In this episode of In-Ear Insights, take the audio version of Trust Insights Competitive Social Media Analytics class, taught by Christopher Penn.
Want to watch the full version? Click here to access it.
Subscribe To This Show!
If you're not already subscribed to In-Ear Insights, get set up now!
- In-Ear Insights on Apple Podcasts
- In-Ear Insights on Google Podcasts
- In-Ear Insights on all other podcasting software
Advertisement: Marketing AI Academy
This episode of In-Ear Insights is brought to you by the Marketing AI Academy.
AI Academy for Marketers is an online education platform designed to help marketers understand, pilot, and scale artificial intelligence. The AI Academy features deep-dive Certification Courses (3 - 5 hours each), along with dozens of Short Courses (30 - 60 minutes each) taught by leading AI and marketing experts.
Join Katie Robbert, CEO of Trust Insights, and me, Christopher Penn, Chief Data Scientist of Trust Insights, for three separate courses in the academy:
- 5 use cases of AI for content marketing
- Intelligent Attribution Modeling for Marketing
- Detecting and Mitigating BIAS in Marketing AI
The Academy is designed for manager-level and above marketers, and largely caters to non-technical audiences, meaning you do not need a background in analytics, data science or programming to understand and apply what you learn. One registration gives you unlimited access to all the courses, an invitation to a members-only Slack Instance, and access to new courses every quarter.
Watch the video here:
Listen to the audio here:
- Need help with your company’s data and analytics? Let us know!
- Join our free Slack group for marketers interested in analytics!
What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for listening to the episode.
Hi, my name is Christopher Penn chief data scientist at Trust insights.ai.
And welcome to this masterclass on competitive social media analytics strategy.
Well, that’s a mouthful, isn’t it? today what we’re going to be going through is the what the why and the how of using data, data driven competitive social media analytics, for your strategy to figure out how to get more out of your social media.
So let’s get started.
We’re going to switch things around here.
This class is rated, well, it’s not rated but the theory the ideas, the concepts appropriate for everybody.
The application, the some of the techniques we’re going to show are really appropriate for the most advanced practitioners of social media marketing, data driven social media marketing.
So if you feel like things suddenly get really intense It’s okay, you can go back and watch this as many times as you want while while this is available, and if you have questions, my contact information is available at the end.
So let’s talk about competitive social media analytics and just competitive social media strategy.
What What do people want? What does what did the executives want? In the 2019 PricewaterhouseCoopers survey of CEOs? They were asked what data do they want? And what are they getting three of these categories data about your brand and reputation, data about risks to which the business is exposed, and benchmarking data on the performance of your industry.
peers are all competitive data points, right? These are all competitive data sets.
CEOs are saying, you know, 90% 93% 85% of CEOs want this information and see it as critical or important to their work.
Of course, how many of them are getting it? 2422 and 18% this is not good news for marketers, right? Because we’re, we’re not delivering what the C suite really desperately wants us to be giving them.
And it’s too bad because in so many ways if we had that competitive data that analytics that shed some light on what our competitors were up to, we could be transforming our marketing, even more impactfully then social media from the 2019.
The August 2019, cmo survey Chief Marketing Officer survey, CEO CMOS were asked what degree does the use of marketing analytics contribute your company’s performance? And it is rated higher than mobile marketing and social media marketing.
So analytics, the use of data and unlocking its secrets is vitally important.
When CMOS were asked, what quality knowledge assets do you have that you think a highest competitive intelligence, rated third out of six which is really quite shocking, you know, this is on a scale of one to seven CMOS don’t have the data either or they do.
They don’t think it’s great quality.
So let’s talk about why this is what is it we’re struggling with as marketers.
As social media marketers, we’re having a real hard time proving the value of what we do.
Right social media.
Again cmo survey makes no headway on contributions to company performance, none.
In terms of No, no changes for the better.
CMOS believe that social media contributes not really to company performance.
This is bad news.
If we are the social media managers, right, if we are trying to make a case for increased budgets, more adventurous experiments, we’re not showing that we’re making good headway here.
And this is the one that personally drives a stick through my heart.
The use of analytics to make decisions has been up and down, it’s kind of going in the right direction.
But still, six out of 10 companies are not using data to make decisions.
And when we think about a competition, if we’re in that six out of 10 group and our competitions in the four out of 10.
And we know that marketing analytics delivers higher impact than social media, we could be in a whole lot of trouble.
What’s the impact? Well, no surprise, if our competitors are using analytics to make decisions and watching us and we’re not watching them, we’re going to lose, we’re going to lose money, we’re going to lose opportunity.
And worst case scenario might even lose our employment if our if our company goes under.
Now, I’m not saying social media analytics alone would would drive us out of business, but it would be symptomatic of greater problems within the organization.
So why are we talking about competitive analytics? Don’t we have enough to worry about with our own data? Yes.
We do and that’s a topic for another class.
But competitive data matters for three major reasons.
Number one, we want to understand the conversations, the context, the landscape of what’s happening in our industry.
And we can watch ourselves and our audiences is that’s great.
But there’s a bias there, right? people interact with us, because they like us, or they like us enough to interact with us anyway.
Or they want to have some sort of meaningful interactions with us, whether it’s customer service complaints, or what have you.
But it’s all biased towards us.
If we don’t offer certain product service.
If we don’t think in a certain way, if we don’t appeal to a certain kind of audience.
We may never know that the market opportunity is greater.
Competitive analytics gives us the ability to see that bigger picture.
Maybe, you know, the coffee shop down the street has got lattes, and we don’t we don’t know that that’s missing from our repertoire.
Because if we just monitor our conversations, unless a customer says Hey, why don’t you have lattes? We might never Know that Oh, actually, that’s something people want.
But if we were monitoring our competitor, and all of them are saying off their customers saying, I love the cinnamon Spice Latte.
Well, now we know that something’s missing.
So that’s the first reason.
The second reason we want to see what’s working.
Marketing is difficult.
It is difficult, and it’s getting more and more difficult every day unless you’re just swiping the credit card repeatedly.
And you know, putting more dollars into Mark Zuckerberg pockets.
So we want to know what’s out there.
We want to see the best of the best what’s working, what can we be doing to improve our social media? And one of the best ways to do that is to look at our competitors and to see what’s working for them.
Are they doing some things that we could conceptually do ourselves? Are we doing some things that they’re not doing, we need to know what’s working.
And third, especially in the process of content creation for social media.
Sometimes you get stuck in a rut and you want Find those ideas for inspiration, get a sense of what’s, what’s out there? what’s possible, what are some creative ideas that we could use to maybe add a little pizzazz to the work that we’re doing? So we go as I say, let’s do some competitive analysis.
And then we go and do it wrong.
And what do I mean by doing it wrong? We treat competitive analysis like we’re spending time on Tinder, right? Just start browsing through profiles, swipe left, swipe right, it looks cool.
And doing it very unscientifically, we just kind of fumble around Bumble around I guess, if you want to extend the analogy.
And we don’t approach it from a scientific logical perspective to understand what works, what doesn’t and why we should be paying some attention to some things and not other things.
It’s super easy.
Just look at someone’s profile and, you know, read a few posts and call that competitive analysis.
And I suppose it is, but it’s not scientific and we’re talking about data driven, competitive social media analytics.
data driven means we make decisions with data.
We don’t rely on gut.
We don’t rely on instinct.
Those can be important later on.
But when we’re approaching a problem from a data driven perspective, we want to look at data and then make decisions from it.
Remember, only four out of 10 companies are using data to make decisions.
So there’s a lot of opportunity in every industry, for you to be the one making decisions with data and getting those extra benefits that we solve because again, market analytics contributes more to company performance, and social or mobile by themselves.
So what are we going to need? How do we get started with this can’t just go swipe their profiles, apparently, we’re going to need different kinds of data and as ideally as much as is available about our competitors.
So we will need things like what content they’re posting.
If we have the opportunity to look at some of the rich media that they’re creating.
Link They’re sharing audiences that they’re appealing to engagement metrics, ads and sponsorships, all sorts of information, anything that’s available that’s publicly available without doing anything unethical.
We want that data and we want to be able to analyze to understand what is out there.
Now, here’s where almost every competitive social media analysis goes wrong.
People start gathering all this data, and then they immediately start puking it back, right? Oh, well, this company has this many followers and this many posts per week and they do this and they do this and just get slide after slide after slide of junk.
And you’re like, so what’s important, what do I pay attention to here? I was reviewing a social media competitive analysis deck by consulting firm and it is a social media audit.
And it’s 70 slides of just copy and paste from A gun various tools like what? We can’t make decisions from this.
This is just puking data all over the desk and expecting me the reader to figure it out.
So how do we calibrate? How do we understand of all these different data types of which ones matter? We need something to calibrate against, we need something to measure against, that indicates that have these different data types that has a relationship, a mathematical relationship to an outcome that we care about.
And when it comes to competitive analysis, it’s really difficult to get a sense of what a competitor has got going for them.
Just recently, a couple of major data providers of competitive like website traffic out of business, right? just gone.
So we need something that is a little more durable, that’s accessible, that is apples to apples and that is legal and ethical to obtain the thing that I recommend you do four to benchmark your social media analysis against is branded organic search.
And what we want to test for using statistics using mathematics is Does any of these social media analytics, these numbers that we have access to? Do they have any relationship correlation to branded organic search? When you look in something like a Google Trends, you see the number of times over days, weeks months, that someone’s searching for specific terms, branded organic search is incredibly powerful.
In the book, everybody lies I thought was fantastic.
They talked about how people will type things into Google that they wouldn’t ever say out loud.
When we think about who talks about brands on social media, right? The way people would talk about brands are people who are really happy, really angry, right? The people who don’t feel one way or the other about a brand, don’t talk about on social media.
So using things like brand mentions on social media is not a great benchmark for getting sense of the mind share of the brand itself.
But people will type stuff that they’re mildly curious about into a search engine, or intent things like finding a coffee shop near me know I have this tennis ball on my desk.
I don’t really care what brand it is.
But I might Google logo, but I’m not going to talk about this on social media, I might Google it.
So logos worn off.
So we want to get branded search data from, again, free, publicly available source sources like Google Trends or the SEO tool of your choice.
And we’re going to use that to calibrate our social media metrics.
So that’s the theory.
That’s the idea behind this data driven, competitive social media analytics and strategy.
It’s pretty abstract.
It’s pretty tough to wrap your head around.
So let’s do a walk through example, step by step of how we might approach this and since it We have a couple of major obvious well known social brands like Agorapulse, and its competitor Hootsuite, what we want to do is we want to gather up this data and find out if let’s let’s pretend we’re Agorapulse.
With these examples, we want to find out what Hootsuite is doing that we could be learning from.
First thing we need to do is we need to find out if there’s a they’re there.
If there’s if there’s smoke, there’s fire kind of analogy.
So we want to go into our search data.
And we want to see, is anybody searching for these brands? Yes, people are searching for Hootsuite over time.
And is it actually a bit on the decline? And yes, people are searching for Agorapulse over time, so we know that there is data out there that we can use to to calibrate against if nobody was searching for our brand, be real hard to do a competitive analysis, but you know what? That’s okay.
Because we shouldn’t be doing competitive analysis anyway, for if no one’s searching for if we have a much bigger problems to worry about, then competitive analysis.
competitive analysis comes after you’ve gotten your own stuff fixed up.
So how do we get started? Well, we would want to get apples to apples data.
So using a tool, for example, using the Talkwalker, social media monitoring software, but you can use the data provider of your choice.
If you’re super sophisticated, you could write your own software and download this data directly from social networks yourself.
And I’m looking for all the content that Hootsuite is publishing and said, I want author, Hootsuite here.
And what I’m going to get from the export facility are these massive, massive, massive Excel file spreadsheets, Hootsuite Instagram posts, who tweets Facebook posts, who tweets Twitter posts, and so on and so forth, being able to export all this data.
And what we’re going to do is we’re going to blend it all together and then compare it to those brand new organic searches.
Now, there’s a bunch of different ways you can do this.
You can there’s a very manual very, very painful way Doing an Excel that will take you ages.
Your best bet, however, is to use a tool like the data science tool.
This is one called our our studio.
There’s Python, there’s IBM SPSS, there’s a bunch of different tools you can use.
But what we want to do is we want to get every single spreadsheet, put all in one big spreadsheet, and put our branded search data together in that and say, okay, that’s what we’re going to measure against how many people are searching for Hootsuite.
And how’s that compared to all their social metrics to find out is there a relationship there? So, I went through and did this, you can see barely a sec, something around 15,000 Facebook posts and 3000 Twitter posts and some odd number of Instagram posts.
One, the data processing facility basic turns into one really big spreadsheet, and then we take that and we feed that to an artificial intelligence, machine learning pieces of software that will help us do every possible combination of all those variables likes, the number of dislikes or reactions or haha or funny or sad, you know the reactions on Facebook.
We want to engineer out things like how, how long are these posts are some posts longer than others? How many words are in a post? What are the emotions in these posts? Are they happy? Are they joyful, a sad angry on every network that we have access to all the data we have access to, we want to put that all in that giant spreadsheet and then use artificial intelligence use something like IBM Watson to say okay, compare every possible combination of all these columns in the spreadsheet with that branded organic search the number of brand organic searches and that will tell us which variables matter and which ones don’t.
Because if there are a whole bunch of variables that have no mathematical relationship to the outcome, we care about people searching more for our compassion.
Then we can discard those.
And we can only pay attention to the handful that really have that strong relationship.
So let’s take a look at what this would look like.
Again, out of those 70 some odd different variables and emotions and engagements and number of followers and all that stuff.
We see that Agorapulse what has a mathematical relationship to branded searches for them are Twitter posts that are of high positive sentiment, longer Facebook posts, and more Twitter positive sentiment stuff.
So it’s really interesting there.
The stuff that has a relationship to branded searches on on for girls are content on Twitter that’s using positive, joyful, anticipatory language and longer posts on Facebook.
So we’re going to keep that in mind.
Then we’re going to do the exact same thing for Hootsuite the arch competitor here.
Hootsuite comes up with different numbers, different variables, different things that make their content work better for them.
For them, it’s likes on Facebook favorites on Twitter posts and retweets.
It’s they what dry seems to have highest relationship to those branded searches for Hootsuite, our engagement metrics in their social media.
Now you say, Well, great, what do I do with this information? What we want to do is now we want to apply it to our strategy.
We want to start building out our strategy.
First things first, we’re going to use something like a SWOT analysis.
Now, it’s been a little while since Business School.
SWOT analysis is a way of looking at different types of strategies to an understanding for you and a competitor for you the things that are under your control.
You have your strengths, what you’re good at your weaknesses, what you’re bad at, and then the things that are out of your control your competitors, what are the opportunities that our competitors giving to you, basically, their weaknesses, right? And what are the threats, the things that they’re strong at that you might be weak at? A lot of people do this really, really badly.
And that’s okay.
But we want to do though is not try to navel gaze and guess it all these things, we actually want to slot our data into this to help us build a strategic perspective.
So we know if we’re Agorapulse, joyful, positive content, longer Facebook posts, those are the things that are under our control, we can do more of those pieces of content.
And we know that’s a strength that that has a positive relationship to our outcome.
We know that we have a weak spot.
Our posts are not engaging enough to have an impact on those branded organic searches, but we know that our competitor does.
So this becomes a weakness for us.
How do we mitigate this weakness? What can we do to get people to it engage more with our content.
We look at the competitor, things that are out of our control is their content.
All those same sentiment and emotion variables don’t seem to have relationships.
So their content is just not.
It’s either emotionless or the emotions that they’re conveying are not emotions that that have a relationship to that branded search outcome that that brand awareness outcome.
And we know that that competitor is strong at these engagement metrics.
Now you have a plan of action, how do you shore up your weaknesses? And then how do you double down on your strengths? And how do we double down on doing more of this emotion content and less of how do we do less of the stuff that just not getting engagement? From here, we take that strategic framework and we start testing it.
Remember, up until now, we have done even though we’ve used one of the most advanced AI pieces of software in the world, IBM Watson We still have proven correlation relationship, we have not proven causality.
So now we start testing now we start rolling out content, we start taking advantage of this SWOT analysis to publish new stuff, and we’re going to go back and measure.
It may just be coincidence, that positive content has a relationship relationship.
So we might want to test that and, and either test doing more of it, we’re potentially doing less of it.
It may just be coincidence that Facebook likes drives who tweets engagement.
But if we can get more likes on our stuff, by hook or by crook, we should be able to see a real if there is a causal relation there, we should see that bump in branded organic searches for our brand instead.
At this point, also now experienced social media marketer like you has the ability to go into that data file, sort by these metrics, right, you’re going to sort by Facebook posts.
With the have high numbers like sort by high numbers of Twitter posts, sort by high numbers of retweets and look at the top 10% of those posts, what can you as an experienced social media marketer, gain from that is there certain types of language, certain types of language structures, certain verbs or adjectives or whatever, certain types of photos or videos or images, certain post types that you can use that Hootsuite doing well on that you can use on the Agorapulse account to again, try and get more of those engagements, you know, Hootsuite good at engagement, so how can we borrow concepts and ideas and and, and tips and tricks, not plagiarism? Just the ideas to apply it to our account to take it up to that next level.
We can also set up in a service like Talkwalker you would set up monitors around those specific metrics so you could set up in Talkwalker I want to see post by Hootsuite sorted by Facebook likes or by or by tweets and keep an eye on them over time.
Okay, they continuing to get those high levels engagement.
And so what is it that they’re doing? What is it that we can can see here? one of their top performing tweets is about a report that they did great.
Have we got a report out? That is something that we can test? Can we test language similar to this? They do a very interesting thing.
They asked Have you received your copy yet? Which is neat twist from how a lot of marketers will say, Have you downloaded your copy? Or have you gotten your copy? Have you received an interesting idea? Can we try that phrase as well.
And of course, we can use again, social media monitoring tools.
And that restricted group of top posts based on our competitors, top metrics that we’ve established, who their influencers within that narrow set, not everybody, but who are the key opinion leaders in the that highly engaged content.
Is there a way that if they’re not, you know, employees of the company are under contract with them? Is there a way that we could poach them maybe? Is there a way we could woo them, and use that influence to help boost engagement on our post mitigating our weakness? And perhaps, if we can find a language match with some of these folks use it to reinforce our own joyful positive messaging that scored so well for us in this algorithm.
Again, we’re going to test we’re going to prove this causality using the scientific method, we have a hypothesis that the metrics that work for us are these things, we’re going to test doing more of those, we have a hypothesis that these metrics work for our competitor.
And so now we’re going to take these those those data points, and start testing them to prove causality we do more of this.
Do we get more of that? If we do less of this? Do we do less of that so that causality is really important.
Now, if you are a super advanced social media practitioner, you want to expand your mind? What I mean by that is give some thought to what social media is.
and how it relates to branded organic search was the outcome we’re going after.
Because again, apples to apples.
When we say social media, Well think of this right Twitter, Facebook, Instagram, LinkedIn, Tiktok, Snapchat, Tumblr.
We get it right.
But that’s not what social media is.
Social media, social networks or any service, where the value of the service obeys Metcalfe’s law of network effects, this mathematical equation.
If you have a smartphone, you have a phone, just a telephone right? And you’re the only person in the world has one of these.
This really has no value.
When you have someone else who has it, you can call them right now.
It has value and then Another person gets one and another person gets one, the network’s value increases.
But what’s interesting about it is that your value, the value of your phone goes up.
As more people get these, that’s what makes a social network.
So valuable is it is about not about the company or the network, but is about the number of people that you have access to.
It’s one of the reasons why the the, the legacy networks like Facebook and stuff are going to be so hard to overthrow because this network effect is a massive powerhouse for them.
So think about this, what is it a social network? a blog is not a social network, right? Its value is the same.
Whether one person reads it or a million people read it, and the more people who read it doesn’t get more valuable to you, the reader it just it is what it is.
But imagine what Twitter would be like if you only followed one person to be sad and lonely, right? Just following one person.
You see their posts, there’s no real value there.
So we’re like, Okay, well, what does this have to do? Do with competitive analysis, broaden your perspective on what a social network is? We think when we say social media it’s these things right? But what about YouTube social network and the and is it is a huge social network.
It’s also a search engine.
But that’s another masterclass Cora, the question and answer site is a social network where people can interact in the value comes from the more people participate.
slack is a social network, right? It is a social network where the more people who are in your slack instance, the more valuable it becomes.
And there are tons of slack instances completely out of the view of social media monitoring tools, where real business is being done every day.
I run one called analytics for marketers go to Trust insights.ai slash analytics for marketers at 900 people in there talking about analytics, guess what? That’s a social network Twitch.
The live streaming gaming platform is the social network people watch and stuff 500 pixels, the photography network, Stack Overflow, the the QA for technical stuff and it nerds Same for spiceworks social networks for IT people if you are a b2b tech company and you’re not on those two networks, you are missing your audience.
Pokemon Go is a social network whether or not you you know, you can’t really necessarily do business on it, but you can interact with people.
discord is a is a social network.
Pornhub is a social network, right? People have interactions, and chats and all sorts of stuff on their GitHub, the development social network where people are sharing code is a social network because you can check out code, check in code on projects that are not yours, and interact with people so broaden your mind as to what social media is.
And suddenly some competitive social media analytics gets much more interesting because now you can get data from each of these providers.
And this is where that’s the reason why it’s advanced, as many of them are not in your traditional social media monitoring tools, and do that exact same exercise that we did with just two Facebook and Instagram.
But now you have a number of posts on Stack Overflow number of comments on Stack Overflow for about this vendor and get a much more holistic perspective of what could be driving that branded organic search, especially if you run the correlation analysis.
Nothing is super strong standing out, you’re like, Hmm, maybe there’s a different social network in your industry or your business that isn’t one of the main ones.
But that’s where business is being done.
tools like this is ahrefs, the social the SEO tool where you can see the number of links coming into hootsuite.com.
This is social media monitoring in a way if you are trying to understand where they’re getting links from, and then you can compare that to branded organic search.
And especially if there are other social networks, I see Seesmic in here.
I see South by Southwest Conference in here.
Again, all that data can go into that massive spreadsheet and you can run that analysis and go wow Now I really understand what drives that share of mine Hootsuite.
And now I know I can put it in that SWOT analysis and build my strategy for testing and eventually going after them.
So that’s the walkthrough of how you would do this, you’re going to need some help probably, to do this top soup to nuts the way that I’ve shown it here, you again, you can use, you know, regular spreadsheets and things, it’s just a lot more labor to do it.
It’s much easier to have the advanced machines to it.
And you’re going to need six roles.
This may be in one person, like you’re a data scientist on your team, but maybe two or three people but you’re going to need some help pulling this off.
You will need a domain expert in your industry who can understand especially for those niche social networks where people hang out in your industry, like if you’re in oil and gas.
That’s a podcasting industry.
That’s an industry that consumes podcasts Same for trucking.
You need a business expert who can help you understand does break organic search itself have a relationship to your business outcomes for most businesses it does.
But not all, you will need a scientist or someone familiar with the scientific method help you prove that causality.
Remember, we’re talking just because the supercomputer said there’s a relationship doesn’t mean that’s causal.
So you want someone with that scientific background to help you run tests and produce reproducible reliable results.
If you’re going to go after some of those niche social networks, or you want to build your own software, you’re probably going to need a coder to help talk to those networks and get data out of them.
You need a data engineer to store that data and help you access it.
And that stats and math expert to help you with a lot of that combination of all those metrics, and then running the different algorithms and choosing the one that you want that best fits the data.
In terms of tools that you’ll need to pull this off.
Again, at the most advanced levels, you’re probably going to be looking at using something like IBM Watson Studio to do that massive analysis.
And then these data science tools are Python, command lines, SQL databases, no SQL databases and such.
Now, if you’re like, Whoa, slow down, we don’t have any of this.
You can still take the idea.
Even if you can’t do the super, super technical stuff, you can still take the ideas like the SWOT analysis with specific metrics that you know how to measure and apply the same principles and test that way.
That’s what makes it strategies have the framework but you can fit any of these data points into work at the level of skill that you’re comfortable with.
The reason we have this advanced walkthrough and this is why is this it an advanced master classes so that you can see what’s possible at the highest levels and that gives you a roadmap of where you want to work towards, and the quality of the data, the quality of your analysis will go up as your technical skills increase, but at the very least, if all you’ve got is what you can see in a in your reporting panel, this is still Not a bad place to start being able to understand your strengths and weaknesses, being able to understand your competitors strengths and weaknesses and how they map to yours.
And then building a strategy and testing against it until you find what really works to grow in the outcome that you care about.
And again, I would strongly, strongly, strongly encourage that you benchmark against branded organic search people searching for you, your company, your products, your services, your key executives, by name, that tells you people will have us on their mind or they have our competitor on their mind and we want to get them aware, make them aware of us instead.
So this was a lot.
It’s a lot to think about a lot to try out.
I would encourage you try this stuff out at whatever skill level you are comfortable with.
Try taking that next step outside of your comfort zone into whatever the next analytical tool is including some of the more advanced ones they’ve shown here.
Take that comfort zone.
Traditional social networks that are in every every single monitoring tool and go to some of those niches and try seeing what’s possible in those places.
And if you’d like some more reading of a book that detail some of the more advanced techniques, but happy to answer your questions, if you have them, feel free to drop me a line.
But thank you so much for being a part of this masterclass.
I hope you got something out of it that you can take away and use today and give you something to work on as you expand your own skills.
Again, my name is Christopher Penn chief data scientist of TrustInsights.ai dot AI thanks for being here want help solving your company’s data analytics and digital marketing problems? This is Trust Insights dot.ai today and let us know how we can help you
Need help with your marketing data and analytics?
You might also enjoy:
Get unique data, analysis, and perspectives on analytics, insights, machine learning, marketing, and AI in the weekly Trust Insights newsletter, Data in the Headlights. Subscribe now for free; new issues every Wednesday!
Want to learn more about data, analytics, and insights? Subscribe to In-Ear Insights, the Trust Insights podcast, with new 10-minute or less episodes every week.