[Podcast] Chris Penn on Data Science for Marketing and Public Relations

Chris Penn, co-founder of Trust Insights and an authority on analytics, digital marketing and marketing tech, joins Hacks and Flacks to tell us about the latest advancements in data science for marketing and public relations. We discuss artificial intelligence and machine learning for marketing, the connection between SEO and PR, and he provides some definitive answers on some of our team’s lingering PR and marketing questions – like what’s the rule around duplicate content and keyword density?

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Episode Transcript

Note that this is a machine-generated transcript and may include some errors.

 

Manny Veiga 0:00
Hacks and Flacks is brought to you by March communications, an award winning integrated PR agency. with offices in Boston and Chicago. We help innovative tech companies bring their stories to life. To learn more about our agency or our show visit in March Comms dot com, but for now enjoy the show.

Welcome to hacks and flacks, I’m Manny Veiga.

On today’s podcast. We’re talking SEO analytics and PR measurement with one of the leading experts in that field. Our guest today is Chris Penn. He is an authority on analytics, digital marketing and marketing technology. You’ve probably read his writing or heard him speak on those topics. He also covers things like Google Analytics, adoption, data driven marketing and PR, modern email marketing, and artificial intelligence and machine learning. He’s also co founder of trust insights, a data science consulting firm for marketers. So we’re bringing Chris onto the podcast today to talk about the latest and greatest in the world.

of analytics, SEO, and also to get us help demystifying some common PR and marketing and measurement challenges, and tell us what’s next in this fast moving field. So let’s get into it.

So we’re here with Chris Penn. Chris, welcome to hack simplex.

Chris Penn 1:23
Thank you for having me.

Manny Veiga 1:25
Chris, I’ve always found your your background really interesting, because I know you’ve touched on a lot of different areas, both marketing and communications. I’m wondering if you could kind of just explain some of your background and what sort of perspective it’s giving you around analytics and SEO and PR measurement.

Chris Penn 1:40
Sure. So my background is all over the place. My original academic background, I have an undergraduate degree in political science with a focus on stateless transactional terrorism, which I never use. I have a master’s degree in Information Systems but where all this started turning into marketing was the earliest thousands I worked at a startup I was the the I was the chief technology officer is also the guy clean the restroom on Fridays and

and and over time what was you know update the web server became update the website what was fixed send mail became send the email newsletter and I found myself in this field that we now call marketing technology. Fast forward to the the early 2010. And I was at dream for so I was talking with a friend of mine who’s like you are you are completely wasting your talents working in house at the company. He said go work for an agency. So I went and for about five years worked in a PR agency and got a chance to really explore what was possible with analytics and data. And it was right around the the 2013 when I started dabbling in the our programming language, which is literally the letter R. And that was where I got my introduction to machine learning and artificial intelligence where we can now use very

very sophisticated technology to analyze data in ways that previously were simply were not accessible. And over the last six years, that’s really where, where my career has got us into this whole let’s let’s make data useful. And let’s make data something that we can take insights from and then take action upon because at the end of the day, data and analytics don’t matter if you you never do anything. Seth Godin has a terrific quote, if you’re not going to change what you eat, or how often do you exercise don’t get on the scale.

Manny Veiga 3:32
Hmm, yeah, that’s that’s some great perspective. And actually, we’ll get into that, that that machine learning and AI stuff in a little bit, but just going to do that background. I’m curious, you know, the three sides here, the agencies, the brands and you yourself as a data scientist, what do you think each party kind of used as the most important measurement to gauge the success of their communication strategy?

Chris Penn 3:55
It really is. Very, so wildly.

between different clients, different companies, different agencies, when I was running a marketing technology team at an agency, our our big thing was middle of the funnel like is all of this communication is all this interaction and community building turning into something some kind of tangible business em impact like, you know, leads generated or shopping carts filled or something like that where there’s you can draw a line between the the metric and some kind of meaningful business outcome. A lot of people in the communication space still report on either terrible metrics like impressions, which is the worst, one of the worst measures out there. Or even worse actually, is add value equivalence which is just abominable and should be thrown onto the bonfire of history forever, because it’s meaningless these days. And it companies measure that to or companies even worse, measure activity only, like how many calls did

You make how many pitches did you send, and they don’t really look at the outcome because they have no idea how to measure the outcome. And what has changed so much in the last five years, really since 2007, but over the last five years, especially is that the real world has become digital smartphones, smart devices, the Internet of Things, all these things help us measure and quantify the real world, the physical world. And so we can now see and measure using advanced analytics tools. Yes, you do all these activities. Yes, you have all these impressions. And these are not meaningless, but they are not goals. But you can put that all together in giant databases, and run statistics, statistical analysis and say, yeah, this is what leads to the business outcome we care about. So the most important measurements really are the ones that companies care about, like profit and loss, revenue, new customers, and we are at a place now where there really isn’t an excuse.

Least for larger companies that have budget, there really is no excuse for companies not to be using these advanced analytics tools to say yes, this is all these are all the different things that we do that contribute to revenue.

Manny Veiga 6:12
Yeah, actually kind of your I think you already answered my next question, which was going to be your opinion on what is the least valuable measurement that maybe you can expand on that a little bit? Why are you know, things like impressions and these really broad based analytics, so kind of empty are useless.

Chris Penn 6:28
They’re directionally useful? I mean, an impression is what a you know, a chance that a human being I saw your thing, right and it is so when you look at companies, like for example, out of out of home measurements, they look at like how many people drive by this billboard, and and they count that number we all met by measuring traffic as the number of impressions that billboard had.

We can’t get people to stop using their phones in their car. They’re certainly not looking at your Billboard. So yes, that car passed by that billboard but as a passive impression, it means that

human being could have seen it, but really probably didn’t. And so an impression is a number that is valid only in in the non negative sense. Like if your if your ad or or your copy or your, your article has zero impressions that obviously nobody saw that’s bad. But after that zero number once a good numbers above zero, but then it becomes really only directionally useful. And you should be able to with today’s tools, be able to measure what happens after that impression, you still need the impression. And we’re not saying you know that zero impressions is still bad. But after that, you need to be able to connect the dots to all the things that happen throughout the customer journey until you get to the business result.

Manny Veiga 7:44
Yeah, now it sounds like you’re, you know, sort of speaking our language and talking about really tying your activities from marketing or communications perspective back to actual tangible business goals, right and really starting from those goals and working backwards is that is that kind of we’re getting up

Chris Penn 7:58
Absolutely, and

The one thing that agencies in particular have to deal with that

can be challenging. Your KPIs may not be your goals, your KPIs may not be connected to your business goals. I’ll give you a funny example. I used to work at a at an agency and we had this one client and this client.

The CEO of this client was a was just rapidly in love with himself. And

his, his thing was, he needed to have more Twitter followers than the competitors CEO. Now, we all know in the measurement space that most of the time for most companies in most situations, Twitter followers is a metric it is not a business goal. Like you know, getting X number Twitter followers does not magically create more money for your company. But I define a KPI as a number with which you will either get promoted or fired. If, in this case, this car

told our agency if my Twitter follower numbers don’t go up, you’re fired. Right? So it’s not connected to a business goal. It’s not connected to any kind of logical goal. But it absolutely was a KPI because if that number had gotten down, we would have been fired.

Manny Veiga 9:13
Right? Right.

It definitely matters in some in some respects. Yeah. Even if it’s not necessarily traditionally tied back to the best and most effective way to measure the success of a campaign of course, he focusing in on just kind of one aspect of your expertise here, the SEO thing. You know, obviously, you’ve been in this space for a long time, what have been some of the biggest changes in your view to SEO and say the past three to five years.

Chris Penn 9:38
Seo in the last three to five years has radically changed because of the advent of and the broad availability of deep learning, which is the most advanced kind of machine learning the most advanced kind of AI right now.

The things that used to work in SEO, the tricks the the interesting tactics the the low quality tactics like spamming

blog comments and things don’t work anymore. And they haven’t worked for some time because

deep learning models that are you see in search engines like Google like being like Baidu, etc. They learn from what users do. They learn from what users how users react when Google talks about its algorithm that says there are over 200 inputs into their algorithm only, you know, we think of SEO is like all you need to get inbound links. Well, no, there’s a lot more as one of 200 indicators or quality and the nature of machine learning models and deep learning models is that they are constantly learning, constantly adapting, they’re constantly changing. As user behavior changes. Google wants to reduce things like Pogo sticking where people just go back and forth from search result to back to Google and so on so forth, they want you to find a good result. They want you to find a result that you’re happy with. So things like bounce rate, eggs, rate time on page, those are things that are behavioral aspects that of course, if you’re running Google

analytics, guess what you’re giving that data back to Google, in order for it to turn into machine learning models,

which means that today’s search practitioners this content marketing practitioners also need to be using machine learning technology in order to understand and optimize for the outcomes that they care about. You can’t just pull up, you know, a keyword list, write a bunch of terrible, barely readable posts anymore, and call it a day in content marketing today, you have to be doing advanced things like hierarchical ontology is like topic modeling, like predictive analytics and forecasting, to account for all the different things that Google is a search engine accounts for. And the funny thing is, and this is the part that always baffles me. Google tells you what it wants. Google is very clear in their webmaster chats in their webmaster live discussions in their quality rating guidelines. They tell you this is what we will give you

preference for and

recommendation for if you follow these rules. And for people who don’t have access to machine learning technology, the easiest guideline is create stuff that’s valuable, create stuff that you would want to read. And we call it the three l rule. If you didn’t learn something when you’re writing content, if the content didn’t make you laugh when you’re writing it, or you don’t love it so much that you talk to your significant other about it outside of work, then it’s not good content, don’t publish it, right. But if you meet at least one of those things, that means that the content is valuable to you, and therefore will likely be valuable to your audience. And they offer a very human perspective. That’s the easiest way to tell like Yep, we’re making content is good for SEO because with deep learning, Google is watching users and adapting to us as adapting to us the humans and how we react to their data, which means that the deep learning search results are more human than ever because they reflect us they reflect what we care about. And so if we say

Build Content around the human aspect of I would actually read this for this, if it wasn’t part of my job, I would still read this, I would still share this if I if I wasn’t required to buy my company. You know,

ask yourself, the last blog post you put up, would you have read that it didn’t come from your company? A lot of the time, the uncomfortable answer’s no, not really. And so we need to be in the habit of creating stuff that we love, because we know that there’s time and effort quality put into it.

Manny Veiga 13:31
Those are good points. I think, you know, this reminds me of some some stuff I’ve heard in the past about, you know, SEO, it’s like the difference between writing for people running for machines. And it sounds like what you’re saying is, don’t worry so much about running from the machines because they are smart enough to know that whatever you’re writing for people, if it’s good, it will it will figure it out. It will reward that is that kind of the rule of thumb it is that

Chris Penn 13:51
that is a good general summary. Now, what you do need in order to maximize your your returns is you absolutely do need to write for people and

But you need to write for what people will want. Which means two things, you need to do two types of analysis. One is broad topical analysis because Google, thanks to its natural language processing capabilities, and deep learning skills, understands more than just the keyword. If I type in PR firm, semantically, there are a whole bunch of things that are related to that, right. There’s public relations from this Investor Relations, there is a there is analyst relations, there’s corporate communications, there’s internal communications, employee advocacy, employee relations, all of these are semantically related under the public relations term. And so from a content perspective, I need to understand what of that bucket of things is valuable? What should I be creating content around? And then using predictive analytics? What When Will those things be valuable because as as a civilization as, as a group of humans, we are collectively very, very predictable.

We you know that you know, you shouldn’t bother sending a whole lot of email the week of July 4, right? No one’s home that people on vacation you know, that around just before tax day people are typing in all sorts of you know, tax related terms.

But with software we can look at all these terms in mass and and build calendars that help us plan and predict and and build action plans for the content so that our content is relevant at the right time when people are most interested in what it is that we’re creating.

Manny Veiga 15:36
Yeah, that that predictive analytics stuff, you know, you give us look at some of that in the past I’ve seen I’ve seen your present on and it’s pretty fascinating stuff. It’s, it’s, as you say, it’s almost being able to anticipate topics ahead of time. And that’s I guess, where the heaviest technical lift comes in when you’re talking about this machine learning and applying machine learning or AI to,

to SEO strategy is sort of doing that topic analysis and anticipating

What exactly it is that your readers will want to read? Right? So you’re making a more informed editorial or creative decision.

Chris Penn 16:06
Exactly. And we actually have a four week planning process. So what you do is given any term, you want to find when that term is going to peak and then four weeks out, you want to be planning your content, let’s say in four weeks time know Chatel cheese will be the thing. Okay, so we get together our editorial meeting so okay, what what do we know about nutshell cheese? What can we plan out what kind of stunts of activations could we do? Three weeks out, we prep the content we actually created, whether it’s video, audio, transcript, slideshows, interactive, whatever the case is, we might have, you know, five ways to, like 59 ways to use digital cheese. I just watched a video on YouTube with 59 ways to cook an egg it was that was fascinating. Like there’s there are ways that you definitely shouldn’t do, but

Manny Veiga 16:49
I think I know for so that’s I’m off to a slow start here.

Chris Penn 16:52
But Exactly. Two weeks out, you publish the content, because you want to give search engine crawlers and things time to end

index it. And then the week that term is it peaks, that’s when you want to promote it. You want to share it on your organic social media, you want to do some boosted posts on social, maybe you want to do some retargeting campaigns if you have retargeting audiences to bring the right eyeballs to that content at the right time. And so predictive analytics and just machine learning in general can help you assemble this really in depth perspective of exactly how to plan your content so that you’re there you have the right content at the right time to the right audience. And if you’re doing it well, you will see massive, massive growth. We’ve been using this internally at our company trust insights, you know, obviously since the day we started but really this year we’ve with advances in the software we’ve written it we’ve had literally every single month is that that’s our best month ever. That’s our best month ever generating hundreds of leads a month because we’ve we do what the data tells us to do.

Manny Veiga 17:53
So I can I can clearly see the application for content marketing for social media. Is there a use though as well?

Chris Penn 18:00
For like PR, and you know more that side of communications. Absolutely. SEO is PR and PR is Seo PR is social media. It’s funny. Public Relations used to mean you know, send out a press release or used to mean go take a reporter out to dinner, right those that was that’s like old school madman 1970s public relations. Those days are obviously Long, long God. Public Relations today really means what the name says how your company relates to your public. And so all these digital channels, SEO, advertising, social media events, anything in which you are engaging your public, whoever your audience is, falls under the domain of PR it really falls under how do we get people to pay attention to us, to give us some consideration to share word of mouth with their colleagues or their friends.

And ultimately get a percentage of them to do business with us that’s public relations. treating it as like this. You know, I used to be this little redheaded stepchild in the marketing world, you can’t do that anymore. You can’t do that with any type of market anymore. Now thanks to machine learning, and and and Advanced Data Science capabilities, you can put every single activity and every single metric that you do as a company into one giant get to click exactly what’s a really big spreadsheet and use machine learning models to say, what leads to the business outcome we care about, like new customers, and you can then see, yes, some press releases might be relevant or some social media channels might be relevant, but other ones might not be. But only when you put all the data together and see marketing holistically Can you understand the value of any one thing? It’s It’s so dangerous to take something like PR advertising or content and put it in its own little silo, and not let

all the departments work together to get those business outcomes.

Manny Veiga 20:04
Now that’s a great point. Absolutely. You know, making things more integrated should be the goal. So so that’s been really helpful. Chris talk a little bit about the the evolution of data science and its application to marketing comms. I also wanted to see if he can help settle a few a few questions if you nagging questions from the team here. So I pulled the agency and ask them for, you know, just a few questions that they’ve always been wondering about in various areas of marketing communications, and I wanted to get the, you know, definitive Crispin approved answer. So is that cool with you a few questions appetizer or? Okay. All right. First one. First one is a kind of a common one, actually. And you alluded to it earlier in the episode keyword density, how, how important is it? And am I dating myself by even bringing up the topic of keyword density?

Chris Penn 20:49
Yeah, that shows definitely a much older no longer valid SEO mindset topic density matters, which are you talking about the relevant terms

about the topic that you would normally expect to find in a discussion if we’re talking about nutshell ci is Guess what? cream cheese should be in there somewhere because those are very similar related Jesus right? So what you want to think of is we talked about earlier briefly reference it, there’s concepts in both data science and linguistics called a hierarchical ontology where you have a parent concept, and then you have all these child terms that go with it. And you what you want to do is you want to create content that has that is dense and authoritative and rich about the topic but not necessarily an individual word. Right? Exactly.

Manny Veiga 21:36
So not focusing so much on the individual keywords and, and figure out instead, how you can be dense related to the topical density, that’s a better term for it and I can translate it. Okay, cool. Next one is about duplicate content. So I remember a time you have been doing training content for a long time ever, ever a time where this old duplicate content topic was treated like a capital offense, almost like you cannot absolutely cannot, crossbows, anything and anytime rose, Google is going to

For you.

But there’s still that temptation, right? I’ve created this great piece. I have it on my corporate blog, maybe I also want to cross post at St. LinkedIn. Because I’ve got a great network there. What’s your take on that whole issue of duplicate content and the idea of cross posting? What’s, what’s the story there.

Chris Penn 22:14
So duplicate content. From a technical perspective, if you’re cross posting on like a medium.com, or wordpress.org, there are technical tags you can use called the canonical tag. That should point back to the original content source that is the easiest way to deal with duplicate content in publicly crawl mobile content sources, like a medium calm, for example, social media, social networks. I mean, this was something that was I thought was a really important to highlight from this year Social Media Marketing World where the opening keynote, they showed just how increasingly restrictive and less open social media has become over time from you know, 2014 when Facebook was like, come on, share everything here. We you know, we love you to today. It’s like Facebook saying, nope, you can’t do anything here. We’re not going to give you any organic reach. We’re not gonna let you share links that will penalize them and

The algorithm, so cross posting content to Facebook to LinkedIn to places which are walled off from search engines totally fine, because it’s not gonna affect anything.

The downside is that you also might not be even seen on those networks, if you don’t have if you don’t do what they want you to do. So one of the better practices is to think about not just content, it’s a piece of content, but what is the ecosystem around a piece of content, at least if it’s important, so you might have a research paper or infographic, a webinar or something like that, but then you might do like, for example, right now with this podcast, we are recording audio, right. But I’ve also got my video camera rolling, because I want to take footage of me speaking because I’m going to take that footage. I’m going to slice it up into little 15 and 37 32nd

segments and that will go up on our trust insights Instagram account with closed captioning that can then get obviously ported to LinkedIn to promote this the episode. The audio recording of is of course the podcast but the audio itself

can then be taken to a an AI transcription service. And now that becomes text content. So think less about, you know, duplicate content and more about what kind of ecosystem can we create around content that will let us extend its life that will let us give it to people in the form that they want to consume it in, and ultimately, give us the widest amount of reach possible.

Manny Veiga 24:22
That’s great advice. And actually sort of leads into my next question as well. You touched on social media, and these these areas are sort of walled off from search. But is that the case? I mean, how does social media impact search results?

Chris Penn 24:32
Just broadly, it doesn’t. There is zero impact. We did an assessment last year, we took almost a million URLs, we had all the search data, we had all this shit social sharing data, there was zero correlation between the two they dine at separate tables. Don’t think that social media is going to impact in any way your search results. There’s not even there’s not even a correlation between a piece that’s shared well, and a piece that he ranks well in in search know really

friendship

Manny Veiga 25:01
Wow, that’s that’s really surprising, but super, super helpful to know. And I know a lot of people have been kind of stressing about that. So

that’s great. That’s and and really revealing almost that you were able to find that from the data.

Okay, next question. Just if you had to pick one metric to prove the value of public relations, PR activities, what would it be? And why?

Chris Penn 25:18
It depends? Are we talking about something that we use it a machine learning model, are we talking what the average PR practitioner has access to,

Manny Veiga 25:25
et’s say the average PR practitioner someone who doesn’t have access to that sort of machine learning model,

Chris Penn 25:30
the number one metric you need to be looking at is branded organic search, which you could find to like Google Search Console for your customer, because this is the number of people who are searching for your company or your product or your service by name. So if you are Toyota, so now when people search for Prius or Corolla, or whatever, if you are T Mobile, it’s a number of people searching for you or john ledger, the CEO. You need brand organic search indicates intend it means if somebody has heard of you and is looking for you specifically, and great

Public Relations should inspire that curiosity like, Oh, I just heard about this company, I’m going to go, you know, Google them and check them out. And if your brand organic searches zero, it means your PR is not working.

Manny Veiga 26:10
That’s fantastic advice. What speaking of like measurement, you’ve talked a lot about a lot of different tools here. What are your top three, let’s say tools for measurement, just across the board just for marketing communications.

Chris Penn 26:21
Number one is your CRM, because if you don’t have access to the CRM and to seeing what customers are actually doing, you don’t have the full picture. Number two is your marketing automation system. So you can see what happens to somebody after they’ve raised their hand. You know, are they continuing to consume your white papers in your webinars? A huge part of PR that people forget about people forget think PR is just all about getting big eyeballs. No. It’s also useful things like sales enablement, if if March communications for it to get trust in us, that’s a front page article and say, like the Boston Globe, I would have my sales team mailing that article out to every single prospect in our pipeline saying hey, check this out. We’re in the Boston Globe right. So

you absolutely want to have your marketing automation and the measurement that goes with it. And then the third, of course, is your web analytics. Google Analytics is the gold standard these days and in marketing, and it is one of the best ways to determine what’s happening that impacts your business. We can talk about social media metrics, or search metrics and things like that. But if nobody ever gets to a digital destination that you own, and they can then raise their hand and say, Hey, call me email me get in touch, let’s do a meeting, etc, then you don’t really have a business result you can send out, you know, a million press releases, and if not one person visits your website. It’s completely meaningless. So it’s web analytics for sort of that top, middle of the funnel, your marketing automation for this quarter, middle of the funnel, and then your CRM for the bottom of the funnel. If you’re not measuring your impact across the board and all three, you’re leaving, you’re quite literally leaving money on the table.

Manny Veiga 27:52
Okay, that’s great advice. And actually, I’m glad you made that point about PR enabling sales kind of goes back to the point I made earlier where you know, these things

can operate in a silo right? I mean, everything kind of helps everything else. So there’s more value to public relations then just say getting immediate hit. It’s like what is that media had do for your entire organization? Really? Okay, last question here. So if PR pros want to learn more about measurement where where should they start?

Chris Penn 28:15
The first place we tell anyone to start he is take some free courses from Google Analytics. If you go to to analytics Academy dot with google.com. There are six courses you can take completely for free self paced, to learn the basics of web analytics, measurement and overall digital ecosystem measurement. That’s the first place I would go. The second place I would send people to would be HubSpot Academy because again, you have about 30 free courses. They are from email marketing to inbound to search to marketing automation to CRM. And it’s a great way for a practitioner to get skilled up on what sort of the best met general Modern Marketing practices in terms of measurement specifically, but number one thing people need to take is a basic statistics course.

Understand how to measure and how to count things because there’s so much wrong in, in marketing and NPR, at the the firm I used to work with, there was one employee who, after doing surveys would would add up the percentages and survey results like no, that’s completely long mathematical, you just cannot do that. So having that basic statistics background there, the gold standard, there is MIT open course where again, you can take a free course not a dime spent from literally the best in the world. At MIT, it just takes stats on a one so that you get that that good mathematical foundations. So those are the be the three resources that I think any marketing and communications professional should take.

Manny Veiga 29:47
I love that tip, just like literally getting back to the basics and focusing on mathematical foundations, right, like getting that statistical knowledge. That is something I think I certainly had not thought of, but it totally makes sense and I feel like anybody in this room

industry would benefit from it. So, so great tips there.

Chris Penn 30:02
Think about the difference between an average and median, right? Those are very different numbers, but they’re both measures of central quality of what’s happening in the middle of something. Pr in particular, is highly susceptible to outliers, right? You get one big hit, and then you know, a whole bunch of nothing. The meeting is a better measurement of your overall performance. Now, it may not tell the story that you want to try for a day in the quiet, but from your own internal analytics to know oh, this is this accounts not going well, the media numbers off, the average number can mask that and make things look better than they actually are.

Manny Veiga 30:32
Ya know, you gotta be able to speak that language and understand exactly what it is you’re talking about. If you’re, you’re going to speak about any of this measurement stuff sort of intelligently. So all great tips, Chris, and I know

you know, you obviously write a lot about about these topics, measurement analytics, machine learning all sorts of advancements in these areas. If people want to just learn more from you, where do you suggest they go?

Chris Penn 30:55
So you can go to a couple places. Check out my company trust

sites.ai if you want to see what we do and read our blog and our podcasts and all that stuff, and I just put out a new book relatively recently that is only slightly outdated thanks to the nature of the technology called AI for marketers, the second edition which you can find it AI for marketers book.com or

Manny Veiga 31:15
There you go, folks, ai for marketers book calm. Chris. Ben, thanks so much for your time today.

Chris Penn 31:20
Thank you for having me.

Manny Veiga 31:24
Thanks for listening to the hacks and flex you learn more about our agency or I show by visiting March Calm, calm. That’s March CEO mms.com. And don’t forget to subscribe to x and flat so you can do that on iTunes, or anywhere that you listen to podcasts that we get the latest episode delivered straight to device every time that we come out. Thanks for listening. I Manny Veiga will be back again and will soon

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