In this episode of In-Ear Insights, Katie and Chris tackle the sorry state of digital advertising, and advertising in general. Why is advertising so terrible? Are companies and marketers focused on the wrong metrics? What are we doing with the data we collect, and could we be doing something different and better with it? Find out in this episode.
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.
Sponsor This Show!Are you struggling to reach the right audiences? Trust Insights offers sponsorships in our newsletters, podcasts, and media properties to help your brand be seen and heard by the right people. Our media properties reach almost 100,000 people every week, from the In Ear Insights podcast to the Almost Timely and In the Headlights newsletters. Reach out to us today to learn more.
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.
Christopher Penn 0:02
This is In-Ear Insights the Trust Insights podcast.
AI Academy for marketers is an online education platform designed to help marketers like you understand pilot and scale artificial intelligence.
The AI Academy features deep dive certification courses of three to five hours, along with dozens of short courses 30 to 60 minutes each taught by leading AI and marketing experts.
Jordan Katie Robbert, CEO of Trust Insights in me Christopher Penn chief data scientist of Trust Insights for three of our courses in the academy five use cases of AI for content marketing, intelligent attribution modeling for marketing, and 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 don’t need a programming background or background in data science to understand and apply what you learn.
One registration gives you unlimited access to all the courses and invitation to a members only slack instance, access to new courses every quarter.
Join now and save $100 off registration when you go to Trust insights.ai slash AI Academy and use registration code pen 100 today that’s Trust insights.ai slash AI Academy and use registration code pen 100 today in this week’s In-Ear Insights, there is no escape from advertising.
It is everywhere it is following you around.
It is to the point where when you walk by, too out of out of home billboards and things based on your device location ads can show up on a billboard just for you at that time.
So Katie, bring it up.
what’s good, what’s the situation here?
Katie Robbert 1:42
It is in sane, like it makes me embarrassed as a digital marketer how far we have decided to go to get the attention of consumers for milliseconds, because So the example Chris that you’re giving so one of our good friends Tom Webster sharing on social media that he was in downtown Boston, walking past one of those digital billboards.
And based on his phone’s location, it started to show him an ad for something that he is assumed to care about.
And the ad even acknowledged, you won’t believe the amount of data and money that went into personalized, personalizing this ad for you right at this second.
And it struck him and he shared with us and we also were struck by it of like, Wow, that is insane.
Like, it’s to the point of, you know, the sci fi movies from 20 years ago.
Have you no Minority Report and all of these other tech heavy sci fi movies that the ad experience is going to be 100% personalized, it’s going to scan your retinas the second you walk into a store and say Good morning, Mr.
Penn, we have those socks that you like in stock, and it’s so insane.
And it just it struck me last night as I was trying to watch Probably a cute puppy video and it kept getting interrupted every 30 seconds by an ad and now they’re you have these, you know, ads that are even smarter that know when you take your eyes off, but it stops playing.
how creepy is that? And so I guess the soapbox that I’m on today is how far is too far digital advertising has gone so far that consumers do no longer have a safe place to just watch a puppy video or walk down the street without being bombarded with some sort of attempt at.
Hey, you like oat milk? I’m gonna show you oat milk right now.
Okay, you know and so it just like I’m on a soapbox today.
Christopher Penn 3:47
Well, so here’s here’s the thing on that front, and again, again, it’s a wonderful thing comes from our friend Tom Webster.
If you are not paying you are the product so Has it ever been.
And so for a lot of the free content It’s out there we are the product that’s being sold the advertiser, we are not the, the customer unless we are paying and so you have YouTube premium, which allows you the an ad free experience, you have Netflix, which allows you to watch videos on their service as long as you’re paying for it.
But if you’re not paying for it, then the advertising is the price that you pay.
And the the the question that a lot of people have is okay, well Where’s, you know, where is the the safe haven that where you don’t have to pay there isn’t one and they won’t be one.
Because there’s no money in it for companies to give away free content, except in cases like in b2b marketing were like this podcast, we’re not going to show you an ad for this podcast in this podcast, because this podcast is the ad for the company.
So you have branded content, which is promoting a certain point of view, or you have general content, which is going to be inundated with ads.
Those are your two options if you don’t want to pay now where it gets really iffy and which is why you know, some platforms will inevitably fail are those platforms where you pay and you still get ads Like the new NBC app for the peacock has like there’s like five levels like only the premium super whatever level has no ads at all that the other levels three of what you pay for, still have ads, you just pay less for them.
But to your to answer your question, that’s why we have to put up with this because we’re not the customer.
Katie Robbert 5:19
And I i understand that, you know, I understand that, you know, the advertising dollars are what allows certain content to be created.
I think where I’m getting stuck is and I think this starts to go down the road of ethics and data collection is how much is too much.
And so we know that you know, people are online constantly, they’re connected their Bluetooth, their, you know, phones and their whatever is you know, you name it.
They are attached to some sort of a piece of technology pretty much 24 seven, and advertisers want that data.
They want that data so bad.
They’re probably willing to do unethical things to get it.
And within that, like two seconds of him walking past it, it showed him an ad of something that he may have browsed before.
I, a friend of mine sent me a link yesterday to a piece of exercise equipment.
I looked at the piece of equipment, I’m like, okay, that’s interesting.
And immediately, everywhere I went on the internet was inundated with ads for this stupid thing that I don’t even want.
And God forbid I just look at it online to figure out what the heck My friend is talking about.
Now I have to see it everywhere.
I don’t even want it.
It’s like it’s infuriating to me that.
So companies are spending all of this money to collect your data and customize these things.
For crap you probably don’t even want.
And it’s just it’s it’s so maddening To me,
Christopher Penn 7:19
it is, I guess that there’s two different ways you can approach that.
The first is, when we’re looking at all these different ad systems and things.
The personalization, what’s going wrong there is that the algorithms being used are mistaking attention for interest.
Because there really is no good way to discriminate between the two beyond some behavioral characteristics.
We know that a lot of these ads systems can’t do that.
Because frankly, the compute cost is too high.
Like, if I spend, if I look at a page, and I go and check out the YouTube video on that page, and I go check out the pricing page.
behaviorally, I’d say I’m exhibiting signs of interest, right as opposed to just looking at the page itself and then bouncing off of it.
But again, ad systems are so naive because they don’t have a lot of data to work with.
It’s very thin data to work with.
Okay, you look this page, we’re going to assume you’re interested.
The second I think the the stronger lesson for for a lot of marketers is that your ads suck.
I mean, the reason why you’re having to do all this and compete for scraps of attention because your ads suck, we were sharing last week as three minute long ad from Murphy ladders about you know, this folding ad was hilarious.
It was like, you know, this Mexican looted or wrestler you know, showing off the pizza this ladder just this enormous a comical, funny way.
mildly inappropriate for work, but you know, nothing, nothing about us, but it was it was just good content.
And it was to the point where like, I shared it with friends I shared in our company Slack, I shared it in a couple other slacks.
And I this weekend when I was you know doing some work in the basement, I thought, Hmm, what if I should get one of those ladders like that as an example of an average of advertising is done so well that I Remember the story? I remember the product.
Remember the brand? I know, I remember where to get it.
I haven’t gotten it yet.
But I would say in terms of purchase funnel, I’m very far down behaviorally, because it’s on my mind.
And I don’t know how much it cost the company to make that or what the process was to create that.
But it was so well done that I don’t think of it as an ad.
I think it was a piece of content, it was entertaining.
And by the way, it advertise something.
If companies could figure out how to get away from basically the cheap tricks and deliver real stuff, they do better.
It reminds me a lot of early SEO, like early SEO is all cheap chicks, you know, living off white on white text at the bottom of the page and, you know, contorted titles for articles.
And now, thanks to advances in in Google’s AI, those tricks just flat out work.
You have to create good content or good enough content for the algorithm to even recognize you maybe hope that it will do the same thing for advertisers.
But the other one problem that is a is why advertising stuck like this is the objectives.
Facebook and Google and whoever else have a pretty clear objective, they sell by impression.
When you go into like Facebook ads and go to the ad manager, it says, you know, your effective cost per click whatever, which is code for, we’re still selling cpms You’re still selling cost per thousand impressions, and we’re just gonna calculate this for you.
But it means that their incentive is the impression their incentive is not the click, their incentive is certainly not the action.
And it would be a very different industry, if advertisers only if ad networks only got paid if you actually did the thing.
I don’t know why it hasn’t caught on.
Why advertisers have not pushed ad networks to push to do that because it would benefit them like, I don’t want to pay for ads.
If I’m not gonna get any leads for them right for the company.
I want to pay for leads.
I will have to pay more.
But I don’t know why.
advertisers have not pushed companies to say like, yeah, we’re not gonna pay you for non performance.
Katie Robbert 11:00
Well, I mean, it’s the same reason why impressions and share voice are still metrics that people use to determine whether or not they’re doing a good job.
What I find interesting, and I really like the way we’re thinking about this is, you know, perhaps the solution to this problem of, you know, advertisers spending so much time and money to get the data about the consumer could be solved by just better advertising.
And so, you know, if, if I’m a marketer listening to this podcast, I mean, I know for me personally, it was sort of that light bulb above the head, like, oh, duh, of course, if I made better content, I wouldn’t have to spend so much time and energy, data mining and digging around to try to personalize something for a two second walk by somebody who may or may not care about the thing, but, you know, apparently I’ve done my job because they saw the ad.
Well, yeah, but did they buy the thing in your Still only measuring it on an impression a walk by.
So yeah, they might have walked by it.
But they’d be like, Oh, well, that’s annoying.
I’m out of here, I’m never going to buy that brand.
Again, you could have the opposite effect by over personalizing because you’re basically annoying people into trying to buy your thing I was saying this morning that I assumed that that’s what hell is going to be like, it’s not going to be fire and brimstone, it’s going to be things that just annoy you.
And you can’t get away from it.
And it’s going to be this like compounding situation of annoyance after annoyance.
And I think one of those annoyances is going to be those data mind personalized ads that companies think you care about that you don’t care about because they have crappy content.
I’m definitely on a soapbox today.
Christopher Penn 12:48
The challenge with creating better advertising is action requires talent.
Where’s talent, it requires skill.
It requires proficiency or requires partnering with, you know, a good ad agency.
See a good creative agency and stuff? You know, when you look at the number of times that we’ve had conversations internally about our own company and trying to figure out like, you know, do we need a different logo or different branding or something like that, and the experience we’ve had with a variety of different folks, it’s very hard to get talented people within a budget that you can afford.
And what you get instead is a lot of hack jobs like a lot of the Facebook ads we’ve put up I mean, we’re no bones about it.
Our Facebook ads suck, because we’re not creatives.
We’re not advertisers.
And you know, we do the best we can.
But it’s still not great.
It’s not going to win any awards.
And certainly no one’s going to download a copy of our ad and save it to replay for laughs later on unless they’re specifically laughing at us.
Whereas something like you know, the Murphy ladders thing that is a piece of content you could legitimately save and and watch just for the laughs just for you know, three minutes of humor.
How you get there is right now requires an enormous amount of talent.
Now, that may change over time, as machines get better at creating content, but for right now, you still, if you want to be the best, you still have to go and hire the best.
And there’s no there’s no escaping that.
Katie Robbert 14:14
What’s interesting is, you know, machines learn from the data that you give them.
And if digital ads right now, suck, machines aren’t going to fix that because they’re going to learn to create crappy ads.
And so I don’t see machines taking over and doing a better job because they can only do what they are given like they can only learn from the data set that they’re given.
So I don’t see that fixing the problem, either.
And you know, you’re right about the talent piece.
I think the other side of the equation is that there’s this like now now now mentality of I need it yesterday.
I need good ROI.
I don’t care that you don’t have the time the budget, have the resources, do it now.
Do it immediately.
And then people just start churning out mediocre ads just to get something out and say it got five impressions.
We’re good, okay, my job is safer today.
It’s, it’s a treadmill,
Christopher Penn 15:10
And it’s crazy when you think about it, like, in what other profession can use wasted 99% of your your budget and you’re the 1% you’ve gotten call it a success.
Like, if you were a physician or surgeon like I killed 99%.
My patients that 1% survived like that, we would not be okay with that.
I don’t know why advertising is okay with that.
Katie Robbert 15:31
Well, you know, as we’ve alluded to and talked about before, it’s a misunderstanding of the data itself, of what you’re getting back.
And so they’re looking at the wrong metrics.
They’re looking at impressions, they’re looking at share voice, they’re looking at likes, they’re not looking at how many sales did I get and or they don’t know how to tie sales back to the ad itself, because it might live in two different systems.
And that starts to get, you know, it breaks down in the process.
And so there’s a lot of reasons why Why marketers aren’t able to do much with what they have.
So they’re creating subpar content.
They’re sending out the, you know, these ads that nobody cares about.
And they’re spending all of their time trying to find and pinpoint the exact location of what they assume is their ideal consumer.
Those are all the wrong things to be doing.
Christopher Penn 16:22
So what’s the what’s the path forward for folks? How do they fix this?
Katie Robbert 16:26
So it definitely makes sense to do an audience analysis, but to the depth and detail that companies are doing it.
Personally, I feel like is overboard.
You know, I feel like you can have a few different versions of your ideal customer.
And then you can start to really take a step back and say, you know, let’s look at the advertising we’ve done previously, what has resonated, let’s do more of that.
Let’s do less of the crap that people don’t care about.
You know, let’s be a little bit more sensitive to the fact that consumers are inundated with advertising 24 seven.
So do we want to just be part of the noise? Or do we want to have a more thoughtful approach, and really think about what is the right time to be showing these ads.
Christopher Penn 17:12
And I think you hit on something really important there, too, which is that a lot of the machine learning and AI that’s been built around AD systems is using ads as training data.
And it’s the wrong data to use.
If all the ads suck, there’s a concept in AI called transfer learning where you take the train a model in one domain, and you apply it to a different domain, because the domain you’re applying it to may not have enough robust data to build on.
And so in the case of advertising, if all the ads suck, you know that the data set itself is corrupted.
So you need to find a different data set.
Your audience analysis idea is a really good one.
Because what if you found out for example, that 80% of your best customers, all like Ernest Hemingway, just as an example, and then you took your ad copy? And you said, Okay, now I’m gonna feed this to a system like GPT Three, take my, my unique selling proposition or whatever, and rewrite it in the style of Ernest Hemingway.
Like rewrite it in the style of JK Rowling rewrite it in the style of, you know, he Cummings, if you did that, would you get better results because you’re now actually using the audience data to affect the creative as opposed to trying to use the audience data to catch that microsecond of attention when they, when they actually look at your Billboard.
You create content that appeals to them and to their interests.
I think there’s a there’s strong possibilities for the most data savvy marketers to do that.
And you don’t necessarily need AI to do that.
Like if you have talented writers, on staff who can write in the style of something else you can say, Okay, here’s the corporate message is what we need to get across.
Please go give your best shot to trying to write this like Margaret Atwood, or Stephenie Meyer.
Katie Robbert 18:57
Please don’t do that.
Unknown Speaker 19:00
I mean, to be fair, an awful lot
Katie Robbert 19:03
of a lot more money than me.
Christopher Penn 19:05
Exactly a lot of people like like her work.
Here’s an adamstown.
eel, James, good to be able to show it everywhere.
Katie Robbert 19:16
But to your point, Chris, you know, using that audience analysis to say, okay, majority of my audience is interested in sports.
Does our product tie into sports at all? Is there a way to capture the interest of my audience? Even if I’m making sports puns, even if I’m making, you know, like, analogies, love our product around sports, like, Is there a way to use that data rather than saying, I think at nine o’clock on a Tuesday night, my one ideal customer might be at a basketball game, so let me show them an ad right there.
No, they’re watching a basketball game.
They don’t want to see your ad for whatever, like.
They do better.
Just do better.
Christopher Penn 19:58
Larry Kim calls A lot of came from over a mobile monkey causes the double unicorn where if you can find two overlapping interests, you can create content that feels micro targeted, even though it applies to a very broad group of people.
So his example was people who are liberal, and people who like Star Trek Deep Space Nine, he created a meme that intersected two of these topics, and it blew up for him on Facebook.
And so you know, he paid nothing for it.
They got hundreds of thousands of shares.
And it was because of those overlapping interests.
So if you can use your audience data to create stuff, even for you know, 40% your audience that 40% is gonna be deliriously happy.
And for the rest people to see it and they’ll just it’ll just be another piece of content, just another ad, but for that 40% that’s going to be like magic.
So to sum up, please don’t spray and pray.
Please don’t use AI to deliver bad advertising.
Instead improve advertising, use AI use data, use machine learning to create better ads, and in doing so, you will be able to do generate much, much better results.
If you have comments or questions about this topic or any of the topic, please stop by TrustInsights.ai slack group analytics for marketers go to Trust insights.ai slash analytics for marketers over 1200 other folks are also sick of advertising.
We’ll be happy to chat with you.
And if you want to leave comments on this episode, go over to TrustInsights.ai dot A on the website you’ll see up there.
Thanks for watching and we’ll talk to you soon want
Unknown Speaker 21:28
help solving your company’s data analytics and digital marketing problems.
This is Trust insights.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.
Also published on Medium.