So What? Marketing Analytics and Insights Live
airs every Thursday at 1 pm EST.
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In this week’s episode of So What? we focus on making your SEO data actionable. We walk through tactics to make the most of your data and why timing matters. Catch the replay here:
In this episode you’ll learn:
- how to make your keyword and competitor data actionable
- how to use the data for all your digital channels
- how to use the data for a predictive content calendar
Upcoming Episodes:
- How to build a marketing strategy
- Change management and digital transformation
Have a question or topic you’d like to see us cover? Reach out here: https://www.trustinsights.ai/resources/so-what-the-marketing-analytics-and-insights-show/
AI-Generated Transcript:
Katie Robbert 0:22
Well, hello again, Happy Thursday. Once again, we are the marketing analytics and insights live show I’m joined by Chris and John. You know, so the past couple of weeks, we’ve talked about SEO data. And so two weeks ago, we talked about keyword research. Last week, we talked about competitive research. And so if you’re following along, we assume that now you just have a big old pile of data. And you’re like, so what, what do I do with all this stuff? Well, you are in luck. Today, we are talking about putting your SEO data to work we are going to cover how to make your keyword or competitor competitor data actionable. How to use the data for, for Wow, my Boston accent is really trying to come out today for all of your digital channels, and how to use the data in a predictive content calendar. Um, so John, Chris, where do you guys want to start today?
Christopher Penn 1:18
I think probably the place to start today would be to talk a bit about how to use this data in a forward looking fashion because one of the things that we talked about recently was that you can look out the rearview mirror of your car with like, perfect clarity and know exactly what’s happened, right. But it’s a very limited utility, for figuring out how to drive the car going forward. And the challenge for a lot of people is there’s, it’s difficult to make that transition. Right? It’s difficult for people to go, oh, how do I start forecasting with some of this stuff. And so I think we should probably spend a little bit of time talking about like, what forecasting even is, so that we know how to make use of this data. So when we talk about predictive analytics, which is what we’re really talking about here for using this, this SEO data, we’re talking about, in this case, time series forecasting, saying, here’s a bunch of data from the past. And as long as the data has two key ingredients, we can use to predict forward and those two key ingredients are cyclicality and seasonality. seasonality is changes within a year, this time span of a year. So there’s seasons to a year to seasons, to your data. And cyclicality is repeated patterns in the data now, that can be of any duration. So we’re a B2B business. And so you’ll see like in our Google Analytics, there’s a cyclicality of Saturday and Sunday, no traffic, you know, Monday through Friday, you know, lots traffic, you get this cycle. But there’s also cycles on weeks, on months, even years, some years. You know, there’s like, if you’re a business that does consulting, say, and pull in politics, yeah, there’s every four years you’re really busy. And the rest of the time you’re like, trying to figure out what to do with your life.
Katie Robbert 3:13
And so I know, from past talks we give and when we talk about how to understand how time series forecasting works, we often give the example of Google Maps, because the time series forecast is based on an S-ARIMA model. And so basically, the way that we talk about it is if you think about, you know, getting from destination, a to b, when Google Maps is serving up the information of how long it’s going to take you to get there. It’s using historical data based on that same route that other people have taken and roughly how long it takes them to get there. So that’s where it starts. But it continues to update you in real time based on weather, on traffic, on the speed that you’re going on the time of year, those types of things. And so what Chris is describing is taking that historical data and projecting it forward in such a way that it’s updating, and you can use it right then and there.
Christopher Penn 4:11
Exactly. And that’s why one of the reasons why you have to do so the math on this stuff, because unfortunately, with trend prediction of any kind, you really can’t eyeball it. There’s, there’s and there’s a couple of different types of math that you need to do. One is determine Is there even a trend right? Is there even, you know, something that can be forecasted? So, show you a couple of examples here. Let’s go to I’ll put up this lovely slide, right? Yes, Chris. what
Katie Robbert 4:48
that was, that was not a nice looking graph. It’s fine.
Christopher Penn 4:52
So in this example, there really isn’t a meaningful And there’s some mathematics on screen maybe in another show, we can actually talk through the the the specific mathematics is the statistical testing, but not for the show. But essentially, you’re saying, there is no trend here that you can use to forecast this term. And because there’s no trend, you can’t use forecasting, no cyclicality. If you look at this chart here, there is a trend, it’s weak. But there is a trend that is there in the US, you can forecast with this term. And then you know, this is Tiktok. Again, same mathematics, but you can test it and make sure that Oh, there’s actually a pretty strong trend here. So you can use this. So with your search data, one of the things that ideally, if you’re using software that has predictive analytics capabilities, the software has built in testing to say like, yep, this, this is usable, there’s a trend, or no, there’s not and you know, not to use it for forecasting. So that would be the first and most important thing is, is the data you’re using doesn’t have cyclicality. Now some data and like SEO data, thankfully, is something that it has tends to have a lot of seasonality, and a lot of cyclicality. And particularly for generic terms, when we look at everything from like holiday gift guides to consulting firm to whatever, those are terms that because they’re not really unique. And they’re not really, you know, a small niche. They have a lot of seasonality, a lot cyclicality. And one of the sort of the axioms of forecasting and SEO is the more difficult the keyword term in terms of ranking for the easier it is to forecast, right? Because there’s more volume, and it’s been around longer. So that that’s one of the reasons why we say when when you’re putting together your keyword strategy. We talked about this two weeks ago, you have that core term like analytics, consulting, or change management. And then you use tools to answer the public to build your question caught your your, your corpus of content around that courtroom, but that core term, because it’s so competitive, also makes it really easy to forecast.
Katie Robbert 7:00
That makes sense. Obviously, more data equals a better forecast. And so I know you’re going to walk through putting that predictive forecast together using your SEO data. I do want to sort of mention that obviously, we’re going to be using software that we created. But if you had like a small handful, like less than 10 terms that you really cared about, you could plug each one individually into Google Trends to see if there is any kind of seasonality so that you could sort of have in the back of your mind. Okay, when I want to be talking about change management, it looks like for the past five years, people tend to talk about this in December, which makes sense because they’re putting together their annual plans, you know, so there is definitely ways to use these free tools without having to write any software, will it be as efficient? No, but will it be effective? Definitely.
Christopher Penn 7:51
Exactly. And in some cases, depending on the search term, and whether Google Trends supports it or not, as an example is Google Trends may actually offer a forecast. It does that doesn’t do that consistently. So I pull up Google Trends here. Sometimes you’ll see a little dashed line at the end. And Google will say like, yeah, this is our attempted forecast. So let’s look at the the I guess the the non software route, the non build it yourself software out to what you’re saying, Kate, if we look at this search term for change management, and we look at the last five years, there is a clear cyclicality and the seasonality to riders enter your season, enter your season, and there’s year over year season, those dips there, of course, are the holidays, right? every year. You know that? It whatever Christmas and New Year’s people aren’t searching for this term that they’re doing anything but and so roughly speaking, if you wanted to, you could actually take this graph of this data out export, put it in something like Excel, and just lined up, you know, week over week for every 52 weeks and see, okay, what weeks the in the past has this more or less increasing. So that would be I guess, the the least onerous way to handle that. If you have access to tools like IBM Watson Studio, for example, you can plug the raw data into Watson Studio and have it build you a forecast. We use the programming language R, which does essentially the same thing with a type of model called profit, which is made by Facebook labs. And exactly the same thing, takes five years worth of data back and then projected forward.
Katie Robbert 9:38
And so I think, you know, the past couple of weeks, we talked about, you know, getting that keyword research out of those keyword tools, but then you also want to use a tool like Google Trends for exactly that reason, because it’s literally what it says it’s the trend of search terms. And so how is that specific term going to be trending?
Christopher Penn 10:00
Exactly. So do we want to go into like, a trying to assemble one of these models with Watson Studio? Katie? Or do we want to go straight to processing the data itself?
Katie Robbert 10:12
Let’s just do a quick walkthrough of Watson Studio. No. So let me ask you this question is, is there a free version of Watson Studio that people could play around with that, you know, they don’t have to sign up for an enterprise license.
Christopher Penn 10:26
There is. So Watson Studio offers, believes 50 hours of compute tirelessly, 40 hours, compute time, a month for free at the free tier, and then you obviously have to go on and pay a whole bunch of money for it gets reassuringly expensive. So I’m guessing
Katie Robbert 10:46
that most people aren’t going to be using, you know, if, like, people like us who are just sort of experimenting and seeing what they can do, aren’t going to be using, you know, those 40 hours of compute time.
Christopher Penn 10:58
Exactly, you’re probably not going to do that, it won’t run into that. So this is what Watson Studio looks like, I’m gonna go ahead and take my timeline, my exports, I just hit export on that Google Trends. thing, I don’t have to just take that CSV file, it’s a real simple CSV file. Short briefly on screen here, right? There’s week and then there’s the change management term, real simple, not too, not too terribly complex. I’m gonna start a new Auto AI experiment. We’ll call this change management. Zoom, 20 hours, 20 capacity units per month, is a per hour is what the cost of it is, and you get 50 units to play with. Okay? And that’s per hour. So if you just turn it off, then you’re fine. But choose my multi timeline like that. It says, Hey, do you want to create a time series forecast? Well, yes, yes, I do. My column is change management. My Date column is the week. And I because his weekly data, I’m gonna crank this up to let’s do 26 weeks. So that’s half a year ahead, I hit go. And now it’s going to go and try and and look at this data, analyze it, pick the best algorithm, that that it can from its portfolio of things that knows how to do and then ultimately, spit out an answer. Now this could take anywhere from 30 seconds to a couple of hours, depending on the complexity, this is a relatively very simple data set. So it shouldn’t take more than a couple minutes to run. But what it’s doing now, is it saying okay, well take this five years worth of data that you’ve put in here. And I’m going to do that math and look at look for patterns, look for trends, look for ups and downs, and try and guess, based on all the tools it has, what the best fitting algorithm is for it, and then produce a forecast.
Katie Robbert 13:03
So John, you, you interview a lot of people for marketing over coffee, and you know, you’re pretty active in the marketing events, year over year, do you hear a lot of conversation about predictive forecasting? Are people talking about it? Is it something that you think marketers are using?
John Wall 13:22
You know, I think everybody wants to get there. It’s definitely one of those shiny objects. And, you know, the Unfortunately, the truth is, if you don’t have your data in order, you can’t get to it. You know, and so many people just struggle so often with getting their data in order to get there that they you know, they don’t even know where to start with this stuff. The thing that gets me the most is pretty much every business that you know, both remarketing over coffee or even for Trust Insights you go into, and management is always convinced that they already have the seasonal cycle that they know exactly when things go up and down. And there’s been many cases where we actually run the data and what you know, yeah, you’re right about those two, but actually, here’s three others that are far easier and more important that you’re paying no attention to. So it’s, yeah, don’t leave it to your gut. It’s too important for that.
Katie Robbert 14:08
I think you know, you’re speaking to a larger issue in terms of using data to make decisions, but we can certainly cover that in a future episode as well.
Christopher Penn 14:19
Exactly. While we’re waiting for this, Brian had a question here asking how much SEO work do we do around branded keywords? A lot actually, we use branded keywords and branded search and we use actually use Google Search Console data for branded search terms to measure the impact of brand right to measure your brand strength. It’s one of the best measures available for doing brand equity and brand strength because the more people who are searching for you by name, the more likely it is that you are doing a good job building awareness and trust. Okay, it looks like so what’s happening Under the hood here is that Watson has gone through and you’ve, you’ve been watching the the very cool looking graphics, which hats off to them, I think you could see this in an episode of Star Trek discovery at some point. It’s going through in testing all of the data, and it’s doing three things one it’s doing, what algorithm? Is it, what series of steps you’re going to take in the pipeline, and then what transformations you’re going to do on the data. So it looks like it has chosen a random forest model here as the winner based on the the error metrics chosen plus feature engineering. And what we can see here is no surprise, you know, as as it does is forecast, there’s the Christmas dip, and then so on, so forth. So we can take this forecast results, and then export it and then essentially start building a calendar from you can see its predictions, and it’s forecast values. Now, the one thing I will note here, if we look at the back testing performance on this, and the prediction performance, this is actually not a great fit, right? This is not a super good forecast. It’s It’s okay. But it’s not great. And the reason that’s not great is because some of the the more cutting edge predictive algorithms and not things that find themselves into enterprise tools like Watson Studio, because they’re unstable. And IBM has a reputation deservedly of not selling unstable things with customers. When you build your own code, you can do that you can you can play a little closer to the edge, occasionally falling off. Well,
Katie Robbert 16:41
well, that said, it’s still something that I can use, because what it what it does is for me is it at least validates that, okay, during the holiday season, nobody’s searching for change management, therefore, that’s the time when I should be doing my planning for the rest of the years worth of content. And then, you know, it’s interesting, the, you know, peaks and valleys of the trends are not so significant that I shouldn’t be putting out the content year round. So I should be planning for the next, you know, 50 some odd weeks leading up to the next holiday season where I can, you know, restart my planning,
Christopher Penn 17:17
exactly. Now. So this was a step three of just one keyword, when you do run this through your software that you’ve built, or large scale systems, because obviously one of the things that is a benefit of a system like Watson Studio is you can deploy this model, and then run additional keywords and data through it programmatically. If you have the developer that can feed the data to it with the API it creates. We do essentially very similar with Tableau software. And at some software we wrote in our let’s go ahead and look at this from like a calendaring perspective because no one wants to look at that graph. And what we see here is searchable week by week, if we just sort by column, one of the of these terms. So remember, this is these are the terms that McKinsey, Bain and BCG are all fighting each other over four. So these are terms of the all three, find valuable. These are terms that all three, again, very high Keyword Difficulty for a lot of these. But we’re going to use that as the as our starting points to understand these terms. So this week, the week October 10, digital marketing is the top search term followed business company strategy best in class and management companies. Now if we look out two weeks or three weeks, let’s go to holloween week, right, digital marketing, change management actually starts to pop up there is the number three term in a couple of weeks, followed by strategy and digital transformation. Now if you want to get well, the first and most obvious thing is, you know to what you’re saying, Katie, if you’re if you want to create content for change management, then we know that this is a term that you need to plan for, right? This is a term that you need to focus on. And look at week over week and figure out when in the next 52 weeks or so is this term going to be most popular so that we can build content around it?
Katie Robbert 19:09
And so you know, it’s interesting, too, because it’s like, oh, well, you can roll the topic of change management into a lot of these other keywords that are going to be spiking, in addition, so digital marketing, I can talk about change management, in digital marketing, strategy, digital transformation, all of those things. I can talk about change management in that context. So I’m not solely focusing on line three of change management. I’m looking if my core term is change management, I need to be looking at all of these terms and when they’re going to be spiking, so that I can talk about how change management plays into each one of those things.
Christopher Penn 19:52
You are getting towards one of the secrets that I was not planning on talking about today’s show.
Katie Robbert 19:58
Woman let’s just stop it right They’re
Christopher Penn 20:02
No, there’s this concept of intersectional marketing, which is essentially what it sounds like a Venn diagram of, of different terms, right have different terms or topics or ideas. I was watching a a, a marketer, who works in the adult industry talking about intersectional stuff and and how you can take multiple niches, multiple different areas of focus, and combine them in ways that you wouldn’t necessarily think would be great. But as long as there’s enough interest in each of the niches and those intersections, where you find the diehard fans of both things, So to your point, change management and digital transformation. Now, what you would want to do is not just look at the top list here, but actually run a large scale cross correlation to see what term if we choose change metric, mathematically what term looks the most like change management has the exact same ebb and flow throughout the year, because those are the terms that those are the topics that cluster together, one of the things that people tend to do wrong with SEO tools is they tend to look for semantically similar terms, and group them together. And it’s not I shouldn’t say that’s wrong. But like change management, organizational change, managing change, change management, for companies, you can say they’re semantically related. But if you statistically compute the ebbs and flows of the terms themselves, you may find that things that like change management and diversity, equity and inclusion, may March together, even though they’re they’re different topics. They’re temporarily concurrent. And so you can find interesting intersections to create content that hits both interests at the same time.
Katie Robbert 21:46
Which is funny that you gave that example, because as you’re saying that there are two different things I’m like, those are absolutely 100% related.
Christopher Penn 21:53
Like they are conceptually related. Yes, but not linguistically.
Katie Robbert 21:56
No, not linguistically. But, you know, conceptually, those two belong together. And that’s a topic that I absolutely, it’s actually on my list of things to cover over the next couple of months.
Christopher Penn 22:07
Exactly. If you look at the graph of what this look like, though, you can see for example, here strategy and business company, these two terms, March together pretty well, right? So let’s do make sense. Business company.
Katie Robbert 22:27
So John, not to leave you out, I’m going to give you an assignment because we have to assign you something during every live stream, is you need to go through all of these different colors and match up the corresponding colors, and group them. You know, using the regular rainbow palette,
John Wall 22:45
right? Finding the matching curves in this Where’s Waldo graph?
Katie Robbert 22:49
Exactly. You don’t actually have to do that. But I feel I don’t feel right. If I don’t give you something
John Wall 22:55
yet. There’s not something on the test.
Christopher Penn 22:58
So you can see there’s there’s change management, which is sort of that brownish color, then this there’s business company and strategy, those things actually do March together pretty well. You can see that from a trend perspective, they are fairly well aligned. So those would be three terms that you would say, not are, they’re not a topic cluster, which is again, something that you see a lot in SEO tools, but they are a time cluster. And from a from a forecasting perspective, that time cluster is important, because if you whatever’s going on, and there’s something underlying going on, just like we know, in September of every year, for B2B, that’s budgeting season, right? So all the common things that happen like okay, we need to do an attribution model, we need to do ROI and row as we need to do our incrementality measures and do a uplift model. We know all those things come together, even though they’re not word related. Because people like my butts on the line, I gotta figure out my budget for the next year. What are we gonna do? And so if you can create content that detects that concurrence in time, you’re going to do really well.
Katie Robbert 24:07
So noted. So we wanted to also talk about how to use so the past couple of weeks, we’ve done a lot of SEO, keyword research, how do we use that data across all of our digital channels? Because, you know, obviously, you know, when we talk about keyword research, there’s this assumption that it’s just for writing content, but how do we use that data across other channels?
Christopher Penn 24:35
Depends on the channel. What pick a channel, Katie,
Katie Robbert 24:39
let’s start with email, your favorite digital channel.
Christopher Penn 24:42
It is my favorite digital channel. Very straightforward. Things like emails, just sending content to somebody in their inbox, as opposed to sending the content to the person through Google or sending content to a person to Tiktok so when you look at this calendar, Oh, excellent switch calendar views here. When we look At this thing if we’re ever putting together the email, the Halloween week email for for the TrustInsights.ai newsletter, digital marketing and change management are sort of in the top three terms their strategy and digital transformation that week, I might suggest that the cold open you write be about change management and digital transformation, right? I think that would be a sensible thing for that newsletter to be about when we go out to the first week in December. Right? We have transformation. We have business strategy, but there’s some of the diversity and stuff. So you can see, you know, if you, as you start to pull together your keyword lists and refine them, you can figure out okay, what are the topics from week to week that I might want to be creating content about, or we get towards the end of the year? Looking again, diversity, equity inclusion shoots up to the top at the at the very end of the year? I don’t know why I did that. I don’t know why that would be doing that. But it’d be something that we could investigate and then put that in email. We could require building a cyst rebuilding system that does it. But we could experiment in though curated content we share on social media and in the newsletter. Is there a way to identify specific topics that are in the database and say, Okay, well, the top five topics that are showing up in this following week, can we find news articles about those topics so that the newsletter is time relevant to what people are searching for that week, that’d be a fairly heavy lift. But it is theoretically possible.
John Wall 26:42
There’s a point in there too, one thing that can get missed is, a lot of times you will see cyclical drops. And you don’t know why. And digging in to find out what’s going on during those drops can give you insight into the space and into your customers that you didn’t have before. And that’s just kind of knowing what goes on because most of the time, it’s like, oh, yeah, there’s the you know, you can see Christmas, and you can see the weekends and B2B and stuff like that. But you can stumble upon gold, if you find, you know, peaks or valleys that you right now don’t understand why they’re there.
Christopher Penn 27:13
Exactly. The other thing is to look at these terms. And then again, if you’re doing content curation of any kind, do you have enough sources that have been pulled in that are covering those topics, right, I know for sure that right now, we have the major consulting firms in our content curation system, but we don’t actively look for change management in the weekly you know, download of articles and that’s something that we should probably consider adding it is having something that is consulting focus change management, digital transformation, pulled those articles as a separate thing in to our content system so that we can start recommending, you know, the the best articles of each week in those topics, maybe even start a new section in our newsletter we have right now it’s SEO, social content marketing and data science. We might have a an organizational or consulting. I don’t know what you’d call it, but a section just for that. So again, that would be using, we’re taking this data from from SEO and saying searches just behavior searches, people telling us what’s on their minds. So if we have the information, we should we can probably use it say, Okay, well, we know this is going to be on your mind. Let’s see what we can do to defeat it.
Katie Robbert 28:24
I think it makes sense, I probably lean towards calling it management consultant. Because that kind of covers all of those things like business consulting, change management, all those things. You know, but it’s, it’s interesting to think about it that way. Because it’s not just, you know, writing a blog post and sort of using this as the SEO keyword, everything that you’re doing in a sense, is content creation. So if you’re posting videos on social, that’s just creating content, it’s just a different kind of content. Even if you’re writing just a social post, that’s a different kind of content, your email newsletters, a different kind of content. And so thinking about it in those terms, then this kind of analysis is easier for you to wrap your head around and how you can use it for those other channels. Because it’s all just content creation, the ads that you’re creating for your ad networks, it’s just another kind of content. I feel like I’m, you know, forgetting, you know, a channel or two, but basically just think about everything you’re doing as some kind of content creation, whether it’s written or audio, or it’s a video, it’s a piece of content that somebody is going to consume. So therefore you want to be creating content that’s timely and topical.
Christopher Penn 29:41
Exactly. Ashley Zeckman at her market price B2B form presentation at the most recent event, was talking about using search data to for influencers to identify the topics you want to approach influences about and one of the things I pointed out in the q&a was Do you do that with a forecast? So you just do that with, you know, existing SEO data. She’s like, I just do what the existing SEO data? Well, if you have a forecast, and you know, like when an influences contract is supposed to start, this is the tool that you give them to say, Okay. In Jan, in January and the beginning of q1, John Wall, we want you to be talking about our diversity, equity and inclusion efforts, because it’s gonna be a popular term then. And so your editorial calendar as an influencer will be influenced by the predictive forecast to say like, these are the topics that we know our audience is going to be hearing about, let’s make sure that you are on board with them. And by the way, if you have nothing to offer on the topic, I’ll say Okay, great, let’s defer your content till q2, and bring in somebody else to patch that hole in q1.
Katie Robbert 30:52
Congratulations, John, you have been promoted to the Trust Insights influencer,
John Wall 30:57
diversity and inclusion right up my alley. Listen, number one.
Katie Robbert 31:03
I mean, I wasn’t gonna point it out. But you did. So
John Wall 31:08
jobs, not hiring old white men for his campaigns.
Katie Robbert 31:13
We are nothing if not self aware.
Christopher Penn 31:16
Look at April, the first week of April cost reduction springs to the number two slot? Why? Well, obviously, you know, that’s budgeting season. That’s the new fiscal year for a lot of folks. And thanks. So, in the management consulting world, that would be a topic that we want to have an influencer on board for him to say, Okay, what can we do about, you know, zero based budgeting and things. There’s some other things, Katie, that I thought were very interesting, that could be super compelling for creating dynamic content around. So one of the topics that shows up a lot is Generation Z, or Gen Z, age range? Well, that contents great, except that it obviously has a tendency to age out pretty quickly. But if you were to write some code within a web page, you actually make that web page stay fresh and current, programmatically, and have an ongoing useful tool to people like, you know, as the calendar changes over to becomes 2022. You know, these are the the new age ranges for Gen Z and BERT generation after them. So even things like that, even like, the software that you create, can be influenced by search data.
Katie Robbert 32:22
Hmm, that’s an interesting, that’s an interesting way to think about it. Yeah, I like that. So, Chris, you know, you’re talking about using the SEO data that we’ve researched the past couple of weeks, in the context of a predictive calendar, what if people don’t, you know, so we talked through like the IBM option, the Google Trends option, you know, can they still use that data, if they don’t have a way to forecast it forward?
Christopher Penn 32:52
You can, again, what I was saying is, if you download less five years worth of data, and you line them up column by column in Excel, you can see do a weighted average of, you know, week by week and figure, okay, on average, this week tends to be the highest of the last five years, that’d be a simplified version of this, it’s not going to be as accurate, because there’s no mathematics of the forecasting, but that’d be good enough, it’d be very labor intensive to do it that way. So you’d probably only want to do it like a handful of keywords, because that that does not find a copy and paste. But that would be an option as well. So you don’t have to use the forecasting tools. It’s better if you do about,
Katie Robbert 33:36
well, so it sounds like you’re saying, if you’re going to be using that SEO research that we’ve done, you want to have some mechanism of forecasting, you don’t just want to look at it and go, Okay, I picked this one. And I picked this one. And I picked this one because I like them, or because they’re high difficulty, or no, they’re low difficulty, you know, high volume, I’m just going to pick that one. timing of these things also is just as important.
Christopher Penn 34:01
Timing and time is literally the fourth dimension. And it’s the thing that a lot of these tools just don’t do it. Time is not taken into account and a lot of the software that’s out there, a because it’s hard to get a hold of data, and B because depending on where you are in your content, marketing maturity, it’s a nice to have, right, you need basic pillar content. Like we need to have a change management blog post of any kind. As well as things like okay, we know that’s a core keyword. Katie gotta write this blog post and just put it up. We don’t care when it goes up. It just has to exist, right? Right now we have none of that. And so from a maturity perspective, for that, it doesn’t exist yet. I’m just using this as an example.
Katie Robbert 34:50
No, I know. But I was gonna say Actually, we do have one post a week going out right now.
Christopher Penn 34:55
Right? on change management. Yep. Cool. And so that term, that keyword would be locked in there. And then once you’ve taken care of the basics, you’ve got the top 20 or 30, keywords that are all in the list all in play, and there’s content for them, then you take it to the next level, say, Okay, now our promotion calendar or new content creation, calendar should be time so that we have this co linearity of time co occurrence with the marketing so that that’s why I would say, it’s not an immediate thing, if you just don’t have the stuff, period, right. But it is one of those things for promotions perspective will help make your promotions work better.
Katie Robbert 35:39
Well, and that’s when you start to dip into things like the transmedia framework where if you’re low on resources, but you know, this is important for you to get out there, then you start to think about how you can scale your content. And so you do something like this, where you talk about it, like on a live stream, where you’re recording the video and the audio, and then you start to pull apart the audio transcribe it, that’s your blog content, your video, smaller snippets, those go on social etc, etc.
Christopher Penn 36:08
Exactly. So that’s that’s how you would make use of the data, even if you don’t necessarily have you know, the forecast stuff. Again, the the correlation that you know, the time base cross correlation functions, that’s something that’s built into Excel. So if you have the data, you can do those time based cross correlation functions and understand what words and phrases co occur in time. And that alone may be enough to give you a content calendar, right? If you’ve done your five year average. And you’ve got these terms, you could get a some interesting insights that way.
Katie Robbert 36:46
Well, John, I find that to you this week. So I expect to see that on my desk tomorrow morning.
John Wall 36:50
All right, yes, all the insights.
Katie Robbert 36:57
So I think for this week, that’s it. I mean, there’s always more that we can talk about. There’s lots more things that you can do with that information. But you know, to get started, you know, we’ve again, two weeks ago, we talked about doing the basics of keyword research and how to approach that. Last week, we talked about doing that research on your competitors. And now this week, we’ve talked about how to use that data. But really the most important takeaway, if nothing else, is that timing of using that data matters. Because if you’re creating content, and it just kind of goes into the ether, nobody’s gonna see it. But if you’re creating it on that, even if it’s, you know, a very lightweight forecast, then you’re creating content when people care about it. So that is the most important way to use that information.
Christopher Penn 37:46
Exactly. So yeah, I’d say that does it for I guess this three part mini series. If there’s a new mini series that you want us to tackle, let us know we can pop out a slack group level link for that in just a bit. But I think that’s it for this week. That’s it. All right. Thanks for tuning in. Folks. We’ll talk to you next time. 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 Trust insights.ai slash t i podcast, and a weekly email newsletter at Trust insights.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.
Transcribed by https://otter.ai
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Trust Insights (trustinsights.ai) is one of the world's leading management consulting firms in artificial intelligence/AI, especially in the use of generative AI and AI in marketing. Trust Insights provides custom AI consultation, training, education, implementation, and deployment of classical regression AI, classification AI, and generative AI, especially large language models such as ChatGPT's GPT-4-omni, Google Gemini, and Anthropic Claude. Trust Insights provides analytics consulting, data science consulting, and AI consulting.
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