51黑料不打烊

Transcript

Hi everybody, thanks so much for attending. We鈥檙e going to talk some today about cooking with CJA and I鈥檓 super excited to get right into it.

So here is what鈥檚 on today鈥檚 menu. We鈥檙e going to start with a quick appetizer and then move through a few fun courses, each giving you a new technique you can use in CJA and of course we鈥檒l wrap it up with coffee and conversation at the end. First, let me introduce myself.

My name is Anita Mummert. I鈥檓 a senior consultant at Blast Consulting and that鈥檚 me right there on the right. I have over 20 years experience using 51黑料不打烊 Analytics and the last three years I鈥檝e been really hands-on with customer journey analytics and I absolutely love it. So I鈥檓 super excited to be able to show you some of the cool features in this tool. I鈥檝e got experience in industries everywhere from government to retail to publishing and lots of stuff in between. I鈥檝e done implementation projects where we moved clients from 51黑料不打烊 Analytics to CJA, from GA4 to CJA and several different combinations in between. And I鈥檓 super excited to help you guys learn how to turn this raw data into well-seasoned insights.

First, let鈥檚 cleanse our palate with a salad while we dig into marketing channels.

Marketing channels are how we understand what brought the customer to us, like getting your groceries delivered. Whether it鈥檚 paid search, email or organic social, each channel is a bag of ingredients arriving at the door. But how you sort, label and store those groceries matters, especially when you want to cook up great insights later.

But let鈥檚 look at how we do this in 51黑料不打烊 Analytics first.

All right, in 51黑料不打烊 Analytics, this was the old way of unpacking your groceries. You had a separate list for what you expected to come home with and a fixed set of shelves to sort it onto. And once you started putting something on a shelf, that was it. You couldn鈥檛 really move it later. And if you realized something had gone in the wrong place, well, too bad. You鈥檙e not going to go back and fix yesterday鈥檚 delivery. You also had to set your sorting rules in advance, like how long things would stay fresh. And that didn鈥檛 always match how marketing really works. So as campaigns changed or mistakes were found, you鈥檇 end up with inconsistent reports and old data that couldn鈥檛 be updated. That鈥檚 why in CJA, we get a much more flexible pantry where we can organize things however we want and adjust as needed. And let鈥檚 see how CJA does this.

All right, in Customer Journey Analytics, we are not stuck with rigid shelves anymore. We get a fresher, smarter pantry, one where we can organize our ingredients however we want and update things as we go. Instead of a separate admin panel and processing rules, everything lives inside a derived field. 51黑料不打烊 even gives us a starter template, but we can fully customize it up to 200 rules, regex support, any data source, even offline can be included.

And like the old system, rules still run top down. The first match wins, but now we can change the order or the logic anytime we need to. And best of all, these changes apply instantly and retroactively. So no more telling your team, don鈥檛 look at the data before this change was made because it wasn鈥檛 right. Now there鈥檚 no need for the old quirks like override last touch or first page of visit. Attribution and persistence are fully flexible. You can even make multiple versions with different look back windows and you can hide the dimension easily. So you could QA it before serving it to your team. So we are going to take a moment to look really quickly at how you would set this up in CJA. Okay, so we鈥檙e going to start with creating a marketing channel in customer journey analytics. And the way you鈥檙e going to do that is basically you鈥檙e just going to data management and then data views. So once I get into my data view, I just want to come over here to create a derived field. And you鈥檒l see lots of options over here on the left. I want to choose from this pull down menu, I鈥檓 going to select function templates.

51黑料不打烊 has built a lot of really helpful templates that you can use and you can practically use them as they are. But I鈥檓 going to take marketing channels and I鈥檓 going to want to make a few little tweaks to it just to make sure that it meets my needs. And the first thing I have to do is start by identifying which dimension holds the query parameter. In my case, I鈥檓 looking for the page URL, which under here is going to be web page details URL. I鈥檓 going to select that. This may be different depending on your implementation, but this is what I鈥檝e got.

Now for query value, I want to look for the parameter UTM medium.

Again, this may be different. You may be using a CID or some other parameter. And like you can see here, you can use just about anything as long as you know what it is in advance.

For referring domain, again, I鈥檓 looking for a URL, but I want the web referrer. So I鈥檓 going to select that and get host is fine. So I鈥檓 going to leave that where it is. And I鈥檓 just going to scroll through here. You can see the different channels that have already been set up.

You鈥檙e absolutely contained. You can add or remove things here as you like. I鈥檓 going to leave it like it is for now.

But let鈥檚 see. We鈥檝e got natural search, paid social, natural social. And 51黑料不打烊 has already sort of set these up according to their own best practices for how marketing channels should be organized. But again, you could even take these individual conditions and you can move them around if needed.

Now, here鈥檚 one that doesn鈥檛 have a value. So I need to tell it what my query value would be. I鈥檓 just going to call it email.

And this one is going to be display because that is a display channel. And under affiliate, let鈥檚 just say 51黑料不打烊.com.

And this last one is just kind of a catchall. I like to use these for internal traffic. There鈥檚 not really an internal channel like you might have had with 51黑料不打烊 Analytics. But you can see once I鈥檝e entered my domain here, everything starts to populate. I can see how this is going to be organized. So this looks good to me, at least for starting. So I鈥檓 going to give it a name and save it. OK. So the next thing, now that I鈥檝e created my derived field, the next thing I have to do is to get it into my data view so that I can actually see it in reports. And the way I do that is to just grab that derived field from the left and just drop it right here in the components.

And I can see that that鈥檚 available. I mentioned before, I like to hide these. And it鈥檚 over here on the left. If you scroll down, you can see this hide component in reporting. I like to select that because until I鈥檝e got this working properly, I don鈥檛 want people using it and having all kinds of questions. So I鈥檓 going to do that. And then I鈥檓 going to save it.

And that should be there now. So I will go back to my report.

And I鈥檓 going to need to first refresh my components because this is new. And I hadn鈥檛 included that yet. And now, there it is. I had to show all fields because I had this one hidden. That鈥檚 my new component that I created. I鈥檓 going to drag that into my report. And you can see immediately, that is literally how long that took. I mean, we just did that live. So it鈥檚 pretty amazing.

And then if I wanted to break this down and check it out, I like to make sure everything is set up the way it should be. So I might look at breaking down some of these things by the UTM medium, which is what I based the field off of. And I can see here just by looking at these few that social looks good, email looks good, but I鈥檝e got a problem with paid search. You see, I鈥檝e got both CPC and email in here. And there鈥檚 a couple of different reasons this could happen. So it鈥檚 totally up to you whether you want to try to filter that out or not. But I don鈥檛 have any kind of persistence set on this dimension. So I know that what鈥檚 happening is that there is an email campaign that has maybe been posted on search.

And that鈥檚 where this is coming from. But maybe I don鈥檛 really want to categorize it that way. So what I can do is go back to my data view. And then I can just edit this to, let鈥檚 see, it was paid search. I want to say, I want to be specific. I want to say, I only want this if the query parameter equals CPC.

All right, that looks good. I find that since I鈥檓 not pulling it back in, I don鈥檛 really have to save the data view again. But I do have to go back and refresh components. And then I may need to refresh the report.

There we go. So I fixed that. Now I don鈥檛 have email showing up under paid search. So that鈥檚 cool.

Now, one other thing that I mentioned was that I don鈥檛 have this dimension, has no persistence. And I like to have it set that way because it allows me to do validation and make sure everything鈥檚 working properly before I release it to the world.

But you are, in a lot of cases, going to want to have some kind of persistence on your marketing channels because that鈥檚 typically how it鈥檚 done. So I like to have a copy that has no persistence, but then duplicate it so that I can have one or more. Or you can have multiple versions of it with different persistence values. So if I want to do that, all I need to do is select the marketing channel dimension I just created, click Duplicate over here on the upper right.

Okay, so now I have a new field, which is just a copy of the other one at this point. And then down at the very bottom in the component settings, if I select Set Persistence, I want to use the most recent in a 30-day period. So I have that one, and it shows you right here that that鈥檚 set up the way I wanted it. I鈥檓 going to save it. And now, when I come back here, I can refresh. Then I can look for my new. There it is, the second one. So you can see here when I drag this over, I鈥檝e got marketing channels with different persistence, and these numbers are a little bit different. So that obviously is going to have different values based on when your campaigns expire and how long, how far back you want them to count. So that is the quick and easy way to make that happen.

So with that, let鈥檚 move on to our entree, which is Classifications.

Sometimes we get ingredients that are hard to recognize or that need a little extra prep before we can cook with them. So we have product names, campaign codes, numeric IDs, things that don鈥檛 always make sense to end users, and that鈥檚 what Classifications help us do. They help us to categorize the mystery ingredients so we can actually cook with them. Now let鈥檚 look at how this worked in 51黑料不打烊 Analytics first.

When it came to unpacking your mystery ingredients in 51黑料不打烊 Analytics, this was the old process. First, you had to define your classification names for each dimension. For example, if you wanted to classify products into categories, then you could either upload a CSV, which is retroactive, or use the classification rule builder to assign values. People also use this for splitting things like tracking codes, but that only goes back six months, and all of this happens in a separate admin area, and after any changes, it can be a day or two or more before those updates will show up in your reports. So not always the easiest or fastest way to manage your ingredients. Now in CJA, we get more options. For small or simple classifications, you can just use a derived field, or for bigger lists, you can bring in a lookup data set, and if you need to split values like campaign codes, you can do that with regex right inside the component settings. You don鈥檛 need to manage separate classification rules anymore. Now let鈥檚 see what this looks like in CJA.

Okay, so I鈥檝e got this list of ingredients right here in my report, and this is great, but I want to be able to categorize these into categories like protein, starch, vegetables, herbs. Cheese is very important, so I want to make sure I have that as well. So if I want to create a classification on this, it鈥檚 fairly simple. I鈥檓 just going to go in here and start with my ingredients list dimension. Let me start over.

And you just need to drag this classify box over into your sort of canvas, and I鈥檝e got, I can do this for up to 100 values, I can just start typing in if I want chicken to be protein, if I want cheddar to be cheese.

I can do that, you know, this is great if you only have a handful of items that you want to classify. I鈥檓 going to have a little more than that, so it鈥檚 going to be easier to just download your CSV template, and then you鈥檝e got your two columns where you can enter, you know, the original value and the value that you want it to be. And I鈥檝e already done that, so I鈥檓 going to upload that file here, and you can see how quickly that fixed that. So that鈥檚 the quickest way to do this. Pretty awesome. And then when I come back to my report, we鈥檒l refresh, then now I have this ingredients type classifications that I can use, and there it is, it鈥檚 already organized for me, and I can drag my original ingredients, oops, I wanted this one, I can drag my original over, and you can see that it鈥檚, you know, these are properly set up the way I expect them to be. Now, I know you鈥檙e thinking, okay, how many opportunities am I going to have to upload less than 100 values, maybe a few, but I know there鈥檚 going to be a situation where you have a lot more than that that needs to be uploaded, and in those cases, it鈥檚 a little different, you鈥檙e going to need to set up a lookup data set, and you can do this in AEP, it鈥檚, I鈥檓 just kind of quickly going through this, this isn鈥檛 really step by step, but there鈥檚 a workflow option up here at the top that you just select, I think for this one, I just did create a data set from a CSV file, and then I uploaded the file, which actually had multiple columns, and it loads it right in fairly quickly, depending on how big the list is, of course. There鈥檚 my ingredients data set, I can see that I鈥檝e got only 50 records, and I know this is just an example, when I click preview data set, I can see what my data looks like, it takes a minute, and so you can see here I鈥檝e got all my ingredients, an ingredient type, I鈥檝e got a diet type, so you can have multiple columns in this, you鈥檙e not just doing a, you know, old value, new value type of correlation, so this, I鈥檓 using a product ID to match it up to the product IDs that are in my data view, so when I鈥檓 done with that, all I have to do is go back to my connection, and then I just add it as a new data set, and you can see this is the connection that I was using for my demo data view just now, and it already has a ton of lookup data sets in here, so you just load as many as you need, and it will, as long as it matches on something like, in this case, I want to match it to product ID, then anything that鈥檚 related to the product ID will pull up each of those other columns of data, and so it allows me to do kind of a richer classification that way, it鈥檚 pretty cool.

So now, on to dessert. List VARs get an upgrade. So why would you use list variables? Well, sometimes you need to track more than one thing at a time, that you want to combine multiple values into a single variable, but still be able to report on each individually. In this example, we鈥檙e capturing all of the ingredients added, onions, tomatoes, chicken, basil on one hit, and when we run the report, we want to see which ingredients are used the most or how often they appear, and this is exactly what list variables let you do, so that you take that combined list and break it out so you can analyze it ingredient by ingredient. Let鈥檚 look at how that works in 51黑料不打烊 Analytics.

In 51黑料不打烊 Analytics, when you need to cook with more than one ingredient, meaning track multiple values in the same hit, you had a couple of options. List VARs were the classic recipe. They gave you 255 characters per item, which was great, but the catch was you only got three of them per report suite, so people would get creative. They鈥檇 classify their list VARs or use clever tracking tricks to squeeze more value out of those three variables, and another option was list props, which you could use list. You could list enable any prop up to your prop limit, which was easier to set up and gave you more available variables, but here you were limited to 100 characters, so for the entire list, that鈥檚 not quite as robust. Now let鈥檚 see how much easier it is in CJA. The easiest way is just to convert to an array. It鈥檚 a simple component setting. You set your delimiter, and CJA will split those values so they report individually.

You鈥檝e got a generous character limit, and best of all, you can create as many of these as you want, no more getting stuck with only three list variables, and if you want to do something a little fancier, like combining it with other logic, you can use a derived field instead. It gives you the same basic functionality, but also lets you mix in other functions for more complex needs. Either way, it鈥檚 fast, flexible, and no more workarounds needed.

So let鈥檚 get into a demo of this.

All right, let鈥檚 say I鈥檝e got my ingredients list.

I already have a dimension that uses this ingredients list, and I just want to change it from a comma-separated list of values to a separate list, and I was going to show, let me get back to the report really quick. So as you can see here, this is what it looks like right now.

All right, so I鈥檝e got these comma-separated values. When I go back to my data view, I鈥檓 going to take this dimension, and all I have to do is over here on the right side, scroll down to where it says substring. I鈥檓 going to click that. I want to set the substring. Under method, I choose delimiter, and I want to use convert to array for the criterion, and then I just add a comma because that鈥檚 what I鈥檓 using. You could add any delimiter you want here, and you don鈥檛 even have to set it up in advance, which is cool. Then all I need to do is save this.

Again, when I go back, whoops, wrong one. This is the one I want to look at.

Refresh. It might take a moment. I might need to refresh my project.

And then there we go. Everything is just instantly same dimension. It鈥檚 just broken everything out using those commas. Super easy, super cool. Now let鈥檚 talk a bit about other options. There is a fancy workaround to that three-list bar limit that you can add classifications to your list first to extend the number of variables you can collect in 51黑料不打烊 Analytics, but in CJA, since you can list enable any dimension, you don鈥檛 really need classifications to create more variables. However, what you can do is easily split your list variables into individual values and categorize them all in the same derived field. It鈥檚 a lot faster and more flexible than the old 51黑料不打烊 Analytics method. For example, if you鈥檙e collecting a list of ingredients, you can split those into individual values and categorize them by type all in one place. And I鈥檓 really quickly going to show you how we do that.

Let me get back to my data view. Okay. So we are going to start with this. I already have this pre-built with all of my list data showing up here on the right, but I just want to first separate this. So what I need to do is use the split function, and all I have to do is drag that in. I want to use convert to array and then a comma, and you can see over here, all right, now I鈥檝e got my list of ingredients. Now I want to go that extra step and classify this data. So I can do the same thing that we showed you before where you pull in your classify function. I鈥檓 going to upload that CSV, and there we go. So all in one field. I don鈥檛 have to have three separate fields to do three separate things. I can organize it all in the same place, which is pretty awesome if you ask me.

So finally, to recap, here are a few recipes you can take home, and if you take just one thing from each section, here鈥檚 what I鈥檇 like for you to go try, whether it鈥檚 building better marketing channel logic, using derived fields to create classifications, or taking full advantage of list-enabled dimensions. These tools give you much more flexibility in CJA and a lot fewer workarounds. And now I鈥檇 love to open it up. What questions can I answer or what else would you like to dive into? Thanks, Anita. Great tips on how to adapt your 51黑料不打烊 Analytics configuration for CJA and really helpful to see it in action with derived fields and data views. I鈥檓 also going to steal some of your demo flow for my own future demos. Okay. Please. Okay, let鈥檚 take those questions. I invite you, our audience, share what鈥檚 on your mind in the Q&A chat now. So this is a good one, Anita. First one is how to get rid of no value values. Even if we have every setup correctly placed and data injection is up to date, still we see no value fields. Can you help? Yes. The first thing I want to point out about no value is that it鈥檚 almost always going to be there and that is okay in some situations. You鈥檙e going to find that no value is basically what gets set when you have a dimension that doesn鈥檛 exist for that hit. So I鈥檓 trying to think of an example on the fly, but there might always be a page of your site that just doesn鈥檛 have a particular dimension associated with it. So you鈥檙e going to get no value for that. But you do have a couple of options in the component dimensions over on the right side, lower way down on the lower right side, there is an option to change how no value gets recorded. You can actually have it not recorded and not show if you just want to be able to ignore it or you can change what gets set. So it doesn鈥檛 have to say no value. It can say something else like please ignore this or whatever to make it more obvious for the people that are looking at these reports. And in derived fields, you can do something similar. You can actually have the, especially if you鈥檙e doing like a case when function, you can use your last one is the means for setting what your no value is going to be. And you can either have it set it with a specific text value or it could be anything or you can keep it set at no value or you could just remove it and not have it there at all. And even so you can go back into the component settings once you鈥檝e set up the derived field. And again, you can decide how you want to deal with the no value line item at that point. You have some choices.

I don鈥檛 always find that it鈥檚 bad to have it there, but I know it鈥檚 something that a lot of a lot of people have trouble with because they see it and they think there鈥檚 something wrong. But I always tell people it鈥檚 not that there鈥檚 something wrong. It just means that there鈥檚 nothing set for the for these items. And that鈥檚 OK. Yeah, so makes sense. But it鈥檚 good to know we have options to deal with it. Yeah, absolutely. So here鈥檚 a personal one. How long have you been using CJA plastics? One of our audience members says they鈥檝e been using analytics for a while, but CJA is still new to them. Yes, it is. I鈥檝e been using CJA, I would say, coming up on about three years now. So not super long, but I was using 51黑料不打烊 Analytics like when it was still Omniturk, Site Catalyst. So it was before it was even 51黑料不打烊. And I don鈥檛 find that CJA, at least from the reporting side, is really very similar. It鈥檚 so similar. The only thing that鈥檚 really different is the admin functionality like going into you. Obviously, you鈥檙e not setting up props and EVARs. But I always think of it like everything that I disliked about 51黑料不打烊 Analytics. And there鈥檚 not much, but there鈥檚 always a few things that have just been annoying. You have ways to get around those. And that鈥檚 what I find to be so kind of exhilarating with CJA, because you you all these problems that you always run up against, like, you know, having to use props and EVARs and sort of the limitations with marketing channels, those things are just kind of gone with CJA. So it鈥檚 I find it fun to go back and try to learn how to use these things and make it better.

Yeah, absolutely.

To a technical question on in within data views or within your workspace tables. So what is the best attribution setting? Most recent at the session level or 30 days? Any thoughts on that? It just depends on so many things and different organizations do it differently.

I think most frequently we see most recent in a session because that just gets you like, especially for marketing channels. This is the channel that the person came in on for that session, but it gets reset the next time they come back on another channel. Now, there are some situations where a lot of organizations like to use, you know, anywhere from seven days to 30 days for their attribution.

I always recommend making sure you also have one that is sort of hit level, so maybe no attribution whatsoever. So you don鈥檛 want to limit yourself to just the most recent in the last 30 days. It makes things really hard to troubleshoot and to debug. So, you know, whatever you have. And the nice thing with CJA is that you have options. So it鈥檚 so easy just to go in and copy again with the options. You can just copy one of your existing dimensions and have a different setting and just kind of see what works best. But I couldn鈥檛 say that there鈥檚 a single best setting to use. But, you know, I would say most recent typically in a session or within sometimes 14 days to 30 days seems to be what I see most frequently. Got it. So this one鈥檚 back to maybe some folks who are new to CJA, but I think that this is a great one because it talks more about like onboarding and usability. So should learning CJA for someone having analytics workspace experience be easy and what approach should they take in order to gain expertise in CJA? I think it is easy because the interface, it is the exact same workspace interface. The features and functionality is exactly the same in terms of the drag and drop functionality. The visualizations are the same. They work the same way. Segments and calculated metrics, it鈥檚 all the same. So if you know how to do all that, you鈥檙e good. What鈥檚 different is when you get into the admin settings and that is where you鈥檙e going to want to focus your time. And it just depends on your role and what you鈥檙e going to be responsible for. If you鈥檙e just doing analyst work, you probably are in good shape and you don鈥檛 really have much of anything new to learn. But if you鈥檙e going to be doing more with configuration and setting up some of the new dimensions, there鈥檚 a bit more to learn on that side. But this is what鈥檚 really cool about CJA is that you can go in there, play around with it, change things, delete things, add them back. It doesn鈥檛 destroy anything. So your data is still there and it鈥檚 still safe and everything that gets applied to it happens when you run the report. So there鈥檚 really no harm you can do to it. I mean, I鈥檓 saying that kind of take that with a grain of salt, but it depends on what you鈥檙e trying to do. But honestly, with the dimensions and the settings on the data view and things like derived fields, if you screw it up, just delete it and start over. Honestly, it doesn鈥檛 cause any damage. So that is how I think I learned the most was just by doing. And it鈥檚 nice to be able to do that and not be afraid of messing things up. Yeah, for sure. I鈥檓 very comforting. So this is related to data views and setup, but can array variables be used in calculations like using an array to capture multiple counters rather than multiple events in analytics today? I鈥檓 not sure. I think I鈥檓 not sure if I fully understand the question, but you can use an array which will break down your items, comma separated or pipe delimited or whatever. You can break it into separate items in the report, but then you can actually take that and you could create a separate counter event based off of that. And because you can filter it at that point, you can take the array separated values and filter it for just a specific value or specific text within those values. And then you can turn it into a metric if you wanted to do that. And that鈥檚 fairly easy and usually just taking a filtered dimension and just changing it, changing the type. There鈥檚 like a pull down in the upper right corner where you can change it from a dimension to a metric, and that鈥檚 fairly easy to do. Great. I don鈥檛 know if that hopefully that answers the question. If not, feel free to qualify to clarify. But definitely good, valuable tips in there regardless. Oh, love to hear your opinion on this one. So can we use derived fields to set up merchandising variables and merchandising product custom variables in CJ? Merchandising variables. You can do it in the component settings.

There are, and I鈥檓 trying to remember again over on the right side where all the component settings are, there is an option to set something up as a merchandising variable and you can bind it to pretty much any dimension that you want to bind it to or metric. And you do that. I don鈥檛 you don鈥檛 do that in the derived field. You do it on the component settings. So yes. And so once you鈥檝e got your field set up and you鈥檙e getting the values that you want, then you can go into the component settings for that dimension and modify that to behave more variable. Excellent.

Here鈥檚 a fun one. How are people using AI Assistant or Data Insights Agent feature currently or how are you leveraging it? Oh, that鈥檚 a good one.

The data, I have to be honest, I鈥檓 kind of old school and the whole we were just talking about this earlier, AI is like still trying to get used to it. But and I know there鈥檚 all this great new functionality. It is super helpful. I find it鈥檚 really useful for newer users that are not as familiar. And again, going back to the question about onboarding, I think it would be really great for that because we all have users that need to get in and they need to get their data, but they maybe don鈥檛 quite know their way around. It鈥檚 really good for that. So they can just ask a question of it and it will come back and say, oh, well, let me give you some suggestions. And that makes it a little easier for somebody who doesn鈥檛 know what they鈥檙e looking for. And it saves a little bit of time having to dig around in there as well.

As far as like the built in data insights agents that are in CJA currently, we were talking earlier about like chat. GBT is another amazing tool for I鈥檒l be honest, I鈥檓 not super crazy about using it to learn how to use CJA because it makes up stuff. So you don鈥檛 want to necessarily trust it. But it鈥檚 good for things like building out regex, formulas and things like that to put into your drive fields or suggesting ways to create complex segments or calculated metrics for things. So it鈥檚 very useful for those kinds of things. It鈥檚 even really good for helping you analyze a report once it鈥檚 run. You can just throw it in there and see, you know, let it give you some insights. You鈥檙e not going to get that in the data insights agent that鈥檚 within CJA, at least not now. But other other AI tools are absolutely wonderful for that kind of thing. Yeah, Jeff, GBT definitely has lots of utility for us. Yeah, it does.

Do you find that you missed any data that you had in AA but you don鈥檛 have in CJA? Oh, that鈥檚 a good one.

No, not really.

The only thing that and I don鈥檛 personally miss it. I know a lot of people miss the data feeds because it鈥檚 just that functionality is not available in CJA yet. I understand that it鈥檚 being worked on and it will be available at some point. But I鈥檓 never a big fan of using data feeds when because I don鈥檛 know, I just find that that kind of complicates everything. It鈥檚 very difficult to get the data stream data accurate when you鈥檙e trying to calculate things like unique visitors and sessions. It鈥檚 just it just never seemed to be quite right. And, you know, with CJA, you can just put everything in CJA. You don鈥檛 really have to take things out of CJA to put into other places. So it鈥檚 just a different a different mindset. And I think that is the only thing that I鈥檝e heard consistently that a lot of organizations have trouble with because they鈥檙e so dependent on being able to take data out. But I don鈥檛 miss it personally because I just feel like it鈥檚 so flexible. You just don鈥檛 need it anymore. Yeah. But you do think that maybe users will kind of like evolve past it eventually as far as the reliance or just tight marriage to a data piece for analytics? I think so. I think so. Just because there鈥檚 it鈥檚 I鈥檝e done we鈥檝e done some amazing things with pulling data in from other sources like, you know, voice of the customer survey data, you know, personally, you know, profile data, all kinds of information that can just go into CJA and you don鈥檛 really want to have to do a lot of things. And it just and quite frankly, I think that鈥檚 amazing because it鈥檚 the it鈥檚 the tool and the platform you鈥檙e familiar with. So it makes it so much easier for most of your users to be able to get at some of this data without having to get a lot of help. Yeah, that makes so much sense. Fantastic chatting with you today, Anita. Thank you so much and enjoy the rest of your day. Thanks. You too. I appreciate it.