# Using Profiles to Power Personalization ### About this export | Field | Value | | --- | --- | | **content_type** | course | | **platform** | contentstack-academy | | **source_url** | https://www.contentstack.com/academy/courses/data-insights-using-profiles-to-power-personalization | | **language** | en | | **product_area** | Contentstack Academy | | **learning_path** | data-and-insights-practitioner-certification | | **course_id** | data-insights-using-profiles-to-power-personalization | | **slug** | data-insights-using-profiles-to-power-personalization | | **version** | 2026-03-01 | | **last_updated** | 2026-04-28 | | **status** | published | | **keywords** | ["Contentstack Academy"] | | **summary_one_line** | This course focuses on putting your unified customer profiles to work through sophisticated audience building and personalization capabilities. You'll learn to create dynamic, real-time udiences and deploy personalized e… | | **total_duration_minutes** | 30 | | **lessons_count** | 9 | | **video_lessons_count** | 8 | | **text_lessons_count** | 1 | | **linked_learning_path** | data-and-insights-practitioner-certification | | **linked_assessment_ref** | LMS_UNCONFIGURED_COURSE_ASSESSMENT | | **markdown_file_url** | /academy/md/courses/data-insights-using-profiles-to-power-personalization.md | | **generated_at** | 2026-04-28T06:55:50.169Z | | **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 | 30m 14s | | Released (if known) | 2026-03-01 | | Product area | Contentstack Academy | ### Description _This course focuses on putting your unified customer profiles to work through sophisticated audience building and personalization capabilities. You'll learn to create dynamic, real-time udiences and deploy personalized experiences across multiple channels._ ### Overview ### What You'll Learn This hands-on session teaches you to transform unified profiles into actionable marketing campaigns through: * advanced audience segmentation * cross-channel activation * web personalization. You'll master the tools needed to deliver relevant, personalized experiences at scale. ### What We'll Cover We'll start with building sophisticated audiences using real-time computed attributes, including complex time-based logic for use cases like cart abandonment and rule sets with AND/OR logic for precise targeting. You'll learn how our audiences differ from traditional static lists by functioning as living, breathing computed attributes that update in real-time. We'll cover exporting audiences to hundreds of marketing platforms including ESPs, CRMs, and ad tech, and integrating Cloud Connect data seamlessly into audience definitions. You'll explore the reporting system to gain insights into audience composition and overlap, then implement web personalization using the Pathfora SDK to deploy campaigns like modals and forms. Finally, we'll cover the Experiences interface for creating personalized campaigns without coding. ### 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 data-insights-using-profiles-to-power-personalization/ ├── 01-data-insights-course-4--building-an-audience · video · 595s ├── 02-data-insights-course-4--audience-mechanics · video · 96s ├── 03-data-insights-course-4--leverage-warehouse-data-in-audiences · video · 56s ├── 04-data-insights-course-4--activating-audiences · video · 67s ├── 05-data-insights-course-4--save-time-with-actions · video · 76s ├── 06-data-insights-course-4--unlock-insights-with-reports · video · 534s ├── 07-data-insights-course-4--web-campaign-personalization-sdk · video · 212s ├── 08-data-insights-course-4--streamline-campaigns-with-experiences · video · 178s ├── 09-data-insights-course-4--quiz · quiz (LMS only) · 3 min ``` ## Lessons ### Lesson 01 — Building an Audience #### Video details #### At a glance - **Title:** 24-data-insights-building-an-audience - **Duration:** 9m 55s - **Media link:** https://cdn.jwplayer.com/previews/LVm9uAFn - **Publish date (unix):** 1752889734 #### Streaming renditions - application/vnd.apple.mpegurl - audio/mp4 · AAC Audio · 113453 kbps - video/mp4 · 180p · 180p · 127895 kbps - video/mp4 · 270p · 270p · 135135 kbps - video/mp4 · 360p · 360p · 143562 kbps - video/mp4 · 406p · 406p · 148506 kbps - video/mp4 · 540p · 540p · 163364 kbps - video/mp4 · 720p · 720p · 187010 kbps - video/mp4 · 1080p · 1080p · 260143 kbps #### Timed text tracks (delivery) - **thumbnails:** `https://cdn.jwplayer.com/strips/LVm9uAFn-120.vtt` #### Transcript Audience building in Lytx at the core is super easy. Just go into audiences, you'll see all of your existing audiences. Lytx comes pre-built with a number of audiences out of the box. So like if you expand it, you'll see things like anonymous profiles and highly engaged users and some of those kind of things. That's what you'll see in a brand new account on day one without doing anything. And then obviously you can go in here and create any number of custom audiences based on your data, based on your specific use cases. When you go into the audience builder, so when you go to build audiences, there's really only two things to keep in mind kind of at a high level. One, you can build Lytx audiences on existing audiences. So usually we'll call those building block audiences. You can think about a use case where, you know, maybe I have a consent audience or audience of high value users in the U.S. or audience of users who have an email address or whatever it may be. You don't want to redefine that logic every single time that you build a segment that uses, say, your consent rules. So you can go in here, build an audience, and then when you come to build a new audience, you can select essentially any of the existing audiences to include in that logic. So for instance, I can search for, say, like known email, which is one of our out-of-the-box audiences, click that, and it'll add that logic to your segment definition. And then you can stack additional rules and ands and ors and all that kind of stuff on top of it. So keep in mind that you can build audiences on top of other audiences. We try to keep the, like, the depth of those includes. Within reason, customers sometimes can do some crazy things and have, you know, an audience that includes an audience that includes an audience that includes an audience that includes an audience. And sometimes that makes the logic difficult to understand. So I wouldn't go terribly deep on those inclusions as a best practice, but there's not really any hard limitations. When you add either a rule, which we'll do here in a second, or an audience, you'll always be presented with included by default. You can toggle it to exclude. And then these counts on the right hand side are real time. The one thing to note about these counts is under the hood, this gets pulled from Elasticsearch. So sometimes, like, if you're doing live testing and pushing a profile in and then building an audience, these numbers will be slightly delayed compared to the profile view, which reads directly from the actual entity store in Bigtable. So just keep in mind that there's some caching, some delay in the actual calculation of these numbers while the data sort of makes its way to Elasticsearch and whatnot. It really only impacts you if you're, like I said, doing a thing in the UI to collect data and then going to build a segment and expect it to show one. It won't always show one right away or whatever that user number is. But for the most part, the counts are pretty close to real time. I think in my testing last week, it's like 10 to 15 minutes and all of the numbers in the audience query should be up to date. And then the other thing you can do, as long as there's users that come back in the audience, is you can sample recent users. So this will pull up a bunch of anonymous profiles because they don't have names yet, but you can click on one of these and actually go to explore the profile just as you're trying to sort of play with and understand the system. The segments at the core in the UI, at least I should say, are built up of rules and rule sets. So rule sets, just think about it as a group of rules, and then rules are the individual logic. We'll probably in a follow-up conversation, maybe go in under the hood how segments are built and touch on filter QL and some of that, which is like the code, the language, the query that the UI builds. But I think we'll save that for a more technical deep dive. But as an example, if I delete this rule, I can go, one thing I would ignore is this content affinity tab is legacy. You're going to open it and there's generally not going to be any content affinities. This thing's going away in the new builder because we don't use it anymore. So just as you see that sort of ignore and pretend that it's not there. The other thing to be aware of is the custom rules. So this is where all of the attributes that we have walked through how to add and change and manipulate and create on the profile, you can ultimately access them and build whatever logic you want. So if I wanted to, for instance, say like, you know, anybody that has had a page view ever, I could add that condition. And then you could add additional rules to the rule set. So like if I did email exists, these two rules in the UI are essentially linked together. So I can switch it and say I want it to be an or or an and pretty basic sort of stuff. I can include or exclude one of them. And then if I were to add another rule set, it's another group of rules that you can then and an or against that top set of rules. So if I did like score frequency is greater than 10. So now you have this rule set, which contains these two rules that have their sort of independent and or switcher. And then I can adjust the logic of this rule set. If I were to add another rule, say like score frequency is exists, whatever bad rule because they're the same ones. But so now these two things work together. These two things work together. And then you can toggle if you want to use both rules or whatever. So it's it's creating this big essentially like and or statement under the hood, which we can show, but just know that you have rule sets so that you can group logic together. And then you have rules which represent the individual rules to be applied. So then the other thing that I wanted to touch on that will definitely come up. Actually, there's two things. So one, you'll see the show unpopulated fields is automatically checked. So it should be on for everybody. If you happen to uncheck it, it's going to hide all of the fields that don't yet have user data on them. So like if I do this, it's going to hide a bunch of fields that maybe we haven't collected first name, last name stuff that doesn't have information yet. So almost always you're going to want to make sure that this is checked. It should be checked by default, but it's a total gotcha of like, I don't see my field. It's not there. How do I build a segment? It generally means that you don't have any users with data on that yet. And then more importantly, field info, which is sort of a background job, hasn't ran yet to update some of those stats. So just kind of a foot gun to always make sure that that's checked. It's going away in the new builder and it's just on. And then the other thing that is a little bit hairy, we'll say, is it's really, really powerful, but it's also a little bit confusing in the UI to use some of that date calculation logic. So if I choose a field first and foremost, that is a time field. So for instance, like event last time seen is a map of the event name and then the time stamp that you last saw it or the time stamp that you first saw it. So if I go in here, for example, and say I want to look at page view, it's going to bring up the sort of date math calculator for lack of a better term. And the first thing to notice, you can do it based on a relative date. So one that slides with you versus specific date. So if a specific date is I want to evaluate this on June 13th, 2025, I can do that and it does it one time. The relative date allows you to do things like I want to reevaluate this an hour in the future for every user based on that date. What I did, because this is always really complicated to explain, I built a picture to try and explain this, which I can share afterwards as well. But essentially, in this UI, if I go back here just real quick, so there's essentially the relative date and there's after, before, or exists. Exists is super easy in that it just evaluates that that key exists. It doesn't care about the time stamp as long as that key's there. So that's just sort of like a check of I've ever made a purchase as an example. But there's after and before and there's in the past and in the future. So this picture sort of breaks down that logic. So for instance, if I say, after one hour in the future, let's say it's 3 p.m. right now, the green, it's going to look at 4 p.m. for my time and then have any time after that, which probably doesn't have any use cases, but technically you could build it. After one hour in the past is going to look an hour in the past. So 2 p.m. in this case, and then look forward from there, essentially. The before one hour in the past is going to look an hour behind and then any time before that. And then before one hour in the future, goes in the future an hour and then looks backward. All of this is horrifically complicated. One of the things that we're working to do, which you'll see in some of like actions and that kind of thing, is like for cart abandonment, we want to pre-build a segment for you that says, okay, we wanted to pull in anybody that has abandoned a cart in the last 30 minutes and hasn't made a purchase in 24 hours, which is a super simple use case, really difficult to build with this particular logic. So you'll see it in the UI, know that this is one of the big focuses for us and one of the reasons that we're rebuilding the segment builder so that we can simplify a bunch of this logic and make it a little bit more human friendly. However, the power of it is super, super cool and that it can do sort of these forward date calculations to reevaluate in the future to see when you're in that segment or not in that segment versus relying on events to come into the stream. #### Subtitles (WebVTT) ```webvtt WEBVTT 1 00:00:00.000 --> 00:00:18.000 Audience building in Lytx at the core is super easy. 2 00:00:18.000 --> 00:00:21.600 Just go into audiences, you'll see all of your existing audiences. 3 00:00:21.600 --> 00:00:25.600 Lytx comes pre-built with a number of audiences out of the box. 4 00:00:25.600 --> 00:00:29.600 So like if you expand it, you'll see things like anonymous profiles 5 00:00:29.600 --> 00:00:32.400 and highly engaged users and some of those kind of things. 6 00:00:32.400 --> 00:00:36.500 That's what you'll see in a brand new account on day one without doing anything. 7 00:00:36.500 --> 00:00:40.100 And then obviously you can go in here and create any number of custom audiences 8 00:00:40.100 --> 00:00:43.100 based on your data, based on your specific use cases. 9 00:00:43.100 --> 00:00:48.200 When you go into the audience builder, so when you go to build audiences, 10 00:00:48.200 --> 00:00:53.300 there's really only two things to keep in mind kind of at a high level. 11 00:00:53.300 --> 00:00:57.800 One, you can build Lytx audiences on existing audiences. 12 00:00:57.800 --> 00:01:00.900 So usually we'll call those building block audiences. 13 00:01:00.900 --> 00:01:05.600 You can think about a use case where, you know, maybe I have a consent audience 14 00:01:05.600 --> 00:01:08.900 or audience of high value users in the U.S. 15 00:01:08.900 --> 00:01:12.300 or audience of users who have an email address or whatever it may be. 16 00:01:12.300 --> 00:01:16.000 You don't want to redefine that logic every single time that you build a segment 17 00:01:16.000 --> 00:01:18.500 that uses, say, your consent rules. 18 00:01:18.500 --> 00:01:21.000 So you can go in here, build an audience, 19 00:01:21.000 --> 00:01:22.600 and then when you come to build a new audience, 20 00:01:22.600 --> 00:01:26.800 you can select essentially any of the existing audiences to include in that logic. 21 00:01:26.800 --> 00:01:30.900 So for instance, I can search for, say, like known email, 22 00:01:30.900 --> 00:01:33.000 which is one of our out-of-the-box audiences, 23 00:01:33.000 --> 00:01:36.800 click that, and it'll add that logic to your segment definition. 24 00:01:36.800 --> 00:01:39.400 And then you can stack additional rules and ands and ors 25 00:01:39.400 --> 00:01:40.700 and all that kind of stuff on top of it. 26 00:01:40.700 --> 00:01:46.300 So keep in mind that you can build audiences on top of other audiences. 27 00:01:46.300 --> 00:01:51.000 We try to keep the, like, the depth of those includes. 28 00:01:51.000 --> 00:01:54.000 Within reason, customers sometimes can do some crazy things 29 00:01:54.100 --> 00:01:57.000 and have, you know, an audience that includes an audience 30 00:01:57.000 --> 00:01:59.300 that includes an audience that includes an audience that includes an audience. 31 00:01:59.300 --> 00:02:02.000 And sometimes that makes the logic difficult to understand. 32 00:02:02.000 --> 00:02:07.400 So I wouldn't go terribly deep on those inclusions as a best practice, 33 00:02:07.400 --> 00:02:10.100 but there's not really any hard limitations. 34 00:02:10.100 --> 00:02:15.100 When you add either a rule, which we'll do here in a second, or an audience, 35 00:02:15.100 --> 00:02:18.300 you'll always be presented with included by default. 36 00:02:18.300 --> 00:02:20.300 You can toggle it to exclude. 37 00:02:20.300 --> 00:02:23.700 And then these counts on the right hand side are real time. 38 00:02:23.700 --> 00:02:27.400 The one thing to note about these counts is under the hood, 39 00:02:27.400 --> 00:02:29.800 this gets pulled from Elasticsearch. 40 00:02:29.800 --> 00:02:32.800 So sometimes, like, if you're doing live testing 41 00:02:32.800 --> 00:02:35.400 and pushing a profile in and then building an audience, 42 00:02:35.400 --> 00:02:39.000 these numbers will be slightly delayed compared to the profile view, 43 00:02:39.000 --> 00:02:43.400 which reads directly from the actual entity store in Bigtable. 44 00:02:43.400 --> 00:02:45.500 So just keep in mind that there's some caching, 45 00:02:45.500 --> 00:02:49.200 some delay in the actual calculation of these numbers 46 00:02:49.200 --> 00:02:53.000 while the data sort of makes its way to Elasticsearch and whatnot. 47 00:02:53.000 --> 00:02:55.400 It really only impacts you if you're, like I said, 48 00:02:55.400 --> 00:02:57.900 doing a thing in the UI to collect data 49 00:02:57.900 --> 00:03:00.300 and then going to build a segment and expect it to show one. 50 00:03:00.300 --> 00:03:03.900 It won't always show one right away or whatever that user number is. 51 00:03:03.900 --> 00:03:07.700 But for the most part, the counts are pretty close to real time. 52 00:03:07.700 --> 00:03:11.300 I think in my testing last week, it's like 10 to 15 minutes 53 00:03:11.300 --> 00:03:14.800 and all of the numbers in the audience query should be up to date. 54 00:03:14.800 --> 00:03:15.800 And then the other thing you can do, 55 00:03:15.800 --> 00:03:17.700 as long as there's users that come back in the audience, 56 00:03:17.700 --> 00:03:20.000 is you can sample recent users. 57 00:03:20.000 --> 00:03:23.200 So this will pull up a bunch of anonymous profiles 58 00:03:23.200 --> 00:03:24.100 because they don't have names yet, 59 00:03:24.100 --> 00:03:27.000 but you can click on one of these and actually go to explore the profile 60 00:03:27.000 --> 00:03:30.600 just as you're trying to sort of play with and understand the system. 61 00:03:30.600 --> 00:03:35.400 The segments at the core in the UI, 62 00:03:35.400 --> 00:03:39.100 at least I should say, are built up of rules and rule sets. 63 00:03:39.100 --> 00:03:42.300 So rule sets, just think about it as a group of rules, 64 00:03:42.300 --> 00:03:44.900 and then rules are the individual logic. 65 00:03:44.900 --> 00:03:46.800 We'll probably in a follow-up conversation, 66 00:03:46.800 --> 00:03:49.200 maybe go in under the hood how segments are built 67 00:03:49.200 --> 00:03:50.800 and touch on filter QL and some of that, 68 00:03:50.800 --> 00:03:56.100 which is like the code, the language, the query that the UI builds. 69 00:03:56.100 --> 00:04:00.300 But I think we'll save that for a more technical deep dive. 70 00:04:00.300 --> 00:04:04.500 But as an example, if I delete this rule, I can go, 71 00:04:04.500 --> 00:04:07.400 one thing I would ignore is this content affinity tab is legacy. 72 00:04:07.400 --> 00:04:10.300 You're going to open it and there's generally not going to be any content affinities. 73 00:04:10.300 --> 00:04:13.300 This thing's going away in the new builder because we don't use it anymore. 74 00:04:13.300 --> 00:04:17.200 So just as you see that sort of ignore and pretend that it's not there. 75 00:04:17.200 --> 00:04:19.200 The other thing to be aware of is the custom rules. 76 00:04:19.200 --> 00:04:22.700 So this is where all of the attributes that we have walked through how to add 77 00:04:22.700 --> 00:04:24.600 and change and manipulate and create on the profile, 78 00:04:24.600 --> 00:04:27.300 you can ultimately access them and build whatever logic you want. 79 00:04:27.300 --> 00:04:30.600 So if I wanted to, for instance, say like, 80 00:04:30.600 --> 00:04:36.900 you know, anybody that has had a page view ever, I could add that condition. 81 00:04:36.900 --> 00:04:40.500 And then you could add additional rules to the rule set. 82 00:04:40.500 --> 00:04:50.000 So like if I did email exists, these two rules in the UI are essentially linked together. 83 00:04:50.000 --> 00:04:54.900 So I can switch it and say I want it to be an or or an and pretty basic sort of stuff. 84 00:04:54.900 --> 00:04:57.400 I can include or exclude one of them. 85 00:04:57.400 --> 00:04:59.200 And then if I were to add another rule set, 86 00:04:59.200 --> 00:05:03.800 it's another group of rules that you can then and an or against that top set of rules. 87 00:05:03.800 --> 00:05:10.500 So if I did like score frequency is greater than 10. 88 00:05:10.500 --> 00:05:14.100 So now you have this rule set, 89 00:05:14.100 --> 00:05:18.600 which contains these two rules that have their sort of independent and or switcher. 90 00:05:18.600 --> 00:05:22.300 And then I can adjust the logic of this rule set. 91 00:05:22.300 --> 00:05:29.100 If I were to add another rule, say like score frequency is exists, 92 00:05:29.100 --> 00:05:30.600 whatever bad rule because they're the same ones. 93 00:05:30.600 --> 00:05:32.900 But so now these two things work together. 94 00:05:32.900 --> 00:05:34.000 These two things work together. 95 00:05:34.000 --> 00:05:36.400 And then you can toggle if you want to use both rules or whatever. 96 00:05:36.400 --> 00:05:40.200 So it's it's creating this big essentially like and or statement under the hood, 97 00:05:40.200 --> 00:05:45.500 which we can show, but just know that you have rule sets so that you can group logic together. 98 00:05:45.500 --> 00:05:52.000 And then you have rules which represent the individual rules to be applied. 99 00:05:52.000 --> 00:05:57.100 So then the other thing that I wanted to touch on that will definitely come up. 100 00:05:57.100 --> 00:06:02.500 Actually, there's two things. So one, you'll see the show unpopulated fields is automatically checked. 101 00:06:02.500 --> 00:06:06.300 So it should be on for everybody. If you happen to uncheck it, 102 00:06:06.300 --> 00:06:10.800 it's going to hide all of the fields that don't yet have user data on them. 103 00:06:10.800 --> 00:06:16.100 So like if I do this, it's going to hide a bunch of fields that maybe we haven't collected first name, 104 00:06:16.100 --> 00:06:18.200 last name stuff that doesn't have information yet. 105 00:06:18.200 --> 00:06:22.100 So almost always you're going to want to make sure that this is checked. 106 00:06:22.100 --> 00:06:26.000 It should be checked by default, but it's a total gotcha of like, I don't see my field. It's not there. 107 00:06:26.000 --> 00:06:31.400 How do I build a segment? It generally means that you don't have any users with data on that yet. 108 00:06:31.400 --> 00:06:33.900 And then more importantly, field info, which is sort of a background job, 109 00:06:33.900 --> 00:06:35.900 hasn't ran yet to update some of those stats. 110 00:06:35.900 --> 00:06:39.100 So just kind of a foot gun to always make sure that that's checked. 111 00:06:39.100 --> 00:06:42.300 It's going away in the new builder and it's just on. 112 00:06:42.300 --> 00:06:49.900 And then the other thing that is a little bit hairy, we'll say, is it's really, really powerful, 113 00:06:49.900 --> 00:06:54.800 but it's also a little bit confusing in the UI to use some of that date calculation logic. 114 00:06:54.800 --> 00:06:59.000 So if I choose a field first and foremost, that is a time field. 115 00:06:59.100 --> 00:07:03.700 So for instance, like event last time seen is a map of the event name 116 00:07:03.700 --> 00:07:07.900 and then the time stamp that you last saw it or the time stamp that you first saw it. 117 00:07:07.900 --> 00:07:12.600 So if I go in here, for example, and say I want to look at page view, 118 00:07:12.600 --> 00:07:18.800 it's going to bring up the sort of date math calculator for lack of a better term. 119 00:07:18.800 --> 00:07:22.300 And the first thing to notice, you can do it based on a relative date. 120 00:07:22.300 --> 00:07:25.600 So one that slides with you versus specific date. 121 00:07:25.600 --> 00:07:30.000 So if a specific date is I want to evaluate this on June 13th, 2025, 122 00:07:30.000 --> 00:07:32.000 I can do that and it does it one time. 123 00:07:32.000 --> 00:07:39.000 The relative date allows you to do things like I want to reevaluate this an hour in the future 124 00:07:39.000 --> 00:07:41.500 for every user based on that date. 125 00:07:41.500 --> 00:07:46.300 What I did, because this is always really complicated to explain, 126 00:07:46.300 --> 00:07:51.900 I built a picture to try and explain this, which I can share afterwards as well. 127 00:07:51.900 --> 00:07:57.200 But essentially, in this UI, if I go back here just real quick, 128 00:07:57.200 --> 00:08:02.600 so there's essentially the relative date and there's after, before, or exists. 129 00:08:02.600 --> 00:08:05.700 Exists is super easy in that it just evaluates that that key exists. 130 00:08:05.700 --> 00:08:07.900 It doesn't care about the time stamp as long as that key's there. 131 00:08:07.900 --> 00:08:13.000 So that's just sort of like a check of I've ever made a purchase as an example. 132 00:08:13.000 --> 00:08:17.000 But there's after and before and there's in the past and in the future. 133 00:08:17.000 --> 00:08:22.300 So this picture sort of breaks down that logic. 134 00:08:22.300 --> 00:08:26.200 So for instance, if I say, after one hour in the future, 135 00:08:26.200 --> 00:08:29.100 let's say it's 3 p.m. right now, the green, 136 00:08:29.100 --> 00:08:33.900 it's going to look at 4 p.m. for my time and then have any time after that, 137 00:08:33.900 --> 00:08:38.500 which probably doesn't have any use cases, but technically you could build it. 138 00:08:38.500 --> 00:08:42.600 After one hour in the past is going to look an hour in the past. 139 00:08:42.600 --> 00:08:48.000 So 2 p.m. in this case, and then look forward from there, essentially. 140 00:08:48.000 --> 00:08:52.300 The before one hour in the past is going to look an hour behind 141 00:08:52.300 --> 00:08:54.200 and then any time before that. 142 00:08:54.200 --> 00:08:58.300 And then before one hour in the future, 143 00:08:58.300 --> 00:09:00.500 goes in the future an hour and then looks backward. 144 00:09:00.500 --> 00:09:03.000 All of this is horrifically complicated. 145 00:09:03.000 --> 00:09:04.500 One of the things that we're working to do, 146 00:09:04.500 --> 00:09:06.500 which you'll see in some of like actions and that kind of thing, 147 00:09:06.500 --> 00:09:08.300 is like for cart abandonment, 148 00:09:08.300 --> 00:09:10.800 we want to pre-build a segment for you that says, 149 00:09:10.800 --> 00:09:14.800 okay, we wanted to pull in anybody that has abandoned a cart in the last 30 minutes 150 00:09:14.800 --> 00:09:16.800 and hasn't made a purchase in 24 hours, 151 00:09:16.800 --> 00:09:18.700 which is a super simple use case, 152 00:09:18.700 --> 00:09:21.500 really difficult to build with this particular logic. 153 00:09:21.500 --> 00:09:26.800 So you'll see it in the UI, know that this is one of the big focuses for us 154 00:09:26.800 --> 00:09:29.100 and one of the reasons that we're rebuilding the segment builder 155 00:09:29.100 --> 00:09:30.900 so that we can simplify a bunch of this logic 156 00:09:30.900 --> 00:09:34.300 and make it a little bit more human friendly. 157 00:09:34.300 --> 00:09:37.500 However, the power of it is super, super cool 158 00:09:37.500 --> 00:09:40.000 and that it can do sort of these forward date calculations 159 00:09:40.100 --> 00:09:42.700 to reevaluate in the future to see when you're in that segment 160 00:09:42.700 --> 00:09:46.100 or not in that segment versus relying on events to come into the stream. ``` ```transcript [00:00] Audience building in Lytx at the core is super easy. [00:18] Just go into audiences, you'll see all of your existing audiences. [00:21] Lytx comes pre-built with a number of audiences out of the box. [00:25] So like if you expand it, you'll see things like anonymous profiles [00:29] and highly engaged users and some of those kind of things. [00:32] That's what you'll see in a brand new account on day one without doing anything. [00:36] And then obviously you can go in here and create any number of custom audiences [00:40] based on your data, based on your specific use cases. [00:43] When you go into the audience builder, so when you go to build audiences, [00:48] there's really only two things to keep in mind kind of at a high level. [00:53] One, you can build Lytx audiences on existing audiences. [00:57] So usually we'll call those building block audiences. [01:00] You can think about a use case where, you know, maybe I have a consent audience [01:05] or audience of high value users in the U.S. [01:08] or audience of users who have an email address or whatever it may be. [01:12] You don't want to redefine that logic every single time that you build a segment [01:16] that uses, say, your consent rules. [01:18] So you can go in here, build an audience, [01:21] and then when you come to build a new audience, [01:22] you can select essentially any of the existing audiences to include in that logic. [01:26] So for instance, I can search for, say, like known email, [01:30] which is one of our out-of-the-box audiences, [01:33] click that, and it'll add that logic to your segment definition. [01:36] And then you can stack additional rules and ands and ors [01:39] and all that kind of stuff on top of it. [01:40] So keep in mind that you can build audiences on top of other audiences. [01:46] We try to keep the, like, the depth of those includes. [01:51] Within reason, customers sometimes can do some crazy things [01:54] and have, you know, an audience that includes an audience [01:57] that includes an audience that includes an audience that includes an audience. [01:59] And sometimes that makes the logic difficult to understand. [02:02] So I wouldn't go terribly deep on those inclusions as a best practice, [02:07] but there's not really any hard limitations. [02:10] When you add either a rule, which we'll do here in a second, or an audience, [02:15] you'll always be presented with included by default. [02:18] You can toggle it to exclude. [02:20] And then these counts on the right hand side are real time. [02:23] The one thing to note about these counts is under the hood, [02:27] this gets pulled from Elasticsearch. [02:29] So sometimes, like, if you're doing live testing [02:32] and pushing a profile in and then building an audience, [02:35] these numbers will be slightly delayed compared to the profile view, [02:39] which reads directly from the actual entity store in Bigtable. [02:43] So just keep in mind that there's some caching, [02:45] some delay in the actual calculation of these numbers [02:49] while the data sort of makes its way to Elasticsearch and whatnot. [02:53] It really only impacts you if you're, like I said, [02:55] doing a thing in the UI to collect data [02:57] and then going to build a segment and expect it to show one. [03:00] It won't always show one right away or whatever that user number is. [03:03] But for the most part, the counts are pretty close to real time. [03:07] I think in my testing last week, it's like 10 to 15 minutes [03:11] and all of the numbers in the audience query should be up to date. [03:14] And then the other thing you can do, [03:15] as long as there's users that come back in the audience, [03:17] is you can sample recent users. [03:20] So this will pull up a bunch of anonymous profiles [03:23] because they don't have names yet, [03:24] but you can click on one of these and actually go to explore the profile [03:27] just as you're trying to sort of play with and understand the system. ``` #### Key takeaways - Connect **Building an Audience** 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 — Audience Mechanics #### Video details #### At a glance - **Title:** 25-data-insights-audience-mechanics - **Duration:** 1m 36s - **Media link:** https://cdn.jwplayer.com/previews/XqZ5gtQA - **Publish date (unix):** 1752893435 #### Streaming renditions - application/vnd.apple.mpegurl - audio/mp4 · AAC Audio · 113683 kbps - video/mp4 · 180p · 180p · 133750 kbps - video/mp4 · 270p · 270p · 143402 kbps - video/mp4 · 360p · 360p · 147302 kbps - video/mp4 · 406p · 406p · 150798 kbps - video/mp4 · 540p · 540p · 165708 kbps - video/mp4 · 720p · 720p · 190716 kbps - video/mp4 · 1080p · 1080p · 258939 kbps #### Timed text tracks (delivery) - **thumbnails:** `https://cdn.jwplayer.com/strips/XqZ5gtQA-120.vtt` #### Transcript So, that's the basics of segment building. The only other thing I guess to touch on, we've touched on this a few different times, but we think of audiences very different than most marketing platforms and that most marketing platforms are building an audience, that audience is static, I'm going to sync it to my email tool and we're going to send one email blast to that audience. Linux audiences, or segments as we call them in the API, are living and breathing, they're actually far closer to like a computed attribute, or I present them as facts on the profile more times than not. So you're creating a set of rules to evaluate each time that event comes in, and then you're surfacing the result of that on every single individual profile. So instead of just having this list of people, you actually have this fact whether I am in or not in a segment on every single user's profile, like a computed attribute. It's one of the things we, like, that's one very unique difference of our segments is they're fundamentally the kind of basis of how you can trigger actions, right, entering into a segment, exiting a segment, updating a profile. So they're much more living, breathing, calculated in real time, not this like fixed static thing that doesn't change that you push to a tool, then you forget about it. #### Subtitles (WebVTT) ```webvtt WEBVTT 1 00:00:00.000 --> 00:00:19.100 So, that's the basics of segment building. 2 00:00:19.100 --> 00:00:22.680 The only other thing I guess to touch on, we've touched on this a few different times, 3 00:00:22.680 --> 00:00:27.160 but we think of audiences very different than most marketing platforms and that most marketing 4 00:00:27.160 --> 00:00:31.140 platforms are building an audience, that audience is static, I'm going to sync it to my email 5 00:00:31.140 --> 00:00:34.760 tool and we're going to send one email blast to that audience. 6 00:00:34.760 --> 00:00:39.080 Linux audiences, or segments as we call them in the API, are living and breathing, they're 7 00:00:39.080 --> 00:00:43.880 actually far closer to like a computed attribute, or I present them as facts on the profile 8 00:00:43.880 --> 00:00:45.400 more times than not. 9 00:00:45.400 --> 00:00:51.880 So you're creating a set of rules to evaluate each time that event comes in, and then you're 10 00:00:51.880 --> 00:00:55.160 surfacing the result of that on every single individual profile. 11 00:00:55.160 --> 00:00:59.160 So instead of just having this list of people, you actually have this fact whether I am in 12 00:00:59.160 --> 00:01:04.600 or not in a segment on every single user's profile, like a computed attribute. 13 00:01:04.600 --> 00:01:09.360 It's one of the things we, like, that's one very unique difference of our segments is 14 00:01:09.360 --> 00:01:15.320 they're fundamentally the kind of basis of how you can trigger actions, right, entering 15 00:01:15.320 --> 00:01:18.400 into a segment, exiting a segment, updating a profile. 16 00:01:18.400 --> 00:01:23.600 So they're much more living, breathing, calculated in real time, not this like fixed static thing 17 00:01:23.600 --> 00:01:26.720 that doesn't change that you push to a tool, then you forget about it. ``` ```transcript [00:00] So, that's the basics of segment building. [00:19] The only other thing I guess to touch on, we've touched on this a few different times, [00:22] but we think of audiences very different than most marketing platforms and that most marketing [00:27] platforms are building an audience, that audience is static, I'm going to sync it to my email [00:31] tool and we're going to send one email blast to that audience. [00:34] Linux audiences, or segments as we call them in the API, are living and breathing, they're [00:39] actually far closer to like a computed attribute, or I present them as facts on the profile [00:43] more times than not. [00:45] So you're creating a set of rules to evaluate each time that event comes in, and then you're [00:51] surfacing the result of that on every single individual profile. [00:55] So instead of just having this list of people, you actually have this fact whether I am in [00:59] or not in a segment on every single user's profile, like a computed attribute. [01:04] It's one of the things we, like, that's one very unique difference of our segments is [01:09] they're fundamentally the kind of basis of how you can trigger actions, right, entering [01:15] into a segment, exiting a segment, updating a profile. [01:18] So they're much more living, breathing, calculated in real time, not this like fixed static thing [01:23] that doesn't change that you push to a tool, then you forget about it. ``` #### Key takeaways - Connect **Audience Mechanics** 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 — Leverage Warehouse Data in Audiences #### Video details #### At a glance - **Title:** 26-data-insights-cloud-connect-audiences - **Duration:** 56s - **Media link:** https://cdn.jwplayer.com/previews/ti1OfDR6 - **Publish date (unix):** 1752893441 #### Streaming renditions - application/vnd.apple.mpegurl - audio/mp4 · AAC Audio · 114446 kbps - video/mp4 · 180p · 180p · 140379 kbps - video/mp4 · 270p · 270p · 154849 kbps - video/mp4 · 360p · 360p · 153389 kbps - video/mp4 · 406p · 406p · 158945 kbps - video/mp4 · 540p · 540p · 177952 kbps - video/mp4 · 720p · 720p · 205252 kbps - video/mp4 · 1080p · 1080p · 287467 kbps #### Timed text tracks (delivery) - **thumbnails:** `https://cdn.jwplayer.com/strips/ti1OfDR6-120.vtt` #### Transcript Cloud Connect audiences or audiences that are built on Cloud Connect data, all of your rules, all of your Cloud Connect attributes are going to be under custom rules. They just get prefixed with CC underscore under the hood. So the other day when we were meeting and we went through and pulled that big query data in to create the first name, last name, and pull in the annual revenue, all of that data lives and exists on the profiles. It functions just like a normal attribute. So this is where you would then go and build an audience. You can combine them with the sort of standard streamed attributes versus the Cloud Connect ones. #### Subtitles (WebVTT) ```webvtt WEBVTT 1 00:00:00.000 --> 00:00:20.000 Cloud Connect audiences or audiences that are built on Cloud Connect data, 2 00:00:20.000 --> 00:00:21.440 all of your rules, 3 00:00:21.440 --> 00:00:24.200 all of your Cloud Connect attributes are going to be under custom rules. 4 00:00:24.200 --> 00:00:28.040 They just get prefixed with CC underscore under the hood. 5 00:00:28.040 --> 00:00:31.880 So the other day when we were meeting and we went through and pulled that big query data in 6 00:00:31.880 --> 00:00:35.480 to create the first name, last name, and pull in the annual revenue, 7 00:00:35.480 --> 00:00:38.040 all of that data lives and exists on the profiles. 8 00:00:38.040 --> 00:00:40.680 It functions just like a normal attribute. 9 00:00:40.680 --> 00:00:43.000 So this is where you would then go and build an audience. 10 00:00:43.000 --> 00:00:47.080 You can combine them with the sort of standard streamed attributes versus the Cloud Connect ones. ``` ```transcript [00:00] Cloud Connect audiences or audiences that are built on Cloud Connect data, [00:20] all of your rules, [00:21] all of your Cloud Connect attributes are going to be under custom rules. [00:24] They just get prefixed with CC underscore under the hood. [00:28] So the other day when we were meeting and we went through and pulled that big query data in [00:31] to create the first name, last name, and pull in the annual revenue, [00:35] all of that data lives and exists on the profiles. [00:38] It functions just like a normal attribute. [00:40] So this is where you would then go and build an audience. [00:43] You can combine them with the sort of standard streamed attributes versus the Cloud Connect ones. ``` #### Key takeaways - Connect **Leverage Warehouse Data in Audiences** 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 — Activating Audiences #### Video details #### At a glance - **Title:** 27-data-insights-activating-audiences - **Duration:** 1m 7s - **Media link:** https://cdn.jwplayer.com/previews/rczEmn3z - **Publish date (unix):** 1752893445 #### Streaming renditions - application/vnd.apple.mpegurl - audio/mp4 · AAC Audio · 115224 kbps - video/mp4 · 180p · 180p · 146308 kbps - video/mp4 · 270p · 270p · 165890 kbps - video/mp4 · 360p · 360p · 172603 kbps - video/mp4 · 406p · 406p · 181778 kbps - video/mp4 · 540p · 540p · 214555 kbps - video/mp4 · 720p · 720p · 262770 kbps - video/mp4 · 1080p · 1080p · 396645 kbps #### Timed text tracks (delivery) - **thumbnails:** `https://cdn.jwplayer.com/strips/rczEmn3z-120.vtt` #### Transcript So from there, we won't touch too much on this because we've covered a lot, but one of the things obviously you can do with a segment is export it. So if I go into any of my segments like this No6Sense data, I can hit Export. It's going to pull up all the different export channels that we support. You can push it to MailChimp, to a Webhook, to Adobe, to anywhere on the planet, essentially, that you want to push to. And it's going to push those members to it. Most of the exports have the option to backfill, like Eric was just talking about, to where you can sync all of the users that are currently in it. Or if you just want all of the new members that join it, that's usually an option in most of the exports as well. I think we've covered imports and exports in pretty decent length, so we won't spend too much time there. #### Subtitles (WebVTT) ```webvtt WEBVTT 1 00:00:00.000 --> 00:00:18.640 So from there, we won't touch too much on this 2 00:00:18.640 --> 00:00:20.720 because we've covered a lot, but one of the things 3 00:00:20.720 --> 00:00:22.760 obviously you can do with a segment is export it. 4 00:00:22.760 --> 00:00:25.040 So if I go into any of my segments like this No6Sense 5 00:00:25.040 --> 00:00:26.620 data, I can hit Export. 6 00:00:26.620 --> 00:00:28.920 It's going to pull up all the different export channels 7 00:00:28.920 --> 00:00:30.100 that we support. 8 00:00:30.100 --> 00:00:31.840 You can push it to MailChimp, to a Webhook, 9 00:00:31.840 --> 00:00:34.600 to Adobe, to anywhere on the planet, 10 00:00:34.600 --> 00:00:36.400 essentially, that you want to push to. 11 00:00:36.400 --> 00:00:39.040 And it's going to push those members to it. 12 00:00:39.040 --> 00:00:40.680 Most of the exports have the option 13 00:00:40.680 --> 00:00:42.600 to backfill, like Eric was just talking about, 14 00:00:42.600 --> 00:00:46.600 to where you can sync all of the users that are currently in it. 15 00:00:46.600 --> 00:00:49.000 Or if you just want all of the new members that join it, 16 00:00:49.000 --> 00:00:51.760 that's usually an option in most of the exports as well. 17 00:00:51.760 --> 00:00:54.560 I think we've covered imports and exports 18 00:00:54.600 --> 00:00:58.160 in pretty decent length, so we won't spend too much time 19 00:00:58.160 --> 00:00:59.720 there. ``` ```transcript [00:00] So from there, we won't touch too much on this [00:18] because we've covered a lot, but one of the things [00:20] obviously you can do with a segment is export it. [00:22] So if I go into any of my segments like this No6Sense [00:25] data, I can hit Export. [00:26] It's going to pull up all the different export channels [00:28] that we support. [00:30] You can push it to MailChimp, to a Webhook, [00:31] to Adobe, to anywhere on the planet, [00:34] essentially, that you want to push to. [00:36] And it's going to push those members to it. [00:39] Most of the exports have the option [00:40] to backfill, like Eric was just talking about, [00:42] to where you can sync all of the users that are currently in it. [00:46] Or if you just want all of the new members that join it, [00:49] that's usually an option in most of the exports as well. [00:51] I think we've covered imports and exports [00:54] in pretty decent length, so we won't spend too much time [00:58] there. ``` #### Key takeaways - Connect **Activating Audiences** 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 — Save Time w/ Actions #### Video details #### At a glance - **Title:** 28-data-insights-actions - **Duration:** 1m 16s - **Media link:** https://cdn.jwplayer.com/previews/mlweezyZ - **Publish date (unix):** 1752893452 #### Streaming renditions - application/vnd.apple.mpegurl - audio/mp4 · AAC Audio · 114467 kbps - video/mp4 · 180p · 180p · 138041 kbps - video/mp4 · 270p · 270p · 149652 kbps - video/mp4 · 360p · 360p · 154910 kbps - video/mp4 · 406p · 406p · 161100 kbps - video/mp4 · 540p · 540p · 180955 kbps - video/mp4 · 720p · 720p · 214918 kbps - video/mp4 · 1080p · 1080p · 311057 kbps #### Timed text tracks (delivery) - **thumbnails:** `https://cdn.jwplayer.com/strips/mlweezyZ-120.vtt` #### Transcript Actions, what they allow you to do is essentially has a pre-built template that you basically fill in the blanks. So if I wanted to go and build an abandoned cart, we have a template. It asks you the questions. So I want to use event last timestamp. Use the cart event name. We recommend cart add. You say cart add, purchase. We recommend purchase. You can choose those windows. So how long do you want to wait before you assume that they've abandoned their cart? How long do you want to wait until they have sort of that window of purchase before you reset them? And then you can name it. You create the audience and it does all of that logic for you under the hood. It creates the rule. It sets up all of that kind of stuff sort of like just in a few clicks. So we're trying to make big steps to making things easier and easier and kind of more prepackaged but also still have support for the complexity and the value that the CDP can offer to an enterprise customer that wants to define everything on their own. #### Subtitles (WebVTT) ```webvtt WEBVTT 1 00:00:00.000 --> 00:00:21.000 Actions, what they allow you to do is essentially has a pre-built template that you basically 2 00:00:21.000 --> 00:00:22.000 fill in the blanks. 3 00:00:22.000 --> 00:00:25.600 So if I wanted to go and build an abandoned cart, we have a template. 4 00:00:25.600 --> 00:00:27.000 It asks you the questions. 5 00:00:27.000 --> 00:00:29.760 So I want to use event last timestamp. 6 00:00:29.760 --> 00:00:30.760 Use the cart event name. 7 00:00:30.760 --> 00:00:32.040 We recommend cart add. 8 00:00:32.040 --> 00:00:34.920 You say cart add, purchase. 9 00:00:34.920 --> 00:00:36.400 We recommend purchase. 10 00:00:36.400 --> 00:00:37.720 You can choose those windows. 11 00:00:37.720 --> 00:00:41.080 So how long do you want to wait before you assume that they've abandoned their cart? 12 00:00:41.080 --> 00:00:43.980 How long do you want to wait until they have sort of that window of purchase before you 13 00:00:43.980 --> 00:00:44.980 reset them? 14 00:00:44.980 --> 00:00:46.260 And then you can name it. 15 00:00:46.260 --> 00:00:50.280 You create the audience and it does all of that logic for you under the hood. 16 00:00:50.280 --> 00:00:51.280 It creates the rule. 17 00:00:51.280 --> 00:00:54.000 It sets up all of that kind of stuff sort of like just in a few clicks. 18 00:00:54.000 --> 00:00:58.400 So we're trying to make big steps to making things easier and easier and kind of more 19 00:00:58.400 --> 00:01:04.760 prepackaged but also still have support for the complexity and the value that the CDP 20 00:01:04.760 --> 00:01:07.400 can offer to an enterprise customer that wants to define everything on their own. ``` ```transcript [00:00] Actions, what they allow you to do is essentially has a pre-built template that you basically [00:21] fill in the blanks. [00:22] So if I wanted to go and build an abandoned cart, we have a template. [00:25] It asks you the questions. [00:27] So I want to use event last timestamp. [00:29] Use the cart event name. [00:30] We recommend cart add. [00:32] You say cart add, purchase. [00:34] We recommend purchase. [00:36] You can choose those windows. [00:37] So how long do you want to wait before you assume that they've abandoned their cart? [00:41] How long do you want to wait until they have sort of that window of purchase before you [00:43] reset them? [00:44] And then you can name it. [00:46] You create the audience and it does all of that logic for you under the hood. [00:50] It creates the rule. [00:51] It sets up all of that kind of stuff sort of like just in a few clicks. [00:54] So we're trying to make big steps to making things easier and easier and kind of more [00:58] prepackaged but also still have support for the complexity and the value that the CDP [01:04] can offer to an enterprise customer that wants to define everything on their own. ``` #### Key takeaways - Connect **Save Time w/ Actions** 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 — Unlock Insights w/ Reports #### Video details #### At a glance - **Title:** 29-data-insights-reports - **Duration:** 8m 54s - **Media link:** https://cdn.jwplayer.com/previews/oZ8MuLnl - **Publish date (unix):** 1752893458 #### Streaming renditions - application/vnd.apple.mpegurl - audio/mp4 · AAC Audio · 113541 kbps - video/mp4 · 180p · 180p · 134102 kbps - video/mp4 · 270p · 270p · 144724 kbps - video/mp4 · 360p · 360p · 155602 kbps - video/mp4 · 406p · 406p · 161454 kbps - video/mp4 · 540p · 540p · 183782 kbps - video/mp4 · 720p · 720p · 218070 kbps - video/mp4 · 1080p · 1080p · 313442 kbps #### Timed text tracks (delivery) - **thumbnails:** `https://cdn.jwplayer.com/strips/oZ8MuLnl-120.vtt` #### Transcript So, reports sounds simple. I would say that our reports are very different than sort of a traditional analytics tool. We're not like a Google Analytics where you're going to go in here and it's the best place to see page views and, you know, click paths and some of that kind of stuff. You can get at some of that data, but we're not an analytics tool. We're really more of an insight and personalization tool. So what our reports focus on are helping you uncover sort of new facts, new aspects, new information about users, the relationship between audiences, the things that they're interested in, that sort of stuff, far less about like how many pages have they viewed and how many sessions have they had, and like that stuff's still there, but it's not necessarily the core goal. So we'll go in and we'll create a report, and then I will show you a report that we built with Actions that shows a little bit more information. To create a report, it's super easy. You just go create a report. We only have one type right now, which is a custom report. Just name it demo. There are some controls around like privacy and sharing, so if you want to create a report only for your boss and share it with them, that stuff is kind of built in. We won't do that for now. We'll just create a new empty report, and you're presented with this blank screen. Reports are built of components, and we have four different types of components supported today. We'll show each of these other than Dataflow because it's off temporarily due to some technical challenges, but composition essentially allows you to understand and compare how your audience is composed, so you're able to go in, for instance, and say I want to create a composition report, and we'll just say we'll call it interest overview as an example. I can then go in here and say pick any number of audiences. I think it's limited to three or four right now, so we'll just choose all for demo purposes, but you could choose multiple audiences if you want to compare two audiences to each other, and then you can choose any of the fields to understand the distribution of values across those segments, across the users in those segments. One of my favorite things to demo is if you go to Linux content, which is the content scores, the interest scores, you can build a component on that, and what it's going to do is it's going to break down, obviously for Petsy, sandbox site, ignore the sort of like usefulness of the topics, but for Petsy, it's going to break down the top interest topics, the top interests essentially for each of those audiences, so in the case of the all audience, you can see that more people are interested in dogs than outdoors than parks than bulldogs and Frenchies, whatever, so again, ignore the data, it's arbitrary sort of test data, but you can think about somebody like a big customer could use this and understand not just interests across their core audience, but you can understand how interests are different between, you know, multi-purchasers versus new users who have never made a purchase, and then you can uncover maybe the overlap in topics and interests that help sort of engage them and get them to make their first purchase. That's one of the ways that you can use composition. You can do this with any of the fields, but the reason that I always demo the content is you can actually take it a step farther. If I build another component, we will just say interest, we'll just do the all audience for demo purposes, we'll do Linux content again, but if you notice, it also asks for an optional subfield, so if I go in here and put in dog, you can pull in essentially the distribution of scores for any of your topics in this case, so I can see that a lot of people are interested in dogs, but are those people just a little bit interested or are they super interested, and if they're super interested, maybe you want to target this cohort of people who are heavily interested in dogs with new dog products or whatever, so if I do the distribution on that particular topic and save it, it's going to not just show the breakdown of the top interest for the audience, it's going to actually show, and again, demo accounts, so ignore the weird data, but it's going to show the distribution of specific interest scores for that particular topic across those audiences, so you can then determine if they're high or low. You can do the same kind of a thing, but anyway, you get the idea, so it's super useful in looking at source, where they came from, it's going to show you a distribution of those values. If you have actual user data, you can do by location and understand, are the people in the US have different levels of interest than some other key origins, so composition to me are one of the most useful types of score or types of report because it allows you to really understand how the values for that particular field are distributed across users for a particular audience, it allows you to really drill in and dive. The other ones are pretty straightforward as well, so there's a size component, so if you just wanted to compare the size of, say, the all audience and the whatever frequent users audience, you can save that, and it's going to give you a breakdown of the sizes, there's a few different ways to sort of visualize this, it could be stacked, you can do hiding the trend lines, you can visualize by just numbers, so there's lots of different ways you can build your own dashboards to analyze the size and the growth and the movement. I'll show you a more pretty sort of built report, but that's what size does, it allows you to compare the size over time along with the size compared to other audiences. Audience overlap allows you to see how much the audience membership for one or more audiences overlaps with each other. So if we do like all and known, this is going to be a very silly example, but you can, so how much the known users overlap with the all audience overlap with the known users, and some of the overlap, like this is overlaps in the actual chart, but there's no user, so builds a Venn diagram that shows you the overlap, and then the cool part about all of these, maybe the most powerful part about all these reports that's different than a traditional analytics tool, is you can actually go into these, and you'll notice how it calls out the users and has a little curvy arrow, it'll actually take me into the segment builder to build an audience of the users that match that criteria, so for instance, if I wanted to go in here and just build a cohort, an audience of the users that are both known and in the all audience, again, silly example, because everybody's going to be in the all audience, I can click it, it takes me into the segment builder, and it pre-populates the rule that selects that specific group of people, so that you can then target them with emails with whatever it may be. Most analytics tools allow you to sort of get insights, activating those insights down to the individual user is extraordinarily difficult, you'd have to either export things or go look at your warehouse, or Google Analytics can't do it at all, so that's where we differentiate heavily from a traditional analytics tool, it's not so much about just like getting numbers to report on, it's getting insights and then being able to activate those insights at the individual human being level, all sort of in real time. Real quick to look at a not terrible, sort of like hacked together report, one of the actions that we've created builds an audience comparison report, so you choose any number of audiences, in this case, I just wanted to compare the 30 day profiles to anonymous profiles, the first anonymous profiles that are more than 60 days, and see how they evolve and change, this is how you can sort of visualize the size over time, this is the breakdown of the interests across those audiences, this is the overlap, and then the bottom ones are essentially a distribution of all of our behavioral scores, so you can see not just which scores are in those audiences, but how high or low particular scores are across those three audiences and compare them sort of in a stacked chart, so lots of ways that you can start to compare information, uncover insights or sort of like little facts that you can then build an audience on and activate, for instance, you know, a lot of these audience members are interested in dogs, but the interest are low, so maybe we don't want to target them with a campaign, we want to do something else that has a higher sort of per capita interest. #### Subtitles (WebVTT) ```webvtt WEBVTT 1 00:00:00.000 --> 00:00:19.480 So, reports sounds simple. 2 00:00:19.480 --> 00:00:24.240 I would say that our reports are very different than sort of a traditional analytics tool. 3 00:00:24.240 --> 00:00:27.540 We're not like a Google Analytics where you're going to go in here and it's the best place 4 00:00:27.540 --> 00:00:32.240 to see page views and, you know, click paths and some of that kind of stuff. 5 00:00:32.240 --> 00:00:35.660 You can get at some of that data, but we're not an analytics tool. 6 00:00:35.660 --> 00:00:39.500 We're really more of an insight and personalization tool. 7 00:00:39.500 --> 00:00:45.860 So what our reports focus on are helping you uncover sort of new facts, new aspects, new 8 00:00:45.860 --> 00:00:50.460 information about users, the relationship between audiences, the things that they're 9 00:00:50.460 --> 00:00:56.260 interested in, that sort of stuff, far less about like how many pages have they viewed 10 00:00:56.260 --> 00:00:58.820 and how many sessions have they had, and like that stuff's still there, but it's not 11 00:00:58.820 --> 00:01:00.980 necessarily the core goal. 12 00:01:00.980 --> 00:01:06.340 So we'll go in and we'll create a report, and then I will show you a report that we 13 00:01:06.340 --> 00:01:09.680 built with Actions that shows a little bit more information. 14 00:01:09.680 --> 00:01:12.220 To create a report, it's super easy. 15 00:01:12.220 --> 00:01:13.700 You just go create a report. 16 00:01:13.700 --> 00:01:16.700 We only have one type right now, which is a custom report. 17 00:01:16.700 --> 00:01:19.140 Just name it demo. 18 00:01:19.140 --> 00:01:22.900 There are some controls around like privacy and sharing, so if you want to create a report 19 00:01:22.900 --> 00:01:25.940 only for your boss and share it with them, that stuff is kind of built in. 20 00:01:25.940 --> 00:01:27.460 We won't do that for now. 21 00:01:27.460 --> 00:01:32.660 We'll just create a new empty report, and you're presented with this blank screen. 22 00:01:32.660 --> 00:01:38.740 Reports are built of components, and we have four different types of components supported today. 23 00:01:38.740 --> 00:01:44.380 We'll show each of these other than Dataflow because it's off temporarily due to some 24 00:01:44.380 --> 00:01:52.420 technical challenges, but composition essentially allows you to understand and compare how your 25 00:01:52.420 --> 00:01:56.900 audience is composed, so you're able to go in, for instance, and say I want to create 26 00:01:56.900 --> 00:02:02.820 a composition report, and we'll just say we'll call it interest overview as an example. 27 00:02:02.820 --> 00:02:06.340 I can then go in here and say pick any number of audiences. 28 00:02:06.340 --> 00:02:10.620 I think it's limited to three or four right now, so we'll just choose all for demo purposes, 29 00:02:10.620 --> 00:02:14.540 but you could choose multiple audiences if you want to compare two audiences to each 30 00:02:14.540 --> 00:02:20.340 other, and then you can choose any of the fields to understand the distribution of values 31 00:02:20.340 --> 00:02:24.580 across those segments, across the users in those segments. 32 00:02:24.580 --> 00:02:29.620 One of my favorite things to demo is if you go to Linux content, which is the content 33 00:02:29.620 --> 00:02:34.900 scores, the interest scores, you can build a component on that, and what it's going to 34 00:02:34.900 --> 00:02:39.060 do is it's going to break down, obviously for Petsy, sandbox site, ignore the sort of 35 00:02:39.060 --> 00:02:44.300 like usefulness of the topics, but for Petsy, it's going to break down the top interest 36 00:02:44.300 --> 00:02:49.860 topics, the top interests essentially for each of those audiences, so in the case of 37 00:02:49.860 --> 00:02:53.580 the all audience, you can see that more people are interested in dogs than outdoors than 38 00:02:53.580 --> 00:02:58.420 parks than bulldogs and Frenchies, whatever, so again, ignore the data, it's arbitrary 39 00:02:58.420 --> 00:03:04.180 sort of test data, but you can think about somebody like a big customer could use this 40 00:03:04.180 --> 00:03:08.740 and understand not just interests across their core audience, but you can understand how 41 00:03:08.740 --> 00:03:13.900 interests are different between, you know, multi-purchasers versus new users who have 42 00:03:13.900 --> 00:03:18.100 never made a purchase, and then you can uncover maybe the overlap in topics and interests 43 00:03:18.100 --> 00:03:22.300 that help sort of engage them and get them to make their first purchase. 44 00:03:22.300 --> 00:03:24.900 That's one of the ways that you can use composition. 45 00:03:24.900 --> 00:03:28.460 You can do this with any of the fields, but the reason that I always demo the content 46 00:03:28.460 --> 00:03:31.460 is you can actually take it a step farther. 47 00:03:31.460 --> 00:03:44.100 If I build another component, we will just say interest, we'll just do the all audience 48 00:03:44.100 --> 00:03:48.700 for demo purposes, we'll do Linux content again, but if you notice, it also asks for 49 00:03:48.700 --> 00:03:54.100 an optional subfield, so if I go in here and put in dog, you can pull in essentially the 50 00:03:54.100 --> 00:03:59.740 distribution of scores for any of your topics in this case, so I can see that a lot of people 51 00:03:59.740 --> 00:04:03.860 are interested in dogs, but are those people just a little bit interested or are they super 52 00:04:03.860 --> 00:04:07.220 interested, and if they're super interested, maybe you want to target this cohort of people 53 00:04:07.220 --> 00:04:13.140 who are heavily interested in dogs with new dog products or whatever, so if I do the distribution 54 00:04:13.140 --> 00:04:19.860 on that particular topic and save it, it's going to not just show the breakdown of the 55 00:04:19.860 --> 00:04:23.820 top interest for the audience, it's going to actually show, and again, demo accounts, 56 00:04:23.820 --> 00:04:28.780 so ignore the weird data, but it's going to show the distribution of specific interest 57 00:04:28.780 --> 00:04:33.220 scores for that particular topic across those audiences, so you can then determine if they're 58 00:04:33.220 --> 00:04:34.500 high or low. 59 00:04:34.500 --> 00:04:41.020 You can do the same kind of a thing, but anyway, you get the idea, so it's super useful in 60 00:04:41.220 --> 00:04:44.140 looking at source, where they came from, it's going to show you a distribution of those 61 00:04:44.140 --> 00:04:45.220 values. 62 00:04:45.220 --> 00:04:49.540 If you have actual user data, you can do by location and understand, are the people in 63 00:04:49.540 --> 00:04:56.540 the US have different levels of interest than some other key origins, so composition to 64 00:04:56.540 --> 00:05:00.700 me are one of the most useful types of score or types of report because it allows you to 65 00:05:00.700 --> 00:05:07.300 really understand how the values for that particular field are distributed across users 66 00:05:07.300 --> 00:05:10.860 for a particular audience, it allows you to really drill in and dive. 67 00:05:10.860 --> 00:05:15.260 The other ones are pretty straightforward as well, so there's a size component, so if 68 00:05:15.260 --> 00:05:21.460 you just wanted to compare the size of, say, the all audience and the whatever frequent 69 00:05:21.460 --> 00:05:26.980 users audience, you can save that, and it's going to give you a breakdown of the sizes, 70 00:05:26.980 --> 00:05:32.300 there's a few different ways to sort of visualize this, it could be stacked, you can do hiding 71 00:05:32.300 --> 00:05:36.980 the trend lines, you can visualize by just numbers, so there's lots of different ways 72 00:05:36.980 --> 00:05:41.780 you can build your own dashboards to analyze the size and the growth and the movement. 73 00:05:41.780 --> 00:05:47.140 I'll show you a more pretty sort of built report, but that's what size does, it allows 74 00:05:47.140 --> 00:05:53.860 you to compare the size over time along with the size compared to other audiences. 75 00:05:53.860 --> 00:05:58.580 Audience overlap allows you to see how much the audience membership for one or more audiences 76 00:05:58.580 --> 00:06:00.660 overlaps with each other. 77 00:06:00.660 --> 00:06:16.060 So if we do like all and known, this is going to be a very silly example, but you can, so 78 00:06:16.060 --> 00:06:22.460 how much the known users overlap with the all audience overlap with the known users, 79 00:06:22.460 --> 00:06:25.980 and some of the overlap, like this is overlaps in the actual chart, but there's no user, 80 00:06:25.980 --> 00:06:31.500 so builds a Venn diagram that shows you the overlap, and then the cool part about all 81 00:06:31.500 --> 00:06:35.100 of these, maybe the most powerful part about all these reports that's different than a 82 00:06:35.100 --> 00:06:40.020 traditional analytics tool, is you can actually go into these, and you'll notice how it calls 83 00:06:40.020 --> 00:06:44.060 out the users and has a little curvy arrow, it'll actually take me into the segment builder 84 00:06:44.060 --> 00:06:49.180 to build an audience of the users that match that criteria, so for instance, if I wanted 85 00:06:49.180 --> 00:06:53.940 to go in here and just build a cohort, an audience of the users that are both known 86 00:06:53.940 --> 00:06:57.540 and in the all audience, again, silly example, because everybody's going to be in the all 87 00:06:57.540 --> 00:07:02.580 audience, I can click it, it takes me into the segment builder, and it pre-populates 88 00:07:02.580 --> 00:07:07.260 the rule that selects that specific group of people, so that you can then target them 89 00:07:07.260 --> 00:07:10.260 with emails with whatever it may be. 90 00:07:10.260 --> 00:07:15.340 Most analytics tools allow you to sort of get insights, activating those insights down 91 00:07:15.340 --> 00:07:20.180 to the individual user is extraordinarily difficult, you'd have to either export things 92 00:07:20.220 --> 00:07:26.060 or go look at your warehouse, or Google Analytics can't do it at all, so that's where we differentiate 93 00:07:26.060 --> 00:07:30.100 heavily from a traditional analytics tool, it's not so much about just like getting numbers 94 00:07:30.100 --> 00:07:35.540 to report on, it's getting insights and then being able to activate those insights at the 95 00:07:35.540 --> 00:07:40.780 individual human being level, all sort of in real time. 96 00:07:40.780 --> 00:07:45.660 Real quick to look at a not terrible, sort of like hacked together report, one of the 97 00:07:45.660 --> 00:07:51.580 actions that we've created builds an audience comparison report, so you choose any number 98 00:07:51.580 --> 00:07:55.660 of audiences, in this case, I just wanted to compare the 30 day profiles to anonymous 99 00:07:55.660 --> 00:08:00.340 profiles, the first anonymous profiles that are more than 60 days, and see how they evolve 100 00:08:00.340 --> 00:08:06.140 and change, this is how you can sort of visualize the size over time, this is the breakdown 101 00:08:06.140 --> 00:08:13.180 of the interests across those audiences, this is the overlap, and then the bottom ones are 102 00:08:13.180 --> 00:08:17.980 essentially a distribution of all of our behavioral scores, so you can see not just 103 00:08:17.980 --> 00:08:23.140 which scores are in those audiences, but how high or low particular scores are across those 104 00:08:23.140 --> 00:08:27.660 three audiences and compare them sort of in a stacked chart, so lots of ways that you 105 00:08:27.660 --> 00:08:32.540 can start to compare information, uncover insights or sort of like little facts that 106 00:08:32.540 --> 00:08:36.860 you can then build an audience on and activate, for instance, you know, a lot of these audience 107 00:08:36.860 --> 00:08:40.020 members are interested in dogs, but the interest are low, so maybe we don't want to target 108 00:08:40.020 --> 00:08:44.340 them with a campaign, we want to do something else that has a higher sort of per capita interest. ``` ```transcript [00:00] So, reports sounds simple. [00:19] I would say that our reports are very different than sort of a traditional analytics tool. [00:24] We're not like a Google Analytics where you're going to go in here and it's the best place [00:27] to see page views and, you know, click paths and some of that kind of stuff. [00:32] You can get at some of that data, but we're not an analytics tool. [00:35] We're really more of an insight and personalization tool. [00:39] So what our reports focus on are helping you uncover sort of new facts, new aspects, new [00:45] information about users, the relationship between audiences, the things that they're [00:50] interested in, that sort of stuff, far less about like how many pages have they viewed [00:56] and how many sessions have they had, and like that stuff's still there, but it's not [00:58] necessarily the core goal. [01:00] So we'll go in and we'll create a report, and then I will show you a report that we [01:06] built with Actions that shows a little bit more information. [01:09] To create a report, it's super easy. [01:12] You just go create a report. [01:13] We only have one type right now, which is a custom report. [01:16] Just name it demo. [01:19] There are some controls around like privacy and sharing, so if you want to create a report [01:22] only for your boss and share it with them, that stuff is kind of built in. [01:25] We won't do that for now. [01:27] We'll just create a new empty report, and you're presented with this blank screen. [01:32] Reports are built of components, and we have four different types of components supported today. [01:38] We'll show each of these other than Dataflow because it's off temporarily due to some [01:44] technical challenges, but composition essentially allows you to understand and compare how your [01:52] audience is composed, so you're able to go in, for instance, and say I want to create [01:56] a composition report, and we'll just say we'll call it interest overview as an example. [02:02] I can then go in here and say pick any number of audiences. [02:06] I think it's limited to three or four right now, so we'll just choose all for demo purposes, [02:10] but you could choose multiple audiences if you want to compare two audiences to each [02:14] other, and then you can choose any of the fields to understand the distribution of values [02:20] across those segments, across the users in those segments. [02:24] One of my favorite things to demo is if you go to Linux content, which is the content [02:29] scores, the interest scores, you can build a component on that, and what it's going to [02:34] do is it's going to break down, obviously for Petsy, sandbox site, ignore the sort of [02:39] like usefulness of the topics, but for Petsy, it's going to break down the top interest [02:44] topics, the top interests essentially for each of those audiences, so in the case of [02:49] the all audience, you can see that more people are interested in dogs than outdoors than [02:53] parks than bulldogs and Frenchies, whatever, so again, ignore the data, it's arbitrary [02:58] sort of test data, but you can think about somebody like a big customer could use this [03:04] and understand not just interests across their core audience, but you can understand how [03:08] interests are different between, you know, multi-purchasers versus new users who have [03:13] never made a purchase, and then you can uncover maybe the overlap in topics and interests [03:18] that help sort of engage them and get them to make their first purchase. [03:22] That's one of the ways that you can use composition. [03:24] You can do this with any of the fields, but the reason that I always demo the content [03:28] is you can actually take it a step farther. [03:31] If I build another component, we will just say interest, we'll just do the all audience [03:44] for demo purposes, we'll do Linux content again, but if you notice, it also asks for [03:48] an optional subfield, so if I go in here and put in dog, you can pull in essentially the [03:54] distribution of scores for any of your topics in this case, so I can see that a lot of people [03:59] are interested in dogs, but are those people just a little bit interested or are they super [04:03] interested, and if they're super interested, maybe you want to target this cohort of people [04:07] who are heavily interested in dogs with new dog products or whatever, so if I do the distribution [04:13] on that particular topic and save it, it's going to not just show the breakdown of the [04:19] top interest for the audience, it's going to actually show, and again, demo accounts, [04:23] so ignore the weird data, but it's going to show the distribution of specific interest [04:28] scores for that particular topic across those audiences, so you can then determine if they're [04:33] high or low. [04:34] You can do the same kind of a thing, but anyway, you get the idea, so it's super useful in [04:41] looking at source, where they came from, it's going to show you a distribution of those ``` #### Key takeaways - Connect **Unlock Insights w/ Reports** 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 — Web Campaign Personalization SDK #### Video details #### At a glance - **Title:** 30-data-insights-pathfora-sdk - **Duration:** 3m 32s - **Media link:** https://cdn.jwplayer.com/previews/TVahcmxA - **Publish date (unix):** 1752893501 #### Streaming renditions - application/vnd.apple.mpegurl - audio/mp4 · AAC Audio · 113545 kbps - video/mp4 · 180p · 180p · 135576 kbps - video/mp4 · 270p · 270p · 148797 kbps - video/mp4 · 360p · 360p · 159979 kbps - video/mp4 · 406p · 406p · 168022 kbps - video/mp4 · 540p · 540p · 193598 kbps - video/mp4 · 720p · 720p · 235130 kbps - video/mp4 · 1080p · 1080p · 346780 kbps #### Timed text tracks (delivery) - **thumbnails:** `https://cdn.jwplayer.com/strips/TVahcmxA-120.vtt` #### Transcript Here's what in our UI we call experiences, the SDK under the hood that powers them is called Pathfora. And then in WordPress and Drupal, they're called widgets. It's all fundamentally the same technology, what it allows you to do. So it's built on the back of our web personalization SDK, which I'm not sure if anybody has seen this and played with it. But Pathfora is just like a pure JavaScript SDK that allows you to surface campaigns on the site super easily. So you don't have to actually go into the source code and create a bunch of things and it doesn't require a huge lift. It is without a doubt one of our most popular features because of the ease of use. It allows you to do things like you've seen probably a dozen times as I've demoed Petsy. This little lead capture in the bottom left corner is powered by Pathfora. So it's just like layered on top. This one is on every single page view, but how you would use it is you would only show that lead capture to users that are unknown, right, as a proxy to sort of gather their email address. It automatically collects inside of Linux when you actually submit those forms and whatnot. So this is one of the things that's powered by Pathfora, but Pathfora can do a lot of different things. So there's examples on here that we can kind of run through depending on time, but you essentially can like surface a modal in the middle of the screen and you can customize the styling and all that kind of stuff to your sort of heart's content. The examples on this demo site are pretty sort of like default. The modal is, so there's basically there's messages, there's forms, there's subscriptions and there's gates. The message is just being able to surface a message on the screen. You can do a bunch of different layouts. There's the modal in the front. There's the slide out in the bottom left. There's this sort of bar at the top, buttons. You can even do inline where Pathfora goes and replaces or injects it into an HTML element like a class selector that you choose. The, without a doubt, the most popular are messages because it allows you to do a sort of promotion or forms, which are essentially lead capture. So as an end customer, I can go in here and we'll walk through some examples and it'll make a little bit more sense, but Linux automatically installs and loads Pathfora for you. And then if I were to go, for instance, to Petsy and just copy this configuration, which is just a simple form, it's going to say, sign up as my headline. The message is going to be submit this form and it's just going to use the default fields. You can customize all the fields, build your own form, whatever you want to do. But just as an example, like if I close this, open my console and paste that. So we do a lot of this stuff automatically, but you can go in and just do it with JavaScript, use Pathfora, trigger this modal. And then if I were to fill in this information and submit it, it's already kind of pre-wired to collect into Linux. So it's going to handle the jstag.send call for you. It's going to send the email, the name, all that stuff. It's already pre-mapped in the common schema. So it makes collecting data and doing things like lead captures super, super simple. #### Subtitles (WebVTT) ```webvtt WEBVTT 1 00:00:00.000 --> 00:00:23.740 Here's what in our UI we call experiences, the SDK under the hood that powers them is 2 00:00:23.740 --> 00:00:25.920 called Pathfora. 3 00:00:25.920 --> 00:00:30.600 And then in WordPress and Drupal, they're called widgets. 4 00:00:30.600 --> 00:00:34.160 It's all fundamentally the same technology, what it allows you to do. 5 00:00:34.160 --> 00:00:38.920 So it's built on the back of our web personalization SDK, which I'm not sure if anybody has seen 6 00:00:38.920 --> 00:00:39.960 this and played with it. 7 00:00:39.960 --> 00:00:45.880 But Pathfora is just like a pure JavaScript SDK that allows you to surface campaigns on 8 00:00:45.880 --> 00:00:47.880 the site super easily. 9 00:00:47.880 --> 00:00:50.760 So you don't have to actually go into the source code and create a bunch of things and 10 00:00:50.760 --> 00:00:52.200 it doesn't require a huge lift. 11 00:00:52.200 --> 00:00:57.200 It is without a doubt one of our most popular features because of the ease of use. 12 00:00:57.200 --> 00:01:01.840 It allows you to do things like you've seen probably a dozen times as I've demoed Petsy. 13 00:01:01.840 --> 00:01:06.400 This little lead capture in the bottom left corner is powered by Pathfora. 14 00:01:06.400 --> 00:01:09.440 So it's just like layered on top. 15 00:01:09.440 --> 00:01:13.720 This one is on every single page view, but how you would use it is you would only show 16 00:01:13.720 --> 00:01:17.600 that lead capture to users that are unknown, right, as a proxy to sort of gather their 17 00:01:17.600 --> 00:01:18.880 email address. 18 00:01:18.880 --> 00:01:23.120 It automatically collects inside of Linux when you actually submit those forms and whatnot. 19 00:01:23.120 --> 00:01:28.000 So this is one of the things that's powered by Pathfora, but Pathfora can do a lot of 20 00:01:28.000 --> 00:01:29.000 different things. 21 00:01:29.000 --> 00:01:35.440 So there's examples on here that we can kind of run through depending on time, but you 22 00:01:35.440 --> 00:01:38.760 essentially can like surface a modal in the middle of the screen and you can customize 23 00:01:38.760 --> 00:01:42.720 the styling and all that kind of stuff to your sort of heart's content. 24 00:01:42.720 --> 00:01:47.280 The examples on this demo site are pretty sort of like default. 25 00:01:47.280 --> 00:01:53.280 The modal is, so there's basically there's messages, there's forms, there's subscriptions 26 00:01:53.280 --> 00:01:54.720 and there's gates. 27 00:01:54.720 --> 00:01:59.280 The message is just being able to surface a message on the screen. 28 00:01:59.280 --> 00:02:01.920 You can do a bunch of different layouts. 29 00:02:01.920 --> 00:02:03.520 There's the modal in the front. 30 00:02:03.520 --> 00:02:05.080 There's the slide out in the bottom left. 31 00:02:05.080 --> 00:02:07.960 There's this sort of bar at the top, buttons. 32 00:02:07.960 --> 00:02:13.160 You can even do inline where Pathfora goes and replaces or injects it into an HTML element 33 00:02:13.160 --> 00:02:17.040 like a class selector that you choose. 34 00:02:17.560 --> 00:02:22.760 The, without a doubt, the most popular are messages because it allows you to do a sort 35 00:02:22.760 --> 00:02:25.720 of promotion or forms, which are essentially lead capture. 36 00:02:25.720 --> 00:02:30.320 So as an end customer, I can go in here and we'll walk through some examples and it'll 37 00:02:30.320 --> 00:02:34.920 make a little bit more sense, but Linux automatically installs and loads Pathfora for you. 38 00:02:34.920 --> 00:02:39.440 And then if I were to go, for instance, to Petsy and just copy this configuration, which 39 00:02:39.440 --> 00:02:43.720 is just a simple form, it's going to say, sign up as my headline. 40 00:02:43.720 --> 00:02:46.760 The message is going to be submit this form and it's just going to use the default fields. 41 00:02:46.760 --> 00:02:51.560 You can customize all the fields, build your own form, whatever you want to do. 42 00:02:51.560 --> 00:02:57.360 But just as an example, like if I close this, open my console and paste that. 43 00:02:57.360 --> 00:03:02.520 So we do a lot of this stuff automatically, but you can go in and just do it with JavaScript, 44 00:03:02.520 --> 00:03:04.560 use Pathfora, trigger this modal. 45 00:03:04.560 --> 00:03:08.640 And then if I were to fill in this information and submit it, it's already kind of pre-wired 46 00:03:08.640 --> 00:03:10.360 to collect into Linux. 47 00:03:10.360 --> 00:03:12.600 So it's going to handle the jstag.send call for you. 48 00:03:12.600 --> 00:03:15.160 It's going to send the email, the name, all that stuff. 49 00:03:15.160 --> 00:03:17.840 It's already pre-mapped in the common schema. 50 00:03:17.840 --> 00:03:23.000 So it makes collecting data and doing things like lead captures super, super simple. ``` ```transcript [00:00] Here's what in our UI we call experiences, the SDK under the hood that powers them is [00:23] called Pathfora. [00:25] And then in WordPress and Drupal, they're called widgets. [00:30] It's all fundamentally the same technology, what it allows you to do. [00:34] So it's built on the back of our web personalization SDK, which I'm not sure if anybody has seen [00:38] this and played with it. [00:39] But Pathfora is just like a pure JavaScript SDK that allows you to surface campaigns on [00:45] the site super easily. [00:47] So you don't have to actually go into the source code and create a bunch of things and [00:50] it doesn't require a huge lift. [00:52] It is without a doubt one of our most popular features because of the ease of use. [00:57] It allows you to do things like you've seen probably a dozen times as I've demoed Petsy. [01:01] This little lead capture in the bottom left corner is powered by Pathfora. [01:06] So it's just like layered on top. [01:09] This one is on every single page view, but how you would use it is you would only show [01:13] that lead capture to users that are unknown, right, as a proxy to sort of gather their [01:17] email address. [01:18] It automatically collects inside of Linux when you actually submit those forms and whatnot. [01:23] So this is one of the things that's powered by Pathfora, but Pathfora can do a lot of [01:28] different things. [01:29] So there's examples on here that we can kind of run through depending on time, but you [01:35] essentially can like surface a modal in the middle of the screen and you can customize [01:38] the styling and all that kind of stuff to your sort of heart's content. [01:42] The examples on this demo site are pretty sort of like default. [01:47] The modal is, so there's basically there's messages, there's forms, there's subscriptions [01:53] and there's gates. [01:54] The message is just being able to surface a message on the screen. [01:59] You can do a bunch of different layouts. [02:01] There's the modal in the front. [02:03] There's the slide out in the bottom left. [02:05] There's this sort of bar at the top, buttons. [02:07] You can even do inline where Pathfora goes and replaces or injects it into an HTML element [02:13] like a class selector that you choose. [02:17] The, without a doubt, the most popular are messages because it allows you to do a sort [02:22] of promotion or forms, which are essentially lead capture. [02:25] So as an end customer, I can go in here and we'll walk through some examples and it'll [02:30] make a little bit more sense, but Linux automatically installs and loads Pathfora for you. [02:34] And then if I were to go, for instance, to Petsy and just copy this configuration, which [02:39] is just a simple form, it's going to say, sign up as my headline. [02:43] The message is going to be submit this form and it's just going to use the default fields. [02:46] You can customize all the fields, build your own form, whatever you want to do. [02:51] But just as an example, like if I close this, open my console and paste that. [02:57] So we do a lot of this stuff automatically, but you can go in and just do it with JavaScript, [03:02] use Pathfora, trigger this modal. [03:04] And then if I were to fill in this information and submit it, it's already kind of pre-wired [03:08] to collect into Linux. [03:10] So it's going to handle the jstag.send call for you. [03:12] It's going to send the email, the name, all that stuff. [03:15] It's already pre-mapped in the common schema. [03:17] So it makes collecting data and doing things like lead captures super, super simple. ``` #### Key takeaways - Connect **Web Campaign Personalization SDK** 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 08 — Streamline Campaigns w/ Experiences #### Video details #### At a glance - **Title:** 31-data-insights-experiences - **Duration:** 2m 58s - **Media link:** https://cdn.jwplayer.com/previews/dRHImNo3 - **Publish date (unix):** 1752893520 #### Streaming renditions - application/vnd.apple.mpegurl - audio/mp4 · AAC Audio · 114054 kbps - video/mp4 · 180p · 180p · 132277 kbps - video/mp4 · 270p · 270p · 141890 kbps - video/mp4 · 360p · 360p · 149083 kbps - video/mp4 · 406p · 406p · 154030 kbps - video/mp4 · 540p · 540p · 170857 kbps - video/mp4 · 720p · 720p · 197197 kbps - video/mp4 · 1080p · 1080p · 274857 kbps #### Timed text tracks (delivery) - **thumbnails:** `https://cdn.jwplayer.com/strips/dRHImNo3-120.vtt` #### Transcript But what it allows you to do is instead of going into the raw path for a library and doing JavaScript stuff, you can just go in here and add a new experience. We have some predefined examples. If you just want to drive traffic, I want to capture leads, I want to present a message, I want to recommend content. We'll just do drive traffic for a simple one. You can say the URL you want to target, let's do petsy.linux.com, and then anyway, it'll walk you through a wizard of, okay, well, where do you want it to be? I want it to be a slide at the bottom left, and I want to change my headline to purple, whatever, sample headline, sample body. You can change your call to action, you can change the positioning. You choose the audience that you want to target. So I'll just do all for this one, but it has the targeting against the Linux audiences built-in automatically. So it makes it simple to only show specific offers, promotions, lead captures to predefined cohorts that you have in your account. Then there's a number of customization options on like I want to show it only on the first page view. I want to show it after five seconds. I want to hide it after five seconds. I want to show it on 30 percent page scroll or whatever percentage I want. I want to show it basically infinite configurability all the way down till we have an override where you can write code to overwrite it, to do a lot of different things, to tailor it to whatever that customer wants. The end result though, if I hit preview and go to petsy.linux.com, in theory, so now instead of seeing the lead capture, you see my very ugly pink headline sample model. So it's a really, really simple low-lift way to present promotions. We have it built into our content recommendation library. So you can just make a recommendation that pops up. You don't have to go in and talk to your web developer and launch new source code. You can just plop it on top. Like I said, you can put it in your tag manager, you can put it into your source code. It's super, super flexible, but it's without a doubt one of the most common ways to get started just because it is such a low-lift thing. The forms make it dead simple to collect data and that it already just gets mapped, and it's already just going to come into Linux. You don't have to do any sending, you don't have to do any mapping. So those are the biggest features. So that's experiences in our UI. #### Subtitles (WebVTT) ```webvtt WEBVTT 1 00:00:00.000 --> 00:00:18.720 But what it allows you to do is instead of going into the raw 2 00:00:18.720 --> 00:00:21.160 path for a library and doing JavaScript stuff, 3 00:00:21.160 --> 00:00:25.040 you can just go in here and add a new experience. 4 00:00:25.040 --> 00:00:28.400 We have some predefined examples. 5 00:00:28.400 --> 00:00:29.480 If you just want to drive traffic, 6 00:00:29.480 --> 00:00:31.240 I want to capture leads, I want to present a message, 7 00:00:31.240 --> 00:00:32.600 I want to recommend content. 8 00:00:32.600 --> 00:00:35.600 We'll just do drive traffic for a simple one. 9 00:00:35.600 --> 00:00:38.840 You can say the URL you want to target, 10 00:00:38.840 --> 00:00:43.200 let's do petsy.linux.com, 11 00:00:43.200 --> 00:00:48.800 and then anyway, 12 00:00:48.800 --> 00:00:49.880 it'll walk you through a wizard of, 13 00:00:49.880 --> 00:00:51.200 okay, well, where do you want it to be? 14 00:00:51.200 --> 00:00:53.120 I want it to be a slide at the bottom left, 15 00:00:53.120 --> 00:00:56.360 and I want to change my headline to purple, 16 00:00:56.360 --> 00:01:02.280 whatever, sample headline, sample body. 17 00:01:02.280 --> 00:01:03.920 You can change your call to action, 18 00:01:03.920 --> 00:01:06.080 you can change the positioning. 19 00:01:06.080 --> 00:01:09.000 You choose the audience that you want to target. 20 00:01:09.000 --> 00:01:10.240 So I'll just do all for this one, 21 00:01:10.240 --> 00:01:11.960 but it has the targeting against 22 00:01:11.960 --> 00:01:14.320 the Linux audiences built-in automatically. 23 00:01:14.320 --> 00:01:17.600 So it makes it simple to only show specific offers, 24 00:01:17.600 --> 00:01:19.560 promotions, lead captures to 25 00:01:19.560 --> 00:01:22.520 predefined cohorts that you have in your account. 26 00:01:22.520 --> 00:01:26.160 Then there's a number of customization options 27 00:01:26.160 --> 00:01:28.200 on like I want to show it only on the first page view. 28 00:01:28.200 --> 00:01:29.640 I want to show it after five seconds. 29 00:01:29.640 --> 00:01:31.040 I want to hide it after five seconds. 30 00:01:31.040 --> 00:01:32.600 I want to show it on 31 00:01:32.600 --> 00:01:35.160 30 percent page scroll or whatever percentage I want. 32 00:01:35.160 --> 00:01:39.960 I want to show it basically infinite configurability 33 00:01:39.960 --> 00:01:41.800 all the way down till we have an override 34 00:01:41.800 --> 00:01:43.880 where you can write code to overwrite it, 35 00:01:43.880 --> 00:01:46.040 to do a lot of different things, 36 00:01:46.040 --> 00:01:48.720 to tailor it to whatever that customer wants. 37 00:01:48.720 --> 00:01:50.160 The end result though, 38 00:01:50.160 --> 00:01:55.680 if I hit preview and go to petsy.linux.com, 39 00:01:56.080 --> 00:02:05.080 in theory, so now instead of seeing the lead capture, 40 00:02:05.080 --> 00:02:07.880 you see my very ugly pink headline sample model. 41 00:02:07.880 --> 00:02:09.080 So it's a really, 42 00:02:09.080 --> 00:02:12.040 really simple low-lift way to present promotions. 43 00:02:12.040 --> 00:02:14.880 We have it built into our content recommendation library. 44 00:02:14.880 --> 00:02:16.800 So you can just make a recommendation that pops up. 45 00:02:16.800 --> 00:02:18.240 You don't have to go in and talk to 46 00:02:18.240 --> 00:02:20.720 your web developer and launch new source code. 47 00:02:20.720 --> 00:02:23.720 You can just plop it on top. 48 00:02:23.720 --> 00:02:25.720 Like I said, you can put it in your tag manager, 49 00:02:25.720 --> 00:02:26.720 you can put it into your source code. 50 00:02:26.720 --> 00:02:28.080 It's super, super flexible, 51 00:02:28.080 --> 00:02:30.040 but it's without a doubt one of 52 00:02:30.040 --> 00:02:31.840 the most common ways to get started 53 00:02:31.840 --> 00:02:34.560 just because it is such a low-lift thing. 54 00:02:34.560 --> 00:02:37.400 The forms make it dead simple to collect 55 00:02:37.400 --> 00:02:39.720 data and that it already just gets mapped, 56 00:02:39.720 --> 00:02:40.960 and it's already just going to come into Linux. 57 00:02:40.960 --> 00:02:42.560 You don't have to do any sending, 58 00:02:42.560 --> 00:02:43.840 you don't have to do any mapping. 59 00:02:43.840 --> 00:02:46.560 So those are the biggest features. 60 00:02:46.560 --> 00:02:50.640 So that's experiences in our UI. ``` ```transcript [00:00] But what it allows you to do is instead of going into the raw [00:18] path for a library and doing JavaScript stuff, [00:21] you can just go in here and add a new experience. [00:25] We have some predefined examples. [00:28] If you just want to drive traffic, [00:29] I want to capture leads, I want to present a message, [00:31] I want to recommend content. [00:32] We'll just do drive traffic for a simple one. [00:35] You can say the URL you want to target, [00:38] let's do petsy.linux.com, [00:43] and then anyway, [00:48] it'll walk you through a wizard of, [00:49] okay, well, where do you want it to be? [00:51] I want it to be a slide at the bottom left, [00:53] and I want to change my headline to purple, [00:56] whatever, sample headline, sample body. [01:02] You can change your call to action, [01:03] you can change the positioning. [01:06] You choose the audience that you want to target. [01:09] So I'll just do all for this one, [01:10] but it has the targeting against [01:11] the Linux audiences built-in automatically. [01:14] So it makes it simple to only show specific offers, [01:17] promotions, lead captures to [01:19] predefined cohorts that you have in your account. [01:22] Then there's a number of customization options [01:26] on like I want to show it only on the first page view. [01:28] I want to show it after five seconds. [01:29] I want to hide it after five seconds. [01:31] I want to show it on [01:32] 30 percent page scroll or whatever percentage I want. [01:35] I want to show it basically infinite configurability [01:39] all the way down till we have an override [01:41] where you can write code to overwrite it, [01:43] to do a lot of different things, [01:46] to tailor it to whatever that customer wants. [01:48] The end result though, [01:50] if I hit preview and go to petsy.linux.com, [01:56] in theory, so now instead of seeing the lead capture, [02:05] you see my very ugly pink headline sample model. [02:07] So it's a really, [02:09] really simple low-lift way to present promotions. [02:12] We have it built into our content recommendation library. [02:14] So you can just make a recommendation that pops up. [02:16] You don't have to go in and talk to [02:18] your web developer and launch new source code. [02:20] You can just plop it on top. [02:23] Like I said, you can put it in your tag manager, [02:25] you can put it into your source code. [02:26] It's super, super flexible, [02:28] but it's without a doubt one of [02:30] the most common ways to get started [02:31] just because it is such a low-lift thing. [02:34] The forms make it dead simple to collect [02:37] data and that it already just gets mapped, [02:39] and it's already just going to come into Linux. [02:40] You don't have to do any sending, [02:42] you don't have to do any mapping. [02:43] So those are the biggest features. [02:46] So that's experiences in our UI. ``` #### Key takeaways - Connect **Streamline Campaigns w/ Experiences** 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 09 — Data Insights: Using Profiles Quiz #### Lesson text **This lesson is a knowledge check hosted in the Academy LMS.** This companion Markdown contains **no quiz questions, answers, scoring rules, or explanations**. #### Key takeaways - Connect **Data Insights: Using Profiles Quiz** 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/data-insights-using-profiles-to-power-personalization/data-insights-course-4--building-an-audience | /academy/md/courses/data-insights-using-profiles-to-power-personalization/data-insights-course-4--building-an-audience.md | | /courses/data-insights-using-profiles-to-power-personalization/data-insights-course-4--audience-mechanics | /academy/md/courses/data-insights-using-profiles-to-power-personalization/data-insights-course-4--audience-mechanics.md | | /courses/data-insights-using-profiles-to-power-personalization/data-insights-course-4--leverage-warehouse-data-in-audiences | /academy/md/courses/data-insights-using-profiles-to-power-personalization/data-insights-course-4--leverage-warehouse-data-in-audiences.md | | /courses/data-insights-using-profiles-to-power-personalization/data-insights-course-4--activating-audiences | /academy/md/courses/data-insights-using-profiles-to-power-personalization/data-insights-course-4--activating-audiences.md | | /courses/data-insights-using-profiles-to-power-personalization/data-insights-course-4--save-time-with-actions | /academy/md/courses/data-insights-using-profiles-to-power-personalization/data-insights-course-4--save-time-with-actions.md | | /courses/data-insights-using-profiles-to-power-personalization/data-insights-course-4--unlock-insights-with-reports | /academy/md/courses/data-insights-using-profiles-to-power-personalization/data-insights-course-4--unlock-insights-with-reports.md | | /courses/data-insights-using-profiles-to-power-personalization/data-insights-course-4--web-campaign-personalization-sdk | /academy/md/courses/data-insights-using-profiles-to-power-personalization/data-insights-course-4--web-campaign-personalization-sdk.md | | /courses/data-insights-using-profiles-to-power-personalization/data-insights-course-4--streamline-campaigns-with-experiences | /academy/md/courses/data-insights-using-profiles-to-power-personalization/data-insights-course-4--streamline-campaigns-with-experiences.md | | /courses/data-insights-using-profiles-to-power-personalization/data-insights-course-4--quiz | /academy/md/courses/data-insights-using-profiles-to-power-personalization/data-insights-course-4--quiz.md | ## Supplement for indexing ### Content summary This course focuses on putting your unified customer profiles to work through sophisticated audience building and personalization capabilities. You'll learn to create dynamic, real-time udiences and deploy personalized e… This course focuses on putting your unified customer profiles to work through sophisticated audience building and personalization capabilities. You'll learn to create dynamic, real-time udiences and deploy personalized experiences across multiple channels. What You'll Learn This hands-on session teaches you to transform unified profiles into actionable marketing campaigns through: advanced audience segmentation cross-channel activation web personalization. You'll master the tools needed to deliver relevant, personalized experiences at scale. What We'll Cover We'll start with building sophisticated audiences using real-time computed attributes, including complex time-based logic for use cases like cart abandonment and rule sets with AND/OR logic for precise targeting. You'll learn how our audiences differ from traditional static lists by function ### Retrieval tags - Contentstack Academy - data-insights-using-profiles-to-power-personalization - Building - Audience - Mechanics - Leverage - Warehouse - Data - Audiences - Activating - Save - Time - Actions - Unlock ### 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: data-insights-using-profiles-to-power-personalization. Union of lesson topic tokens: Building, Audience, Mechanics, Leverage, Warehouse, Data, Audiences, Activating, Save, Time, Actions, Unlock, Insights, Reports, Web, Campaign, Personalization, SDK, Streamline, Campaigns, Experiences, Using, Profiles, Quiz. Do not embed or retrieve LMS-only quiz items or mastery exam answer keys from this export. ### Asset references | Label | URL | | --- | --- | | Video thumbnail: Building an Audience | `https://cdn.jwplayer.com/v2/media/LVm9uAFn/poster.jpg?width=720` | | Video thumbnail: Audience Mechanics | `https://cdn.jwplayer.com/v2/media/XqZ5gtQA/poster.jpg?width=720` | | Video thumbnail: Leverage Warehouse Data in Audiences | `https://cdn.jwplayer.com/v2/media/ti1OfDR6/poster.jpg?width=720` | | Video thumbnail: Activating Audiences | `https://cdn.jwplayer.com/v2/media/rczEmn3z/poster.jpg?width=720` | | Video thumbnail: Save Time w/ Actions | `https://cdn.jwplayer.com/v2/media/mlweezyZ/poster.jpg?width=720` | | Video thumbnail: Unlock Insights w/ Reports | `https://cdn.jwplayer.com/v2/media/oZ8MuLnl/poster.jpg?width=720` | | Video thumbnail: Web Campaign Personalization SDK | `https://cdn.jwplayer.com/v2/media/TVahcmxA/poster.jpg?width=720` | | Video thumbnail: Streamline Campaigns w/ Experiences | `https://cdn.jwplayer.com/v2/media/dRHImNo3/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/` |