Analytics is inherently rearward-looking, looking at what happened. Yet if we want to increase the value and impact of analytics, we have to look forward, to help plan. How do we do this? In this episode, learn 3 different approaches for improving the value of analytics.
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Machine-Generated Transcript
What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for listening to the episode.
## Christopher Penn 00:17
In this week’s In-Ear Insights, let’s talk about analytics, adding value.
One of the challenges that we have with analytics is its very nature analytics is inherently, a look in the rearview mirror, what happened right as the fundamental purpose of analytics to understand what happened.
And the challenge that we have to deal with is, you shouldn’t drive the car looking at the rearview mirror only right, you have got to be looking at the windshield.
And so Katie, the question I would put to you as a decision maker, as an executive is, how do you use something that’s a rearview mirror? How do you balance that with looking forward with deciding what to do with it being proactive? And how can people who are using analytics who are data driven, can provide proactive value with their analytics data?
## Katie Robbert 01:15
Well, I mean, you sort of you hit the nail on the head, in terms of the issue is that analytics are reactive.
And so one of the things is making sure you’re not waiting too long to look at that data.
So if you only sit down and look at your data, once a year, at your yearly planning, things could have gone, you know, six ways to sideways, and you will never know.
And there’s nothing you can do about it.
So that’s, you know, sort of the first thing and so we were talking earlier, Chris, about, you know, setting up automatic notifications for anomalies, for example.
So even if you can’t be in your analytics system, every minute of every day, you can set up some notification to say, if it goes above or below this threshold, let me know, so I can do something about it.
So I think that sort of the first thing in terms of providing value, the other thing is, you can’t just rely on your data to make decisions.
And I mean that in a way of like, if you’re only ever looking at your Google Analytics, and nothing else outside of that dashboard, you’re probably making very limited decisions.
Because you’re not talking to your customers, you’re not paying attention to the conversations people are having online, you’re not looking at Google trend data, for example, you’re not even just doing basic exploration of what people might be interested in the next couple of weeks.
And so I feel like your analytics is a good starting place.
But if that’s the only thing you’re looking at, then you’re not making the best decision possible and providing the most value.
## Christopher Penn 02:53
I think the key one of the key words, you just said there is trend, one of the things I have not seen people do with their analytics data is good through any kind of software that can do trend detection, because there’s a big difference between an anomaly which is you know, a one off or a period of unusual activity, and then goes back to normal.
And a trend where something is broken out on that level has changed, it’s continuing to change as a sustained change.
So, for example, the pandemic the first few months, that was a gigantic anomaly, right, as it’s the biggest anomaly you’ll see in your data.
Ever since then, the trend has been back to the way things were beforehand, it fits and starts with all the stuff that happened.
But that is clearly the trend now.
And even in something as simple as like your channel data in Google Analytics, you know, your your traffic from social your traffic from search, I don’t see anybody and I’ll raise my hand that’s also included, because I haven’t written the software yet.
To do trend detection to say, Okay, this is not just an anomaly, which is what tools like Google Analytics 4 can do built in.
But this is a trend that you should pay attention to.
Real simple example.
Suppose you started getting some traffic from Tiktok.
Right? Maybe not a lot, but it’s enough that’s detectable.
It’s enough that would trend detection software to say, Hey, this looks like it might be a thing.
If you don’t have that, you don’t know that it’s a thing until to your point, you’re looking at your annual review, like, Oh, we got a lot of traffic and Tiktok this year that we didn’t expect, it would have been better to know that, you know, seven months ago when your bat first started?
## Katie Robbert 04:32
Well, yeah, when you could have done something about it and continued, you know, building upon that, and that’s, you know, it’s it’s interesting that you paint it that way, because I think a lot of companies feel like that kind of trend detection is out of their reach, because it involves machine learning because it involves artificial intelligence, but it doesn’t have to.
You can do very basic calculation to say, you know, here’s what this could look like.
I mean, I used to do that with my budgets, when I was managing different product lines.
And say, if the spending continues to up to spend it this way, this is where we’ll be at the end of the year.
In terms of the remainder of our budget, it was a very simplistic trend forecast.
And so I knew roughly every month, here’s the number that I have to hit in order to stay on budget.
And so, you know, I wasn’t using machine learning, I wasn’t using artificial intelligence, I was literally using a piece of paper, a pen and a calculator and said, Okay, this is what it could look like.
And if you have that historic data, you could do something similar with, you know, just pick, you know, website traffic, or just pick traffic from email.
And you could do something similar.
So these are the numbers that I need to hit in order for it to go up or down.
## Christopher Penn 05:51
Totally built into software, like from Tableau, for example, or click or IBM, Cognos is just simple trend lines, like slap a trendline on this data.
And it’s even now built into Data Studio Data Studio now supports three different types of trend lines.
So in a lot of ways, there really is almost no excuse not to have a trend, at least trend charting.
It’s better if there’s some code that can do the trend detection and say, like, hey, it looks like there’s a seven day trend for this thing, or there’s a 14 day trend for this thing.
That’s harder to do.
But at the very least, you’re right.
I mean, you can even export in Microsoft Excel, and just do the trend detection in Excel.
It’s not, it doesn’t have to be sophisticated.
In fact, the most sophisticated trend detection and anomaly detection tools in machine learning only deliver like a percentage or two point percentage point or two better performance than literally getting out a ruler and slapping it on a shard sometimes.
## Katie Robbert 06:51
Well, and with that, you know, that’s the only part of the story, you as the human still have to make judgment calls to understand.
Is it anomaly or is it really a trend? And so let’s say our site got, you know, hacked with, you know, bots, and we got all kinds of, you know, website traffic that we didn’t expect, we would need to look into that go, Okay, that was a true anomaly.
Even though Google is telling me hey, you’re the traffic’s your website’s picking up, this might be a trend, let me go ahead and notify you.
We still have to make that judgment of No, it’s not real, or yes, it is something we changed something positively.
And now it’s picking up.
You know, the same is true of those outside factors where, okay, what’s going on with politics? What’s going on with the economy, what’s going on with economics, what’s going on with people in general, the job market any of those things to say, Okay, this is why the thing is happening.
And so we’re gonna let it ride or we’re going to capitalize on it and continue doing more of it.
## Christopher Penn 08:00
I think that macro economic data is another thing that you’re right.
People aren’t using enough.
I mean, there’s so much of it.
And at least in the United States, which is where we’re based, much of it is free provided from the government, like here’s just a bunch of data.
And we don’t spend enough time looking at it last week, there was a debate in one of the other Slack channels that were in about the coming recession, and the National Bureau of Economic Research, and B er publishes how it judges whether there’s a recession and I looked at the eight indicators, they listed their documentation like these are the things we look at.
And only one of the eight is is in the red, the other seven are still trending upwards.
So I said, I’m not convinced that at least from the this dataset, that there’s a recession looming, I think there’s definitely recessionary pressures.
And I definitely think there are sectors that are going to hit harder than others.
But there’s so much weird excess demand floating around in the system, that it’s not enough yet to cause.
I mean, we have labor shortages everywhere.
I was getting I was doing some travel planning for an upcoming conference with the MAE comm conference that we were we presented in August in Cleveland.
And the air travel system this weekend alone canceled, like 10,000 flights.
And like so I’m driving, because it’s only a nine hour drive and, you know, a six hour delay on top of a two hour flight with an hour before checking it.
It’s a wash.
Yeah.
Those are the kinds of data points that you could start to synthesize into something proactive.
And I think that’s the big question is how do we overall pivot from being reactive with our analytics data to being proactive trend detection definitely is a major part of it.
What else can we do that would allow us to be more proactive with our data?
## Katie Robbert 10:00
I always come back to the basics of, you know, planning.
And, you know, thinking through Do I have a plan that extends beyond today? If I don’t have a plan that extends beyond today, that’s where I would start.
And, you know, to be quite frank, that’s where I’m at today is, you know, we’ve been sort of humming along, and now we’re finding ourselves in the quote unquote, summer slowdown season.
Now that’s my opportunity to reinvigorate our planning to say, what else are we going to be doing? What else can we do that provides value? What if we’ve not done enough of that we need to be doing more of and start to plan that out.
So that I’m being so that I have the opportunity to be more proactive versus just waiting for things to draw up and be like, Okay, now we need to do something.
## Christopher Penn 10:51
No, I think that makes sense.
I’m thinking, though, for some of this data, trend detection, forecasting, I mean, yes, a lot of it.
Predictive analytics is actually in a really precarious spot right now, because this is something I said to folks were asking about it.
For the upcoming Content Marketing World Conference, predictive analytics, which has been a mainstay for many industries, will get less and less valuable over the next 50 100 years, because as climate change increases, things get more unpredictable, right? It’s like, oh, look, there’s you know, it was over the weekend, someone said this, the French newscaster made a fake map of like super hot temperatures in 2014, and tweeted it saying this is what the climate could look like in 2050.
If we don’t do something, and that was the actual forecast this weekend, it’s only eight years later, I saw those, oh, those anomalies are going to keep increasing at at a record pace.
And so Predictive analytics is going to get harder to to some things, you know, like we’ve talked about in the past, like Holiday Gift Guide, that’s probably not going to change.
But the specifics may be governed by like, Oh, I was going to get, you know, a lawn mower for Christmas.
But, you know, lawn mowers have a 12 month backlog.
So you’re not getting a lot more because so I think the other fund a foundational piece, in addition to planning that we’re not doing enough of, and I think our company specifically is Okay, on this front.
But I know a lot of companies are not just talking to customers.
On a regular frequent basis, one of the best changes that we made recently, that anybody with a community can do is to start to ask a question of the day in your community.
And just the answers of what just the answers alone.
Actually, nothing of that just pinging people just reminding them that the community exists has spurred like, if you look at the numbers, right, a 300% increase in participation.
But we in that also gets people talking about the challenges that they’re facing.
There’s one this morning.
So asking how to how to put Click Funnels data into Google Analytics.
You and I were talking before the show about, we’ve got a lot of clients who are doing Google Analytics work with us.
But when you look in our community, which is lovingly placed here, TrustInsights.ai AI slash analytics for marketers.
That’s what people are talking about a lot of the time, like, how do I do this? This isn’t working.
I feel like as much as it might be like two more eggs in a basket than we’re comfortable with.
The customers lined up with their basket saying we need Google Analytics.
## Katie Robbert 13:32
Yeah, no.
And I agree, I think that that is, you know, one of the better, more scalable things that we’ve started doing in recent months is asking a question of the day in Slack.
And so you know, to, you know, peek behind the curtain a little bit, we have a spreadsheet of questions we could ask.
And once a week, I go ahead, I look through the different questions, and I pre programmed them so that they drop every single day.
Now, could I you know, just drop them every single day, like manually? Absolutely.
But I could also take 20 minutes on a Friday and program them for the following week.
And then when they drop, we just see the conversation starting.
And Chris and I are getting a lot of really good rich information directly from people in our community of what they have, what problems they’re having today, right now.
And Chris, your point, engagement has gone up exponentially.
And so it’s not only people responding to the questions, but I feel like it’s encouraged people to ask standalone questions outside of the question of the day, which is the kind of conversation we want to see in that community anyway, so that we can really get a good understanding and, you know, so we do that.
But then the other thing that we do is, once a quarter, we do a one question survey, where we ask literally one Question about what’s going on with you right now, and your digital marketing.
And we’ve done this, maybe for the past two years or so.
And we get a really good baseline understanding of the biggest challenge that you have, at any given time.
And it doesn’t take a lot of overhead for us to do this.
And completely optional for people to respond, we tend to get a pretty decent response rate.
And then we can look at that data and say, Okay, this tells me that we need to build more courses around Google Analytics 4, which we did, we took the data that we got from the one question survey, and we’ve started building courses.
And so we now have the Google Analytics 4 course, we have a Google Search Console course, we’re going to be working on a Data Studio course and attribution course.
Because what we’re seeing is not only are people moving from job to job, so they’re looking for refreshed skill sets.
They’re also just I want to try something different, or technology is changing so quickly, who can help me learn to stay, you know, so that I can keep pace with everyone else?
## Christopher Penn 16:08
Yeah, I’ve heard the same.
I was talking to a friend of mine not too long ago, saying it’s just getting increasingly difficult to even know what to pay attention to much less stay current, so that the topics can look around around, you know, NF T’s and web three and all that stuff.
And there’s, I think there’s, it’s a topic for another show, there is value in the underlying technology, every implementation, so far I’ve seen is stupid.
But there’s value in technology, but to their point, not only is it difficult to keep up with understanding the technology, but then you have stupid implementations of the technology that obscure its value, and make it even more difficult to learn.
Even Google Analytics, you know, we have and we’ve put together a Google Analytics course that I think does a decent job of explaining things.
But the way that Google itself implemented some of the features is just dumb.
And it makes it harder to use, like having configuration options, being three different places, instead of like a central settings.
I’m still scratching my head about that two years later.
That obtuseness is makes it hard for people to keep up.
And so again, from unlocking the value of analytics, and making it useful, if you, if you can’t even get the software to work correctly, without taking a course or or hiring an agency, then of course, you’re not going to extract value from it.
And then you may end up at a point where your stakeholders say we don’t see the value in analytics anymore.
## Katie Robbert 17:47
Which, you know, and I don’t know the exact statistic off the top of my head, but we know from, you know, the twice a year cmo survey, the value that executives see and analytics, you know, it goes up and it goes down, but it goes down more often than it goes up.
And that means if they’re not seeing value in analytics, they’re not giving you the budget that you need, because you can’t justify what it is you’re doing.
And it becomes this vicious cycle of you can’t justify why you should have a job in the first place if they don’t see the value in the work that you do, because you don’t have the data to support it.
## Christopher Penn 18:25
Exactly.
And to your point earlier about other things being macro things having an impact, and making it difficult to forecast one of the uncomfortable trends we’ve had to deal with really, it’s gotten worse in the last decade is people have become more fact resistant.
It’s it’s a good way to put it.
And that can affect a culture of becoming data driven, right? If people are saying, well, no, my opinion outweighs fact.
Or just you know, you show somebody piece of data and their conclusions they draw from is exactly the opposite of what the data says.
It it challenges the usefulness of analytics, because if you only like your analytics, when it’s telling you things you want to hear, then you’re not really using analytics.
## Katie Robbert 19:13
Well, in this, you know, unfortunately, Chris, you’re not just sort of, you know, giving examples, we’ve both experienced this firsthand.
few jobs ago, I had a stakeholder that we used to refer to as the No one.
And so regardless of the data that we would put in front of him, he would say, I know best I know what the customer wants.
We’re going to do it this way, which completely contradicted what the data was demonstrating what the customers were actually saying because it didn’t align with what he personally wanted the product to do.
Now fast forward.
We have clients now that as we’re talking through the different analytic systems, the dashboards and reporting a lot of the feedback and quite honestly, pushback that we get is, well, we want to use whatever system makes up slugfest which I can understand to an extent, but if you are glossing over everything that’s not working and only focusing on the positive, then you’re not really fixing the issues.
And you can keep repeating the same mistakes over and over and over again and wasting money wasting resources.
All that good junk.
## Christopher Penn 20:22
Yeah.
And when you take a step back and look at the big picture, yeah, you’re kind of circling the drain.
Because you’re ignoring the macro picture, what’s going on? I think so.
I think we’ve settled on three things, right? Hey, the frequency, the cadence, the process of looking at analytics has to become more frequent.
In order to catch trends sooner to you’ve got to be looking at trend data, looking for trends, not just what happened.
But is there a trend in there somewhere that you should be leveraging, particularly again, with Google Analytics, you should be looking at your channel groupings.
If you’re using Google Analytics, 4, and you’ve got good governance, that is channel grouping should hint to you what’s on an upward trend, what’s on a downward trend, we’ve noticed for ourselves, SEO, organic search has been on a downward trend for us for some time.
On the other hand, our communities, our email newsletter, our Slack group has been on a substantial upward trend for life for the company so far.
And three, paying attention to macro data, starting to work it into your forecast, I’m in the process right now putting together some data for the Trust Insights newsletter, which you can get at trust insights.ai/newsletter.
And it’s all the macro stuff that I look at to determine whether it’s recession is coming, because the NBR data I think, is too limited.
Because I want to know, from my data that I think is important, is is the recession probable? And if it is, then you and I can work it into our forecasts for the company, our cash flow management, how much money do we do we bank in the war chest versus paid ourselves? What sectors are likely to be impacted? Like, are there companies, maybe we should be targeting pharmaceutical companies in our marketing as an example.
But if you don’t have that macro data, you can’t make those decisions.
So at least somebody in your company or on your team or at your agency that you’ve hired, should be able to provide you with that data.
So you can use it for judgments.
What else Katie for making the most of analytics,
## Katie Robbert 22:26
you know, I feel like those are three really good places.
And I want to revisit the first one, which is the frequency of looking at your analytics, as someone who over the course of my career has been, you know, inundated with daily reporting, and look at this data.
And every day, here’s the thing.
If you need people to pay attention to the data, every single day, scale it back, focus on one or two metrics at a time, do not give them a full scale, you know, you can, if you’re just listening to this, you could, you would know that my hands are like extended to either side of the screen, do not give them everything under the sun, to look at focus on what’s the most important prioritize your data and scale it down.
And you know, you can automatically email it to them or show it to them, shove it in their face, print it out, leave it on their desk, whatever you need to do.
But make sure it’s only one or two metrics.
Because what ends up happening and I’ve been guilty of this as well is you become blind to it, you become numb to it, because it’s just too much.
So you don’t see anything in it day after day after day.
Because I’m just looking at too much.
And so I start to ignore it.
And so it becomes one more email that hits my inbox every morning at 8am that I just ignore, because I can’t do anything with it.
But if I’m getting just one metric that goes up or down, and I need to make a decision with it, then I will pay attention to that period.
And I can see Chris your wheels are spinning you’re you’re getting a thought of something.
But in terms of getting people to pay attention to the analytics more frequently.
It needs to be less, you can’t ask people to focus on the whole shebang, every single day, it’s too much prioritize your data down to one or two the most important metrics and focus on those and then you can sort of you know, rotate through which metrics you’re paying attention to.
But don’t try to do too much.
And that’s how you’re going to get people to pay attention to it more frequently.
## Christopher Penn 24:31
on Amazon, you can buy these programmable you know like led little LED boxes, basically just like a screen, but you can have them called like API’s and stuff.
I wonder how hard it would be to partake to buy one of those and program it.
So justice you tie in one KPI like goal completions for Google Analytics example.
I just programmed to have a green arrow, yellow arrow or red arrow just to put it on the wall and that’s the only KPIs you walk in the opposite Hey, oh, it’s a red arrow crap.
## Katie Robbert 25:03
ticker, quite honestly,
## Christopher Penn 25:04
exactly.
But I think if you, if you could agree on like one or two KPIs, and literally just had that like right next to the clock on the wall green, yellow or red arrow, that would be real time monitoring of your data, you probably want to have like a seven day average or something.
So it’s not like changing all the time, but at the very least, would tell you, oh, oh, the clock is showing a yellow error.
We’re not really making forward progress in our marketing.
## Katie Robbert 25:29
Like today, we’re down.
Okay, we need to do something about that today, we’re up.
Okay, we can focus elsewhere.
And I think that that would be a really easy win.
For any company, it doesn’t even have to be automated with a, you know, smart ticker or something like that.
You can literally have one metric on a dashboard, that you email out to people, you can even email it out multiple times a day.
But just one metric, just start there.
And then people get into the habit of okay, here’s the one metric.
I’m about to see where we stand, and then we can make decisions based on that.
## Christopher Penn 26:06
Coming this holiday season, the Trust Insights analytics clock.
Only 9999.
## Katie Robbert 26:17
I mean, it better be flashy looking.
Otherwise, people just blend into everything else.
But on that, you know, on that note, Chris, I mean, you know, smart devices are in most everyone’s home at this point, you know, you could program your smart device, hook it up to your Google Analytics or whatever to, you know, every three hours just announce your goal.
completions are up by 5% or your goal completions are down by 5%.
You should probably do something.
## Christopher Penn 26:49
Yep, I’m serious.
I’m gonna find like a weather appliance and just rejigger the wiring inside or something that would be funny.
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