Too Hot for Main Stage: Help Shape the Product

[Music] [Wenjing Yang] Thank you, everyone, for joining us today. I know there's tons of great sessions that happen at the same time. You made the right choice. - [Jacob Draper] This is the best one. - Yes. - This is number one. - Yes. - Sorry. - For sure. Welcome to Too Hot for Main Stage 2025. Whoo! Yes! Yes!

I've definitely had the pleasure of meeting some of you these two days. For those I haven't met, my name is Wenjing Yang. I'm a senior design manager at Adobe, and here is my fantastic co-host. Hi. I'm Jacob Draper. I'm a senior product manager here at Adobe, and I'm excited to not do much, honestly.

Other people are going to do things, and I'm going to send them up on the stage. And so that's why I love this session, honestly. - I don't have to do anything. - Yeah. So your participation in session like this is crucial because the products that we created are really shaped by your feedback. And this is one of those key moments that your voice really help influence what comes next. You see, we collect feedback in a few different ways, Adobe Forum, beta programs, customer advisory board, customer visits, customer care tickets, usability testing, etcetera, etcetera. And this is one of the most impactful sessions, believe me. Well, if you are not already one of our customer advisory board or usability testing members and you would like to join, please let us know afterwards. We would love to get you involved. But today, our focus is real-time feedback, right here and right now. And we've already said you are in one of the most exciting, engaging sessions, full of intrigues, some backstabbing as well. Just a little backstabbing. You'll understand what I'm talking about later. Yeah. Just a little. Just a little. Yeah. Cute backstabbing. It's cute. So yeah, this session is what we want your attention.

And just so you know, we're not collecting feedback into a void. Here's the proof. These are some features from the past sessions that we made through the road map and even shipped, including some highly used, highly valued sessions or features like BI integration tools, quick segments, quick insights, awesome stuff. - Really, really-- - Yeah. I'm working on real time CJA right now. It's going to come out. Yeah. Yeah. I'm super excited for that. Very awesome stuff coming out of what we learned from this session. And also, just as important on the flip side, some of the stuff that we decided to put a little bit on the back burner because they didn't resonate. So we can blame you. And you can't blame us.

So here's how we're shaping the product today. First, you will see five different feature concepts, and you will get five different presentations. Second, you will get a chance to provide feedback to each one of them during and after the presentation. Then after you were introduced to five of them, we'll run a live poll that will vote on your top favorite one, the most valuable one to you or to your organization. And from that live poll, we'll pick top two. Then we will invite-- Here's the fun part, we'll invite two of you from the audiences, come on the stage, and really defend on why your top voting should be the top one. So we want really passionate argument. Please take notes on the one that really matters to you. You have to win. Yeah. You have to win. And then in the end, there will be one winning features and one winning defender.

So one winner, only one.

And when evaluating those features, we want you to consider impact and values. And instead of how polished or visually appealing they are, think of questions like, does this feature solve the significant challenges for you or your organization? Will it drive efficiency, save time, cut costs, or increase revenue? Is this something that would make a real difference in your workflow? What's not important right now is how exact it looked or designed because those are very early concepts that meant to spark conversations. So think impact and values over aesthetics. Some of these babies are ugly.

But they are very, very valuable. - Super useful. - Sorry. And that's why we want your feedback as well.

And the great part of this session is you had a chance to win prizes. Win prizes. - Yes. - Win prizes. I know you are collecting swags here and there, but we got anxious. If you were chosen to come on the stage and defend for your top features, you'll get a chance to win $250 if you're the winner and $150 if you're not the winner. Yeah. So if you are the winner, you can go home and say, "I got a 100 bucks from Adobe because I lost a lot more out there in the casino." So you can be plus 100 with your $250 gift card. And I was told that Adobe employee is not eligible to win, right? We, no. We can't win, I asked. - Also-- - Yeah. There was a sighting. Someone told me that they saw someone who's really tall that they think actually is Ben Gaines in a trench coat on top of Trevor Paulson's shoulders. And he's, like, just going around just saying he got tall from stretching. He cannot win nor can Trevor underneath him. No, none of those scenarios, no large trench coat people in trench coat situations. Not for Adobe. - It's for you guys. - Yeah. And these should be very easy to recognize. - So keep an eye. - Yeah. Please. Keep an eye on. If you see Ben riding on Trevor's shoulders wearing a trench coat, please let us know. It's terrifying.

So this session needs your participation. So now please get out of your phone and your computer. Go to pollev.com. Enter TOOHOT2025. It may ask you to register. You can totally skip it. We can keep your feedback anonymous. So please be honest with us. We won't know who you are. I feel like some of you want to tell us who you are and want us to know. - Do that as well. - How mad you are at us. - And that's okay too. - Yeah. - I'm fine with that. - It's your decision. That's fine. So again, it's pollev.com and the code is TOOHOT2025. This is the most important thing, your participation is why we do this. So I appreciate you taking the time to get your phone out and to play along today.

Okay. So we have a poll right now. Let's do a test poll. - Yeah. - Yeah. Have you attended Adobe Summit before? Yes or no? This is my first time. I'm super excited. Whoo, Wenjing! Yeah. First time. We've asked her to join this session and host that session. This is amazing. Okay. - Half-ish. - Yeah, we have half and half. - Half-ish, half. - Yeah. - That's not bad. - Yeah. If this is also your first time, welcome. If you have been to Adobe Summit before, thank you so much for coming back.

Okay. - So we're sitting-- - More. 60-40. - More-- - Yeah. Yeah. More people who have been here before. More returners. That's good. Yeah. Okay.

So another question. How many of you have been to Too Hot for Main Stage before? - Please just raise your hand. - Raise your hand. - Give a yell. - All right. Okay. We've got some returning people. It's not bad. It's looking 50-50 as well. Okay. I like it.

If you have been to Too Hot before, you'll know that we kind of pick a theme to theme our presentations around. Do we have any guesses what the theme is this year? Yell them out to me. - I'm curious. - Look at our outfits. Yeah. Okay. We got a secret. What do we got here? Game show. Game show. Oh, that's pretty good. I'm giving very Bob Barker from '83, an '83 Bob Barker. Okay. What else? Game Show? - March Madness. - March Madness. Oh, that's a good one. I like that one. My March madness is when I come to Summit and get really tired. That's what I call March madness. It's just exhaustion from Summit. Okay. March madness. Other guesses? What was that? - 007. - 007, that's a good guess. Other guesses? High Roller. Mr. and Mrs. Smith. High Roller, Mr. and Mrs. Smith. Not appropriate for work, sir.

Excuse me. Not Mr. and Mrs. Smith. Any other guesses before we go? Rat Pack. Rat Pack. Ooh, that's a good guess. I like that. I'm not nearly that cool. Our presenters are almost that cool. I am not that cool. I couldn't do it. Okay. I heard a couple that got it right, and let's get into it right here. Okay, so this year's theme, it was one that we put a lot of thought into, okay? And it is 007 secret agent mission data possible. That's what we're going for today. I'm hoping this gives a little bit less Bob Barker now and a little bit more like cool secret agent guy. So assembled before you guys today are our most promising potential field agents. They've been training tirelessly to become the most effective masters of infiltration and espionage. Okay? The fact that these five people up here look so normie and regular and relatable is kind of the point. Okay? When you're trying to infiltrate to steal state secrets or like the colonel's secret recipe, who do you want to send in? You can't send in Dwayne The Rock Johnson. Sticks out like a sore thumb. Come on. What you need to send is someone who looks like, I don't know, like a healthy Macaulay Culkin, for example. Like myself. That's the type of person you send. That's a callback joke to last year too. I will never let it die. It's fine.

Healthy Macaulay Culkin is who you must send because they can be sneaky. But the funny thing is our presenters actually are too close to like the Dwayne The Rock Johnson style. We're not talking about the presenters. What I'm talking about are the features today. Okay? So that's what we're trying to figure out is which feature is going to like quietly do its job in the shadows with like a pen and like a shoelace and then like melt away into the shadows but then return just when you need them. That's kind of the thing that we're talking about. Okay? That's what you need to keep in mind is how you're listening to how these features are going to earn their AA status or status. Status is funner to say. AA status, which is AA is Adobe Analytics, guys. And for copyright reasons, we're not saying the other thing. It's AA, okay? So that's what they're trying to earn today is the AA status to see if they can actually get built, okay? Who will be the last spy standing? This is Mission Data Possible. Welcome, thank you for being here.

Thank you. Yeah, it was good.

Classified top secret in that you will see this and get this presentation at the end of when you go back to your Summit stuff. But I'm going to go through what we're going to talk about today. We're going to start off with this. This is our welcome and our briefing. We're doing this right now. We're going to go through our spy roll call, where you'll see ahead of time the features, who's going to present these features. Then we are going to do Operation: Elimination, which will look just like this. We will explode the losers today.

I asked, they said no. It's fine. It's okay. We'll pretend to explode them. We'll be left with two features standing. We will have the final showdown. Remember, this is where we will call for members of the audience to come up and to argue for why their feature is the one that should be the last spy standing. And that's what we'll be left with here today at the end is your favorite feature that you guys have voted on and worked on. And there are prizes too. For the winner, $250.

For the not winner, 150. So it's the not winner. The loser still walks away with something pretty good. Okay. So we're going to get started. We're very high-tech, carry very much about security. I'm going to get my thumb on here and get this going. Okay. It's scanning for access.

Do you guys hear? Do you hear that? Do you hear some people rolling up? I feel like I hear a car that also is a submarine pulling up. Can you just hear? Yeah. I think that's a squirrel suit. Someone's landing in a squirrel suit and that smells like someone came through the sewers. Someone chose sewers, bad choice. Does not get your points to go sewers. Okay. So we have our contestants here. We have Explain Why by Agent Werkmeister. We'll do Gamifying Workspace with Agent Whitchurch. Analytics Easy Mode will be presented by Agent Penrod. In-Line Derived Fields by Agent Tangren. And then Natural Language and Analysis Workspace by Agent Baker. I am very, very pumped for you guys to see what our presenters have prepared today. And it has come from a lot of hard, good work, a lot of garage week projects and ideating, and like real good heavy R&D. So I really love it. So now speaking to my contestants, who again are features who actually don't have corporeal bodies, but are represented in the presentation by my presenters. Your mission, if you choose to accept it, is to tell us why your feature will be the last spy standing. Tell us why you deserve that AA status, and why we should entrust you with the state analytics secret so you can get our job done, okay? All right, we're going to get going. Are you guys pumped? Are you guys excited? I'm very excited. I'm very excited.

I'm super excited. Okay. We're going to start off with agent Jennifer Werkmeister on Explain Why. Okay? So our first feature, Explain Why, has all the answers. Speaks Japanese, Portuguese, Pig Latin, Latvian, ninth grader, which is like a lot of rizz and stuff. Preppy. My daughter says Preppy all the time. I don't know. Not my favorite. Esperanto. That's one of the languages. Middle management or as we call it at Adobe Analytics, Ben Gainsies. Okay. That's middle management.

I'm sorry, our Explain Why is very, very good. Okay? Massive intellect, but can Explain Why effectively utilize that intellect to infiltrate your heart. No, that's last year. Last year was like a dating show, not the infiltrate your heart part. Sorry, mixing up the themes. We're going to stick with secret agents. Jennifer, take it away.

[Jennifer Werkmeister] Thank you very, very much. So as Jacob mentioned, it's not about me, although I'm sure you can see the resemblance to The Rock. Yes, everyone.

It is about the secret agent in our midst. Not only a secret agent but the world's best intelligence agent. Agent X-Plain, her intelligence network is unparalleled. When you have data misbehaving, when numbers spike, when metrics fall off into the abyss, she's the one who can help you to understand why.

So most of her missions are top secret, but she has cleared a small selection of her portfolio for me to share with you today. The first mission, a curious experiment. So, mad marketing scientists have pitted two experiences against each other in a brutal head-to-head challenge. And in an unexpected turn of events, experience A, best experience B. But why? Agent X-Plain is here to tell you.

So, with a click, she activates her internal AI. She comes through all of the data points highlighting the key insights and she's the one who gets the results.

In a second, she's provided the most statistically significant findings. And it looks like experiment A drove browsing behavior with converting traffic coming from marketing channels.

All right. Mission number two is a little bit more serious. We have a case of missing persons. The persons in question, those who made it to the checkout page but did not make a purchase. Now, if anybody can find them, it's Agent X-Plain. It seems like Agent X-Plain is hiding. Why is she hiding? To find people.

It's a great, great question. Great question. I just... I ask the hard questions here. I do.

Well, with one click, she isolates the population. And with another click, she scans through every metric and every dimension looking for those lost people. And just in seconds, she has the answer. So, it looks like people were making it to the checkout page with clear eyes and full carts. But that anticipation of a purchase soon turned to rage, frustration. What's happening? Looks like something is broken in the checkout UI.

And our third mission, things have gone from bad to worse. Now, anybody who has seen an indicator like this 15 minutes before a QBR knows you need to get to the bottom of it ASAP. And Agent X-Plain is really upset, you can tell. She has a big frown. She's very serious. - This is a very serious situation. - Yeah. So as you all know, trying to get to the bottom of why a metric is misbehaving, especially under that kind of pressure can feel like diffusing a bomb. But don't worry, Agent X-Plain has your back.

Again, with a single click and some statistical analysis and the help of AI, she has the answer. Is it clicking? Is it moving? Imagine that there's a click.

And the help of AI, she has the answer-- The baby's ugly. Okay? We told you. Told you the baby's ugly. The demo gods, am I right? So we found when we actually went through this earlier today, not only was there frustration in the checkout but we're seeing that there's a lot of browsing behavior from returning customers. But of all that browsing behavior, they're not making a purchase. So now you know it's time to examine what's the difference between these two experiences. Why are happy purchasing customers coming back and they're not buying anything? For mission number four, we have a happier tale. Now the client in this mission is no stranger to strange visitors, but when the number of visitors spikes that is strange indeed. So who is there to explain it? Agent X, she's going to help you understand why are they here and where are they coming from.

So again, she isolates the population with a click and with another click and another impossible analytical feat, she has already gotten to the bottom of things.

Let's take a closer look, and it looks like the campaign in a couple of marketing channels was extremely successful. However, as for the where these people come from, it looks like Idaho. Now, what the client did that resonated with Idahoans, that remains mystery. I'm not making the potato joke. I'm not going do it. No. No. So why should you hire Agent X-Plain? Well, first, she's powerful. She uses the power of AI to dig through all of the possible answers and come up with things that you never would have even thought of. She's fast, as you saw, she can get to the bottom of things in seconds. And of course like all AI, she is 100% accurate. JK, JK, don't tell legal.

It's not true.

So the next time your dashboards are misbehaving, the next time you think why did that number spike, why are those orders so high, did the intern accidentally run a Fourth of July sale in August? Or what is it? No. Black Friday sale in July? - Black Friday. - That's it. Yeah. That works. Don't blame the intern, just call Agent X-Plain. She can get to the answer super fast and maybe even make you look like a hero the next time your boss asks why the metrics have tanked right before a big meeting. So the question is, are you ready to hire Agent X-Plain? Because she's ready to work for you. All right.

Okay.

If you all go fresh or pollEV page, you get a chance to provide feedback to our Agent X to the Explain Why feature.

- It's a good one. - When did this trip? Yeah. - I have this-- - Positive feedback is great. Negative feedback is okay too. It's okay. This is a safe space. We'll-- For people-- We'll only cry when we leave, not in here. Here's not a crying place. That's for later. But yeah, send it all in. Whatever you guys think. We've got some time. We want to get your feedback. Again, like we'll do our little voting stuff, but this is helpful for us to know as we're looking at development, like what we need to do, what we need to prioritize. So toss the feedback in, what you think. - It's really helpful. - Yeah. And for some of you who might be a little late, please go to poll, pollev.com, and the code is TOOHOT2025. And you will get a chance to provide feedback. And a reminder, while the presenter is presenting, you can also refresh your page, go to provide feedback for that specific agent. I like this one. - I like emoji one. - Yeah. We should just do more feedback in all emojis. Yeah. And can explain that to us. - Yeah, maybe. - For sure. Yeah. Why not? It might speak emoji along with Ben Gainsies. It might. Yeah. Cool. Let's see who our next agent is.

So some say spycraft is like a chess match between global powers. Some other says it's for something even bigger, like making sure a country has the best fast food chicken chains. Right? High stacks. - High stacks. - Indeed. Our next agent is an expert in strategic maneuvers, not about invading animus but here to analyze data. Not as dramatic but quite important at the same time. Russell, let's welcome. Whoo.

[Russell Whitchurch] Thanks, Wenjing.

I feel a little underdressed, but that is intentional because I am here in disguise as a Summit attendee. So-- Whoa. You guys got infiltrated. How does that feel? Man. For those who weren't at my session yesterday, I had a pretty awesome Pac-Man suit on. And if I have one regret today is that I didn't wear it to this session. But oh, well.

So, just letting you all know that this session is pretty cutthroat. We're all AA agents, but you never know who you can trust.

Some AA agents might also just be double agents.

AA agents, I guess. Like AA battery? Is that what-- Just putting it out there. Okay. I could never ask for you to trust me, but I do want to let you guys in on a little secret.

All of the other AA agents here today have been infiltrated by AI.

Who knows what smoke and mirrors they'll show you? Thankfully, you can rest assured that the feature that I represent is not AI compromised. In fact, not only that, there is an actual working prototype.

CJA can do a lot. I mean a lot lot. There's so much untapped potential that we offer and many users overlook it simply because they don't know about it. With Achievements, everyone can see what is available to them, which gives them the opportunity to explore and gain knowledge of the features that can immensely help their ability to gain insights. That dev sandbox that you have lying around can be put to great use.

If you're already a seasoned veteran in the product, Achievements allow you to proudly display your expertise.

You can be known as the go-to person for segments in your org, while your colleague could be known as the go-to person for Journey Canvas.

Our prototype is built on a customizable and expansive framework. Virtually everything that you can do in the product, including counting the number of times an action was taken can be included as achievements. All it takes is a simple JSON object to define it, and you're good to go.

Not only does it apply to Analysis Workspace but it can apply it to all dependent platform and applications. You'll be able to see users that have experience in multiple applications for those particularly hairy cross application questions. It's worth noting that all of these things this prototype can do today. It's working.

So let's get into it.

Here I'm in platform. I'm just going to create a profile schema here really quick.

And I'll just go over here to create schema.

Select individual profile. Click Next. Give it a name. Then click Finish.

Come over here and add a field group.

Click Retail. And then once I have that field group, I'll click Save, just creating a schema. You'll see that as soon as I save my first schema, I get a notification. Clicking on it reveals that I just earned an achievement for creating my first schema. Here, you see a list of achievements, both locked and unlocked. Looks like creating a profile schema not only unlocked an achievement but also gave me progress towards another achievement as well. So now that I know how to finish off this achievement, I'm going to go ahead and create an event schema to make progress there. Add a field group and done. Going back to the achievement page shows that I have made progress on it. As previously mentioned, this applies anywhere in platform, including Customer Journey Analytics. Looks like we got an easy one here, create a segment. Let's hop on over to CJA and do that. Drag and configure a dimension, and done. Achievement unlocked. Now, every achievement has a description tied with it as well as a link to documentation. So if a user wants to learn more about a given feature, they have a direct channel to learn all about it before they decide to pursue getting the achievement. Here I see the documentation about calculated metrics. Now that I've learned about them, I can dive right into the UI and get the achievement for creating one.

I'll create a simple one here, like events per purchase, and as expected, I get the notification saying that I unlocked the achievement.

Since my achievement can be whatever we want it to be, we can enable users in our organization to follow any desired enablement path that we want and let them do it at their own pace. They are structured in a way to help them learn as well as give them the recognition that they deserve for the experience that they have gained in the product. And quick side note, if you're worried that users will clutter up Workspace with trash components, achievements can be configured to listen on specific sandboxes or data views, so they don't mess with your pristinely curated production data. Do I get a pretty badge? - Yes. - Badge pretty I get? - Yes. - Awesome. - Absolutely. - I like pretty badge. All right. Now as mentioned before, what I've shown you today is a literal working prototype. We would need buy in from other apps and services in order to fully implement, but there's nothing deceiving here.

So if you vote for this feature, we how can we expand upon it? Some very realistic possibilities include the ability to disable specific achievements. There'll be a lot of out-of-the-box achievements available, so if you don't want users accessing a given feature, you can just turn it off.

Permission based achievements. If there are features that you're okay with users having, once they've had enough experience, then this is a distinct possibility. Certainly help alleviate permissions management on some of the more complex but harmless features.

Or maybe even having the ability to showcase your achievements on Experience League Communities. Imagine asking a question on guided analysis and getting a response from somebody who has an achievement that indicates that they've used every guided analysis panel and shared those reports with users in their organization. It kind of lends a lot of credibility to their answer. So if you trust me, vote for Gamifying Workspace, and let's provide a tangible path for users in your org to expand their skill set to become experts just like you.

All right. Russell, thank you. Excellent. Let's talk about Gamifying Workspace for a second. Take some time. Send us some feedback. Again, very helpful, as we consider getting this into production. Ooh, okay. "Give it to us already." I like that one. But the-- Sorry. It's not on the road map yet, unless we get more good feedback. I like that. Okay. Okay. Gimmicky. That's fair. It's fair. Again, all feedback is good feedback. It's helpful even if it's negative. Again, Russell will save his crying until he leaves. You won't have to see it. You won't have to see it. I promise.

Okay. I'll give you just like 20 more seconds, and then we'll get started on the next one. So get your feedback in here quickly.

How we doing, Wenjing? We're getting a lot of good feedback coming through. We've got it. We're collecting it. Yeah. Yeah. I have an agent here working for me. - Oh, nice. - Yeah. - That's awesome. - Mm-hm. I didn't know that. So-- - Well, secret. - Secret. Yeah. Secret agent. I saved my spot for Too Hot 2026. Oh, nice. I like that. That's very good. Okay. Shrug emoji. With that, let's move on.

Okay. Awesome. So out for our next agent. I want to talk a little bit about the marks of an excellent spy. And that's the ability to blend in anywhere using any language as they may be called into like Macau or Florence, Italy, or Des Moines, Iowa, at any moment.

Des Moines, they call that the Macau of the Midwest, if I'm remembering correctly. Anyone from Des Moines here? Oh, yes, a Des Moineser.

Welcome, thank you. How is it coming from the Macau of the Midwest to the Macau of the Southwest? Oh, nice. Awesome. Welcome.

I am excited that you're here, and there will be more Des Moines jokes later.

Natural Language in Analysis Workspace that we're talking about is sure to be able to accomplish a lot just like a spy who would be in Des Moines, Iowa. What kind of spy might be in Des Moines, Iowa? Like a corn spy maybe. I don't know.

We've got a Des Moinesac. We have a "demoniac" here.

And the joke about corn, including the little joke about corn, that was kind of lame. And it's like the Idaho joke earlier. It was also lame. It wasn't good. So if I could get the camera to zoom, zoom, more, more.

I'm sorry for that lame joke, and I will be better. Okay, thank you. No more corn jokes about Des Moines. It's lazy, I understand, I'm sorry. But who is not lazy and who is here today to present Natural Language in Analysis Workspace is Taylor Baker. Come on up, Taylor.

[Taylor Baker] You know what, Jacob undermined the corn joke right off the bat. I added that little corn icon. I think that may be my greatest contribution to this presentation. We'll see. Let's see what happens. Okay.

So ladies and gentlemen, spies of the digital realm, welcome to our clandestine briefing.

As operatives of the field of data, you're no stranger to slick gadgets. Just as Q equipped 007 with an exploding pen in GoldenEye, just to note, legal said I couldn't include actual images of the movies on the screen, but I could say them out loud. So I am going to say them out loud.

I don't think that's true.

I think I'm close friends with legal and Louise might be here.

She's here. She's mad.

So just as Q equipped 007 with an exploding pen in GoldenEye or Ethan Hunt scaled the Burj Khalifa, as you can see there. No image from the movie, but referencing Ethan Hunt, in Mission Impossible, we're here to unveil some equally impressive tools in Analysis Workspace. These gadgets won't self-destruct in five seconds, but they will make your missions in CJA smoother than a martini, shaken, not stirred.

Let's introduce the first one, a license to calculate. As the great spy linguist Natasha Romanoff once said, "I only act like I know everything." In the world of CJA, mastering the language of data analytics is crucial to blending into any data and any environment, like Des Moines, Iowa, any environment you can think of, Burj Khalifa, etcetera. In the world of CJA, it's critical to know these languages. And fear not, rookie agents, we're introducing a tool that's so powerful that it will make you feel like you've got a PhD in data-ology. I'm making up data-ology. I know some of you actually do have PhD's in this room. It's made up. Mandy, you have a PhD? Maybe-- But come to think of it, let's just jump into this. So picture this, you're a fresh faced AA agent. You're eager to prove yourself in the field of custom analytics. You've deduced that this plus icon here in the left rail is your entry point, so well done. It's good to notice that right off the bat. But as you stare at this calculated components builder, you feel kind of overwhelmed. You feel like you're trying to diffuse a bomb with your eyes closed, but don't panic, agent. Remember your training, you're resourceful, and you're clever, and you're about to discover a secret weapon.

Presenting component, calculated components, your license to calculate using natural language. It's like having a universal translator for data minus the risk of accidentally starting World War III.

Enter the data insights, agent, your very own Q-branch in chat form. Russell threw the AI features under the bus earlier. I just have to say only one of my features is AI. And I'm working on AI products, so I'm very excited about them. And not at all offended by Russell right here. He's not mad at all. This one is a sigma prototype, but I built it myself and it is magical. But it is something we're actually considering. We need your votes. I have two features by the way, so I'm sort of cheating. But this is the first in my natural language features. So this is like having a universal translator for data. Enter the data insights agent. Here you can see we already typed in this chat icon. Your mission, should you choose to accept it, is-- Let me scroll down. Oh, my gosh. I don't know. Sorry. You know what? We went through the rehearsal, but then you have to actually scroll in real life and it becomes more challenging. So you type Create a filter for analytics spy movies that includes mister in the title. And then suddenly the data insights agent springs into action, its digital synapses firing like a laser watch cutting through steel. It's as if Moneypenny herself is translating your request into the language of data. Your filter then materializes in the component rail faster than you can say for your eyes only. And once you drag it into the free form table, you're looking at all the spy movies with mister in the title. And I think it might be rerunning the GIF, but it did happen. Let's begin-- I don't want to wait because I want to see all of these other amazing ideas that people are working on. Okay. So after your successful mission, after you already created that filter magically using AI, but quite accurate AI, not to throw the other comment on the bus, you start to think about having-- You're having this existential crisis, and you're wondering, "Am I a data analyst or am I a data duplicate?" And you're staring out your office window like Jason Bourne, wondering what his identity is and-- That happens to me all the time. - Yeah. - All the time. It's like this, you're staring in the mountains. Lehigh actually kind of does have a view like this, just not water because it's a desert. But if you're not agent, dynamic questions and Workspace is about to become your personal intelligence network. It's like having a whole agency of analytical spies at your fingertips minus the risk of a mole in your midst.

Now pay attention, AA, as Q would say, this future is your window into the collective mind of analytics operatives worldwide. It's like having a crystal ball, but instead of seeing the future, you're seeing the most relevant questions in your data universe. After creating your calculated component, you go back into your Workspace project and you notice a series of recommended questions appear below your panel. But dynamic questions just aren't any questions, they're dynamically generated based on your specific data and the collective wisdom of your other agents in Analysis Workspace. So not only do you get to see those questions but you can click on one of them as you can see here in this demonstration. And this is a real live prototype, Brandon George, our engineering king built this and it looks amazing, and no AI, I have to say. But it's true spy movie magic, you can click on one of them and then it builds a panel of visualizations and analysis for you. And all you have to do is click on one of those questions that other people in Workspace are asking. Remember, in the high stakes game of data espionage, the right question can be more powerful than any gadgets. As the great spy philosopher Ethan Hunt once said, "Your mission, should you choose to accept it, well, in this case, your mission is to ask smarter questions and this feature ensures that you'll never be at a loss for words." Okay, so again, sort of cheating because I have two features, but I think they're both exciting and great. I'm biased because I worked on it. Imagine this. You've just used natural language to create a calculated component that would make even the most seasoned data analyst green with envy. That's the one on the left. But your mission isn't over yet. Dynamic question kicks in, the one on the right. And it suggests questions and analyses that could blow this case wide open. It's like having a team of the world's greatest detectives finishing each other's sentences. Agents, these new features are your license to calculate and analyze using natural language. They'll help you infiltrate the most complex data sets, extract the intelligence that you need, and make you look like a brilliant spy doing it. Remember, in the world of analytics, every day is a chance to save the world one insight at a time. Now go forth, may your queries be as sharp as a throwing knife and your insights be as clear as an invisible car. Class dismissed.

Thank you so much, Taylor. Please provide feedback about Natural Language in Workspace. You don't have to use natural language. It's not corny. That was so sweet. Yeah. It's totally fine to use emojis. That's so nice. Now I have to use natural language.

Oh, yeah. "Reason number 432 of why schema and taxonomy matters." I like that one. That's a very, very good one. All right. Keep it coming in. - It's looking very positive so far. - Yeah. And I like that an awesome way to inspire users. I agree with that. That's kind of what we're going for here is not to replace but to make it easier and help you get faster to that stuff. That's awesome. It could be good to see what others are asking. Great collaboration moment here. The top-- I mean, yeah, it's close. The calculated metric thing is new, okay? The questions aren't there, okay? I know they aren't. Because we had to build a prototype and it was hard.

Okay. Awesome. - We'll get it going here. - Oh, yeah. Thank you very much for that feedback. - It's great. - Let's move on.

So in spying, it's often taken for granted that you need a great team to get the job done. Think the guy or the girl in the chair in the movies, the one that really guiding the spy through crowded markets so they can escape their tail. In-Line Derived Field is kind of like that girl in the chair. It won't help you escape assassins, but it will really. - Yet. - Yet. - Maybe in the future. - Yeah. Who knows? You could put assassin escape on the road map. - Yeah. For sure. - For derived field. It will transform data, for sure. - For sure. - Yeah. Maybe it will transform you to escape, yeah. - Yeah. That's-- - Yeah, that might be the future. Yeah. Yeah. And, Derek, I heard, has had a leap out of a moving train in Munich to escape to safety. And I'm curious, who is that girl in the chair for him in that mission? What? What? That mission is supposed to be classified? Oops. Sorry. Shh. You don't know. Derek, passing over to you.

[Derek Tangren] Thanks, Wenjing.

Thank you. I'll just say at the beginning, so for anyone who did attend Russ's session yesterday and you think he hasn't been compromised by AI, I'll leave that up to you.

Okay, a few years ago, as part of a special initiative here at the CJA, that's the customer journey agency, we developed a highly specialized piece of equipment to aid our top AA agents with all the data challenges they encounter in the field. It allowed our agents to do some things never before possible and to do that with ease, such as applying data transformations on the fly and retroactively. This project was code named Derived Fields, and in many ways it revolutionized many of the things that we do here at the CJA. One of the challenges that we've heard from our agents in the field is that limiting those to only the highest level of security clearance, in other words, being a CJA admin or a product profile admin at times presents a challenge.

This can create extra work for those administering agents in attempting to address the customizable needs from their users. Our hope with this initiative is to extend some of the functionality to a wider range of agents while keeping appropriate guardrails in place. What you're about to see is some of our latest advancements. In fact, we've already started field testing them in some locations. So if you have access to CJA Labs, you can check out the first part of what I'm about to show you, which we've code named In-Line Derived Fields.

Here we have a simple report in Analysis Workspace of the top analytics spy movies, including favorites like License to Analyze or From Summit with Love. The real heads know From Summit with Love is the best one. The real heads know. Yeah. In looking at our report, we noticed we have a couple of data anomalies that we need to clean up. We can do that by selecting the values and choosing to combine them into a single value. So if we have data that we notice hasn't been collected properly, it's easy to fix and keep going with our reporting. We'll take care of these two issues quickly, but let's say we want to do something a little more dangerous. We can also use this to quickly group several values together and create groupings on the fly. So I can put all the reporting Impossible series movies together with just a few clicks. Even if I forget one, it's easy to add it in. I'll just finish grouping the person identity series together, and then we'll finish up with Customer Journey Analytics series, a personal favorite of mine. I hated Analyze Another Day. That was the worst. It was really bad. - Yeah. It was-- - Not good. Did not live up to. Golden ID though, so good. But who doesn't love some of those iconic lines from that series like "Analytics, Customer Journey Analytics?" Or "I like my data streaming, not stored." It's the best one. After I finish with my customer reporting, which is classified for your eyes only and not visible to others, and you can cause your changes to self-destruct as though they were never there. Again, this is ready for field testing by you if you have proper customer journey agency clearance by visiting CJA labs. Now I likely shouldn't show you this next part, but I've been assured by the director that you can be trusted. We're exploring making even more sophisticated in-line modifications. Let me show you an example.

I'm here back at my classified analytics by movies report. We'd like to dig in to understand who some of the best analysts were from the Customer Journey Analytics movie series. As we bring over our analytics spy movie actors, we realize each set is in a delimited list. This presents a particular challenge. Now if I have admin security clearance, I can go into the data views and create a derived field in order to fix this. However, without that security clearance, my options are limited and the time's ticking down when I need to have this analysis wrapped up so I can get back to watching my favorite CJA analyst, Sean Seifer. I'm a Daniel Cluster guy.

I think he's really changed the role. Yeah. He's like a number two for me. - No. That's fair. - Okay. I'll click into this new icon representing other aspects of In-Line Derived Fields. I'm presented with a dialog box where after providing a simple prompt, I'm able to parse down to just what I'm looking for. But even if my needs change, like I want to see all the actors, I can go back in, modify my prompt, and get the report I'm looking for. Timothy Token, underrated. I'm going to say it, underrated. I don't know. I don't know.

Again, these reports are for your eyes only, and although we are considering looking at ways to make these useful transformations available and accessible to other agents.

Again, this is highly classified information. And if it falls into the wrong hands, it could mean the end of data analysis as we know it. If this would help you in the field, please let us know. Thanks.

Thank you, Derek. Thank you. All right, let's get to the feedback. Ooh, excellent. Winner, someone's calling their shot right now. Okay, I like that. I like that. We're going to go-- Also drooly emoji. That is not safe for work, my friends.

Goodness gracious. Okay, we're going to go ten more seconds. You can still hit this for a little bit, but we're going to get moving on because we're getting there close to time and we have one more awesome feature, okay? So keep that coming in but I want to finish up with this here. Oh, did it-- No, it didn't work. It's fine. A good spy makes spying so effortless that no one even knows they're doing it. Like we're really big on data and analytics here, obviously, like, it's our whole thing. But there's a statistic that suggests of the last four first dates you've been on, at least one of them was with a spy.

I think that's real. And you didn't know that it was true, but it is because I set it up here and I'm wearing a tuxedo.

So that's what Analytics Easy Mode is like. Disregard the weird placement of the mouse because it's supposed to be an O. But Analytics Easy Mode works really awesome, does its job so effortlessly. It'll make your life easy and awesome. Luke, come on up.

[Luke Penrod] So again, you're kind of hung up on last year's theme. - I love the last year's theme. - We did the dating theme. But this is the James Bond theme. Yeah, I liked the dating theme, it was fun. That's why you have his jacket from Casino Royale.

- Focus. - Yep. All right. We've seen a lot of useful spies today with some intriguing abilities, but explain why you would put your fate in the hands of one capable field operative when you can have an entire army of them at your disposal. The spy I'm about to reveal to you today brings with it a host of its spy associates.

First, a word of caution. This spy is ultra top secret. If this information is leaked, we will disavow all knowledge of this presentation.

Unlike some of the spies you've seen today, up to this point that operate only in Customer Journey Analytics, In-Line Derived fields, natural language and Workspaces. - This is the cute backstabbing. - Excuse me. It's so cute, this backstabbing. - It is, isn't it? - Yeah. It's so cute. Yeah. Not that bloody.

Spy Easy Mode has a license to kill your KPIs anywhere it's needed. It carries passports and currencies for both Customer Journey Analytics and Adobe Analytics. So where are my Adobe Analytics users today? Any of you? All right. - Yeah. - Awesome. Spy Easy Mode is here to save your world as well.

Now it's time we get you briefed on what Spy Easy Mode is all about. You or the end users in your organization might not be aware that there are many useful sleeper agents who have already been deployed and are lurking in the shadows of Analysis Workspace just waiting to be activated for your own secret missions. For the spy uninitiated, let's open our Spy 101: Field Guide to learn about sleeper agents.

A sleeper agent is essentially an undercover operative in a country or an organization or, in this case, a product, who doesn't have an immediate mission but is ready to go to work whenever they're activated. Make no mistake, there are many sleeper agents in Analysis Workspace. They've been biding their time for years, blending in, ready to be activated at a moment's notice.

So around which corners of Analysis Workspace are these sleeper agents concealed waiting for their call to action? Dun-dun-dun.

Even more effective than a stealth enabled nuclear submarine, many of these spies are hidden behind ultra-covert right click menus.

When you right click a dimension or a visualization or a panel or even a dimension item or a metric-- Sounds like some of you know about these spies already. That's crazy. I thought they were very well hidden.

Or like a black light on invisible ink, they might be lying in wait behind a settings icon that is only revealed on hover.

But their days of undetected submergence are over. Sleeper agents, it's time to exit the shadows of the right click menu. Spy Easy Mode is here to activate you.

Let's meet Sophia. She's a special ops coordinator at MI6, and she's been quarterbacking her fair share of covert missions. Now the MI6 director is demanding information about each field agent's involvement in various missions in CSV format.

Sophia has the information in front of her in Analysis Workspace, but she can't figure out how to export it. She could have sworn she once saw an export option around here somewhere, but where is it sleeping? Where is it hiding? What does she do? Well, she calls her analytics admin of course. Right? Isn't that what happens? No. Wait, Sophia. Wait. There's a better way. Analytics Easy Mode on the far left of Analysis Workspace takes command of the left rail in order to showcase these sleeper agents, these sleeper features, if you will, and their unique abilities.

With Easy Mode selected, as Sophia moves her cursor around Analysis Workspace, she immediately sees all the right click and settings options that are available for any object conveniently visible in a combined view in the left rail. There's no more having to right click on UI element after UI element, wondering which areas of Workspace might have features sleeping beneath them. Just look at all these features now activated and ready for Sophia to use.

From here, Sophia can easily see the export full table option and select it.

We've been looking at free form tables, but Easy Mode works anywhere in Analysis Workspace. If Sophia decides that it would be easier to visualize this data in a line graph, Easy Mode is there to help. All the actions and settings available in the line graph's right click menus and settings icons are now visible in a combined view in the left rail.

When it comes to your own world saving analytics missions, take advantage of all the amazing tools that are already available in Analysis Workspace and are just waiting to be activated with Easy Mode. Thank you.

Okay, we want feedback about Easy Mode.

- Winner-winner. - "Winner-winner chicken dinner." I love that. "Let's wake up Sophia." Yes. I totally agree.

One more feedback coming in.

How can we improve? Yep.

- Not safe for work, guys. Come on. - No comment on that. No comment on that. - "Love it." - Rogue. Rogue crew. Okay. Let's go. Let's move on. Yeah. Okay.

Yeah, once you get the eggplants out, you're cut off. This is it. You've seen all features. And this is where we vote. We want you to vote on your favorite. Remember we said impact and values over aesthetics? So please thinking about what's important for you, your workflow, your organization, instead of how they look, they can grow. They can grow better based on your feedback and our reiteration. So more thinking about the values. Let's see.

What-- Whoa. Uh-oh. - All right. - Explain Why. We will go for 30 seconds. So we will cut this off very quickly because we know what we have to do after this. - Right? - Yeah. - We have to have some argument. - Yes. And yell at each other in the nicest way. Okay, we're looking, ooh, Inline Derived Fields. - Easy mode. - Easy mode is getting up! Easy Mode is pushing up towards that. Ooh, that's looking pretty good. That's close to Explain Why. In-Line Derived Fields looks like it has it, but will Explain Why take over. Oh, boy. Okay. We have ten more seconds, and then we're going to call it. Oh, my gosh. Okay. Oh. I think what we're having is some ranked choice voting where people are abandoning other features, which is fine. That can be done. That's okay. Okay. Five. - Four. - Four. Three. - Two. - Two, one. One. All right. That's it. - Cut. Cut. - All right. We're cutting it. Cut. Explain Why. Okay. - Explain Why is going to do it. - Explain Why. All right. We're going to do Explain Why. - Yes. - Okay. All right. Oh, man. Now, guys, we're going to have the final showdown. So we are doing-- We will start with In-Line Derived Fields. That was the big winner, again, you're going to come up on stage, argue for a solid 30 seconds. Then you'll get down. We'll have somebody else come up for Explain Why. So who wants to come up to do In-Line Derived Fields, to argue for In-Line Derived Fields, and have a chance at some money? Anyone. Oh, this is the whole point, guys. This is it. There's $250 on the line, and you can come up and argue for In-Line Derived Fields. - Yeah. Come on up. All right. - Whoo.

Okay. Here, I'll come down. 30 seconds on the clock. [Jawala] Sure. So from here? Yeah, just right here. So I'm tagging implementation-- Nice and loud in the microphone. - Right here. - Yeah. So technical analyst. - Nice and loud in the microphone. - Okay. Sorry. Yeah. Okay. So it is not always possible to plan ahead, right? And we are humans. We do mistakes, right? So being an implementation guy, sometimes I do mistakes and it reflects in the data. And having that kind of flexibility at the Analytics Workspace level will save a lot of time.

Technically, say, time is like money for us. And going through that hard routes to correct the data right through the processing rules and deployment again even for those small things, it's a hassle. I think smallest mistakes should be corrected with the smallest effort. Awesome. Excellent. - Your name? - Jawala. Jawala. Thank you, Jawala. All right. Now, come on up. We got it. We got it right here. We had a very quick hand. And you have 30 seconds. So we can finish and then vote. Okay, you are arguing for Explain Why. - All right. - And what's your name? - [Megan] - Megan. Megan. - Megan, go for it. - All right. So I voted for Explain Why because it'll save our analysts and our developers a ton of time. I don't know about you all. When we run A/B testing and experimentation, our team never gets asked questions when test beats control, always get asked questions when control beats test. Right? Something must be wrong. There must be a tagging bug. Nope. This can help our analysts complain, like, nope. Not a tagging bug. This is why. X, Y, Z, right? Just last week, we saw a big spike in visits. Our analysts and developers dug in. Is Adobe broken? What's going on? What's going on? There was an expected-- We did a ton of spend up in prospecting, right? Very quick and easy, Explain Why could have told us, like, "Yep, your last touch practice prospecting channel spiked. That's why." Again, saving our analysts and developers a ton of time, restoring confidence in the data for all our users because they can quickly and easily get to that answer. Nice. Excellent. Thank you. Everyone, hand for Jawala, hand for Megan. Now let's get up here and vote. We're going to vote real quick, guys, because we're going to hit our time perfectly. - So let's see where we-- Okay. - Whoa. This is fascinating that Explain Why is ahead of In-Line Derived Fields because In-Line Derived Fields took the field so handily. So this is fascinating. You guys are weird.

Okay. It means they're both. They're both. - That's right. That's fair. Okay. - It's so hard. Now we're down to-- Ooh, it's getting closer though.

Jeff, you're only one man. You can't impact the vote that heavily. - Oh, your painting works? - Oh. Oh, you got the old one? Okay.

Yeah. All right. Okay, we're going to give it ten more seconds and then we're going to call it, and it's looking like it's Explain Why. Ten, nine, eight, seven, six. No, it's not even moving. We can call it. - Explain Why. Explain Why. - Whoo! - Explain Why. - Whoo! Jennifer, thank you. Mission accomplished. We've had our last spy standing. This is it. This is our last by standing is Explain Why. The last thing, I know we're finishing up right on time. Please let us know how we've done. Give us a survey. If we are doing a good job, they'll let us come back and do it again and maybe I can afford this tuxedo jacket.

Thank you very much for coming. Thank you, everyone. Thank you so much.

[Music]