So What? How to forecast your marketing budget

Well, hey, howdy everyone. Happy Thursday. Welcome to So What the Marketing Analytics and Insights Live Show. I'm Katie, joined by Chris and John. How's it going, guys?

Yeah, it's just finished my Richard Simmons deal a meal lunch. In the pre-show, we were just we were talking about the different uh fad, sort of scammy kind of weight loss programs that kind of make the circulation. And I mentioned that uh in the 80s, uh, I had a family member who was subscribed to the Richard Simmons deal a meal. And so I'm gonna have to go back and do some research to see what that included. But anyway, uh getting back on track, uh, in today's episode, we are talking about how to forecast your marketing budget.

Uh the best ways to forecast your marketing budget uh for to get some good outcomes, uh, what to do with the forecast um for planning your budget allocation and an example of how forecasting earned a client more than 29% revenue. So a real uh case study on how this works. So Chris, where do you want to get started today? Let's get started with uh what it is that we would want to be forecasting to uh as a good place to start. Remember that with you know all data.

Um if you have data that includes a time series component, like you know, the the date of something, you can forecast. So that's the minimum requirements. You have numeric data and you have a date. And if you have enough of that data, you can forecast uh using you know the machine learning or predictive analytics or or data science tools of your choice. There's so many to choose from on the market now.

What you do is you get all your data probably into something you know uh like a spreadsheet, or maybe you extract it straight from a system like Google Analytics, and then you feed it to the software. And and the general rule of thumb is for every four periods you have of data, you can project one period forward. So if you have four quarters of data, you can project a quarter forward. If you have uh four years of data, you can project a year ahead. You can do projections um with less back data, but they do get increasingly unstable the longer out they go.

So, like if you have a year of data, you can forecast a year ahead, but the data that you're gonna get uh you know towards the end of that forecast is is much less reliable. It's kind of like if you think about it, you can pretty reliably forecast tomorrow's weather. I mean, less so these days, thanks to climate change. Um, but in general, it's easier to know what the weather's probably gonna be tomorrow than it is in a week, a month, and certainly in six months. You know, we have no idea what the weather's gonna be, except that we're you know we're pretty sure it's gonna be warm.

I've always you know wondered about you know taking a year's worth of data and forecasting it forward for the next year, because to me, when I hear that, that assumes that this year is going to be identical to last year. And I know that is maybe the only thing I know for certain is that that is not gonna be the case. I don't know what's gonna be different, but I know that something's gonna be different. So I personally don't feel comfortable forecasting that far out with pretty much anything. And that that's a reasonable precaution to take.

Now, the challenge for a lot of marketers is that the tools we normally use don't have forecasting built into them, right? We have, of course, our good old friend Google Analytics. And it does have a little bit of anomaly detection stuff, but really forecasting is kind of absent from here. Our friends over at TalkWalker, for example, have uh the ability to do uh forecasting on particular trends. Uh and I can show you a very quick example of that.

Um I've bit let's do let's do Google Analytics 4 as an example. And as with as you would expect, you know, there's there's a decent amount of data because this has been a discussion topic for a while. And then what it will do is it will produce a forecast of all dimensions of this and search and social and stuff like that. And then you can see an additional uh in this case, this forecast is built out, looks like about a uh a little bit more than a month uh of where it thinks uh it's gonna go. So there are some tools on the market now that are starting to have that forecasting capability uh built into them.

But there's it's still very difficult to find something off the shelf. Um things we tend to do for ourselves actually is to take data from systems we know and use uh use machine learning tools to do that forecasting. That way we kind of know uh we have we have some control over what the forecasting is, uh, which is important, and we have a sense of okay, well, what are what are the things that we would want to be able to forecast for? So let's take a quick look at an example. Let's look at uh our friend Google Analytics.

We're gonna look at just uh the Trust Insights website. Uh, where did I put that? That went to the wrong window. There we go. So this is based on uh I think I had said the three years, but um, but this is the estimated number of sessions to uh our website.

Now, here's an important caveat with forecasting. The um the the data has to have cyclicality and seasonality has to have patterns in the back data. If there's no patterns, you can't forecast something, right? I would not even wager even a dime to try and forecast, say, the 2024 presidential election. We have no data for it, and previous elections don't count.

Um so with this, uh, because we're a B2B company, we're consulting firm. Um, our data has clear patterns in it. Our our data has patterns from you know when people are on vacation uh and things like that. So this is what the our our year could look like, probably will look like based on a few years of past data. We've been fortunate enough to have Google Analytics installed on our site since October of 2020.

So we have a lot of data to go back to. It's interesting because I look at this and like, yep, so beginning of the year, everybody's trying to figure things out, they kind of cool it a little bit in February as they have all these new plans and strategies that they're trying to figure out how to execute. So they're not looking at anybody else but themselves. Then you have July, when everybody's on vacation, uh, and those are the two dips, February and July. Totally makes sense.

And but then you have end of year when all of that planning starts again, and they're looking for resources, free templates, all those things, and we start to come back up and search. So it's like, okay, I can understand the cyclicality and seasonality of our numbers. And these are estimated numbers. And whether or not we hit these numbers month over month is really going to depend on what it is we're doing. Because we could, you know, I could go back historically and look.

Well, did we release a new paper or did we release a new book or webinar or something that maybe accounted for a spike in November last year but didn't happen the prior two years. And that sort of goes back to my comment of yeah, I can sort of trust it this far out if we are behaving identically to how we've behaved before. Exactly, or at least similar enough. And there is um some good evidence that we're pretty predictable. I mean, uh us personally, um, as well as the industry as a whole.

Sure. The next thing to do is if we want to break this down, Google Analytics 4, if you've configured it properly and you're you're using good tagging and governance, you can extract out the default channel groupings. So we are familiar with default channel groupings. If we go into our the advertising menu here and go into conversion paths, we can see the default channel groupings, email, organic search, organic social, and the role that they play. So in addition to having this information, we can now start to forecast out what does this look like.

We know without a doubt that email is our single largest uh channel, our single largest driver of every kind of conversion. And so when we go into our our data and we now we can forecast just the email portion of our traffic, uh we can say, okay, well, there's there there's some peaks and valleys here. That big dip in February that's from email that's from previous years we forgot maybe I don't know what we did wrong with email in in February's past but that's uh sort of what's been forecast now the question to ask logically is well we look at this forecast we don't have to accept it okay well this is just what's gonna happen we can say well maybe we don't want a big dip from our email in February maybe we we want to try and patch that hole so Katie when you see that as a decision maker you see oh it looks like we got some some rough rough sailing in February and July what are your inclinations for trying to fix that well I mean you're going in assuming that we've done something wrong um I know our company and I know that we consistently send out you know our email newsletters so I definitely don't think it's a matter of us forgetting um I would actually put money that we did not forget to send the email that is the one thing we are a hundred percent consistent on I would take a look at other factors so back to sort of you know the overall traffic you know are people is this like the season of unsubscribe um you know are people getting too many newsletters from you know us and everyone else but then I would also want to look at the actual content that we created in those particular issues to say you know how is this different than other months where you know we had a higher uh number of sessions coming to our site from email. You know, what's the difference? Were we, you know, going too hard on promoting and not enough on just, hey, here's some helpful stuff, or vice versa.

And so I think it's not as easy as looking at this going, okay, email's broken, we got to fix it. There's a lot of different layers to understanding it. So as the decision maker to your question, Chris, my first question is, well, what kind of content do we produce in February, you know, that's not necessarily converting to you know people coming to our website. And or what are the other things that are happening in February outside of email that may be, you know, is it just email or is it the month of February in general? Those are good questions.

It is not just the month of February in general. So if we take a look at organic social data, February's you know off to a slow start there, but then we see this ramp up throughout the year. We do see that dip in July, but but social media, organic social analysis this by the way, includes our free Slack community, analytics for marketers. We bundle that in organic social. And so this would include and and we've made some really big strides in the last uh year and a half of trying to to improve the quality of that community and also the the traffic that we get from it.

So that's organic social. If we look uh at organic search organic search yeah February's a bit low there um but then so again is so is April so on and so forth. And then if we look in on referral traffic referral traffic actually goes the opposite way you know January and February are great months for referral traffic and then the rest of the year kind of falls off a cliff. We know the we have a pretty good idea of what's going on here um behind the scenes but the different channels do uh differ. Now the thing that's important to then uh remember is to look at uh something like your attribution analysis and say well which channels are responsible for you know a certain types of conversions this is for people filling out forms on our website right email is is is priority number one organic search is actually priority number five um you know referral traffic is is priority number two so when we look at this referral traffic chart uh wow you know you need uh we got to be real careful the second half of the year that the things that we do in the beginning of the year keep doing those things to keep driving that referral traffic yeah it's I think that we all and not us exclusively I mean like all of us you know in the industry like beginning the year we're all hyped up want to do stuff and then you know Q2 rolls around and we're all tired already um I'm tired already and it's January 12th John when you look at this when you look at all of this data you know what questions do you start to ask well on the email side it's definitely you know you just want to dive in over there and look at okay what are the opens what are the clicks what content is working there's a bunch of questions on that front um the referral traffic is the one that really jumped out at me is interesting though to see it so high in January and then kind of languish for like the whole rest of the year like you presume that you've got August and December are going to be dead so that's fine.

But I don't know it almost strikes me as like this one is there's definitely learning here. It's kind of like a net promoter you know it's you know if somebody's willing to pass that traffic on what's the the idea behind that and and I don't know what are and you guys are both you know more adept at GA classification than me as far as this stuff. You know, what would be the valves to turn on or the actions to take to try and improve this one. Referral traffic is all about getting traffic from places that aren't search engines, not social networks and not ads, ad systems, right? So this is um guest uh placements on podcasts.

This is uh guest blog posts, this is speaking at events, right? Where people, you know, the event uh has a listing on their on their site. This is any place where you can get traffic where someone's clicking through from somewhere else, that again is not a search engine uh social media site or or an ad system. So wherever else that we could get people you know referring other people to us would be would be the important thing. Um this may mean you know, uh having our team go out and start sourcing guest podcast speaking opportunities, and particularly in May, which is really low, uh August and then December.

But I would say May and August would be prime times to say, okay, let's go hit the podcast circuit. Um maybe uh, you know, last August, for example, we released our private social media communities paper. We did a really good job promoting that um to our audience through email and stuff like that. We did a not at all good job of reaching out to fellow podcasters and YouTubers and Twitch folks and and doing interviews and saying, hey, this you should pay attention to this thing. Yeah, it's you know, without getting too far down a rabbit hole, we're not great at that piece of promotion in terms of referral.

So when we release a new paper or you know, article or book or whatever, we don't then also pitch it around to say, do you want Katie or Chris as a guest on your show to talk about this thing? And so, you know, that's something that we should be rolling into our plan as we are, you know, trying to scale, and that would hopefully increase uh some of these metrics. But doing it in a way that is a little bit more consistent and not just paying attention to you know May and August, but so that you have a little bit more of you know a consistent number across month over month. Another thing that's important to do is to look at where your referral traffic is coming from. Right.

So this is from our our December report. Where is where are we currently getting referral traffic and is there opportunity to get more from those sources? So we see social media pulse that community that's an online community that uh run by our friends over at Agora Pulse. Could we do more there? Sure.

Yeah we could post a lot more there than we currently do which is none um and and stuff like that. Uh Scott Brinker's Martech uh Chief Martech website could we do more there? Sure. You know, pitching out the the Martech 9000 uh we did a lot of stuff with that in you know it's sort of the middle of last year but then we kind of didn't really pick up and run with it. Doing more things with our friends over Talk Walker doing more stuff on LinkedIn.

So there's there's opportunities and looking at your data once you've seen the forecast you then you know to what Katie was saying earlier you get then have an idea of what levers should I pull and and existing site traffic uh from places you're already getting referral traffic is a is a very straightforward lever. Can you go back a chart? So it's interesting when I look at this one this again sort of goes back to my question of what else is happening. So, in order for us to get referral traffic, we are then dependent on other sites, other podcasters, other things for that traffic to come through. And I know anecdotally that May and August are some of the peak conference season months.

And so people are traveling. People aren't necessarily recording. And if they are, they're releasing them on a delayed schedule in June, July, and then September, October. And so it makes me wonder, you know, how much of this is in our control when we are dependent on other marketers to be promoting us in their stuff because you know they're wrapped up in preparing for their conferences, or you know, maybe they bank, you know, 10 interviews in February and release them over time. And so ours will hit in you know July and not, and so we still sort of miss that window.

And that's a very good point. So that's where things like your attribution analysis really do come in handy because you, yeah, some stuff is in under your control, some stuff isn't. Referral isn't really under your control, right? You you you can do your best to pitch things out, but you know, something big comes out, and pretty much everybody gets distracted by the shiny object. Right now, literally everybody.

In fact, I got a request this morning from an event at speaking saying, Hey, can you talk about chat GPT uh in your in your talk? Like, sure, I mean I can make the whole talk about that if you want. Um, but it is it's not under our control. We have some level of control, some with social media in terms of what we post, how often we post, and things like that. We have no control over the algorithm, uh the various algorithms on those on those services.

We do have some control over things like who we follow and how often we follow people, but that's about it. With organic search, you have almost no control, right? You can put up good content, you can get links to it, uh, and that's about it. The rest is in the hands of the machines, and we have no idea um what happens after that. Um, Google just released their new webmaster guidelines uh about a month and a half ago, and there's you know new stuff in there now that that uh you have to uh uh obey for lack of a better word uh to do well.

Things like email, you have a lot of control over email. It's one of the reasons why it's such a dominant uh force with our with our marketing. You choose who to send to, you choose what to send, uh people subscribe to it, and if you as long as you're not sending garbage to those people, they tend to stick around. Um and so you choose your promotion schedule, you choose what goes in every newsletter. So there's a lot of control there.

Uh SMS messaging, you have a lot of control over. You know, John's been running the the marketing over coffee text line now for for quite some time. Um private social media communities, you have a lot of control, right? When you're in analytics for marketers, we decide what the question of the day is. We decide if we're gonna run a contest of some kind.

Uh, there's there's all sorts of things. So I think scoring the different channels that you have access to uh as uh the level of control you have over the outcomes is a really good exercise. So, where does the budget fit into all of this? The budget fits into this in two different places. Um, the first is four channels which are paid, obviously.

You know, we don't do a whole lot of paid advertising. Um fact we do pretty much none. Um if this chart were a say a paid email uh slide where it was like, okay, here's what we're paying. Um, and you you could forecast, you could say, hey, February and July look weak. You could say, okay, well, then let's look at our budget allocation for the year.

And maybe if we rescale what we're doing budgetarily um to be sort of the inverse of this, like let's spend more at the week, the week spots, maybe we could reverse that. So uh one of the things that uh we talked about this earlier and said, okay, well, let's say on any given month, you're gonna spend 50% of your budget for that month, right? So it's a given, you're gonna spend a certain amount of money every month because just because you have to, you're always on ads, things like that. If you take that those um activity bars, right? Uh your your likely, what's likely to happen, what's not likely to happen, and you essentially invert it and rescale it, um, you get a okay, how much of my uh how much effort should I be putting in into that in a payment, right?

Maybe I should spend more uh and you know 84% of my budget this month or 86% of my budget this month or or however much. And so that's where the budget comes into play for anytime you're spending hard dollars, look at the channels. But even when you're not, um even if you're just looking at effort, right? So this is if we look at organic search. If I have 20 hours to allocate um to organic search in terms of time, how much should I uh allocate?

How much should I push towards in any given month? Or even every given week? Like, should I put 10 hours this week into optimizing our content? Should I put in five? Um by essentially inverting the forecast.

If our goal is to minimize those losses, um, this is how you would do it. You'd say, okay, let's let's do less or more. A really good example of this, and I don't have a slide because it's still under NDA. Um, is we are working with a casino uh a couple of years ago, and they provided us um the daily uh gambling floor revenues for the casino every day for the I think they had five years worth of data. And they said, we want to know um what's gonna happen using these types of predictive analytics so we can plan promotions so that we don't have you know big gaps in revenue.

So we ran the forecast and we gave them 15 days of the year. These are the 15 days that are gonna be the weakest. Um you're gonna you're just gonna lose money those days. They said, Great, we're gonna plan promotions for the week of those those 15 days that were above and beyond what they had already planned. They did so, um, and they did a very good job.

You know, you they used the loyalty mechanisms and their mobile apps and stuff like that. And at the end of the year, when we looked back year over year for the same machines, the same tables and stuff like that, they had earned 29% more revenue by running promotions when things were weakest. I would imagine that, you know, so we don't have that type of granular data, and we also don't run that kind of a business. You know, if we were to break down the customer lifetime value, uh, you know, and get really granular for any what is the value of any given visitor to our website? You know, it would take some calculationing.

Calculationing. Wow. It would take some calculations on our part. Uh, but we could do it, and then that would help us get to, you know, for those, you know, uh marketers who are being asked, but tell me the exact amount of money that you have to spend on search versus email. If you have the data to calculate customer lifetime value and then can drill down all the way down to here's what you know a single user website is worth, here's what an email open is worth, here's what, you know, so on and so forth, then you can get really granular.

The other side of this is you have to have that flexibility and that agility to be able to adjust your budget. And so a lot of organizations don't have that. It's like the budget is set on January 1, and that's it. They can't adjust it up or down. Um, John, do you run into this when you're talking with other companies when you know you're suggesting, you know, predictive might be a good solution?

And, you know, do they say, oh, that would be wonderful, we could do that, or things have been set in stone for 18 months, we can't change it. Yeah, that's one of the, you know, it tends to just match as far as company size, right? The bigger the organization, the more the concrete sets. And the, you know, it's always exciting to have the startups that are like, yeah, sure, we can, you know, up the budget on the ad campaigns tomorrow, as opposed to, you know, the the groups that are like, yeah, no, you know, the TV ads have to be two months in production, so money available today is not going to make any difference until you know next quarter. So yeah, there's always a challenge with that.

But I think, you know, just knowing where you're at and you know what you should at least how you should be adjusting, put still puts you ahead of the game. You know, it's better than just you know, flatlining your budget and praying that works. Um another question with that though, like the casino example is interesting, just in that they wanted to buoy the days they knew were the worst, but that you'd like you still have the question of like, well, you know, if we had done that same promotion on better days, would we still have gotten the lift? You know, there's kind of the assumption that you're doing your worst on those lowest selling days, and that's the best place to put the money. Um does that tend to track from other stuff that we've seen?

Uh because obviously it does seem to make sense intuitively. And you don't have this problem if you have a capacity issue. Like we at Trust Insulence would have it, like there's certain times of the year where we don't want to be promoting or pushing because there's more work in the pipe than we know what to do with, you know, and so it's you always do want to fill in the lower capacity times. Well, that's a strategy question, right? It boils down to do you bolster your weaknesses or do you double down on your strengths?

And there is no one answer to to decide, you know, that that is a strategic question, depending on how strong your strengths are and how weak your weaknesses are, right? So when we look at something like referral traffic in our case, yeah, it's pretty weak, but it's also relatively small numbers. When we talk about when you look at, okay, well, how much traffic are we talking about? Is it relevant? Yes.

Um, but our strength is in our email marketing. So if I had 10 hours of time to allocate to something, um, I might allocate, you know, I might redo these charts as a stacked bar percentage, like, okay, of 100% of work units that week, maybe I might allocate, you know, four or five percent to referral traffic and and the other 70 to to email marketing. But then you start you start to get into the situation of the attribution. Like, what is this channel doing? Is it driving awareness?

Is it driving engagement? And so you have to, where I would sit, I would have to add on that layer of okay, great. Email is our strongest channel, so I don't want to adjust what you're doing. I actually need you to focus on referral because it's our weakest, because awareness is one of our issues that we're trying to resolve. And so it would be a different conversation depending on where in the funnel all of those channels fit.

Exactly. And so the the oh, there aren't black and white answers to these questions. They are dependent on your strategy and what you know about your company. That's one of the reasons why I am very hesitant to just you know suggest anyone just blindly trust what comes out of a predictive algorithm because you've got to know the circumstances, you know, the data behind it, uh, the anomalies have happened in the past. You know, what a real simple one is you might have a what looks like a down month, and then you're like, oh yeah, that's right.

That was the month we forgot to put Google Analytics on the new site relaunch. So there's no data, right? So it's a bunch of zeros. Knowing that, you also know that you have to do some some feature engineering and some some cleaning on the data because you know it's not reliable. Um we I think John, you were probably gonna say the same thing I did.

We have a question um uh from Shane. Sorry, John, we're covering your face. How much data would one need to make a viable forecast? I'm a smaller company, and this would be useful, but I don't know if that I have enough data to make this a viable option for myself. Um go ahead.

It kind of goes back to what we said at the beginning of the show. It's sort of a four to one ratio, three to one ratio, four to one ratio. If you have four months of data, you can forecast a month ahead. If you have four years of data, you can forecast reliably four years, uh, you know, a year ahead, with the caveat that you know there may be seasonalities and and there are uh an increasingly large number of black swans swimming around, right? So um this time last year, uh a whole bunch of folks were looking at you know Russia putting an awful lot of troops along its borders, you know, and fast forward to you know in about uh six weeks from today, last year, Russia did a full-scale illegal invasion of Ukraine, right?

That threw the entire everyone's forecast right out the window, right? Uh, you know, if you're doing if you're building your forecast in January 2020 looking for how's the year gonna go? And they're like, oh, look, as of uh April 1, uh we're all just in our basements in our pajamas and not leaving for the our houses for the next two months. So uh, but yeah, three to one, four to one is generally a good ratio of if you have uh for how much data you have in the past versus how much you can forecast forward and have statistical relevance, assuming again there's cyclicality and seasonality in the data. Uh and I apologize, John.

I cut you off. I want to make sure you get your point out. No, no worries. There is though, there's a killer point in there of having that attribution analysis done because we've seen this tons of times where you know you've got a client and they're saying advertising on LinkedIn and Facebook and Instagram, and for some reason they're all wound up about Instagram and the campaigns there, and they're like, okay, we're getting more budget, it's all going there. And we go back and do the analysis, and we're saying, look, even if you increase your Instagram ads 20 times, like it's still not even going to be like a third of your your link.

I'm getting joked out. A third of your LinkedIn ads. You know, we see campaigns that it's not worth the effort to try and double or triple, you know, unless you know that hey, we've only tried five ads and we've only spent a couple hundred bucks and we want to like jump up to the $2,000 a month level to make something work. But a lot of times we see people chasing goals that you know we're like, no, you need to put that money in another channel. Like a great example is we see a lot of customers where they need to be doubling down on email.

Like we just know that, hey, everybody in your space is killing it with email and you're not. So it's pretty obvious that you need to put the money there. So stop uh, you know, working on your latest TikTok video and you know, go chase real money that can make a difference. I was gonna say, with that, um, you know, when we first started Trust Insights five years ago, we didn't have any data of our own because we had literally just started. So we didn't have anything we could forecast with.

And so we were more reliant on third-party data sources. And so if you are, you know, like Shane, you're a small company, you don't feel like you have enough of your own data. Think about what what's the question you're trying to answer. If I trying to understand, you know, when's a good time to be pitching my services, am I trying to understand, you know, when people are gonna be searching for an organization like mine? Um, there's a few different ways that you can approach that using third-party data, such as the Bureau of Labor Statistics, uh, other financial data that I'm sure Chris can rattle off a few sources.

Google Trends is one that we always always go back to because that's really helpful to understand uh search. It's also it seems paradoxical, but it's not when you think about it. It's the further up the funnel you go, the easier it is to forecast because you have more data, right? If you were if you have a consulting firm and your sales cycle is six months, um, right, it is basically gonna be six months before you have any data to look at whatsoever, much less be able to forecast. But you can look at website traffic today, right?

If you as long as you're getting like anyone visiting your website, you can start forecasting. One of the things that uh we recommend strongly to people that were building out their Google Analytics is you have conversions at each layer of your funnel. You have an awareness conversion, which is our case is a a new user, you have an engagement conversion, like a subscription to a newsletter. And then, yes, you have your your money conversion. Hey, I I want to talk to John Wall today.

Um, you know, and that's your so your money conversion. You may not have enough data in the lower funnel conversions, but you know basic logic, right? If your website gets no traffic, you're nothing's gonna float out the funnel, right? Uh, call it a customer journey, call it whatever you want. The the reality is if no one visits your website and no one knows who you are, you're not going to get any leads, right?

It's just not going to happen. So you can look at data further up the funnel and forecast faster with that. So when we look, for example, we're looking at um, this is uh the thank you pages on the trust insights website, right? This is the people who've gone and done something, and there are a number of you know, sources and mediums in there. If you look at just new users, what gets new people in the door?

Period. Um, we see uh similar sources but not identical ones, but there's more things to work with. Um for example, we see for just getting new people, YouTube is actually fairly high up on the list, right? Um, and so shows like this, it may not be yet showing up here, right? In our conversions, but it for sure is getting people in the door, and then we have to obviously work to say, okay, well, how do we now persuade somebody to go from awareness of us for that YouTube traffic to signing up for the newsletter, joining the Slack community and so on and so forth, and then eventually calling John Wall to see, you know, if John can get you in a car today.

I think we should uh we've been talking about the John Wall dance, and so maybe we make the John Wall dance the uh opening page on our YouTube channel just to keep people engaged and get them in. I'll have to call Paula Abdul and work up a routine. You could so you know that's another aspect for Shane's Shane's question is yeah, if you don't have those bottom of the funnel metrics in sufficient quantity to do a reliable forecast, step further up, step further up in the funnel and see what do you have to work with. What you know, where could you be getting traffic from that uh results in an awareness level conversion? One of my favorites is brand organic search, right?

Organic search traffic in general. We like organic search traffic, we like people searching for us by name, so we want to see more of that. Um, for our awareness, we have these newsletters, we have different websites. How do we what can we do then to to improve our referring traffic sources? Um, this is this marketing over coffee podcast.

We should probably do something with that. John Wall slacking again. It's I I'm glad to see that on there. At least we don't have to justify the existence of the podcast. It's still doing something.

So if we bring this back to budget, so now we're talking about attribution analysis and sort of understanding which channels. So, you know, let's say I'm focused solely on awareness, and I want to allocate most of my budget to driving awareness because we know once people come into our ecosystem, they do fairly well with staying engaged and then deciding that they want to work with us. So, what I would do with this is I would say, all right, I know that email, the two different email newsletters that we have are driving a really good amount of awareness. Cool. Where I would start to focus is what are some maybe uh quick wins that I could do looking from the bottom up to say, all right, what has stopped working that I can then you know reallocate funds towards?

So Facebook, we don't really do a lot with Facebook for trust insights in general, but I might look at uh you know, inbox uh insights, our LinkedIn version of our newsletter. Is there more promotion we can be doing that? So we've been posting it consistently, but you know, is there a better way to you know write up the social posts so that people know what this thing is about? That seems like low-hanging fruit. Um, you know, we looked at the you know, marketing over coffee podcast, we have the marketing AI Institute, you know, our friends over there, you know, marketing profs, people that we know, is there more that we keep doing there to be boosting these numbers, knowing that our email newsletters are already pretty strong?

So that's the way I would look at this in terms of allocating budget. I always go from the bottom up. What are the quick wins that we can get to boost these numbers versus monkeying with the things at the top that are already working? And that's where attribution analysis also comes in handy. Uh, you know, if you are spending 20% of your budget on Facebook and Facebook is yielding 0.54% of your conversions, you know that you are overindexed, right?

You know you're spending way more than you're getting on that. And that's that's an important part of this uh of budget forecasting is to look at the results you're getting and say, are they commensurate with the investment that you're making? If you're spending you know 5% of your your budget or your staff time on email, but you're getting 25% of your conversions, you're on you've understaffed email, right? You've not got enough people working at you're not sending enough email because it's it's clearly a channel that will work for you. A real good example on this chart uh is Bing, right?

We spend zero percent of our time optimizing for Bing, right? Zero, and yet it's still delivering new visitors. Now, organic search is different because if you optimize for one search engine, you tend to optimize for all of them if as long as you're following best practices. But this is a case where you know that might be an opportunity. We look at something like the marketing AI Institute, you know, there's you know 0.89% of conversions came from that, but we haven't really done very much since Maycon, since the Maycon conference.

If we you know invested writing a you know one guest blog post a month for them, or maybe it had just had chat GPT do it for us, um, would that yield a greater amount of results, right? So to your point, Katie, there may be you know little diamonds in the rough in here, and if we put in just a little bit more effort and you know some assistance with our our AI friends, um, could we see commensurately larger results? One of the things that um you know, again, is that low-hanging fruit in terms of content production? If you have a referral, uh, you know, referral uh traffic situation like we do, where it's like, yeah, we we kind of really want our referral traffic to go better. Well, what are some easy ways to get additional referral traffic?

Guest posts, right? And we do so what every single week, most weeks, except for holidays. If we took the transcript from so what, chunked it up and said, Okay, well, this section of the show was really good. Throw that into you know uh open AI's uh GPT models, say just turn this into an article and then shop that around. It's still our words, it's still our ideas, it's still our thinking, just may put into a different format.

That's a a low effort, low investment way to create content that we could then place for referral traffic, hopefully, and see if it does well. Mm-hmm. Yeah, I think that there's a lot of opportunity when we start to look at this. And I this is the point that I was making in this past week's newsletter, um, uh inbox insights. If you're not subscribed to our newsletter, uh it's trust insights.ai slash newsletter, that you can find that as a weekly email that you'll get uh perspective from myself and Chris.

And I was talking about how we tend to get impatient and impulsive, and we don't want to take the time, like we've been talking about this data for almost 40 minutes now. And you know, that's not a long time, you know, in the general scheme of thing, but what we've seen and what we've experienced and what we've done ourselves is we don't want to do this work. We don't want to pick apart the data points to really understand where we could be, you know, making real change. We want to just do things, we want to take action, we want to, you know, shoot first, ask questions later, which is not a great tactic or strategy if you are hyper focused on getting results from the actions that you're taking. And so this is the work that you need to do up front.

You need to set aside some of your budget to invest time into understanding the data so that you know what happened, you know what's going on, so that you can make those decisions to say, you know what? We thought that email was the way that we should go, but now with a deeper look, we actually see that there's a lot of referral opportunities in terms of driving awareness as opposed to just doubling and tripling down on email. Because, you know, what if we start, you know, losing our audience? Well, then we've focused we focused on all the wrong things, and now it's going to take us even longer to gain those other channels back that we've been ignoring. Exactly.

So the forecast for your budget is derived from the traffic or the aware uh the engagement or the conversions that are already in your analytics data. Take that data out, forecast it, you know, forecast with whatever you've got for however much data you've got as far ahead as you can with that three to one or four to one ratio, and then look at your attribution models to decide what priority is are each of the channels, how much do you need to invest, right? If you if email is 70% of your conversions and you're investing 90% of your time, you may need to throttle back on it. If you're investing four percent of your time, you need to increase your staffing on it. That's a good way to determine what should have priority, and then from there, build your action plan.

Okay, what are the what are the things you have that you know can drive referral traffic or email traffic or social media traffic based on what you already have? Use the modern tools that are available, um, AI-based tools to dramatically increase your productivity. That way you can be more places without having to necessarily be more people. And, you know, to do the hard pitch because that's who we are. Uh, if you want help figuring out any of this stuff, you can go to trustinsights.ai slash contact and talk to the one and only John Wall.

He may even do a dance. Um, but he can help, you know, get you sorted in terms of, you know, do I have enough data to be running a predictive forecast? Or can Trust Insights run a predictive forecast for me using other data sources to help me understand what I should be doing next with my marketing? There's a lot of different ways to approach answering this question. Exactly right.

Any final thoughts before we uh forecast what's next? Ouch. I forecast getting back to work. That's my forecast. Um, you know, I would say don't make hasty decisions.

Make sure you're really exploring your data to understand what's going on, and then you know, set your budgets, commit to spending money. Um, you know, it's fun to just do stuff, but then maybe it was the wrong thing. So definitely take the time to do this type of analysis. All right, that's gonna do it for this week. So we'll see you all next week, folks.

Thanks for tuning in. 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 at our weekly email newsletter at trustinsights.ai slash newsletter. Got questions about what you saw in today's episode?

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