[Music] [Travis Sabin] Thank you for joining us today. This is the Analytics Madness: Tips and Tricks session for Making the Final Four. My name is Travis Sabin. I'm a Product Manager on the Adobe Analytics team. I work primarily on Workspace and the frontend visualizations and things like that. So hopefully this is the session you're signed up for, wanting to be at. If it's not, you'll have a good time anyways, but thanks for joining us. Everybody should have got a handout, or if you didn't get a handout, they might have run out. A chance to scan the QR code. There's a chance to win money during this session. So if you want to win some money, fill out a little bracket, in terms of which features you think might win today as we're going through some of these tips and tricks that we got from the product. So today we're going to be going through The Tantalizing Twelve. We have 12 features that we're going to talk through from four different regions, and I'll highlight each of them as we go through them. And then after each region, you will, as an audience, vote on which one is your favorite. And that'll be that region winner. And then at the end, we'll have a final four, and then we'll vote on the final four to see who our overall champion is. This is very much in the theme obviously of March Madness, we're in that time of year, basketball, college basketball is great. Who's got a decent bracket going right now? I'm very proud of you. Like, mine is totally trash. Whose is busted? Probably the rest of you. Okay. We had a great weekend at college basketball this last weekend, so hopefully you watched. I love college basketball, and this very much steals from that theme. So, hopefully we'll have some fun today. Again, it'll be very interactive, so have your phones out, ready to engage and participate. I like to move around, so don't get nervous or worried. I'm not going to pull you on stage. This isn't a show in Vegas, but I like to walk around when I'm talking because otherwise I get antsy on the stage and it's too restrictive. So for our session today, here are the four things that we're hoping to accomplish. One, understand the latest features that will make it easier for you or the stakeholders you work with to start or continue your analysis within Adobe Analytics. Two, empower your users to get rich insights faster than ever before and within their existing workflows without taking them out of the context of what they might normally be doing. Three, getting your data exactly where and how you want it for more streamlined analysis. And then, four, we're going to do a sneak peek at some stuff that we're working on that will be coming hopefully here in the near future. I did this session last year, so anybody who was here last year, you kind of know how it goes. It's very similar. The features are different, and what we're going to talk about is a little bit different, but the structure is very much the same, so hopefully, last year you had a good time, but we'll hopefully have a good session here today as well. The Utility Regional.
So we got three features here. They're all about making your life easier and more useful and getting in and doing what you need to do a little bit faster. So the first one is kind of a hybrid. It's two features packed in one. They're simple, but they're effective. There are two navigational shortcuts that we've built into the product. So previously, when you wanted to add a new viz to your project panel, you had to open up the viz library, drag and drop it directly on, which is fine. That's still a good way to do it. But this last year, we added a little Viz Plus button at the very bottom of the panel. So you can quickly click on that and select the one you want and it immediately is added to a canvas, so without having to move your mouse around a whole bunch to drag and drop that on. So we've added most of the visualizations that we have in the viz rail on the little plus button there. So you can quickly add anything that you want really quickly and easily right onto the canvas, without having to move your mouse too far away and forget what you're even looking for when you start moving the mouse over there. The next is this sorting mechanism. Previously, the left rail was always sorted by our recommendation. You can now change it to be categorical. So if you're looking for a calc metric or one of our Adobe provided metrics, you can quickly sort by those and find the one you're looking for. Or you can change it to an alpha sort. And let's say you don't remember exactly what the name of a component is, but you remember it might start with the letter A or B, or whatever it might be. You can more easily scroll through that list and see them alphabetized to find exactly what you're looking for. So I wanted advertiser. I found it because I was able to sort by that, and now I can drag and drop it directly on the canvas. So those are two relatively simple but pretty straightforward things that we've done, just to make it a little bit easier to navigate around the product and find exactly what you're looking for a little bit faster than maybe before. So that's number one, navigational shortcuts. Number two, Dynamic Row Deletion. Another probably small feature in some people's eyes, but really, really powerful. So before, when you had a set of data, maybe you have a specific, in this case, an item that is throwing off your data because it's just so much more data than everything else. In order to get rid of that, you have to open up the filter rail and filter it out. But now, we've added this X that you can just click on, and it'll automatically get rid of that row really quickly. And so if you've got a bunch of data that you don't want in that table, you just click all those Xs and they're immediately gone. And then your data totals automatically update with what the remaining values that you have there. If you want to add it back, you just open up the filter and you just remove it from the exclude list, and it's automatically added back. And you can see it's tied to a specific visualization, so I remove it from my table. And just like you would expect, it updates the viz or the line chart, or this case a bar chart I should say, to remove it really quickly and automatically. So you don't have to worry about keeping anything in sync and removing it in one place and not having to it remove it in another. So pretty simple, but again, really, really easy, especially when you're trying to curate data that you want to send to somebody else. This is really easy to get that table just to show exactly what you want without having to use the filter logic to try and find and type out a whole bunch of different complex rules and if-then statements and things like that. So pretty simple, but also very powerful. Then the last one is Dynamic Drop-Down Filter. So we've had static drop-down filters for a very long time. So if you come in and you open up a dimension and you pull up the dimension item list from it, you select the ones that you want, and then you drag those onto the canvas and then you press Shift, it will turn them into a drop-down. So if you didn't know about static drop-downs, here's a freebie, but a really, really great feature. This is great, but sometimes I have a component or dimension that isn't always or doesn't have all the dimension items that I wanted. So instead, I can drag the entire dimension and Shift, and I can create a filter out of that whole dimension. I don't have to pick the dimension items ahead of time to curate this list. So now I don't need to know, as the admin or whoever, if I'm curating this project, which dim items to care about. My end users can do that. I can just drag and drop the whole thing on, and they can manipulate it how they want. - [Man] Whoo! - The dynamic ones-- Yes, whoop-whoop. The dynamic ones have the little filter icon thing. You can see at the top, the static ones do not. Now if I'm making a selection, my static ones influence all my dynamic ones but not the other way around. So if I pick something like, in this case, I'm going to pick chili, and I go back and I pick a static dimension drop-down. There's a chance I might get no results because they don't-- The static and the dynamic ones don't work in sync like that, but the dynamic ones do. So if I update my countries to US, now my regions only have US appropriate regions. Now all my cities are going to be California based cities. So I can make one selection across the dynamic drop-down and it influences all the rest. So, me or my end users don't make poor choices when we're trying to choose from these drop-downs and finding things that don't go together. So again, I choose Texas as my region. Now I've got all these Texas cities. I've got only the United States as my countries. And I can see how these, kind of, play and work together to populate this data. So really, really handy to build these dynamic drop-downs in sync with maybe some static ones that you might have to easily carry the data that you're looking for and make it that much easier on your end users. This is particularly helpful if you have a component that may have additional data coming in later that isn't available in your dataset right now, and so you can't set up a drop-down for an item that doesn't exist, so you have this dynamic one. So when it gets added to the dataset, it will automatically be populated in this drop-down list. Just like you can with static, you can remove the labels, you can delete the drop-downs through right click, get rid of it completely, and you can start over if you want to. But really, really useful feature for data curation and making it that much easier on your end-users to manipulate the content that they're looking for. So that is dynamic drop-downs. All right, pull out your phones. This is the first voting session of this session, I guess. What is your favorite feature? Navigational shortcuts, dynamic row deletion, or dynamic filters. So we'll wait a minute or two to start getting results in, and we'll see who is the winner from the Utility Regional.
Five, four, three, two, one. Okay, we're calling it. Dynamic Filters wins our Utility Regional, so that is our first one. They're the first one to make it into the final four today, our dynamic drop-down filters. So all of you have filled out a bracket ahead of time. Who had dynamic drop-down filters as their winner of this one? All right. We've lost half the group. I apologize. You're busted already. But some of you are still in contention for some money, so that's great. All right. Let's go to Democratization.
So first feature here is Intelligent Captions. And one thing I forgot to point out, maybe you've picked up on this as we've gone through it. This is a CJA and traditional analytics session. So there are some features that are in one place and the other or both. At the bottom of the slide, I've labeled the boxes of CJA, the AA box. If they're highlighted, in this case, this is a CJA only feature. If they're both in red, then it's both of them, and so on and so forth. So just as a clarification for you, so you know depending on what products you're entitled to, which ones you may or may not have access to. Just want to point that out. So first one, Intelligent Captions. This is a new Generative AI feature that was released last year. If you have a dataset here with a line chart, you can see up in the corner of the line viz, we have this new little icon you can click on. You pop that open, and it'll open this little drawer with an intelligent caption summary to interpret the data for you. So if you're sharing this out with other stakeholders who may not be as data literate as some of you, this can really interpret really quickly what you're looking at here in the line chart. So we've got seasonality, min, max, spike, decline. I can copy these and paste them elsewhere if I want to put it in a presentation, or I can edit which ones are displayed by closing out the little icon or whatever it might be, to display or not display some of these caption features if I don't want all of them displayed. I just have to click Apply, not just clicking them off. But you can see really quickly an easy way to understand what the data itself is looking like here. Now if I share this out, like I said, with other stakeholders using one of the features I'll show in just a minute. They open up this project with a Share with Anyone link. If you have the intelligent captions drawer open, it will be open when they open the project. So again, if you're sharing this with executives or other non-data literate stakeholders, then they have this ready to be interpreted and understood line chart right there all on the canvas, ready for them to go. So right now, this is only supported in the line chart, but we are working on supporting it in bar and a handful of other visualizations in the next year hopefully. So that is our first feature, intelligent captions. Second, this is Data Dictionary. Anyone who was here last year, I gave a sneak peek of this 'cause we were working on it, and it just released this last summer. Data dictionary is awesome, probably one of the most underrated tools and features that we've released in recent memory. This is all about making it easier for users to better understand what data they have available at their fingertips. So in the far left rail, you have this little book icon. You click it open. If you're an admin, you'll see Dictionary Health and Quick Filters. Non admins will see just the Quick Filters to show the components. You open up one of the components, you can see whether it's approved, the description. What other components it might be used with or similar to, or any tags you might have. If you find something on the canvas that is really helpful, or in the data dictionary, you can just drag and drop it directly on the canvas from the dictionary itself. So you don't have to go back to the left rail, find it, and then drag it on. I find that visits are a related component, I click on that, and now the dictionary switches, I can drag visits directly on the canvas, so I can use that one straight from the dictionary itself. Really handy to find the data that I'm looking for and then use it immediately on the canvas itself. So I can see here my Regions is not approved. As an admin, I can come in, I can approve it, so all my other stakeholders know that this is the regions component that they should be using as opposed to some other duplicates that might not be as helpful. And if I don't like what Adobe has provided in terms of the frequently used with or similar to components, I can overwrite those. I can remove the ones that we have provided by excluding them, or if there are certain ones that I always want to include, I can do that. If for some reason I want to include regions as a similar regions, which makes no sense, but if I wanted to do that, I can. As an admin, I can update this to show exactly the components that should be used with this. Now when I come back home as an admin, in the Dictionary Health I can see which components are missing a description, which ones are duplicates, which ones don't have any data, and which ones are not approved. I click on the View, and it updates the filter in the left rail, so I can see all my duplicates by name or definition are grouped together. So I can go through and I can clean that up. If I have a bunch that are missing descriptions, I can find that. I can come in, I can add the description to it right from the canvas, make it really easy for these components to be better understood by my end users so they know which ones they should be using, what the meaning of them are, and so on and so forth. And then, once I have added it, you can see that it's been removed from the missing descriptions list. And then any that I don't have any data, this can help me know that I need to go back and either maybe something's wrong with my implementation I should check out or the data itself isn't being configured properly, and I can look into that. And then the last thing we've done is we've taken a lot of this great Metadata from the dictionary, and we've added it to the little information icons on the components. So you can see some of those as a shorthand if you don't wanna open up the data dictionary, and then you can, like you just saw, open the data dictionary directly from the little info icon as well. So there's a ton of value here in the data dictionary in terms of making it that much easier for your users to understand the data, to clean up your data, and make it that much more digestible for other people who are coming in, especially newer users who are trying to learn what is available to them at their fingertips 'cause we find from the customers we talk to that a lot of their new users don't know what they have available to them. They're not sure what components to start with, and this can help get them off the ground and running. So that is data dictionary. All right. Last one in this region is the Share with Anyone Links. I show that real quickly with the intelligent captions, but this is-- Also I can't say the same thing, I guess. They're all great features, but this one's really good, too. Share with Anyone Links is an easy way to share a project out with anyone, like the name implies, who does not have credentials or an account with Adobe Analytics. So if I have an executive who can never remember their login or a marketing team who doesn't have an Adobe account or Adobe login with us, period, but they want to see the results of the campaign we've been running together, I can create a project, save it, open up the share menu, and I get the share with read only modal where I can turn it on, activate the link, it's off by default, and then I paste it in as a URL string, and this is the read-only version of the project that I, or anyone I share this link with, get access to.
I like that, the oohs and the aahs. Ooh. Now, it's a read only project, but there's some slight manipulation you can do. They can adjust the date range, so if they want to see a different time period than the one that you'd set up as the default or taking advantage of the drop-down filters that we showed before, any drop-downs that you've already preconfigured here in the project are also editable. So they can do some minor slicing and dicing that is a controlled environment that they're not gonna break, and they can have confidence knowing that what they're going to do isn't going to ruin anything, they can go in and do some minor manipulation. So if they want to see how one region is comparing to another or one device type is performing against another, they can do that all within that read-only project without breaking what you maybe have curated for them. So really, really cool. Now let's say if on accident your link goes viral for some reason 'cause people are really obsessed with the project you put together, it's that cool. You can come in and you can generate a new link, which will disable the previous link. So if I come back and I try and reload this project 'cause I just disabled it, I'm going to get a message saying, "Eh, can't do that anymore." I've disabled it. That way it doesn't run rampant and nobody's looking at my data that I don't want them to. But I can also require some experience cloud authentication. I can just turn the link off altogether if I don't want it going active anymore. So there's some controls here from a security perspective. If you're concerned about it getting out in the wild that you can do to disable it and make it so other people can't come in and just go hog wild with it. So that is Share with Anyone Links. So those are our three features here. Time to get your phones back out and vote once more. So tell me, which one is your favorite from this region? The Intelligent Captions, the Data Dictionary, or the Share with Anyone Links? We'll give it a second or so to see the results come in.
Ooh, did I oversell Data Dictionary? I don't want to influence. I should be unbiased.
Not that I oversold it 'cause it is amazing, but I should be an impartial judge.
I don't want to get pulled up into a betting scandal.
It's close. All right.
Okay, another 10 more seconds.
Can it do it? Does everyone love Intelligent Captions enough? Oh, man. It's almost there.
Five, four, three. Oh! Oh! Okay.
Time's up. Okay. Intelligent Captions takes it in the surprise that upset. Okay. Who picked Intelligent Captions? Who is still perfect on the first two? Oh, we've got a few people. Okay. All right. We've got two more to go. Let's see if we can get somebody. $200 is on the line. So, all right. Third region is the data region. So first is Bot Reporting in Analysis Workspace. Let's take a moment of silence and mourn the passing of reports and analytics this past year. For me, it's not a moment of silence. I should be rejoicing. Some of you, it's probably a little more disappointing. But anyways, part of a longstanding reason people always went to RNA was because of the bot reporting that existed in there. We didn't have support for that in Workspace. So in preparation for the end of life, we got bot reporting in Analysis Workspace this last year. And anyone and everyone who is a Workspace customer can take advantage of that. But the first thing you got to do is turn it on. If you had it on before for reports and analytics, then you're already good to go. It's off and running. But if you don't, come to the admin section, go to your Report Suites. Under the General Settings, you click on Bots here. And then you have to just enable this IAB bot filtering. That's the default rules that we can apply, or you can apply your own custom rules. As long as you have one of those two things set up, that'll turn on the bot data for you and you can come in and start reporting on it. We have a pre-built template here under the Reports tab. You open it up, you click on Bots, and now we've got this bot report that takes basically the two reports that we had on reports and analytics, combines them with some additional Workspace goodness and has this bot report pre-canned, ready for you to go and consume. So you can see which bots are getting the most page views, bot occurrences, and things like that. You can see the two metrics here have these little yield icons on them. That's because they're coming in as a summary data source, which means you can't combine it, as it says there in little text, with other things other than the handful that are associated with it, including other time dimensions. But you can come in and use it here in Workspace, alongside the rest of your data. So if I've come in here, we've got a-- This is why we have dynamic drop-downs is because your bots might change overtime, which is necessary to us creating this, and so we got a two for one out of this one. But my bot name, I can choose that to filter my data, if I'm curious on how one bot is performing against another. In this case, I'm curious on the Google bot. I can see how that is performing in terms of my bot page views and occurrences and things like that. And then I've also added here. If I open up the left rail, I might want to look at the bots themselves. That same icon exists on the left rail. So you know that this component is a little special. You got to handle it carefully, treat it, love it, but don't take advantage of it. And then, so once you come in, I've-- If I come down to this other report here, and let's say, I want to look at page views, I can come in and pull that, and I can drag and drop my page views metric alongside my bot page views metric. So I can compare my current page views right next to my bot page views. So I can see how they're performing against one another, if the ratio was over indexed one way or another, and I can do the same thing with my occurrences here. Even though they are coming in as a summary data source, I can report them side-by-side because they're utilizing the page dimension, and then I can get the same metrics across both of them. So that is bot reporting. This is only available in Adobe Analytics. We have some bot stuff we're working on for CJA. We don't have anything yet, but right now that is just for Adobe Analytics. So that is our first one. Next is Derived Fields. This is-- I shouldn't influence you guys, but this is a gamechanger, to be completely honest. And so this is for CJA only. And Derived Fields is like everything you could ever want, all the things that you complain about in traditional analytics, solved primarily by derived fields. You can do non-destructive data transformations that you can rename, restate your data at report time. So it doesn't change your data underneath, but at report time, you can report on it however you want. So you can change and combine things together. You can rename them. And I'll highlight. There is so much you can do here. I'm only going to show three use cases here with derived fields, but there is a ton packed into this. And there's even more coming this summer. So first, let's say I want to come in. Create a derived field. I'm going to use some of our default functions that we've curated for you, so I'm going to do a find and replace. So I'm going to do page name, and I have this URL string. And I'm-- Instead of calling it the URL string, I want to just call it landing page 'cause that's much more easy to understand. I want to call this one search instead of a URL string with the search. I want to call this Homepage, and then it will restate my data. You can see on the left or on the far right, the percentage breakdown that those had instead of looking at the URL strings as my dimension items. I can do the same thing with this other set of referring URLs. So I want to come in and find my URLs that have the terms Google, Bing, Yahoo, and I want to just lump those all together and call those Search. Instead of having three separate individual results, I have one single result here. I'm doing the same thing with a different referring URL for my social terms. So I have Twitter, Facebook, t.co. I add those, and now I label them as social. And again, you can seize the output on the right-hand side, my breakdown of what search and social is as it represents my data, now that they're combined as a single entity. So it makes it that much easier to understand, again, what the data I'm looking at. Lastly is Marketing Channels. We have a marketing channels template that you can use to help set up your marketing channel rules within CJA. You can customize it and change it however you want, but really quickly out of the gate, you can get your marketing channel results, and you're off and running with the marketing channels in CJA 'cause that's one thing that I know people have been asking for a long time. So those are just three really quick used cases on what derived fields can do, but there's so much more power beyond what it can do for you, beyond just these three. So derived fields, very cool feature. All right. Last one for this region is Full Table Export. So I'm sure many of you are familiar with or aware of our exporting limitations. We maxed out at 50,000 rows a few years back, and you guys still hit that limit and you want to do more. So, hey, I hear you. More power to you. There's more data these days, and you got to get it where you need to get it. So we have full table export. So to use full table export, you have a project setup. You got to come up to the menu here and go to the export section of the components. This is way more complicated. I'm going to show. I'm going to bypass it in a breeze. And basically just going to point it. But you come to the Exports, the Locations, and you have to set up a location account. Once you set up a location account, you can send this data out to a bunch of destinations, including Azure, S3, GCP, Snowflake, whatever you're interested in. You set up those accounts, and once you have one of those configured, you can come back to Workspace, to a project you've got. You right click on the Table, click Export Full Table, and then it opens up this full export table kind of modal. Now this is pretty standard in terms of setting one up. You give it the name, dimension, but there's some really, really cool, handy things that this can do for you, beyond just the fact that this will export millions of rows of data and not hit the 50,000 limit. But this table itself that it's showing you here on the canvas, these side-by-side dimensions. If anyone was in my session last year, we talked about flat view in Freeform Table. That's not coming yet, but this lays the groundwork for it. So now I'm not going to get a breakdown of action name, account region, and site section breaking each other down. I'm going to get concatenated dimensions put together for each of those three. So the values for action name, region, and site section become one single row. So you can use it as a shortcut if you want to get some flat tables exported out of Adobe Analytics. We'll get flat-view sometime, it's coming, I promise. But this is a shortcut to get to it. Once you have your table set up, again, you can remove, adjust, and manipulate this to be whatever you want. Then you can send it on your schedule, and you've got it up. So now I've got four rows. There are four-- Yeah, four columns of dimensions and three demetrics, and then I send it and share it. Once it's gone out-- Oh, I've got a meeting here in a few minutes. You go to your exports log, and it will show up what's going there, and you can see that it's been published and successfully sent, and you're off and running. So that is full table export. So three features for this region.
Get your phones back out. Let's see if we have another massive upset like last time, if we can game the system. Vote for the one that you think is the best out of these three in the region, whether it's bots, derived fields, or full table export.
Okay. Five, four, three, two, one. Okay. Derived Fields has won. Who picked Derived Fields? Is anybody perfect still? We got a few. Okay. All right. It's going to be close. All right. Last regional for the afternoon is the sneak peek. This is a fun one. This is stuff that, again, we're working on. No timelines or anything like that, but this is stuff that we're currently investigating, exploring. Even with some of you who might be in the room, you might have seen this if we've been on phone calls together. This is what we're currently working towards. So-- Excuse me. The first is Channel Comparison. So just like you have in segment compare in traditional analytics, we're working on a channel comparison tool for CJA. So a lot of CJA is done by doing cross channel analysis. And channel comparison is a great way to leverage that kind of data and see how they're behaving together. So we're adding a new panel type called Channel Comparison. You can either add it from the picker in the free form in the panel itself or dragging it from the left rail. You pick channel comparison and open it up on the canvas. You have to just pick two channels, just like with segment comparison. So I'm going to pick web and mobile. I'm getting really crazy here in my use cases. And then, you select your container. How do you want to view your data by? And then you'll see there's this included components section, which will automatically curate the data that you've built based on what you set up. So part of this is, when you're setting up your data views in CJA, you need to specify which metrics are associated with which channel or which components are associated with which channel. So we know these are web, these are mobile, these are cross-channel components, and so we'll pull from that list. You can customize it and adjust it however you want, but we pull from that to know what to do here. So you get this great report with a nice little intelligent caption at the top that has a hyperlink down to maybe something that's interesting to go to one of the tables, or you can just start scrolling through itself. So we've got a bunch of key metric summaries at the top. We've got some sizing of the channels, the overlap, and then similar to what we have in Segment Comparison, you can see the differences between the top metrics, the top dimensions. But we've blown this project out of the water in terms of what you can see in segment comparison today by adding a bunch of intelligence to each of these to make it more digestible for users. But then we've also added a trend. We've got two flows to compare your primary metric we've identified, how checkouts are performing for web versus mobile, and we have some cohort retention as well. So you want to see how one channel is retaining your users versus another, and you can compare them all right there, side-by-side. So this is all done. It takes a second to run, potentially, depending on how much data we're culling through. But really quickly and easily, without you having to build a whole bunch of analysis, you can just run this and be like, I want to know how my email is performing against my SMS. And you can come in, choose those two channels, wait 10 seconds, and then you've got this quick output to really digest and understand what's happening on these two channels. And then obviously the great thing with CJA or with Workspace, right click, create a segment, go do something else with it, dig deeper, and activate on it potentially even more so. So that is the first one, Channel Comparison. Next, Project Commenting. So collaboration is all the rage, not as all the rage is maybe GenAI perhaps, but still commenting is a very common thing we're seeing across our tools, and we're embedding commenting directly within Workspace. Now we don't have to take your analysis outside to Slack, which you still can, or teams, wherever you might be, but you can comment and talk directly in the product. So we've added a new left or on the right I should say, right rail or a comment rail, where you can see the comments that are tied to the project. I can create an entire project or a comment at the project level, and then I can do some of these actions here on the comments themselves. Just, interact with them to like, reply, all this traditional stuff that you can do with any kind of commenting service. So I can reply and say, "This looks great, but I was able to get it myself. We're good to go." And then post this, and now Jaden knows that I got what I needed, and he doesn't need to come in and do anything to adjust it or anything like that. So I can also comment, I can just add a new comment to Brandon George, who is in the room actually. Brandon, don't worry about it. You don't do this. Can you find and share with the marketing team? When Brandon gets that, he'll get notified of it. And then I can also add comments not just at the project level but at the panel level, at the viz level, and it's not going to be shown here, but you eventually will do them at the cell level in a free form table, if there's a specific place that you want to add a comment. So let's say I want to add a comment on this specific key metric summary. I'm going to comment and ask Jake to pull something, and I want him to go and look at it and get that ready for me. Once I submit and post this comment, even though this is on just for this specific visualization, it will get added to the comments rail, so it's there with the rest of the project comments. And then Jake will get because he was tagged, he will get a little pulse notification, which is that little bell up at the top there, and then he will also get-- Yeah, right there. He'll get an email telling him that, "Hey, he's been mentioning this specific project. Why don't you come back in, follow this, and reply and notify the team about what's going on?" So that is project commenting, a great way to just keep that conversation within the context of the project that you're working on, to make sure your users get their questions answered, if they want to know what does this mean, how do I use this, anything like that, all within the context of the project itself. So that is Project Commenting.
All right. Last one is Journey Canvas. This one is pretty cool. This is a new visualization type that we're working on. You drag it onto the canvas. It's primarily built for our AJO customers, but even as a non-AJO user, you can come in and choose any metric that you're interested in. I'm going to pick users. I do that, and I start with a blank canvas. I can build to my heart's content, but it doesn't start with anything though. So I have to come and add some dimension items or a metric or a segment that I want to. I drag one on. In this case I want to know the project load to sharing workflow, for example, let's say. So I pick project load, and now I'm going to find project share. I pull up that dimension item, and I'm going to drag that one onto the canvas, and I've got these two little nodes. They're still not connected or doing anything, but they're there. So I'm building out this canvas with the things that I want. So now I've got people going from launch, to load, to share, and I need to connect all these. So I'm going to right click on the node, and I'm going to connect to another node, and now I can start building this little flow visualization from these arrows to connect launch to project load. And as I connect the nodes, you can see the numbers are updating, because now there's an actual journey that people have to go through in order to get to that end state of project sharing. So my numbers have adjusted. Now I'm gonna build out a more complicated one. You don't need to watch the whole building say, so I'm going to fast forward here. Now I've got Workspace Launch Project Load, some additional actions, and then, again, my project share state. Now I want to know what people are doing, maybe potentially as-- I thought that was my microphone. Sorry. Someone's getting down in another room. All right. But I want to know people who are going, potentially, they're diverting along this journey to the segment builder. Now this is very much like a Fallout report, at least currently. I'm going from A to B, to C to D. But in this case, I want to know a diversion. People left the project load page, and before going to drag-drop, they go to the segment builder. And you can't do this with flow today or with Fallout today. You can't have a diversion. You have to just go in a sequential order. This gives you way more flexibility. So now I can see people who go from project load to drag-drop. That's my happy path, so I'm going to color it green because that's where I want them to go. But they might go to the segment builder, and so I'm going to make that red to say this is the diversion that people are taking. And now I have these color-coded things to say exactly what is happening along the path here. So I can see where people are leaving the flow but coming back into it. So very cool. Another thing is, maybe I want to know two different segments, how they filter into the starting flow itself. So they don't have to start in the same place. They can both come. In this case, I can use a segment as a start, my America's segment and my EMEA segment. And they can both filter into the exact same starting point. So I have two different starts coming into an additional sequential point, which, again, is not something you can do in our flow tool today or in our follow tool. You have to just start at point A and move on to point B. So very, very powerful to come in and have those two different sections converge into one. And then maybe I want to know about people who just bypass this whole thing altogether and they go directly from project load to project share. And they have a random later starting point, they skip everything else, and I want to see how that comes together. So now I've got this journey with a bunch of different scenarios built-in that's really flexible and pliable for me, and I can adjust it however I want. There's a ton of right click actions on here that you can do. As you already saw, I changed the color, I can create an audience. If you were in my session last year, I can analyze in between with a different tool called Journey Explorer. I can see what is happening between these two nodes in a different one, visualization that we could do as an output. And then you can build a crazy, crazy journey. So you can zoom in and out to go exactly where you need it to be in order to see exactly the part of the canvas that you're working on. So a lot of really great, flexible analysis here when it comes to journeys. This is like taking fallout and flow and birthing a baby on steroids that can do all sorts of crazy stuff. So that is Journey Canvas. That's our last one. So now let's have our semi-- Oh, well, that's not a surprise. I shouldn't say that. They are all great. Pick which one you like the best.
And we'll see what we got. Five, four, three, two, one. Okay. Journey Canvas wins it.
All right. Who picked Journey Canvas? Okay. Is anyone perfect still? All right. There's two of you duking it out. We'll see if you get it right at the end. Okay. So now we're on to our final four. So as a recap, hopefully you're understanding now how the features that we've talked about tie into our objectives originally. That navigational shortcuts, dynamic row deletion, and drop-down filters make it easier to start or continue your analysis, that Intelligent Captions, Data Dictionary, and Share with Anyone Links are great features to empower other users to use the tool to get to their insights faster in their workflow without sending them somewhere else. And then three, that bots, derived fields, and full table export make your data much more flexible and available wherever you want it to make your analysis that much better. And then we saw some really cool stuff to show up as possible here in the near future. So we started with 12. We've reduced it to four. Let's talk about-- Let's take our final poll of the day to see what our champion is out of the four, Dynamic Drop-Downs, Intelligent Captions, Derived Fields, or Journey Canvas. So take a moment, get your last vote in for the day, and we'll see what the winner is.
Okay. Five, four, three, two, one. Okay. Journey Canvas is our winner.
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