're pulling from systems. 15 00:00:50.280 --> 00:00:51.760 We do what I call enrichment. 16 00:00:51.760 --> 00:00:55.000 So that's where our behavioral scores are calculated. 17 00:00:55.000 --> 00:00:56.240 Audience memberships are calculated. 18 00:00:56.240 --> 00:00:57.520 The model scores are calculated. 19 00:00:57.520 --> 00:01:01.920 So there's a bunch of things that are happening to where we're improving, updating, and adding 20 00:01:01.920 --> 00:01:04.880 additional context onto the profile. 21 00:01:04.880 --> 00:01:08.960 Based on the results of that, it then can trigger things. 22 00:01:08.960 --> 00:01:13.720 Most of the triggers, certainly the most common triggers, are around segment membership. 23 00:01:13.720 --> 00:01:18.280 So at that point in the pipeline, once data has been collected, we've done all this analysis, 24 00:01:18.280 --> 00:01:22.520 now we understand all of the audiences that this user is either a member of and no longer 25 00:01:22.520 --> 00:01:26.520 a member of or isn't a member of and now will be a member of. 26 00:01:26.520 --> 00:01:32.200 At that point in time, you can essentially use what we call a trigger to say, Eric is 27 00:01:32.200 --> 00:01:38.080 now joining segment A. Because Eric's joining segment A, I want to fire off that information, 28 00:01:38.080 --> 00:01:42.560 that profile, in these 16 different systems, or I want to fire this webhook, or I want 29 00:01:42.560 --> 00:01:47.400 to do something downstream based on that specific signal. 30 00:01:47.400 --> 00:01:49.320 So segment entry is one of those. 31 00:01:49.320 --> 00:01:51.280 I'm now a member of a segment. 32 00:01:51.280 --> 00:01:53.080 Segment exit is one of those signals. 33 00:01:53.080 --> 00:01:55.760 So now I'm no longer a member of that segment. 34 00:01:56.000 --> 00:01:57.000 Yep. 35 00:01:57.000 --> 00:02:00.800 A new trigger, I guess, technically, is flows. 36 00:02:00.800 --> 00:02:06.000 We'll go through and talk about flows specifically, but flows is somewhere between segment and 37 00:02:06.000 --> 00:02:07.000 attribute. 38 00:02:07.000 --> 00:02:11.360 It's a little bit different than its own special thing, but sort of like flow, stage, step 39 00:02:11.360 --> 00:02:15.240 membership is also a trigger, but it's all contained kind of within flows, which is in 40 00:02:15.240 --> 00:02:17.240 a segment context. 41 00:02:17.240 --> 00:02:25.120 But yeah, the triggers are super important in that it's how data gets out of the system 42 00:02:25.480 --> 00:02:28.200 and kind of understanding what you can do and what you can't do with them is important. 43 00:02:28.200 --> 00:02:32.560 And then also for our jobs, you have the non-trigger base, which is sort of like on a cadence. 44 00:02:32.560 --> 00:02:35.560 We're going to go through and just do a scan of the users in that segment and pass it. 45 00:02:35.560 --> 00:02:37.080 That's still a possibility as well. 46 00:02:37.080 --> 00:02:44.400 But I think more and more, we try to do everything in that sort of real-time streaming system. 47 00:02:44.400 --> 00:02:47.200 Every time a trigger happens, it sends to the information. 48 00:02:47.200 --> 00:02:59.360 Yeah, the other thing that we probably won't get into very deep here is there are sort 49 00:02:59.360 --> 00:03:02.640 of like candidates to be triggered later. 50 00:03:02.640 --> 00:03:09.200 So it's the concept of like, maybe we need to look at this profile again in the future. 51 00:03:09.200 --> 00:03:13.080 And that's another thing that we look at during the same evaluation. 52 00:03:13.120 --> 00:03:20.400 So if one of these custom rules has been inactive for five days, that would be like, as soon 53 00:03:20.400 --> 00:03:25.800 as they have any activity, it would make them a candidate to be inactive five days in the future. 54 00:03:25.800 --> 00:03:33.560 And that's another thing that happens all at the same time that we're calculating these triggers. ``` ```transcript [00:00] Once you have a profile built and you start to build audiences, what's the actual mechanism [00:22] to allow you to do something with that? [00:24] How do we know somebody just entered an audience? [00:27] How do we know they exited an audience? [00:28] How do we know a value changed? [00:30] How do the jobs that are real-time syncs even work at all? [00:34] All of the answers to those questions are what we call triggers. [00:37] So essentially, this is where I'm going to explain it like a noob. [00:40] If we want to go into more detail, Eric can go into much more detail on the processing [00:43] pipeline. [00:44] But essentially, data comes into Lytx. [00:46] You have raw events. [00:47] It's the stuff that we're collecting. [00:48] It's the stuff that we're pulling from systems. [00:50] We do what I call enrichment. [00:51] So that's where our behavioral scores are calculated. [00:55] Audience memberships are calculated. [00:56] The model scores are calculated. [00:57] So there's a bunch of things that are happening to where we're improving, updating, and adding [01:01] additional context onto the profile. [01:04] Based on the results of that, it then can trigger things. [01:08] Most of the triggers, certainly the most common triggers, are around segment membership. [01:13] So at that point in the pipeline, once data has been collected, we've done all this analysis, [01:18] now we understand all of the audiences that this user is either a member of and no longer [01:22] a member of or isn't a member of and now will be a member of. [01:26] At that point in time, you can essentially use what we call a trigger to say, Eric is [01:32] now joining segment A. Because Eric's joining segment A, I want to fire off that information, [01:38] that profile, in these 16 different systems, or I want to fire this webhook, or I want [01:42] to do something downstream based on that specific signal. [01:47] So segment entry is one of those. [01:49] I'm now a member of a segment. [01:51] Segment exit is one of those signals. [01:53] So now I'm no longer a member of that segment. [01:56] Yep. [01:57] A new trigger, I guess, technically, is flows. [02:00] We'll go through and talk about flows specifically, but flows is somewhere between segment and [02:06] attribute. [02:07] It's a little bit different than its own special thing, but sort of like flow, stage, step [02:11] membership is also a trigger, but it's all contained kind of within flows, which is in [02:15] a segment context. [02:17] But yeah, the triggers are super important in that it's how data gets out of the system [02:25] and kind of understanding what you can do and what you can't do with them is important. [02:28] And then also for our jobs, you have the non-trigger base, which is sort of like on a cadence. [02:32] We're going to go through and just do a scan of the users in that segment and pass it. [02:35] That's still a possibility as well. [02:37] But I think more and more, we try to do everything in that sort of real-time streaming system. [02:44] Every time a trigger happens, it sends to the information. [02:47] Yeah, the other thing that we probably won't get into very deep here is there are sort [02:59] of like candidates to be triggered later. [03:02] So it's the concept of like, maybe we need to look at this profile again in the future. [03:09] And that's another thing that we look at during the same evaluation. [03:13] So if one of these custom rules has been inactive for five days, that would be like, as soon [03:20] as they have any activity, it would make them a candidate to be inactive five days in the future. [03:25] And that's another thing that happens all at the same time that we're calculating these triggers. ``` #### Key takeaways - Connect **What are "triggers"?** 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 "triggers"?. What are "triggers"? in Data Ingestion & Profile Construction (data-insights-data-ingestion-profile-construction). ### Retrieval tags - What - are - triggers - data-insights-data-ingestion-profile-construction - lesson 15 - What are "triggers"? - data-insights-data-ingestion-profile-construction lesson ### Indexing notes Index this lesson as a primary chunk tagged with lesson_id "15" and topics: [What, are, triggers]. 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