So What? Trust Insights Wrapped

Well, happy Thursday, everyone. Welcome to So What, the Marketing Analytics and Insights Live Show. I'm Katie, joined by Chris and John. Um, this week, this is our last show of 2022. Uh next week is right before uh US Christmas if you celebrate, and after that is right before the new year, which everybody will experience regardless of what you celebrate.

Uh and so this is gonna be our last show for 2022. We will be back again in uh January 2023 with some fresh content, new ideas. We'll be nice and rested. And so what we wanted to do today for this week is to do our own version of wrapped. And so if you subscribe to things like Spotify or Apple Music or any other kind of um like membership where you do a lot of activity, Peloton does it, Strava does it.

Uh they sort of give you your end of year stats of what you did throughout the whole year. So we wanted to do our own version of it with our own live stream. Um do a little recap on uh uh putting your data into a Looker Studio dashboard and just you know figuring out how to use this all of this information because at the end of the year, all of these subscriptions give you like here's your data, here's what you did, and we wanted to figure out the so what? What the heck do you do with all of it? So this is our version of wrap.

This is Trust Insights Wrapped. Um, John, did you get your Spotify wrapped? No, you know, because I live out in the hinterlands here. Like, like I need to have all my music on local because you never know when you're not going to have internet and you never know. Plus, I have like all these obscure and weird remixes too.

Like I get all angry if there's a song on Spotify that I can't find. So yeah, I'm I'm representing the uh Luddite community today. What about you, Chris? I think you use Apple music, right? I do.

So an Apple has Apple replay, but I I do I use Spotify mainly for putting together playlists for other people. Um so there were there was a little bit of data there. Um tomorrow, uh Friday the 16th, however, on the Trust Insights blog, we're gonna have the Spotify mega wrapped post as the last post in our 12 days of data. Um we're gonna be looking at the contents of over 30,000 of the most popular Spotify playlists on the web based on um SEO data and see what the most popular, uh most uh used songs were across all these playlists around the world. So that'll be kind of a nice way to cap off uh the 12 days of data and uh and keep it lighthearted.

You know, I might even be persuaded to put together like a playlist of like the top 20 songs that folks can uh can put into their own Spotify accounts if you want to see what the planet listens to. I can pretty much guarantee it's gonna be to no one's exact taste. Isn't that the beauty of diversity though? It is the beauty of diversity, but you know, it it's like putting all your favorite foods in a blender, and you what you get out, not so much. Well, okay, moving on from that visual.

Uh where should we start today, Chris? Well, if we want to use uh Looker Studio, then we should probably go ahead and pop on into that. Uh, if you're not familiar, data studio is now Looker Studio, which is still the worst named product ever. Um we're gonna we're gonna specifically look at youtube analytics. So let's go into the the trust insights uh youtube channel now the thing about uh data studio dashboards and stuff and i i st I just can't say looker um is that we want to make it look at least a little bit nice but it's gonna be challenging to do that with uh as much data as we have to work with so we have to kind of think about um what essentially the basic user story would be so what would that be Katie uh so as the producer of so what I want to know which episodes resonated the most so that I can build on those next year in my content calendar.

Gotcha okay what what does resonated mean? And I I said that purposely so that we could pick it apart because I guarantee that's a user story that you know the most highly engaged well do you mean watch do you mean like do you mean commented and so for me resonated would be uh the most watched and I know that using that you can start to pick apart the um the metrics within that of you know is it total watch time is it people who got to it at all I think probably total watch time is a great place to start um but also number like total views got it okay since we're focusing on so what, we have gone ahead and connected our YouTube channel. Um, one of the first things we're gonna want to do is we are going to want to add a filter. We're going to calling this the so what filter. And our video title uh should contain so what.

And it's gonna help us it's always a really nice uh plug for having consistent naming conventions. Mm-hmm. Because it makes it makes these types of analyses so much easier to work with when you have that consistency. Exactly. So this is total watch time.

I don't love that just a pure table, so I'm going to do uh table with bar chart, just because I think it makes it a little bit easier to understand what's going on. And we're also going to want to add our numbers on the chart. So, and let's just change the layout a bit and make the layout just a little bit bigger to 1600 by 900. I was gonna say I can't read any of that. And I have, well, I would say I have good eyesight, but with my glasses, I have good eyesight.

Right. So let's go ahead and just go quick hop into view mode here. So in terms of what got the most watch time all year is so what how to do a UX on. Let me fix the spacing on this uh resize columns fit to data and hop back out. Okay, uh then identifying red flags in the job market, AI assisted content marketing, and so on and so forth.

So these are the the episodes of so what. Uh well, one thing I was we should probably ask is should we uh slap a filter on this so we're looking at just 2022? Yeah, I think so. I mean, I think there's value in looking at both. And so, but for the purposes of this exercise, I think we just want to look at this past year, because that's what our wrapped is comprised of.

Exactly. So still how to do a UX audit, but now uh we've got other shows in here that have uh different watch time. So uh using Google Data Studio with Google Analytics 4 data, Postmaster Tools, and so on and so forth. Um, so this is what our go ahead. Oh no, go ahead.

Well, that's weird. I was just saying, because I know that the Data Studio GA41, that was going to be at the top of the list. I'm surprised to see the UX one because that didn't show up in in other stuff that I saw. Exactly. So let's flip this to top 10 just so that we're not dealing with uh stuff running off the page and put a quick summary row on just to make things look a little more tidy.

So that's one way we can look at this. Let's take, I'm gonna duplicate this. We you could do this a bunch of different ways. I'm gonna do um average watch time as our second table. I'm going to do a third table here.

Let's go there with total number of views. And let's do one last one here with video likes. And now let's hop back out. And so now we have from total watch time, how to do a UX audit using Google Data Studio Postmaster Tools, and so on and so forth for average watch time. The people who watched the longest watched the YouTube algorithm, which I guess makes a whole lot of sense if you're on YouTube.

The AMA did us did very well for average watch time, 19 minutes on that episode. Content marketing, uh the show that you and John did on subscription and advertising, where John was ranting. Uh everyone loves a good John Wall rant. Exactly. Why do these people need rants?

I don't understand. Exactly. Accessibility and then pivoting your agency uh and clients to GA4. So uh that's our watch time. We go down to total number of views.

There's Data Studio, uh GA4, Postmaster Tools, UX Audit, and GFOs, a lot of GA4, which no surprise. This was a big year for it. So go ahead. Well, and then just on terms of number of likes, the episode's got the likes, GA4, Postmaster Tools, Mora GA4, social media benchmarks, and applied data science and marketing. So this is kind of the four different ways to look at the so what's of this year.

And you know, it's interesting because you do see the trends very, very quickly in terms of what content resonated the most with our particular audience, and it's mostly around Google Analytics, the marketing platform, specifically Google Analytics 4 and Data Studio. So if if you were to present this to me, what I would do is say, okay, so it looks like people really like the Google Analytics 4 material. What else could we talk about that is still helpful and relevant and timely, or are there episodes where we just didn't explore it deep enough and we could revisit it and sort of do, you know, a bit of SEO to say, let me reference our own content and bring it into this new episode of content around the same topic and really just build on it. So this is a super helpful analysis for someone who's planning out future content. Exactly.

And there's there's a reason why there isn't more of that, and the reason why is that uh there is a paid course that you can take that goes into all that in in much more depth. Um so that would be the the first section of this. The second section I think it would be fun to do is more of that actual wrapped style. So let's do a second one here. Let's take our uh total watch time and put that on here as a a scorecard widget.

Uh we're gonna take our average watch time, uh average view percentage. We're gonna take our likes, let's look at comments, the number of people who subscribed. Oh, we want video comments, not user comments. Um let's tidy these up just a little bit here. And I apologize if you have OCD.

I promise I don't do this to you intentionally. He's speaking to me specifically. Um so let's move our scorecard widgets to the corner here. Let's put our date control on here and default it to the year to date so that it is this year, apply, and then maybe let's add just one visualization for total watch time for the year just to see how how the year looks and now if we jump back into this. Put away the menu bar.

So this year, people have watched 900 hours. Oof. So what? That's a lot of us. That's that's a lot of us.

So I don't think I can handle us for 900 hours. But thank you. Exactly. Um average, people watched about three minutes of the show. Um 53.

Oh, that's the one. I don't want users removed, I want users added. Uh user subscriptions added. We had 257 people subscribe to our YouTube channel. Uh 267 likes, 32 comments.

Uh people on average got through 24% of an episode. And then when we look just across the the total watch time spectrum here, actually, total watch time is not as helpful. Let's do just the number of views. How many views do we get? So it's very interesting.

We have that big spike right in the middle there. Now we all know what that is, right? No, no, is that a specific episode or what's that? So that is a specific period of time. That is when Google Analytics announced, hey, in one year's time, you're gonna lose access to Universal Analytics.

Oh, yeah, the one year marker there. Exactly. Um, so there's a lot of talk about that. Um so in terms of our raw stats for for wrapping up, so what? This is what it looks like.

We had a lot of people paying a lot of attention this year. And it's a good baseline in terms of if you know I had someone who was solely responsible for you know our video content. I would say these are the metrics where we, you know, this is where we shook out for this year. Next year, we want to get average watch time to five minutes. We want to get average view percentage to 28%.

Um, you know, I personally don't care as much about comments, um, but it may be something that the algorithm cares about. And so those would be the things that I would say, okay. This is a really good dashboard for us to be paying attention to to see if we are improving or not uh over the next year. So I think this is super helpful. Yeah, definitely.

I think so. The the one thing I like about being able to do it this way is because what you get in uh YouTube itself is not super helpful because it's it's very canned, and while that's okay, it's it's still not, you know, you can't drill down very specifically and and dig in just individual pieces of data. So using using Data Studio is definitely the way to go. And this uh dashboard also has the so what filter on it. Yeah, so well that's that's what I mean.

It's very hard to restrict that. Well, I know you put it on the page. Oh, you mean oh that's a good question. Let's check. Uh let's slap.

You know, consistency is key. That is true. And we forgot to put that filter on, so let's go ahead and do that. That may change things quite a bit here. I'll bet it will.

And our podcast, there was a podcast in June uh that was our most popular podcast that was around content marketing. Um, so that may change that's true. Uh these stats. All right. You are correct.

There you go. All right. And so actually looks much more consistent. It does, which makes more sense. Um, and so what's interesting is when you add the podcast and the live stream together, which is the majority of our videos, that's where we have 900 hours.

Now we're about half of that, a little less than half of that, uh, which tells me that you know the podcast and other pieces of content, because we have you know talks and other things up there, um, make up the bulk of that, but we're still, you know, not doing that bad in terms of live stream. Exactly, for a market that is very, very crowded. The other thing that I think is really important to take a look at is um taking a look at this data from uh a Google Analytics perspective too, because all this is great, uh, but you also probably do at some point want to say, well, is it is it turning into any kind of business for us? And so you want to fire up your Google Analytics 4 account and just very quickly dig in and say year to date, just conversion pass. Is video at all showing up anywhere?

And the answer is yes, sort of a mid touch point here. It does show up in some of the mid touch points. It also does show up later on in but the chart system doesn't allow you to see uh that in greater detail. Um, this is one of the reasons why we wrote our own attribution modeling for GA4, because this is kind of a pain. Um that said, uh, at least video our video does show up sort of uh as the middle in the middle of the funnel.

So combining this with our Data Studio dashboard, we can see that video is is working for us. And you know, full disclosure, given that we will be uh adding on to our own promotion next year, but in general, our promotion of our own materials is lacking for lack of a better term. Um, I would say that this is pretty good for very little promotion of uh our the stuff that we do. I would agree. So that is us wrapped now.

I guess Katie, from a marketing perspective, what comes next? What do you want to know? Um as someone who's setting the tone for what we're gonna work on next. It would be interesting to sort of see. I mean, uh benchmarks is such a lousy term, but benchmarks is also something that we would want to know of okay, this is what we look like, but what do we look like compared to our competitors?

I know that that's harder data to get a hold of. We would probably have to look at their data within uh YouTube because we don't have access to their channels. Um but just the sheer volume of content that we put out, is this good? Yeah, I yeah, I don't know. Actually, I I have I do know where we could get some of that data, but it would take a lot of digging to do it.

Um TalkWalker has that data in its platform. So if let's go ahead and go to TalkWalker, let's go to our search, and let's put in specifically Google Analytics 4 because that's what we were talking about earlier. The reason I bring it up in terms of like benchmarks, um, you know, and maybe those are the wrong things to look at, but you know, in terms of cadence, we do one show a week pretty much every week, with the exception of a handful. So let's say, you know, we do 45 shows a year. Is that enough?

Is it too much? You know, should we increase the cadence, decrease the cadence? And so those are the types of things in terms of resources I would be looking at in addition to the topics themselves. Right. Okay, so we have on any given day, there's there's a handful of uh videos about it.

Uh, you're talking about 30,000 engagements, potential reach about 700,000 total. Let's take a look at some of the listings. So you have Google Search Central, best call tracking, so just ads, some bounce rate stuff, some tutorials. Uh this is sorted by engagement. So in this particular the highest rated uh the highest engaging video came out in March, end of March from Google itself.

Uh 518 likes, 32 comps for a total of 551 engagements overall, and looks like a reach of about 15,000, so 15,000 views. Um does it say how long the video is? Uh it does not. Because that would be the other thing that I would be interested in. As, as you know, if I were planning this to say, okay, great.

So we don't we do like a 30 to 45 minute show depending on the topic. Is that if we were to change the length of the show, would that change the average watch time? Would that change, you know, people's ability to consume the content because it's too long or you know whatever that those are the questions that I would be asking. Right. Okay, let's take a look and see if that data is even in the file for for usability.

So YouTube. So, John, when you're looking for videos, um, you know, does the length of the video sway your decision in terms of whether or not you're gonna watch it. Well, you know, there's two kind of use cases that come to mind. I mean, one is if you're searching for a specific answer, then this is the the kind of traffic you totally expect to see. And in fact, YouTube is doing a better and better job of chaptering and showing when people are jumping to points so that you can just get the specific question you want answered.

You know, you don't have to watch the whole thing. That's pretty normal. And the the other side of it though is for pure entertainment videos, you know, something where people want to sit down and actually watch the whole thing. And yeah, I don't know, looking at it from that side, it seems like given the average length time, we could compress a little bit, you know, try and get tighter and see how that would affect the overall number of views and number of likes and things like that to see if that would change things. Um But I don't know, it's it's always hard to gauge that because you know, 20 minutes is like classic entertainment length, but 40 minutes is more kind of standard academic deep dive real content, you know.

You know, so it's uh uh and maybe just something to play around with too. There's no reason we couldn't do you know, alternate weeks of shorter and longer to try and kind of see if that affects anything or where it goes. Um and then yeah, it was interesting to see the open QA doing well there. You know, that's kind of like grab bag stuff that does tend to pull some people. So that was interesting to see just show up in the overall list.

There is no variable within the data export for video length. We just have for YouTube specifically, we have likes, dislikes, and views as the the primary parameters. We can get the dimensions of the video, but that's that's about it. No, I think that's fine. Um I was just I was, you know, it was a curiosity thing.

Um, you know, do shorter videos do better than longer videos? And you know, I think John, you gave a really solid answer of, well, it depends on what you're after. If you're there for entertainment, maybe you want it to be longer, versus if you're there to for like a how-to, you probably just want to get your question answered and move on. Now, of these videos, the median number of uh views on a video about Google Analytics 4 is 40. Right.

So that is the median number in this huge data set. So when we go, if we go back to our uh look or studio profile, um let's see. So we're hovering probably around the 15 to 20 for uh as a median number. So we're not that far off from uh you know from from the the category as a whole. Okay.

That's good to know. And what's interesting when we look at the table itself is even though we're focusing on Google Analytics 4, these videos are not all laser focused on it. A lot of them is like roundup news, like Google search news and things like that, uh Google Tag Manager for beginners and so on and so forth. So it's not just GA4. Right.

Well, and I think as you know, as the buzz around GA4 starts to wear off, people will start to look more at the well-rounded Google marketing platform. And so that's something that you know we should be thinking about of have we tackled all the pieces of Google marketing platform as they feed into a Google Analytics instance. And I can say with 98% confidence, we really haven't tackled AdWords, for example, or Google Ads, whatever it's called these days. They keep changing the names of these things, and it just makes me feel old and out of touch because I never get it right anymore. Uh we'll put a little chair emoji in chat.

So yeah, I think those things are interesting. Now, here's the other challenge that from a video content producer that's hard is this is what we know, right? So the the bigger question from a content production standpoint is what are the topics or ideas or things that we're not doing that we could be doing that might do better. That's the burning question that you know, uh content marketers, video marketers are always wondering is what else? What's next?

What's new? What do I need to be thinking about? Um, you know, for us, Google Analytics is a sweet spot because we know it so well, but where we are having the same conversations that everyone else is having. So, what's the new spin on Google Analytics or you know anything else? And so I see that you've just put chat GPT in there, which is like the fresh hot thing, but how long is that gonna last for?

And everybody's writing about it, everybody's talking about it, we've talked about it, and so again, it's another topic that is being so heavily covered. Like, what are the spaces in between? The spaces in between, I think, are what we talk about all the time, which is the so what, right? A lot of these things, Google Analytics for Google Tag Manager, Chat GPT, NFTs, whatever, is okay, it's the thing. It's like frying pans, you know, soup pots and things.

And the so what is yeah, but what do you do with it? Right, how do how do I make this thing useful? Um, rather than having it just be uh yet another thing on my to-do list. Like, how do I how do I use this thing to be helpful? And so, for all these things, I I firmly believe there's a very large market that is untapped of just show me how to use the things and and and get one more thing off my to-do list.

I'll give you an example earlier today. Um, I got a request from our friends over to Goropulse and said, Hey, we want uh we want you to write an article for our site um about your how people should think about their analytics workflow. And I'm sitting here thinking to myself, yeah, I could. Do I have time to do it? Do I want to do it?

Stuff like that. Uh, and I'm like, eh, well, we like our we like our friends at Aurora Pulse, so we should probably do something. How much time do I want to spend on this? So I sat there and thought, well, what if while I'm cooking breakfast, I just turn on my voice memos, I turn on the otter app, um, and I just foam with the mouth for 15 minutes about my analytics workflow. And so I do.

Uh, and then I get the really rough, messy transcript, and I've just stuffed that into um OpenAI G GPT playground, which is the engine the Powers uh the where that gets you to the model faster than the chat version. They're the same thing. I said, please rewrite this. Please rewrite this so that it's not incoherent rambling from somebody for 15 minutes, but it actually is a coherent article. Um, and it does, it preserves I told it to preserve certain things.

Like I want you to keep all the acronyms that I used. Uh, I want you to keep the technical terms. I want rewritten from a professional technical tone of voice. I want it to be uh college age readability. And it turned probably 4,000 words of rambling into a compact 750 word article that was coherent, and I looked over and I shipped it out.

And you know, the that process took six minutes. So instead of what would probably take me an hour, maybe two hours to stand on, you know, bang out the words and second guess myself, I recorded 15 minutes of talking, took six minutes to run it through the engine, and now I was able to produce a good enough article for for guest posting. So one of the things, Katie, that we have on our our list for next year is how can we do more guest posting and writing and content production off our site? This is the process I'm gonna take into it. So that would be the recipe.

And so yes, the shiny object syndrome part of chat GPT will wear off, right? You can already kind of see it. There's a big spike in that purple line, and it's already dropping off pretty fast. Clay Shirke said something a long time ago that I love, and I I recite often. Once a tool becomes technologically boring, it becomes societally interesting, right?

Once once the the shiny objects factor has worn off, then it if it's got legs, people are gonna start using it. So for the content we need to create and the stuff that we want to show on on so what and other things is gonna be focused around, okay, it's great that this thing exists, here's how to use it. And I think that you know, we always try to focus on the how to aspect of our topics, but we could certainly do uh a better job of that. And John, to your point, how do we make it a little bit more succinct? You know, sometimes, like just happened, we kind of go a bit off topic of the original concept of the show, and so maybe it's a little bit more preparation ahead of time to make sure that we're hitting certain points and really driving home here's the so what, here's the so what, here's the so what.

Um so that you know, when people are searching for things on uh YouTube, they can very quickly find how to integrate open AI into your content marketing workflow. Like that's a terrible title, but that's essentially what the gist would be. Exactly. And they could open the video and immediately have an answer. Exactly.

It's just like we've talked for years. How do we get people to use attribution reports better? Right? So this is the trust insights report for the last year from Google Analytics 4. It falls in the category of okay, that's cool.

Right. I I see all the things, that's nice. Um the so what of it is we look at something like Facebook. Two percent of our conversions for this conversion came from Facebook. Are we investing two percent of our time and effort in Facebook?

No. We're not we're we've we've actually specifically decided not to market on Facebook at all and yet it's still delivering something. So um the question there is do we need to do we need to reconsider that we invest uh a lot of time in in Slack and it's about three and a half percent of of the places and times we spend on investing in marketing is that the is that a good use of our time i it's our number five converting source probably so YouTube's kind of down here right um it's it's 0.31% of for this particular conversion for for filling out thank you forms uh now if we were to look at a different conversion like new users to the website that might be different right but that's what you do with an attribution report you don't just stare at it it's not it's not cubicle art it is use these percentages to to make decisions i i know I'm investing x percentage of time money and resources into this channel am I getting the same or better results out you know how much money do we invest in the almost timely newsletter right and and and we get 56% of our conversions from it for this year. That that one would also be you know over 50% at that point we're like is that a risk thankfully no because the the the publisher was also the co-owner of the company um but if this was an external channel that wasn't under our control that's a real risk if if that channel goes away you know, we have a big problem. So when we go back to the purpose of this particular episode, which is you know, trust insights wrapped.

You know, we sort of started that lightweight, hey, let's look at our show. But really, what we're seeing is it's it's a way to organize your data for your past year that maybe people can you know understand a little bit more, make a little bit more actionable. Um, you know, one of the challenges that we're always trying to help ourselves and our clients with that because I think what you call analysis paralysis is there's so much data to look at. Like you exported data from YouTube, no, from TalkWalker for YouTube and then pulled it in, and it was just the sheer number of metrics we could look at. If we didn't have a clear-cut question, then we probably'd still be there looking at it now.

So I like I like borrowing from these more popular platforms like a Spotify, or you know, pretty soon I'm hoping to get my pellet on one to tell me, you know, what I did in the past year, because that's always fun. Um, John, you'll probably get one from Strava, Chris. You know, I think you use a couple of different fitness apps as well. And so it's always fun to see that data for yourself. So thinking about that in terms of how do you bring that into your organization, into your team, to you're still telling the same story, but you're telling it in a little bit more lightweight, you know, maybe easier to understand, digestible pieces.

So borrow from how these other apps are doing it as you're presenting it to your you know, C suite to your stakeholders, as to the decision makers, like, hey, this is marketing team wrapped. Look what we did this year, and so giving you an opportunity to highlight everything but then also say so wouldn't it be great if next year we could get to 25% uh you know average views or 10% watch time and that's what we hope to see in our wrapped of next year for example exactly and I think that that is the other thing that wrapped does I think so well and this is an example of one right um is it's all about you yeah right it's all about you everybody it's you know John and I were talking about this yesterday the reason why so many of these different AI tools like the you know the puts you into a a portrait of you as a Viking or whatever the reason why it's so popular is it's it's your favorite person it's you right it's it's you you know wearing fairy wings it's you as a as a you know action hero but it's it the center of it is is you and so when we think about our reporting right you take your average report is it about you is it about this the stakeholder right uh is it presented from the perspective of the stakeholder or is it presented from the perspective of the tool or marketing team or whoever and and may that's what these that's what these rap things get so right. This is all about you and I like to feel good about myself. John did you get one for marketing over coffee? No I did not I was basically ranting I just can't get myself over the hump of like me me me me me you know you just like don't want to pay that but I don't know.

I've seen some that are so amazing now. I'm I'm slowly starting to lean, so maybe I'm getting pulled out of the Luddite uh quadrant today. Here we'll see how that goes. That's that's our 2023 goal is to you know bring John into at least the 18th century. Some wooden shoes I'll be.

Which is funny because John is Mr. Technology, Mr. You know, I play with all the stuff, but then when it comes down to actually, you know, using it for your own stuff, that I think that's where you you know dig in your heels a little bit. Yeah, well, the tech contrasts with the curmudgeon, you know, that's the old man thing that gets in the way of just buying everything all the time. Uh so as we are wrapping up Trust Insights Wrapped, um, I'll ask you both, and then I'll answer.

You know, what do you hope to see for so what moving into 2023? Chris. I would like to see us build a cookbook. Right. So if we focus on in this episode, here's how you use Data Studio to analyze YouTube data.

Right. Here's how you use Google Analytics for data to understand which page is the most valuable by the end of 2023, with all these new cool tools and technologies and things that allow us to summarize and and fix transcripts and stuff. I would love to see a so what the cookbook, right? Of here's 50 marketing recipes that you can take to the bank today and and and make a difference in your organization. I think that would be a really cool takeaway for everybody to have from a show where this is what we do every week.

I like it. John I'd really like a picture of myself as a Viking. That's number one for next year. Uh but after that, no, I think I I don't know. I just think we've got a lot of great content and just finding a few ways to kind of change it and figure out does it need to be more live streaming or does it need to be more QA or what can we do with it?

I'm just it I think um yeah it's just like any kind of content. It's like you do the first drafts and you kind of keep playing with it until you find something and and I think yeah eventually we'll hit something where it will jump up to the next curve you know and that's what I would really like to do kind of figure out where it needs to be next. And yeah I can see having a recipe book where you know there's 40 segments of it like each episode is a piece of that overall book or something like that. Yeah maybe that's somewhere uh we could stop next because that does seem pretty interesting. Yeah.

Mm-hmm. I would like to figure out you know so we do this show live and then people can watch it afterwards. I would like to figure out you know if we want to continue to do it live how do we get more audience participation? How do we get more people showing up you know during the recording so that we can get more of that interaction. Um but then also just you know really digging into what's working, what's not working and I think that that goes down to Chris what you're talking about of you know the real nuts and bolts of how-tos and outlining it so people know what's coming, what they can expect and maybe they can pre-order you know the playlist ahead of time or the book or however we you know package it together to because they know each piece is valuable but when you put it all together they can you know entertain for 50 people.

Exactly. So day of studio crudetes. So with that, you know, if you're watching this, thank you for uh being along this journey with us. This is as I mentioned at the top of the show, this is our last episode for 2022. We will return in January 2023 uh with some new content, maybe a whole new content strategy.

Who knows? We have a couple of weeks to think about it. Uh final thoughts, Chris, John. Drive safely. Don't uh don't don't do analytics while driving.

Uh what if I just recite my multiplication tables? Sure. Um no, yeah, I I think thanks thank you too for for watching for tuning in, whether you're watching live, whether you're catching the recording, whether you're just reading the transcript. Um we appreciate the attention knowing that in the coming year, even this year, the sheer amount of content people are creating is is greater than ever. And so any attention that any of us earn as a marketer, we have to be thankful.

So thank you. That sounds good. Be sure to show up in 2023. We'll be looking for you at all the events. We're going to be covering a lot of ground next year.

So hope to see you in the world. Happy holidays, everyone, and happy new year. Thanks for watching today. Be sure to subscribe to our show wherever you're watching it. For more resources and to learn more, check out the Trust Insights Podcast at TrustInsights.ai slash TI podcast and our weekly email newsletter at TrustInsights.ai slash newsletter.

Got questions about what you saw in today's episode? Join our free Analytics for markers Slack group at Trust Insights.ai/slash analytics for marketers. See you next time.