Improve Your Data Reporting & Visualization with Customer Journey Analytics

Transcript

OK, so Hello everyone, we’re going to give folks some time to log on, but while you wait, please feel free to play a game of rock, paper, scissors and let us know in the chat where you’re joining us from.

All right, thank you everyone for joining us today. I see people still logging on, but I’m going to get us started because we have a very full agenda for you today.

Welcome everyone to The Perfect Blend. Today our amazing presenter Arindam will be going through how customer journey analytics or CJA can boost your current cross-channel data analysis and reporting on Adobe Analytics, Target or AJO. We design our webinars to be interactive, so we encourage you to ask questions in the question box throughout the presentation. Type them in there because we’ve designated the last 10 minutes or so for Q&A. I also want to mention a couple of housekeeping items before we get started. First of all, we’re presenting in Adobe Connect today and we are live, but don’t worry, this session is being recorded and can be viewed on demand or shared with other members of the team at a later time. You’ll get that recording in an email from us tomorrow afternoon. We will also be sharing a form throughout today’s webinar where you can express interest in learning more about any of the products we discuss here today directly from your solution account manager. By filling out that form, we’re basically able to connect you with your SAM who is of course the best person to explain how each of these products fits within your unique workflow. Lastly, as we’re closing out the webinar, we’ll have a few survey questions that will be at the bottom of your screen. If you could just take a minute or so to answer those, we’d really appreciate it. And with that, I’d love to introduce myself. My name is Jeff Umeguano. I’ve been a digital engagement strategist at Adobe for a little over two years now. I lead the production of our webinar series for all of our Experience Cloud products. Prior to my time at Adobe, I spent two years working in advertising for several global agencies in New York. If you have any questions or comments about today’s event or about your experience with Adobe Connect overall, please feel free to reach out to me. And with that, I’d love to hand it over to Arindam to introduce himself.

Hey everyone.

Thanks Jeff for that. My name is Arindam. I’m based out of Bangalore with amazing weather here. So I’ve been working with the Adobe products for almost eight years now. I started my career with Adobe Analytics, moved to Target, then AP, and so on and so forth. So I’ve worked in all these products. And I have been a customer with Adobe before this. I’ve been a partner with Adobe before this. So it’s not an overstatement when I say that I’ve been where you are right now. So I’ve been there. So that’s something about me. Awesome. Thanks Arindam. With that, let’s go ahead and jump right into the presentation.

All right. So we are all here today to understand how CJ, like first of all, what is CJ, right? And then understand how CJ works with other DX products. Now I have a brief summary of what we are going to go through today. It’s basically some quick introduction around CJ, some high level glossary about it and some key features. And then we’ll get into how CJ plays a role with other DX products. And whenever I say DX, please understand that I’m talking about Experience Cloud as an entire ecosystem. So how CJ plays well with the other DX products, specifically Adobe Analytics and then Target and towards the end AJO. We look at one use case or basically drive a journey around it like end to end use case for how all these come into play. And then talk about some resources, best practices or rather just Q&A towards the end.

So moving on, let’s get into the beginning of it. Let’s understand what CJ is. But before that, I wanted to have a quick poll with the group that we have.

So we just want to understand what is the current level of engagement with CJ? Have we been using it? Is it completely new to us? And I’m assuming a lot of folks who have worked with Adobe Analytics would feel familiar to it, to be honest. So feel free to mark I’m familiar with the basics.

But I see a healthy, a good number for I’m familiar with the basics. That’s good to know. So at least we won’t have to start from scratch, right? But thanks for that. And moving on, right? Let’s talk about CJ for a minute.

So understanding what CJ is, CJ is the Adobe’s next gen analytic solution. And I say next gen, but it’s been out there for a while now. So Adobe’s next gen analytic solution built on the Adobe experience platform. So it allows us to come analyze, complete and omni channel customer journeys, not just website data, but also data from like mobile applications, your CRM sent data platforms, your call centers, even point of sale and in store interactions and much more right. So CJ is a complete package where you can bring data together from multiple different sources. Now, talking about some of the key features about CJ. So CJ basically allows you to connect a lot of data, as I just mentioned. And this data doesn’t have to be just web data, like in case of Adobe Analytics, or like a mobile application data. But this data does come from multiple different sources. It could come from your store, brick and mortar stores, it could come from a CRM, it could even come from maybe some third party vendor or some something like that, right. So it brings a lot of data together. Then we have data flexibility and transformation. Now there’s multiple stages, when you bring this data in, there’s multiple stages where you can clean and transform data, right. So one thing when you’re bringing data into AP, that is when you can use products like data distiller, or just SQL or other, like ETL process processes to bring in cleaner data. And then one when you try to get data from AP to CJ, that is when you get another chance to sort of create the right fields create classifications are different stuff of transformations that can help you with your analysis. Now there’s tons of AI capabilities within CJ as well, stuff like anomaly detection and contribution analysis, which is extremely strong for a lot of different use cases. Now if you’re fresh, or I know that I understand that we have tons of data residing within AP or CJ, then how do we get started, it becomes laborious for us to get started. And that is where you could use templates. These are out of the box Kickstarter dashboards, which will help you sort of get started in the right direction. It you will get to get to have a base or a basic foundation of a dashboard where on top of which you can then start building, then it provides you end to end visualizations. And when I say end to end it, I say, literally from someone becoming a customer or a user for for your organization to the end of the complete lifecycle, where they are, he or she converts, it can show you the entire lifecycle of a customer across different channels. So it’s not just again, the web, but across different channels, how they interact with stores, how they interact with your calls, and so on and so forth. And last but not the least, it talks about data democratization. So you have multiple different roles where each role can have a different level of access to the data. And then you also have, you also get to decide the governance around it. Basically, who gets how much access and so on and so forth.

Apart from that, it just like some questions that you get to answer, and we finally get to answer with the help of CJ, is that what journey steps led to the conversion across different channels, hey, whether my experience serving different experiences on the web was helpful or maybe just an email marketing campaign was helpful, and so on and so forth. So what journey steps led to conversion? And how much did a push notification or a web experience together affect the user and so on. So there’s tons of now different use cases or questions that can be now answered, having all of this data together in one place.

And as Jeff already mentioned, feel free to post your questions in the chat if we get a chance to answer them right away, we will do that or we’ll take those in the end. Quickly moving to a very high level CJ architecture. Now, CJ basically resides on top of AP. Now AP is a massive expansive product by Adobe Analytics, which houses the data lake for multiple different products. So RTCDP, CJ and AJO, all of these three products reside on top of AP. What that means is that a lot of all the data that resides within AP and AP can get data from multiple different sources as I’ve spoken before, it could be batch in nature, it could be streaming in nature, it could come from the website directly, or maybe Salesforce or any other platform, it could land into AP and whatever data resides within AP is now available to CJ for consumption. Along with that AP also has multiple different services like query services, data distillers, which help you transform that data into more meaningful data, which is more readily consumable by CJ.

Now, quickly going from a business perspective, I just wanted to highlight where CJ sits in the entire lifecycle, right. And given the fact that we didn’t attempt to bring all of these different silos together, we want to build or Adobe wanted to build like a platform which can sort of analyze data from multiple channels and then automate and activate different segments and filters throughout different platforms, you can send this data out, you can improve your content, and so on and so forth. And then you can further personalize. So it becomes you get to close the loop on personalization and experimentation using CJ.

Okay, quickly moving on.

Let’s talk about CJ in the entire ecosystem. I’ve spoken about how CJ sits on top of AB. But let’s just quickly take a look at the rest of the ecosystem in terms of the experience from products. It talks about products like Adobe Analytics, Adobe Target and AJO. Now AJO resides within the suite. As you can see here, just like customer journey analytics, AJO also resides within or on top of experience platform data lake. But you have so much data coming in, if you see on the left hand side, you have so much data coming into AB and all of that data is plugged into customer journey analytics. Now this data and now let’s focus in or zoom in a little more on the Adobe products or Adobe suite of products. This data can also come from Adobe Analytics, Adobe Target and AJO in general, right. So anything that AJO does it anyways feeds it back to AP that which is readily available for use. But Adobe Target and AJO, sorry, Analytics also send data to AP for it to be used for multiple different reasons, right. So quickly taking a quick pause, I wanted to understand how many of us are using different platforms and not just different platforms, how many of us are using Web SDK for collecting data? Or are we still on legacy platforms like, or libraries like Adobe AD.js or app measurement I do know a healthy number of folks moving to Web SDK, which is great news for me. This is much higher than expected, to be honest. But this is nice to see that a lot of folks are actually moving to Web SDK. I’m also I would like if please put in in the chart if you’re using multiple different Adobe products at the same time, or you’re just using analytics or target and using Web SDK alongside that.

Okay, so moving on, let’s get into the implementation part of it, right. So understanding how to integrate CJA. And this is where I want to take a pause and explain before any integration. And this is like, this is something that I’ve held to alongside me for the longest period of time, but this is what I follow. So even now, whenever I have to implement something, develop something, but I want to identify what my use cases are, what I want to fulfill, what are the questions that I want to answer. And based on that, I want, I want to keep that in mind while I start creating these integrations or I start collecting it in the first place, or basically developing around it. And then basically, we start optimizing. So we have this process where we run an iterative loops.

And then you keep identifying new use cases you develop for it, and then you optimize and so on and so forth. So this is the lifecycle, we always follow Adobe and it’s always a good practice to have this in mind.

Getting started, let’s also start with a sample use case, right? Let’s understand how we might want to use all of these connections together, all of these data together to have an end to end use case. So let’s take an example where a user comes onto the website and sees like an A B test, they see that A B test this information, this interaction or this data is then collected and sent to Adobe analytics or target in general. And then this data moves from Adobe analytics to CJA. Now CJA helps us identify, hey, which what are the activities that our customers are seeing? What’s the performance for those? How, what we didn’t perform better and so on and so forth. And then you can also club it alongside different sets of data. So for example, if you have data coming in from transactional data coming in, and you want to understand, hey, this variant, did it perform better with the high lifetime value customers or low lifetime value customers? Did this variant perform better with my cart abandoners or someone who always followed through checkout, right and stuff like that. So you club different data sources together, or maybe which variant works better with someone who’s called a call center or not, right. So and moving on, we then can use this data to sort of figure out what segmentation of filters we want to build on top of it, then share it with AJO. So again, this is the entire ecosystem coming into play here, I want to share this segment with AJO, personalized experience for customers using AJO, or maybe just sending them an email or orchestrating journeys for them. And then this data from AJO then flows back into CJA for further analysis, right. So it again, it’s all about closing the loop. It’s all about bringing all of this data together to analyze it for better.

Moving on, let’s talk about CJA plus analytics. And before I get into the technicals, or the benefits of it, I, I saw a trend in the questions that we got while registration, right, a lot of a lot of folks wanted to understand, hey, why use CJA if I already have Adobe Analytics? And what is the difference between CJA and analytics? And do I really need like, should I just add on? Should I just migrate? And stuff like that? So let I’ll take two minutes to answer that sort of question and then move forward. So, understanding CJA and analytics and the differences behind this is that analytics follows extremely strict, rigid, hit based model, whereas an whereas CJA works with a very people oriented or a profile oriented, flexible XGM schema, the amount of data that we have within or typically you would have want to have within AP or CJA in general is much larger than you have in analytics where analytics only hosts data from web and applications where you bring data from any other tag management solutions and you start bringing in data from your websites, web experiences and maybe mobile applications. CJA, as I’ve said multiple times before, is much more adept to handling data from multiple different sources. You have data coming in from CRM systems, your marketing automation tools, your call center, point of sales, and so on and so forth. And all of this data comes through the Adobe experience platform. And the best part about CJA is like according to me is the identity resolution, wherein we have multiple ways to stitch data across these different platforms and data sets. You have multiple different ways you can stitch data, you have field based stitching, you have graph based stitching, and the graph based stitching is something which just really brings the power out of CJA. So you have multiple different data sets being joined together based on a graph that is formed on different identities that come in. Let’s also talk about how you can do cross channel analysis, basically a full like an omni channel journey analysis because of CJA. And it provides much more real time experiences. So the latencies to CJA might be lower than analytics if the data is not coming from analytics, obviously.

And when I talk about using data from multiple different sources, the best part is it is not just for analysis, right? You can build segments, you can build filters, you can use this data for multiple different reasons, you can orchestrate different journeys based on data from multiple sources.

Now, you some key benefits for CJA would be that you go beyond the web data, you get like the identity stitching, you have a very flexible data model, you can choose what to bring in what not to bring in, how to bring that in, and so on and so forth. Now, one use case that I always bring up right is that, hey, I want to understand how many users clicked on an ad, then called customer support, then visited my website and then ended up buying something in store. Now, this basically is a question that pulls data from multiple sources. And with standalone Adobe Analytics, you wouldn’t be able to answer that. With CJA, it’s seamless, right? It’s just seamless if the data is available in AP. Now, coming to the so how you bring in data in how you bring in data into analytics. So Adobe provides out of the box source connector where you just connect the respective reports with any starting data in. Now, I’ve highlighted some benefits of that here.

I’ve just highlighted some benefits here. And I forgot to answer a question like, if I already have analytics, do I need to add on CJA? Now, the best part about it is if let’s say you are fresh, and you don’t have analytics, you don’t have CJA, and you’re thinking, what do I get? You would want to get CJA, right? You want you want the more powerful tool of both of them. But if you have analytics, and a lot of folks would have analytics already, you have like legacy implementation done, you have a lot of teams plugged in, you have marketing decisions being taken on top of analytics, and you can’t just disrupt track, start with taking CJA and then keep adding different data and then slowly migrate to CJA. That’s the correct process you would want to take. Now, I’ve just added some key benefits of why you would want to bring in data. And then let’s go through the steps of how you do it, right? It’s an out of the box native connector that is present, all you have to do is basically select the data, when I say select the data, you have to select the respective reports read from analytics. And of course, the analytics should also be in the same Adobe org as AP, but you select the corresponding reports that you want to bring in, you can define or sort of put in custom mapping, if you want to, let’s say I want to say, hey, even for goes to page name, and that sort of a mapping that you can do here.

But you define that mapping, this is an optional step, and then you can filter data as well in real time. So basically, I just want to bring in data from the United States and not from, let’s say Europe. So if you have all of that data together in one report, so you want to selectively bring in data, that’s how you can filter it in real time. And then that’s it, you just set it up, you monitor the monitor your data coming in. And it’s that simple. That’s the beauty of the native source connector that you have there. Now moving on to target.

Now, the other question is, let’s talk about CJ plus target, right? And you have a lot of folks working with target would have seen, there’s reporting within target, and there’s reporting this effort as well, where you send the target activity data to Adobe Analytics for a more comprehensive view. This takes it one step further. So connecting Adobe target to customer to CJ provides a deeper experimentation insights, right? It’s it provides you much deeper insights with a cross channel impact analysis, you can understand that, hey, my activity alongside maybe some in store purchase or like cart abandon, a set of cart abandon, abandoners, how does my activity work with them as opposed to someone who goes through checkout, right? So understanding that that gives you a cross channel impact analysis that you can do, which you wouldn’t have been able to do with Adobe target or analytics. Now, just talking about some benefits, again, it’s, it brings all the target activity data together. So you also get a view where you see all your activities together, you can see which activity does well, or basically provides an uplift in any of your KPIs. So and the best part is that these KPIs doesn’t have don’t have to be part of analytics or target, right, these KPIs could come from your in store purchases, maybe so you can now tie in your in store data or your in store purchases to target activities, how my activities within or a web experience impact data impact my future conversions in store, right? So this is something that only you can only do within CJ. Now, it also presents the idea of a feedback loop. Once you have this data, and you can now create segments of on top of this data and then feed it back to target. So let’s say you have, hey, people in my activity, we’re in B and not performing so well, I want to serve them a different activity. So just send that data back or send that send that segment back to target. And then you can have enhanced personalization or AB testing on top of that. So it’s just a way to close the loop or have a feedback loop implemented within that.

Now, again, some sample use cases that you might want to answer or might want to solve for is again, if you have let’s say, in a simple activity on your homepage, and then you want to see, hey, how does it increase conversions across different channels? Now target only gives you basic conversion uplift and test winners and all that, right. So it gives you high level information only on that particular channel. But let’s say I want to track Hey, anyone who’s seen this activity or variant a of this activity, who later clicked on an email and use an application, or something like that. So you tie in that entire journey, how variant a of your activity then leads on to conversion, do they click on an email, do they go to the app or something like that. So that’s how you can visualize that. And then you see a long term behavior, not just immediate conversions, that’s the this So connecting Adobe target to CJ, it turns like isolated experiments into end to end journey, customer journey insights, it helps you optimize not just the test, but the entire journey around. And the process around moving data in from target to CJ, there’s multiple ways you can do that. And for folks who have, let’s say, a 40 setup for a 40 is an integration with sense data from target to analytics. If you have a 40 setup, and then you just did the step before this, you set up analytics plus CJ, that data already comes in from analytics, right, so you don’t have to do anything whatsoever. That’s it. If you don’t have analytics, or you don’t have a 40 foot for that matter, there’s a way that you can do that within target directly. And the best part is that. So there’s one thing that you can do by yourself within target. So you will have to get into touch with your support team or your SAMs, and just ask them, hey, I want to get CJ reporting enabled. The good part is that’s it. That’s all you have to do. And when you get into an activity, you will get an option, depending on your preferences that hey, I want to choose analytics as my reporting, reporting source, or I want to choose CJ as my reporting source and so on. Right. So it’s just that’s pretty much it. That’s the entire process. However, there’s some configurations that you have to do on the CJ side of things. So you have where you define, hey, what is the nature of the data that I’m going to bring in, you have to edit the connection, add the respective data sets. So target will start creating different data sets in AP. Within CJ, now you point to the correct data sets that I want to bring in all these data, all these different data from all these different data sets from target. And this would have metadata around activities, this would have engagement data around activities, and so on and so forth. And then you set up your data views and just just bring them data in and start using that right. Now, one more key feature around this is that around target is that you can start using experimentation panel. Now, I’m not sure if a lot of folks here are familiar with what experimentation panel is. But it was released last year, it’s a it’s an extremely important or a powerful tool for you to basically analyze different experiments or different various variants across different experiments, how they perform what’s the uplift and confidence levels and so on and so forth. I’ll show you some examples after this. But you can start doing that right. Now let’s come to CJ plus AJ. Oh, this is an extremely simple setup, to be honest, like I’ve said this before.

I’ve said this before, the AGO and CJ both reside on top of AP, right. So the AP acts as a base for CJ and AGO. And hence the there’s no connection that you typically have to do, you have this data already in AP, you just have to pull it in. So you will have made this also an out of the box data view or a connection which already brings in the data for AGO into CJ, but you can add this data to other connections also, so that you have this data alongside all the other data that you have. And some benefits are that you get to build much more complex reports you can build, you can analyze journeys across different checkpoints, and so on and so forth. So a lot of different, it unlocks a lot of different visualizations as well. And then you can measure the journey effectiveness across channels, you can understand full journey context, you can have segment based insights. And that’s one of the most powerful things that you can do, you can have segment based insights, you can then again use this as a feedback loop to optimize your campaigns and do an holistic attribution. Now, a powerful feature, which I haven’t spoken of about CJ before is the custom attribution that you can do. So let’s say you have transaction data coming in, and you want to understand, hey, this transaction data that happened today, how does this tie back to an email that was sent seven days before, or rather a journey that took place maybe five days before or a web experience that took place seven days before it. So you have within CJ, and you can do that on the fly.

And then figure out how this this holistic attribution comes into play. Right. So again, let’s talk about an example use case. Let’s say you run a cart abandon journey, you just someone abandoned, abandoned their cart, you send them an email or a push reminder. And then you can with AJ, you can see here, what what is the delivery success rate? What is the how many people open that email, the click through rates, and so on and so forth. But when you bring in CJ, you can then start analyzing here, after my email, or rather after my push notification, how many folks actually returned to the website and completed a purchase? Right? Or did they call the call center after that? How does this journey compare with others in terms of upgrade to my customer lifetime value and so on, right. And last but not the least, you again, you, you get the ability to close the loop on optimizing campaigns. Now CJ makes a geo smarter, it transforms the journey orchestration from a send, send and hope model to a rather data driven decisioning and a continuous optimization model where you can keep optimizing and make data driven decisions. So moving on, let’s spend some time to do a very quick demo, right? So let’s, and I’ve tried doing two things here so that you get like a extremely raw sort of experience, hey, how if I have to do this within two hours or something like that, how do I get on to that? Let me start sharing my screen as well. And then I have another set of dashboards, which I want to show in terms of him as the goal or as the end result of this, what can I achieve out of this? So I’ve tried to take both approaches, I will show you a very raw implementation of it a quick implementation and then how you sort of go through it, right. So let me quickly.

So let’s say I have a very basic sample website. And I’m, I’m not sure if you’ve seen my weekend website before it’s on par with the luma website that Adobe offers and so on. Right. So it’s one of the basic websites that we do testing on. So let’s have a basic website, I’ve designed a very simple target activity, let’s just see the activity as well. So if I go into my target setup, and I see maybe this activity where when activity ID is 275810, we’ll come back to this later. And if I see my experiences, they’re very simple, straightforward, I just want to see how my title and my description of the hero banners impacts conversion. So my experience B will be something like this, which you see right now on your screen. And then let me just move it here. And then my experience is the basic experience where it’s just a yellow, typical yellow button with view trips, and so on, right. So I’ve changed the description, I’ve changed the button and so on. And that’s the only simple activity that I want. Now when I go onto the website, and I start reloading the page, you’ll start seeing network calls to the edge network. Now I have had the opportunity to implement this through web SDK. So if I open this, and if I see if you just take a look, you will be able to see here, I’m sending all this data to analytics, as well as other places, I’ll come to that in a quick minute. And you’ll see here, what is the decisioning propositions that came in? Hey, what were the activities I was considered for? So you’ll see, hey, this is one activity. This is the other activity that I was considered for and which got through. So this is the activity that I’m seeing right now. And so on. So it’s just a very high level, quick introduction. Now, let’s quickly platform, which is like an extremely powerful tag management solution, or rather a holistic bunch of different tools, within which this tags, which is tag management solution in general. And if I come into my property, which is our number of SDK, you can see that I just have one rule, which says, Hey, there’s a page load, and then I want to send events. So one event, I want to fetch whatever activities there are. So I basically request for personalization. And the next event I just have, which will collect analysis, and I will also include render proposition. So what are the activity IDs that are being shown and send it to multiple places. Now, if you ask me how we send data to multiple places, through the edge network, it’s done through data streams, I won’t get into technicals of all of this, and I’m rushing through this because I’m low on time. But you have the capabilities of using data streams, where one data stream will now send data to multiple different platforms, you won’t have to worry about different libraries, different extensions, sending multiple network hits to different products. But you have this one data stream, which will collect data in the way in the edge network, and then pass it along to Adobe target analytics, and even a AP for that matter. And even they can event forwarding, if you want to do that, right, you can send it to third party platforms, you can send it to AWS, and whatnot, right, maybe a logging solution, anyway you want. So through this, like this gets into a B, and let me quickly now open the app, right. So if I get into a B, I you’ll be able to see all these solutions that we’ve spoken of.

And of course, it will take forever to load now, but so I’ve spoken over the Adobe analytics connector, right. So this is the out of the box connector, all we have to do is add data, select the report, sweet and so on, right. So that’s extremely simple process, you said, select what data needs you need to bring in, let’s say I just choose the sandbox, sorry, this report suite, I just want to use a default schema. That’s it. Maybe just do that. And the reason it won’t allow me to go forward is because I’ve already added one report suite alongside if you want to add more, you have to again, do some configuration here. And it will start creating data, it will create a data set for you and start collecting data. Now, if I go into my data, or rather a system view, you can see data coming in from Adobe analytics classifications, you can see data coming from Adobe analytics, you can, this is the data where which comes from, basically the web SDK that I just showed you, and so on and so forth. So multiple places, it is coming in, and then I’m sending it to target for personalization again. Now, coming to how I use this data, it let’s start getting, let’s quickly get into CJ and take a first look about it. So all of this data comes in, and I’ve set it up in my connection, let me quickly show you my connections as well.

So I have one connection, which brings in data from multiple sources, right? So it brings in the web SDK events, which I just showed you, but it also brings in the classifications, brick and mortar events. So this is the in store purchases that I’ve spoken about how data how you can tie into data from multiple different platforms, like call centers, and brick and mortar stores and POS, and so on and so forth. And I’m also bringing in AJO data that you can see here. So journey this is the AJO data. And again, this is like an out of the box integration, these data sets are readily available for you to use. There’s nothing else that you have to do. So right now, we are bringing the web SDK event. So this brings in target, I’m also bringing in the C tax sandbox mid value. So this is the analytics data that comes from the source that I just showed you. And then I have other the AJO data that is brought in. And then I have other data sets that for myself, I have the member data, I have the brick and mortar store data, and so on. It’s of all of this different data coming into the same place. And it basically creates like, I’ll show you a quick preview, but it joins all of this data together to form one multiple different records, right? So let me just quickly show that.

And let’s say I’m using a graph based to check out a field based hitting it will stitch data from all of these different data sets based on the common identifies across.

So this does take a little time, let me quickly move on.

Let’s get into a workspace, right? So let’s say I have one simple dashboard. And for the sake of time, I just want to understand, hey, what are the activities on my web page, I’ve created one simple this thing, I’ve just added my activity IDs, and how many times they were displayed, right? So in the last 60 days, it’s been displayed so many times, let’s just see last seven days. So it’s only 162 times. And this is the if you remember, this is the activity that was we were speaking about 275810. And the best part is that I can sort of create this analysis, let’s say I want to now analyze, hey, how much revenue this these activities brought in. So I can simply do I want to bring in revenue. And this is the last touch attribution that I was speaking about, I will quickly show you how we can change that. Right. So this these are the activities, these are how they basically impact my revenue coming from the brick and mortar stores. And then let’s say I want to edit this, right, I want to say, hey, I don’t want to access this last touch, I want to say, and this is an extensive list of attribution that you can change, you can put it to same touch, you call J curve, and so on and so forth, you can even give algorithmic or custom models here, it’s extremely extensive. So let’s say I just choose linear, or maybe participation. And I say, hey, I want to look back only seven days for my use case, I save I just close them, that’s it, that’s done. And if you see it just changed, it reached a lot more, because now it’s attributing all of the folks who’ve seen all these are in different activity IDs. Now, let’s say I just want to create a segment from all the users who have seen this act for one particular activity, because I want to send them in like an email or maybe enter them into a journey, right. So I create audience from selection.

It will give me Hey, the activity identifier equals this. And then there’s an activity display metric there, I just will name this something people or other users see activity x. And let me just publish this.

Now let’s quickly go into the experience platform and see this audience showing up. Now the beauty of this is that this ties up everything in real time, right. So you’ll be able to see these audiences show up. So you’ll be able to see, hey, users seeing activity x, this is the one that we just created. And now let’s do some let’s continue with our use case, right. So the next step in the use case was how we can then use this within a j o. Let’s go to a j o. So if I go into a journey, if I go into journey orchestration, let’s just duplicate one of these journeys.

I’m just a random, a small journey created. Basically, what I want to do is I want to read any audience, I want to check the gender for those, I want to split it, and then do a random split. So I’m doing an experience testing or an AB testing within this as well. But I want to show hey, men experience a and experience B and then sorry about my naming here, but this would technically be women experience and experience be right. So you can do a B testing within journeys as well. And then let’s say I want to read the from the audience that I just created. So let’s edit this. Let’s pick up the one we just saw, hey, users seeing activity x and let me just use that and save and we can just publish it right. So that’s good to go. Now the thing is that this audience might take some time to populate and it will also take some time to sort of get evaluated and populated to RTCDP. And that is where this data will come from to Asia and so on. And then you can basically maybe schedule this for tomorrow or just run this journey as of now. And let’s just choose a door. Let’s just choose an audience which already has this I’ve been doing this for the entire day today. So have a couple of other ones. Let’s just choose maybe this one. And let’s just publish this right so do and that that’s done you have now a journey where you will have folks entering this journey in real time. And then you can basically send them experiences, push notifications, emails, whatnot, right? I don’t want to get into capabilities of AGO. But that that’s something that you can do. Now, let’s go to the map last step of our process, right? Or that use case, I want to close this loop. This data now again, flows into AP. And let’s go there. Let’s go to AP, let’s go to the workspace.

And let’s just open a dumb journey dashboard, right? So this is what a AGO dashboard would look like you have all of these different journeys coming up. This is just something that I created beforehand. You will have all of these joining coming up. And then you’ll quickly see this process and close this. You have all of these different demo journey that you were seeing there and different portions and then how many folks entered how many folks exited journey failures and whatnot, right? You have all of these error scenarios and everything being tracked here. And then if you want to get into one particular journey, you can do that as well. So you can get into one journey and then analyze the journey canvas. This is an extremely powerful capability within sort of CJ, you get to see the entire journey canvas. And this is where you can change your if you want to see a fallout report, if you want to see, hey, how different sort of custom metrics, evaluate are evaluated on these different steps or how my revenue may be impacted, and so on and so forth. Right. So you can see all of that along this journey. And then you can see, hey, how my actions performed and all that. So it’s just very high level information. I in the, like, I, again, I’m a bit, I want to rush through a couple of things. Now, this is just a very raw, very crude implementation that I just showed you, right? I, it doesn’t look very good. But it’s just to show that how quick that is, this is all you have to do to get started. And I want to show you what the end results might look like, right. So I have some dashboards up with me, these are some of the dashboards that we created in CJ. And if you look at it, right, so let’s look for CJ for target, right? How a dashboard from target data might look like within CJ, and you have this experimentation panel coming, you can see here, what are the variants or what are the activities that people are seeing, how they lead to different product views and conversion rates, and what’s the lift base on my base variant, or basically no offer, and then what’s the confidence percentage and confidence levels and so on, right. So it’s extremely powerful tool to help you understand how different variants impact different custom metrics, right. So let’s, this is for car traditions, you want to see here, how car tradition is being impacted, or how if when I attribute car additions to these different variants, how do they perform? How do these how do they these variants perform and so on, right. So it’s an extremely powerful tool. And you can come up with dashboards like this. Let’s also look at like an overall dashboard. So if once you have data, so much data from multiple different sources coming in, you can create a dashboard which will tell you what are the different data sources that bring that data in how many people so on and so forth. And I quickly want to jump to the journey part of it. So you will be able to see how different journeys play a role, what is the sort of fallout on these different levels and whatnot, how different success metrics can be applied to these different journeys. And then just looking at some ageo highlights on to see, hey, what is the journey engagement percentage or the number of journey failures, the click through rate, and so on, right. So the number of unsubscribes from my journey, and etc, etc. And if I want to then analyze different journeys within this, and this is a like an amazing platform where you have all of your journeys play listed in one place, you understand here with journey led to the highest conversion, or rather if which journey is something that resonates with people, right. And same goes for target activities as well, you can have all of these target activities here, and then understand here, which activity led to a better conversion or had a better impact on my actual metrics down the line, not just immediate analysis.

I know I’ve covered a lot. And I also have rushed through a couple of things, but I’ll take a quick pause here. And I think we are out of time that we want to take questions now. Right. So let me screen. Thank you so much. That was incredible. A lot of really, really great gems in that demo. And as always, you know, the session’s recorded. So if you want to look back on anything in that demo, we will be sending that out to you within 24 hours. So plenty of opportunity to go back and go through the work. While we do have everyone live, I want to go over a few questions you guys have submitted today, as promised. Let’s start off with the first question. How is CJA different from Adobe Analytics? If we have CJA, why do we still need analytics? So this is a question that I took in the middle of the session as well. And again, to reiterate a couple of things, we want to focus on understanding the use cases around it. So if you just have one, you only have web data coming in. And that’s the only thing that we want to analyze. Adobe Analytics is extremely powerful, extremely capable, one of the best tools that you can use for analyzing data. But once you have data coming in from multiple different places you have, as I just showed you have revenue data coming in, you have data coming in from call centers, and so on and so forth. That is when you bring all of that to get data together in stitcher using maybe a graph based stitching or a field based stitching, and then start analyzing analyzing this data together. That is where CJA really shines.

Got it. Okay. And then on CJA, can CJA audiences be shared with target or Adobe campaign? Absolutely. So CJA audiences can be shared not just to Adobe platforms like Adobe target. And you know what, if you have time, can I quickly show that as well? Yeah, for sure. We can go back. Let me start sharing my screen quickly.

I would love to show you how quick that is. Right. So I think I’m sharing my screen if I’m not wrong. Yep. I can see that. Perfect. So now that the we created a couple of audiences, right, and let’s just go back quickly to the audiences that we created. This is again, a native integration. These are readily available to AJO, but you have to do a native integration between Adobe experience platform, RTCDP, and basically target. And all you have to do is choose a couple of them. So let’s hit the one that we created now. And maybe this one, and we let’s just activate these slides will activate to destination.

I think I’ve just chosen one let’s, I want to activate to Adobe target.

No new mapping required. And that’s all that’s done. Now I can send this audience to Adobe target. And if I now target you will be able to see.

Let’s just let this finish. Let’s go to Adobe target.

And this is not just for Adobe target and Adobe campaign, right? This is for any of your destinations that you can configure, you can send this information to, let’s say your Facebook ad marketing platform, right, you can send this to LinkedIn, you can send it to Salesforce, you can send it to any of your marketing automation tools. So just tons that you can do there. And so you’ll be able to see all of this. I just created this, I just shared this. And you can see that, hey, users activity, seeing activity exit just showed up, right. So it’s so quick, it’s so like intuitive to do that. Again, I’ll stop sharing my screen.

Just wanted to answer and show you folks that real quick.

Yep, that was a great example. I think we have time for one more. This one I was particularly excited to get to it talks about multi multi touch attribution, specifically how does CJA consider multi touch attribution and whether or not it’s customizable. Okay, so I was also able to show some of it. But let’s talk about attribution, right? So it it CJA and this is one of the key features where she’s CJA shines over all other analytics platforms, and especially over Adobe Analytics as well, where you can have attribution set at real time where you can change that real time and it it reflects instantaneously, you can go into your data view settings that I just showed you. And you can choose out of all of these different attributions, right, you can choose last touch first touch, and then maybe a G curve or even algorithmic attribution models, which then you can then tie in or basically answer questions like, hey, how was my if someone who’s maybe seen a target activity and then called my call center or support team and then maybe went to the store and purchase something like how does revenue tie back to all of these different steps that it took before conversion, right? So you all have all of these data together, you can create like a flow flow diagram out of any of the visualizations that CJA offers, and then have this multi touch attribution in place to understand how revenue is impacted at each touch.

Got it. Okay. So with all of this considered, I know we’ve been through a ton today, to break it down to the basics, what is the best place to start for someone wanting to implement a new CJA plus AJO CDP setup? Perfect. So I would go back to the basics where we want to understand what are your use cases, right? What is the data that we have? What are some of the use cases that we want to solve for? What are the questions that you want to answer? And then start with the basic, let’s create a data model that start bringing data in, and then have one set of sort of MVP ready. And then we do that process again. And again, we define our use cases, we sort of develop for it, and then you optimize it in an iterative fashion. So that’s the best place or best model to follow when implementing for AJA and AP and CJA in general.

Perfect. Thank you so much for all of the insight. This has been a really awesome session. I hope it’s useful for everyone joining us today. With that, I want to quickly wrap us up for today. On this screen, we have a few survey questions for you, as well as one last opportunity to request more info on any of the products we discussed today. And as a reminder, you will receive the recording of today’s event in an email from us within 24 hours. So with that being said, that’s all for us today. Thank you all again for attending. Have a great rest of your day. We, as always, we really appreciate your time. And we look forward to seeing you at one of our upcoming events.

Thank you, everyone.

I also see some questions in the chat. So someone asked, I’m still audible, by the way, I must be right. So I’m gonna ask where do we create audiences, you can create them within CJA, you can create them within RTCDP and multiple different places, but not, I mean, not in AJA directly. So you do that in RTCDP or in CJA. That’s one of the key highlights of CJA.

Anyways, thank you, everyone. I hope this was helpful. Thanks, Jeff.

Thank you. Have a great day, everyone.