You'll learn how to

Supermetrics check mark icon green

What are marketing measurement problems marketers should be aware of

Supermetrics check mark icon green

What’s Plan-Build-Launch framework

Supermetrics check mark icon green

How marketers can increase the ROI of their campaigns

Subscribe to the Marketing Analytics Show podcast

Learn everything you need to know about marketing analytics.

Join the Supermetrics Community

Transcript

Anna:
Hello, Chris. And welcome to the show.

Chris:
Thank you. Pleasure being here.

Anna:
I am very, very happy to host you. It’s an honor. And today, we’re going to be talking about a very, very interesting topic for our marketing friends out there, which is the measurement framework. And I really love frameworks, the help principles and tactics and different kinds of ideas vary very efficiently. So my first question to you, Chris, is what should marketers and analysts be aware of regarding their measurement as they will no longer be able to rely on third-party data as much as they possibly used to.

Chris:
As once as they once did, yes. That’s so true.

Anna:
Yes.

Chris:
So the world is changing very rapidly in our neck of the woods. So I think it is really easy to overcomplicate a lot of this in our industry because these tools, let’s face it, are complicated, right? There are a lot of moving bells and switches and dials. And once you figure out one tool, you have to figure out how to get it to talk to another tool and so you have a nice clean set of data. And it becomes garbage in, garbage out. It gets really confusing very quickly. And a lot of reasons that happen, what we’ve seen is because too many people are focused on the tool themselves and not enough on the strategy, which is where for us, frameworks and mindset come in. They don’t really have a clearer meaning, most people don’t have a clear mindset and a framework about how they want to actually use these tools.

And so they jump to the tool, and they start splashing around with it, not really being connected to their overall ecosystem when it comes to digital measurement. So what I mean by that, especially the mindset thing first, is let’s say I had a shoe store, and you walk into my shoe store. And I say, Hey, how are you doing? What can I help you find? You’re like, well, I’m looking for sneakers. And I’m like, okay, what kind of sneakers do you want? And I would be moving you as we have this conversation, I’m listening to what you’re saying, I’m responding, I’m changing what I’m going to say to keep the conversation going and, ultimately, the direction of a transaction, hopefully, right? Where you buy some shoes, take them home, and maybe get on our email list for promotions, something like that.

This happens offline normally. And everyone kind of goes, yeah, that’s how offline works. But digitally, I think marketers by and large forgotten that. They actually forgot that the website is now having a conversation with the users, and marketers have got to understand what that website is saying. In other words, it’s got to be able to measure the quality of the conversation between the particular page or stage that the user’s on and the user themselves to make sure that the website is having the conversation we want it to have, right? Just like if I had a shoe store and there was a salesperson who said, Hey, I’m looking for sneakers. And they’re like, we don’t have sneakers. Could you leave? That would be a bad salesperson. I would have a corrective conversation with that salesperson. I’d help them understand and sell better, right? It’s the same thing that happens digitally.

We can see if an offer page is doing its job or if the nurture pages are doing their job, and we can measure these various stages. So one is just understanding and remembering, I guess, more than anything, that there is a very real conversation that’s happening between the users and your brand. And the website is where that conversation’s happening, which is why it’s so important to measure. And when you’re measuring, the more that you understand measurement, and the better that you understand how to use all of these tools, the better able you are to listen, quote-unquote, to their side of the conversation so that you can get a better understanding of what’s actually happening, right? So, for example, one way of measuring would be seeing page views, and that’s an important behavior. A better way of measuring would be page views, scroll, time, and maybe seeing a certain part of the page available for a few seconds to see if they’re actually investigating that part of the page. You can measure those things.

And if we know that those things are happening, we know the page is doing its job. And if those things are not happening, we know we have to go back to design or maybe copy and adjust the page to get it to do a better job when it comes to sales. So that’s kind of the mindset of this is that there’s a conversation going on between the users and the website. As measurement marketers, it’s our job to be able to improve our measurement skills so that we are not ignoring our customers practically. And we can listen to them, see what’s going on in their side of the conversation, and then change and alter the marketing, which is how we adjust our side of the conversation, right through target audiences and offers and headlines and everything else that marketing teams do. So that’s sort of the mindset of this is there is a conversation going on. It’s our job to listen to that conversation.

Then it goes into the next step, which is okay. Well, how do we do that? And that’s the framework. So for us, it is three simple steps. I think all good frameworks are simple. They should be. But it’s the nuance of how you execute on that framework that’s important. So for us, three simple steps are you’ve got to plan out your measurement. You have to then build out that measurement system. And then, of course, you launch it, right? Actually, use it to get results from it. And the trick to that, the secret sauce isn’t just plan, build, and launch. It’s how you actually do that. So if you want, I can go into the planning stage, and we can kind of tackle that or be happy to address any other questions you have. I don’t want to keep talking when I could go for 30 minutes if you let me.

Anna:
I could easily listen to it for 30 minutes, so there is no conflict there. And fantastic. You’ve touched on a lot of really, really good points. I really love the garbage in, garbage out. I do subscribe to this, and I think it’s very important to focus not only on the strategy but also on clean data, what data are you getting in, what data are you getting out, and how you make these decisions because of the way your data is structured will affect the way you’re going to make the decisions. However, let’s indeed talk about the measurement framework. So during the planning stage, marketers should ask the right questions. And I would like you to tell me more about this. How can the analyst, how can performance markers, and how can all the different marketers out there ask these questions correctly, first of all, understand what kind of content they should put out there, which kind of messaging they should structure to keep this conversation going as you mentioned, and how can they ask the right questions to make sure they’re getting the right data to support their further decision making?

Chris:
That is a great question. So let’s talk about that. The planning stage really is where all of that happens, right? There are a lot of people who just are unsure of the questions they’re asking. There’s a lot of confusion, or are they asking the right questions? What do we even do with this information? If we do have it, what actions are we going to take with it? There’s a lot of confusion around plans. And I think plans are the thing that gets skipped the most. Even if people don’t necessarily think they did that, they kind of did. And I think there’s a very specific method of planning, again, high level, very general, but super useful when you take advantage of it. So the planning step, there are really three keys to that. The first, as we talked about before, questions, right? You have to make sure you’re asking questions, certain types of questions, which we’ll talk about in a second.

The second key is to after you get your questions listed, and I kind of think these are like three columns, right? So the first column is all the questions I want to know. The second column is what information will I need to collect in order to get answers to those questions? And then the third column, is the key that everybody misses, but it solves so many problems in the organization, which is the action step. So remember, this is in your planning stage. It’s before you open up that spreadsheet before you open up that data studio, tableau report, before you open up Google analytics or anything like that, you’re thinking ahead on the planning and saying, okay, as an example of a question, it might be, what’s my opt-in rate simple one, right? What’s the opt-in rate for our leads? The information I need to collect, well, I need to collect the number of people who see the opt-in offer.

And there are people who actually saw the thank you page. Now I can figure out my opt-in, right? Well, what actions am I going to actually take when it comes to this? Well, if it’s less than 30%, I’m going to do this. If it’s between 35 and 40%, I’m going to do X or Y, whatever. And if it’s higher than 50%, I’m going to do this other thing. And there’s a method to this. There’s a method to this role play that solves so many problems. So when you think about the actions, most people, and you can tell if you have a problem with this in your organization, is if you’ve ever given somebody a report where you know what the answer is there, and they’re emailing you asking for this answer, and you know. You just think to yourself, if you just look at the thing I just sent you, it’s right there in front of your face.
Right? But it’s not for them. They can’t tell that it’s there. They can’t read it the same way you can. The opposite is true whenever you’re trying to create a report, and you look at it, something like Google Analytics, and you’re like, I have no idea what any of this stuff means, right? I know there’s a story there. If I just understood it well enough, I would magically be able to decipher it like the matrix. And it’s going to make me a supermarketer, but that’s also equally untrue. So when you do this planning stage, right, we’re going back to this QIA process, question information, action. Questions we ask results in how questions, right? So the result questions are very easy. What everyone probably is already asking, things like, what was our sales? How many did we sell? How many leads did we get? The very result of a customer journey, style questions, right?

The more important questions will be the questions because I have to understand how I’m doing that so I can replicate what’s working and start getting rid of stuff that’s not right. Start deprecating what’s not working. So you ask results questions, you ask how questions. Then we go to actually set up the information side. That’s where you collect. And you’re thinking about the behaviors, what behaviors on the site are happening that will answer those questions. So again, using our example of the lead, it was something simple, like a page view when they see the lead and a page view when they see the thank you page. And now I know a lead occurred, right? Keep it at a very high level. Then there’s that action step. And remembering the actions is like role play. And our secret sauce stats, kind of like if this, then that’s, is how you think about it.

So if the number right is lower than the expected range, I’m going to do this one thing. If the number is higher, or let’s say it’s tremendously higher than the range I want, I’m going to do this other thing. And if the number’s just right in that sort of sweet spot, then I’m going to do this other thing. Right? So now I’ve role-played what actions I’m going to do based on the numbers that I’m about to see. Now, if I’m doing reporting in an organization, I am role-playing with the stakeholder who asked me for that report, if it’s at all possible, because a lot of times I’m going to say things like, well, what would you do? And they say, well, if the lead, if the opt-ins are coming in at less than 35%, I’m going to want to break it down by traffic source.

And I go, ah, you didn’t tell me you want a traffic source, but now I understand how you’re going to use this information. So some of the information I’m going to have to collect is going to be a traffic source now, too. So now I’m going to add that to my list. And I would take that upon myself because I now understand how they are going to use this report that ultimately I’m going to generate for them, right? As a person on the data side. And they, it’s highly unlikely, they’re going to get the report and not be able to take an action because I’m going to whiteboard it out with them. I might draw it on the back of a napkin, right? Or a whiteboard and say, Hey, if the dashboard looked like this, if this number was right here, would that work for you? What else would you want to do?

And I sort of just role play it with them so that when they finally do get this dashboard and they see it, all the numbers are where they thought they were going to be. They understand how to “drive the car,” so to speak. So I’m not hearing questions like I can’t find the opt-in rate or what to do with it. They already know where the opt-in rate is. They already know what to do with it because we followed the plan. So I’m making sure it has the right information because we have a solid plan. They’re making sure that when they get the report, they’re actually using the report for the actions they intended to actually take at the planning stage. So that’s the planning stage kind of in a nutshell, why it’s so important in organizations.

Anna:
Fantastic. And I really, really love your point about role-playing with different stakeholders. I definitely do think communication is important. And I’m going to ask you a couple of more questions regarding this, but let’s talk about the next stage, the build stage. You’ve mentioned that storytelling is super important. So how can marketers tell a story with the results of their campaign? And also, like said, you build a report for a particular stakeholder. They know where to find the opt-in rate or any other metrics that they want. But as you know, reporting is way more complicated than that. There can be a variety of different reports.

And as it often happens at Supermetrics, we often read each other’s reports. So, for example, there are quite many times when marketers go in, and then they start reading sales reports, or then if, for example, you’re running an eCommerce business, then you might want to read something about the product and stock and all the data related to this coming from your CRM system, for example. So how can marketers craft this story using all these different data pieces? Not necessarily just marketing, maybe data coming from all the other departments, and how can they communicate this story to a variety of different stakeholders effectively and well? I guess how your framework can support this?

Chris:
Great question. So let’s talk about that build step, right? So the plan, remember the planning step is QIA it’s questions, information, actions, and your role play all that ahead of time. Now you’ve got your plan in place. Then you move to your build. The build again has three keys to it. The first is whatever platform you’re using. Most people are using Adobe or Google analytics right now, but whatever platform you’re using, it has to understand what results you’re trying to achieve. So in the universal analytics days, that was setting goals and something like GA4. It’s now conversion events, right? But it has to understand what milestones you’re trying to achieve. Those are the results. And you define that a certain way. So for us, we use this model called the ACE model, which is we don’t just measure for the end result, right?

We measure to understand the process that’s delivering that result. So in our case, ACE stands for awareness. So we’ll measure when they are aware of the journey that we want them to be aware of. We measure when they’ve completed that journey. And we measure for engagement steps along the way, sometimes one, sometimes multiple, depending upon how long the journey is. And that way, as we’re measuring for those results, we obviously know how many we sold or how many leads or whatever the journey was supposed to produce as an end result, we understand how it’s working or what results it’s producing. But because we’re measuring for awareness and engagement as well, remember, A’s awareness, C’s completion, E’s engagement, we’re measuring for stages. We definitely know where the drop-off is if there is one coming through.

So now we understand how we are getting the results or how we are not getting the results that we’re trying to get. So that’s the first thing is you make sure that your platform is measuring the results. The second thing, equally as important, is traffic. It’s got to understand where the traffic is coming from and what that traffic is trying to do. And this is a big mistake, I think in the analytics world, the data world in general, the first step is you learn there’s a thing called UTMs. And then the second thing is everybody misuses UTMs, in my humble opinion. But it’s because they need to be structured to be properly unlocked. They have to be coordinated to work together. And too many companies use them separately. So they use UTM parameters to identify their email traffic. They use the vendor of Facebook, which uses completely different UTMs to identify Facebook.

And it’s not at all coordinated with the email traffic. And then there’s the Google ads person who’s doing their completely separate UTMs. So what happens? You have these siloed traffic sources that are not at all designed to work together or to report a story of how they are working together. And then people ask Google analytics like, Hey, how are all these different traffic sources causing this result? And analytics is going to shrug its shoulders and go, I have no clue because it’s how the information went in. It goes back to, we talked about before, garbage in. That’s an example of UTMs not being structured to work together and not being coordinated to work together. Telling a story is going to be garbage. It’s going to be much harder to see that story than it needs to be. So you make sure you coordinate those. A very simple way of doing that very again, high level, because it’s different for your organization, but a very high level might be using the campaign, make sure you’re sharing campaigns.

So for us, we have the Measure Marketing Academy, kind of our flagship learning program for this stuff. So when I have the Academy, if I’m doing this podcast right, the podcast traffic has a UTM category for the campaign of the academy. Now, if somebody signs up to become a free member and they get an email whose purpose is to sell the academy, its UTM campaign is going to be an academy. And then if I have a paid, let’s say, Facebook campaign or Google Ads campaign, their UTMs will be UTM academy, right? Where the campaign’s going to be an academy. So all these different distinctly different traffic sources, technically even different types of traffic coming in, some podcasts, some emails, some paid, some shared maybe, or social, all of those can coordinate under that word academy. So now I can go to Google analytics and say, pull up all my academy traffic.

In other words, the traffic that’s designed to move somebody through the academy journey because that’s kind of how we identify it, of which journey it’s there to help them for. And then show me which traffic sources are better at awareness for the academy. Now show me which ones are better at engaging in the academy journey. Now show me which ones are better at completing the academy customer journey. And you will find that traffic sources start to have little personality types. Like Facebook may not be really great at completing a sale. Maybe email’s really good at completing a sale, but Facebook’s incredible at awareness. And maybe Google Ads is really good at retargeting for becoming a lead. And then email is what closes. When I can start to understand how to potentially combine these traffic sources together to get more from them because I understand how they’re more likely to work right for our unique system.

So that’s just an example of kind of results and then traffic, and then seeing that story, which is the third key, right? So the first key is the results under the build. Make sure that the ACE results are set up, awareness, completion, engagement, and then make sure that your UTMs A, you’re using them, and B, that you’ve structured them. So they’re coordinated together. And so then you can go into that third key, which is the story. And that’s where you do have to learn your tool, but you make sure that you are able to tie the specific traffic source to the specific result that it was intended to get. So you can judge it right and say, okay, is it doing its job? This traffic source, I might have a Facebook ad whose sole purpose in life is to make somebody aware of the academy. And by that, we define that as maybe 10 seconds on that page.

If you’re 10 seconds on the page, that ad has done its job, good job, claim credit, you’re off to the races. And then there’s another ad that takes over whose job it is if they haven’t purchased already to get them to mix actually purchased. But the messaging changes because it knows who it’s talking to. So it’s a different salesperson that kind of comes up to help close them. Right? And so we can measure for all that in that story. And you can, whether you’re using just Google analytics reports out of the box, we use data studio a lot. So we get those mostly through data studio, but it’s telling a story of which traffic sources, excuse me, are causing which results. And then we can do a little more deep dive. As for us, we will measure a particular page to say what we call the eyes on the journey.

That’s kind of a report that we teach. And it’s where you measure how many people had an impression of the page, to begin with, like when the page loaded. How many were introduced, that means there are 10 seconds later. How many were interested, which is typically depending upon how the page is built. It might be scroll plus time, like 50% on the page plus 45 seconds or something like that. Then did they investigate the offer? So if there’s a pricing table, did they look at that pricing table for at least three or four seconds? And then did they initiate? Did they click to go to the next step? Right? So we have these constant sorts of x-ray reporting mechanisms that are set up by our marketing team because as much as I’m a numbers guy, I do not want to stare at numbers all day long either.

I have other things to do as the owner of the organization. So I’ve got to direct and change things. And one of those things is training the marketing team to get into data studio reports so they can spend a minute or so and then get back out and get back to work, knowing what actions they’re going to take because they’ve already planned out those actions in the planning stage, but they can see the story of is this thing working like it’s supposed to, right? And then get back and change things if they don’t. One pro tip I can give any organization that’s worked out very well for us is to take a higher design. If you have design resources, then get your designer to do it, but just the graphic designer, right? Our design team, we just had an agency do it, go through them, and have them come up with brand guidelines for what your reports look like.

That way, they’re a little more interchangeable between departments. And if one department’s coming in, look at somebody else’s, sometimes they look radically different. So it might not affect every organization. But if your reports are dramatically different looking, it’s going to be harder to share because I may understand my style but may not understand your E-commerce style. But then, if we’re all sort of the same brand guidelines, the fonts are organized in a similar way.

And I understand these reports are all going to have, here’s the question this is answering, here’s what it should be doing, here’s what actions we’re going to take based upon these answers. Here’s your answer. And now I know that’s the format through every single report in this organization. It’s pretty easy for me to figure out what’s going on no matter where I am. So that’s a way to sort of uniting everything, so you do have a consistent story. And that’s the second step. You got a plan with the questions, information, and actions. Then your build, where you make sure the platform knows your results, knows your traffic, and is tying together those things in a way, so you have a natural story that’s starting to appear.

Anna:
That sounds amazing. I loved your tips on unified UTMs and thinking more in terms of journeys rather than maybe perhaps individual campaigns or individual reports or individual marketing messaging initiatives. And also a great tip on the unified guidelines and unified design. I think this is something we should also try to implement more. We already have some sort of unified design, but it never hurts to maybe even document these things.

Chris:
That’s what we did. We created a brand guideline where we’re like, Hey, write down what the fonts are, how we do tabs, what the size should be, never do this, always do that. Right. Minimize pie charts, all the fun stuff.

Anna:
Amazing. All right. And that brings us to the next, possibly the most exciting stage of the framework. And when I saw the stage and when I saw what it consists of, I got personally very excited because it’s more about looking into the future, forecasting, and optimization. So first, could you please tell me what kind of forecasting techniques can be used to predict different possible outcome scenarios and how your framework can help marketers optimize the campaigns to increase the ROI?

Chris:
Absolutely. So let’s talk about, so again, that third step is launch, right? So we have the planning stage, questions, information, and actions. Then you do your build, you get your results measured, your traffic. You’re starting to see a story of which traffic causes which results. Then you launch, and that’s actually using your system. So the first step, the first key to that step, I should say, is listening. And if you think back to what we initially started at the beginning of this podcast, what are we listening for? We’re listening for the conversation between the website and the users, right, between that customer journey and the users in that customer journey. And is that customer journey having the conversation we want? Now, the way to listen, the secret sauce, is trends and patterns, which data people will be very familiar with. But a lot of marketers are not. A lot of people on the marketing side see a number, they’re like, the opt-in rate should be 35, but it’s not. Some days it’s 35, some days it’s 42, some days it’s 17, right?

There are trends and patterns. And there’s an old bell curve and everything else that all of us on the data side is very familiar with. But marketers typically aren’t. And understanding trends and patterns is such a key differentiator right now in today’s world. Between who gets smacked around when the rules change, like when iOS and Apple had their tiff in early 2021, there are a lot of people who are not used to trends and patterns that could not figure out how to measure that stuff. They’re like, oh, it’s gone. We have to be accurate. We have to be truthful. And that’s not at all true. Accuracy’s nice, but it’s not a thing. Not really, but trends and patterns are. Trends and patterns are stable. So that’s what you’re listening for. So does this specific step have a specific trend that is starting to appear right?

Once you have your trends and you see your basic information that’s starting to appear, and you’re listening to that conversation. Now you at least have an understanding of how the conversation is most likely going, you can start to then forecast your near future. And that’s the second key to this whole launching step, which is forecasting, right? To your point, it’s the thing that most organizations, I think, skip because they have a maniacal focus on what happened to the money I spent last week. And I think that’s good because it’s important to know where you spent your money, right? However, the bigger focus in my head should be, what’s going to happen to the money I’m going to spend next week? Because if you can answer that from a measurement department, which is kind of why measurement marketing exists, the whole point is to be able to say, here’s what’s going to happen, and that’s measurement done well, right?

Most people think measurement is about what’s working and what’s not. And that’s partially true, but the pinnacle of a really good measurement system will tell you what’s coming next, better than average chance, right? No guarantees. Right. But it is a better than average chance of here’s what’s coming down the pike. And the way that we forecast, we forecast for the activities, so there are different things you can forecast for, obviously, but we’ll focus from a business building standpoint, from a revenue-generating standpoint. We’re focusing on the activities that need to happen from marketing to produce the results that, let’s say, the finance team wants them to hit when it comes to getting a revenue goal coming in. So, for example, we will measure, and you’ll start to see a pattern here. We’re never measuring just one thing. We’re measuring stages of things, right?

So whether it results in questions, we understand the end result of the customer journey, but more importantly, you ask questions around, well, how did that actually happen? Whether it’s with the goals when we measure for results, and we use those ACE conversions. So we’re measuring the awareness of the journey, the completion of the journey, and the engagement along the way. And in forecasting, we’re forecasting that. So for us, we have what we call the transact model. And the idea is just that you’re measuring for when they’re aware or when we’re asking them, excuse me, when they’re asking them to buy the product, right? So how many times did we ask them to do it? How many of those, what percentage of those actually will consider doing that? And how many of those will transact actually make that transaction happen? And at what average value?

Now with those four numbers, I can easily predict what the revenue’s going to be. If I feed 100 people into the… That I ask 100 people to buy. If half of them are considered, that means 50 people are going to the cart. If let’s say 10% of those make it through the cart, then I’m going to have those five people buy, let’s say it’s for a $100 average ticket. Now I’ve got my $500 in revenue. So every 100 people I feed in the top, $500 in revenue spits out the bottom. Now I go to marketing, or if I am marketing, I can sit there and say, okay, how do I get more people at the top? Or maybe I work on the efficiency a little bit. How do I make the cart work a little harder, so I don’t have this 90% abandonment rate?

But I can see it. So that’s why I can see it happening, because I can forecast and I’m using it, and this is the key to forecasting is having that expectation and putting yourself out there and saying, here’s what’s going to happen and be 100% willing to be completely wrong almost all the time. But that’s not the goal is not to be right. The goal is to have a forecast and say, here’s how it should be working because it changes the power of the question in the organization. Most organizations are asking what happened. And what we ask is, is this working like it’s supposed to, is this page doing its job? Is this funnel doing its job? Is this customer journey doing its job? Is the blog doing its job? One of the questions we get asked a lot when we do training for especially larger corporations will be in this room, and somebody will say, well, we’re just trying to figure out how the blog is working.

How are users using the blog? And my first question to them is how are they supposed to use the blog? And that’s the first time anyone’s ever thought about that. And this is what most organizations do. We’re just trying to figure out people using the E-commerce site. Well, how are they supposed to use the E-commerce site? We’re figuring out how people are using the homepage. Well, how are they supposed to use the homepage? And that’s the first time anyone’s ever considered that. So forecast that, guess, right? And this is where I know you’re asking about methods, but from my perspective, there are billions of methods, and all of them are equally plausible. The idea is to forecast, not get caught up in the exact method of how you are forecasting. For all I care, you can just guess, which is perfectly fine.

And especially in the beginning, you might need to. You might hand up the data to feed a model, right? So you just guess. You’re like, well, it’s always been between 100 and 150 for these last four weeks. Maybe it’ll be another 150 next week. I don’t know. Let’s guess, put it in there. But the trick is you measure against it. And that’s where the optimization’s key is. Right? So the first is to listen to what’s going on, trends and patterns, and start to forecast based on your near results, what your near future is going to look like or what it should look like. And then you measure against that. So that’s what will tell you where to focus your resources. So like in our case, we might see the academy page maybe isn’t getting enough investigation signals. It’s getting lots of top traffic, and that’s working. They’re sticking around, they’re showing interest, but maybe they’re not investigating.

So, in that case, the marketing team will look at that and say, well, how do we make the page demonstrate more of a value, communicate more of its value because it’s not doing that. Or it might be overcomplicating, and it just won’t shut up and get out of its own way sometimes. And it keeps telling people all the stuff that’s in the academy without just allowing them to buy if they’re ready to do that. But we can measure for those. We can see if it’s working the way it’s supposed to. And the second that it doesn’t match our forecast, we then focus our resources. We all have limited resources in the world. So we’ll focus our resources on that specific spot that’s more than likely to move the needle. And then we measure for a couple of days, and we can see, okay, is that moving the needle? Now, does that mean it’s a 100% perfect split test with… We’re fairly little traffic on our site, so we don’t have that opportunity for a split test.

But if I had the opportunity, of course, we’d do the split test, but meanwhile, I can still sequentially test. And I can outmaneuver and improve the results day over day over day doing that. And we can see pretty quickly because we measure. The way we forecast, we forecast all of these activities. And again, we’re a little more experienced with this. I wouldn’t try this at home, but just to show you the possibility of what’s possible, we forecast all of those activities by week a year out. So we have 52 weeks of the forecast. I can tell you where this company’s going to be revenue-wise at the end of December. And I can do that based on all the activities that marketing’s going to do because marketing has a plan for how they’re going to make all these activities happen. And they are constant week over week, measuring against their forecast to see if they’re right.

So it doesn’t really matter what method they use to me as much as it matters, did you forecast, and are you measuring against just what you thought was going to happen because mysteriously, the more that you do that, the better you get at it. And those guesses that were all over the road, in the beginning, start to get a lot finer tuned. The brain will naturally do this, and you’ll be able to start to see and be like, you know what? Next week I think it’ll be this or hey, next week, we’re going to open up this new advertising campaign. The last time we did that, we saw a spike in organic. So let’s assume that’s going to happen again. And you can start to forecast that. And then again, if you’re measuring out a week ahead of time, it’s really close to when the actual result happened, was you right?
I wouldn’t try to forecast as much three months out, down the road from now, unless I’m measuring each week at a time. I like that. For me, it’s weekly. If I had a ton more traffic, I might go daily as an organization as we grew. But for us, weekly’s perfectly fine. So that’s sort of how we use the measurement system. So as we launch it, listening to the conversation is the first step. So get our trends and patterns. We then start to forecast based on our recent results with the near future potentially should hold. So now we start asking, is this working like it’s supposed to? Is our marketing working like it’s supposed to now? And then we measure against that forecast. That’s the final key, which is the optimization key. And that’s the thing that everybody wants to race toward all the time.

But if you don’t know what to optimize or what’s the thing that’s more likely to move the needle. How do you know what to optimize? Well, this particular framework causes that to happen as a result of just using the framework. You can’t know the specific part that is your needle mover. And then you focus your resources on that, come up with ideas, do your brainstorming, whatever is necessary, go back to your planning process, making sure how you’re going to measure it, what actions you’re going to take, yada, yada yada. And you just sort of rinse and repeat, and you go through the framework hundreds and thousands of times. And every time you go through it, you build just a little bit more measurement muscle. So if you weren’t good at forecasting, in the beginning, that’s perfectly fine. The idea is you’ll get better at it. The more that you use this framework.

Anna:
Amazing. I really love the link between forecast and optimization. It definitely sounds very, very healthy, especially if the organization doesn’t have a lot of data volume or the data might not be very accurate in the beginning. So going from guessing and then fine-tuning your prediction sounds great. And I really love how you’ve structured these steps, how you really outline the approach so that every single company can iterate with every single campaign. So great stuff out there. And now, if the audience would love to learn more about you, I’m pretty sure they will. I’m going to the Academy’s website straight away. Where can they find you, and how can they get connected?

Chris:
Absolutely. So measurementmarketing.io is the name of our organization. So you’re more than welcome to go to that website. We do have a free what we call a toolbox member area, which is a free membership. Just the name and the emails are always required. There are a ton of tools. There’s a dashboard toolkit so you can see some of the stuff in action. There’s a course back there that we give out to toolbox members called the measure marketing framework that actually goes through this framework at the various stages. So if you’re just beginning, here’s how to use it. If you’ve got a little experience, here’s how to use it. If you’re very experienced, here’s how you use it. And so it teaches you all of that, and that is completely free. It’s kind of our way of helping to build the community and, obviously, introduce them to our products if they want to go from there. But if you go to measurement marketing.io/marketinganalytics, so again, measurement marketing.io/marketinganalytics, it’ll take you right to that page.

Anna:
Fantastic, Chris. Thank you so much for coming to the show.

Chris:
Happy to be here, and hopefully, it was valuable. Thanks for having me.

Try Supermetrics for free

Get full access to Supermetrics with a 14-day free trial.
No credit card required.