October 27, 2023 • 41 mins
Remember, every podcast download is a real life human. Let's call them `listeners` for short. As a marketer, your goal is to reach as many customers as possible.
It may seem like more listeners means more customers, but that is not the case. Because there are many reasons to listen and fewer reasons to buy further analysis is necessary.
The truth is that `listeners` are not `customers`, so how do you measure to know the difference. That means, tying a conversion event to each podcast episode.
To learn more about accurate marketing metrics, join us at https://www.adbriefing.co.uk/newsletter/
#MarketingMetris #ConversionRate #ConversionOptimization #WebAnalytics #GoogleAnalytics
Become a supporter of this podcast: https://www.spreaker.com/podcast/adbriefing-copywriting-tips--3257924/support.
It may seem like more listeners means more customers, but that is not the case. Because there are many reasons to listen and fewer reasons to buy further analysis is necessary.
The truth is that `listeners` are not `customers`, so how do you measure to know the difference. That means, tying a conversion event to each podcast episode.
To learn more about accurate marketing metrics, join us at https://www.adbriefing.co.uk/newsletter/
#MarketingMetris #ConversionRate #ConversionOptimization #WebAnalytics #GoogleAnalytics
Become a supporter of this podcast: https://www.spreaker.com/podcast/adbriefing-copywriting-tips--3257924/support.
Mark as Played
Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
(00:01):
Remember, every podcast episode, everyvideo view, every interaction with your newsletter
is a real life person. NowI'm going to share a little bit about
how to optimize podcast episodes to reachthe maximum amount of audience, to create
the maximum number of leads. Andit's just one example of how I help
clients get more from their content.I hope this will be informative to you
(00:25):
because I'm going to give you aspecific technique that shows you where to measure,
how to measure, and then ultimatelyhow to optimize for conversion. I'm
justin hit with ad briefings copyrighting tipsin today's podcast episode is kind of a
micro course. I really want youto take notes and to make sure you're
listening carefully to what's going on here. And since we're in the podcast format,
(00:46):
I want to share these insights inthat context so that you can understand
what's necessary to help your clients orto help your business convert more from podcasts.
First off, podcasts are easy toproduce. I simply wrote an outline,
fleshed out an article, and nowI'm going to do the podcast.
But just because they're easy to producedoesn't mean the topics that you cover are
(01:10):
topics that your audience wants to hear. And so what we need to do
is to drive forward a means ofmeasuring to optimize for longevity, for conversion
rate, and then ultimately for sales. So we have to understand that we
want more listeners, we want alarger audience. But as a marketer,
(01:33):
our goal is to reach customers asmany customers as possible. Now we're buying
customers by investing time and effort incontent creation, and in this particular format,
the podcast, we're creating audio,video and other content that's wrapped around
this audience video. So every podcastepisode has a title, it has a
description, it has a call toaction, it may have hashtags, it
(01:56):
may have all these other elements.And so what we need to figure out
when looking at analytics is what isthe combination of these things that best generates
maximum number of leads and the maximumnumber of sales. Now, some mistake
to worry about engagement, number ofdownloads, and a lot of other factors
because we can't control those things.All we can do is once a customer
or once a potential prospect has engagedin our content, we can only control
(02:21):
the offer of the action that theywill take. Now, when they take
the behavioral action, we'll see that, and we can now see that someone
who is a listener, and thatwe might not really know whether it listens
to the whole episode or just partof the episode, but that listener then
becomes a prospect in our system.Whether it's a click to our website and
now tracked in some kind of analyticsplatform, or actually a lead on the
(02:45):
website. We don't really know anythingabout that episode until that kind of conversion
happens. So if we want tomaximize that conversion, we need to make
offers in the podcast that give ussome means of tracking. So we're want
to turn the listeners into prospects.Now, how do we do that Because
(03:06):
we're now acknowledging the truth that listenersare not customers, and so we need
to measure so that we can targetthe customers and create more listeners who are
potentially customers. So there's two conversionevents. The first conversion event would be
in show, and that's inviting alistener to ask questions or to invite a
website for a free gift. Now, the in show offer is going to
(03:29):
show up in your analytics on thewebsite as a unknown traffic or unassigned traffic
or direct traffic, and that's okay. It is difficult to measure and is
difficult to know that they came froma specific podcast episode. So that offer
will be typically be consistent. It'llbe something simple. We don't necessarily want
(03:51):
to ask them to like and subscribebecause people who are subscribing in a platform,
because our podcasts are syndicated, wedon't necessarily want them to subscribe an
Apple podcast because that doesn't really tellus anything unless our analytics can show us
that they subscribed in that platform.Now, before I talk about the next
conversion opportunity, you have to understandthat a properly implemented podcast is going to
(04:16):
syndicate. So this podcast syndicates acrosstwenty seven different channels. Every one of
those channels has their own analytics.So I promise you I'll give you a
measure you can do in some centrallocation, and then indicators of measurements that
you can do in multiple platforms thattend to be regular platforms like Google Analytics
or the podcast recording location. Sothe next conversion opportunity that you can give
(04:44):
to the listener of a podcast isactually in your description, and so in
the description, you can invite themto a special offer, you can invite
them to a free newsletter, somethingthat's going to get you that opt in.
So the first offer or the firstconversion opportunity is going to show up
as unassigned or direct traffic in youranalytics. It's hard to track. But
again, if you're driving them tosome kind of a capture of a lead,
(05:08):
and that offer is tied to alead, then you now have a
behavioral or conversion event that we cannow have some context to move and you
will see if someone clicked through onthe description from a certain platform, whether
or not they are you know wherethey're coming from, but that's not as
(05:28):
important as you can always go backand look at the episode popularity, and
then on the back end you cansurvey and to find out what topics they're
interested in, because we're really developingcontent around topics, whether it's a podcast
or a video or it's a writtenblog post. That is not as important.
So let's continue. If you makeyour conversion opportunity in the description,
(05:51):
now you can use your Google UTMparameters, whether it be sourced, well,
it's going to be sourcing medium atall times, but depends on how
much you fill that out out.You now have context to know that that
individual clicked through the description to thewebsite that tells you the activity behavioral change
moving from one platform to another,and then when they opt in, of
(06:11):
course you're now going to know thelead attribution. Can you see how this
works? Now, the question becomeswhich episodes are most popular and most likely
to send prospects to our website.We're going to find that out in two
different ways. The first way isthose people who convert the leads who also
(06:33):
become customers. We can look attheir demographics, survey them and determine what
topics they're interested in. That iswhere we're going to start driving the new
content creation. On the metric side, there are three factors in play.
So this is your podcasting platform whichhas the highest potential to reach new customers.
(06:53):
It's not necessarily the podcast episode withthe most downloads. So we have
to ask the question which episodes arepopular as indicated by the number of downloads
in a specific period. Because ifwe know there are a certain number of
downloads in a specific period, wecan look at the number of leads generated
in the same period, and wecan say, out of all of our
(07:13):
podcast traffic, here's all the leadswe've created, and then you can segment
it by whether you have the UTMperimeters or not. The next is what
episodes are populatdor as indicated by leadattribution since published date. So now we
can look at a wider range,a longer time period, and we know
since the source and medium attributions arethere, we can look in the Google
(07:36):
analytics and you can see how manyleads in total versus how many impressions or
downloads in total do we have.This is actually a more more accurate measure,
and so now you can look atthe conversion rates by episode by lead
attribute. But remember none of thisanalytics is it's all representational. None of
(07:57):
this analytics is perfect. So thelast bit is we want to make sure
that we're coding in our source andmedium, and we want to see which
source and medium that's in the poolof sources and mediums used on our podcast
episodes is now contributing to a salestransaction. So this is the most accurate
measure. I want to make sureeverybody's with me still, because this of
(08:18):
course is a mini training course onapplying methodology for conversion rate optimization, specifically
two podcasts. But here's a problem. It's a problem that every publisher faces,
is that no one episode gets enoughtraffic in short periods of time to
be statistically accurate. And so thishas been a problem. Podcast with hundreds
(08:41):
of thousands of viewers could have onlyfive or six thousand impressions or downloads on
a specific episode. Now, thatmight be the episodes that are tracked inside
of the publishing platform for your podcast, whether you're using spreaker or Spotify or
whatever platform you're using. Maybe that'sthe oppressions that are tracked there, or
(09:03):
the downloads that are tracked there,and there could be other downloads elsewhere.
Because the content got syndicated, itgot reused, the offer still remained in
a reuse, Like I let peoplecreate shorts out of my videos all the
time, but because it builds thedrive for my directs, but I can't
measure the directs. Now. Thesecond factor is is that the same podcast
(09:26):
listener may listen to multiple podcasts.Now, a lot of the podcast platforms
don't have that analytics in there,so we can know how many times the
same person listened, and that's becausethe different players don't track back that information
accurately. I know, I've gotan iPhone and an Android phone, and
I'm using different players on each phone, and they're not passing back the data.
(09:48):
And that's okay though, because themeasure I'm going to teach you in
this is useful at the head whereyou're publishing, and it's a representative and
feeds advanced techniques that we can talkabout at the into this program. So
again, the publisher doesn't know forsure how many downloads happen, but we
are assuming that the inaccuracy of theanalytics is consistent, and therefore we can
(10:13):
start doing relative measures to identify whatis likely to be most valuable in generating
leads and generating sales. And whenour attributions are correct and our linking are
correct, and there's an offer inevery episode and there's an offer and a
description, we can then start justfiguring out which hashtags and headlines and stuff
we start testing in order to increasethe traffic for particular campaigns. And by
(10:39):
the way, every episode is acampaign. That's the right way of doing
content marketing. So let's get backon track. How do publishers solve this
problem. How does a business solvethis problem, Well, you turn to
marketers, not just the people writein the copy, but you turn to
marketing analysts to figure out what works. They're going to look at the podcast
as a series of messages, justlike a series of email messages or a
(11:01):
series of direct mail letters, andwe're going to apply similar methodology to figure
out what was attribution for the sale. And then based on the attribution of
the sale, we're going to figureout what topics led up to that sale.
And so we don't know which listenerlistened to multiple podcasts. We don't
know that they didn't just Google andthen go to that podcast and listen to
(11:24):
it on a platform that they're noteven loyal to, and then they heard
your offer in the message, andthen they went directly typed in in a
different browser your website, and thenthey took action and became a lead,
and then from there they became acustomer. We don't necessarily have the ability
to track all that, and that'sokay, because again, we're going to
look for evergreen content. Now,when I'm working with clients, they don't
(11:46):
always agree, but I want tolook for evergreen content and then standardize the
downloads to factor in aging in orderto determine which types of content consistently draws
traffic. So we're in our podcastingplatform. We've pulled up the analytics and
it gives you the title of thepodcast episode, it gives you the data
(12:07):
was published and the number of downloads. And you might think that doesn't tell
you very much to make a decision, but that's why we use a formula,
and you gonna want to write thisdown. We're developing a score that
is going to give us the potentialvalue of that podcast over time. But
we're normalizing the score to compare episodesthat have different aging. This is very
(12:31):
important to understand. These episodes havedifferent aging. You publish something last week
it has twelve listeners, and youpublish something three years ago that has five
hundred listeners, which is better.What we don't know necessarily unless we have
a way of scoring. And thescore, again is a normalization here.
So let's talk about the formula scoreequals aging times and then we have a
(12:56):
parenthesis here for a fraction downloads divideup a period. So we're gonna pull
up a report of the last ninetydays. We're gonna pull up a report
of the last three hundred and sixtyfive days, and then we're gonna use
this formula, and I'll tell youa little bit more about the formula in
order to develop a score that allowsus to relatively compare different aged episodes to
(13:18):
determine which episode has the best performance. Now, this is only the performance
of downloads. This is not youknow your sales and leads performance. But
you need to know what's getting trafficconsistently in order to make sure that those
things have offers in them that cannow pull off the back end opportunity,
(13:39):
which would be a lead generated onyour website. Now, remember, some
of these platforms will let you putin offers as an add on, so
you can end up with the sameoffer in every podcast episode. Some of
them will let you do av splits. Some of them you can't change the
original audio, but you can changethe descriptions. And then, most importantly,
things that score really well well,we don't want to come back and
(14:01):
do headline testing and optimization of keywordsand optimization of hashtags and standardization of content,
because that could mess up something that'salready working the way it was presented.
So again, your score is aweighted measure of potential traffic over time,
and it gets more accurate as agingincreases. So the older the video
(14:22):
is, the more likely This scoreis representational of seasonal variations. It takes
into account seasonal variations, It takesinto account changes in the economy, It
takes into account news headlines, soagain it's more evergreen content. Now,
the aging is the number of dayssince the podcast episode was published, and
this is the number of days sincefirst published date. But it should reset
(14:45):
if you've changed the episode title ordescription significantly, And so that's something you
have to keep in mind. Ifevery ninety days you're optimizing the poor performers,
you may need to look at ashorter time period in order to know
whether the optimization has made a difference. There are times I'll just put a
headline on it because I've recorded apodcast and I just need to get it
(15:07):
out there. But I might comeback later and use a different headline,
and when I'm doing my headline testing, and that episode that was like eight
listeners is now all of a sudden, three hundred listeners because the headline caught
their attention. It broke them outof that droneness or the doom scrolling they
were doing, and they've started todownload. Now. In this measurement,
(15:28):
downloads is the count of downloads duringtheir reporting period. And this is very
important and this number is representational.We talked about how the number is not
very accurate. There's a lot ofreasons, ad blockers, different devices,
there's a lot of reasons why thedownload count is not your most accurate count.
One of the problems that I havewith this podcast and the other podcasts
(15:50):
who manage, is it because wedo such a great job on syndication.
And syndication means the podcast is onGoogle podcasts and Apple podcasts and Spotify and
a bunch of these directories, andit's pretty much everywhere. But are the
more places the podcast shows up,the less accurate it is to know the
number of actual downloads. When itcame to who listened to the podcast.
(16:11):
Now, I know there are toolsthat can help with that, but ultimately,
the we can get the bid,we can get the podcast in the
hands of listeners faster than we canget the tools to register how those people
are. Now. Finally, theperiod. The period is the number of
days in the reporting period. Soa low volume podcast is going to want
to have like three hundred and sixtyfive days. You're going to want to
(16:32):
look at all these traffic over thethree hundred and sixty five days and do
your performance measure. And a highPI volume podcast, which whatever depends HIW
for you, might be ninety days. But the key is we need enough
samples to come up with something statisticallyaccurate because what I've just described here.
Now, using a scoring system allowsus to rank, and then from ranking
we can take specific actions to improveperformance. Like, for example, if
(16:57):
you've got an episode that has alot of views but it's not generating traffic,
you might look into it. Andso the first thing we're gonna do
is gon we're gonna audit the offers. You might say, oh my gosh,
I'm so excited. This got fivehundred and seventy six listeners in the
last twenty days or twenty eight days, but why am I not getting any
leads? Well, you might golook at it and find out there's no
(17:19):
offer in the description. You mightgo look at it and there's no offer
in the audio. Now can wefix that? Yes? Should we fix
that? Probably because we don't careso much about the downloads. Remember,
listeners are not equal to customers,and so even though it gets high traffic,
we'll make a note that the topicgot high traffic, but we need
(17:41):
to do something with that traffic byhaving an offer. And so what we're
doing here is the scoring approach allowsus to focus on those things that have
the potential for an offer to dosomething, and then we're just going to
look at it. We're not changingstuff, but we're going to look at
it and say, oh, waita second. We've got a good description,
we've got good hashtags, we've gota good headline, but there's no
(18:02):
offer in the description. So we'regoing to add an offer at the end
of the description. Now, arepeople going to find the offer at the
end of the description? Is thatoffered? Tech's going to syndicate across all
the different channels that are showing outyour podcast. Probably not, But what
if that five hundred and seventy sixlisteners that month one percent of them two
percent of them could become leads onyour website. You don't want to miss
(18:26):
that opportunity. Next, the scoringsystem helps us figure out what we should
study as controls. If you goin and do this scoring and then you
rank the stuff that's at the bottomof the rank. You don't want to
do more of that. You wantto do the stuff that's at the top,
the stuff that got the highest traffic. Now we're going to talk about
a little bit later how to inform, because again traffic doesn't equal customers.
(18:51):
How to inform yourself. But youdon't want to mess with the podcasts that
have high traffic. If you wereusing this method with a video log podcast
that's all on YouTube, you wantthe impressions because YouTube will spread your content
out more So, if you starttouching headlines and descriptions for high performing,
high scoring content, you're gonna,you know, we're gonna kick yourself in
(19:14):
the butt and hurt yourself because itcould cause an evergreen video to drop out
of YouTube recommendations. Every time youmodify something, by the way these platforms,
uh, you know, stop therecommendations and then reassess it and then
put them back in. Next.You may find content that is scoring okay,
but if you put a but ifyou look at your analytics, you
(19:37):
see that the source and medium orthe specific offer that was in that episode
is going like gangbusters, and sonow we've identified which podcast episode already creates
sales and might need to be promoted. So instead of writing new content,
you take a few dollars and doa pay per click campaign and you amplify
the podcast episode that's already doing well. And then from there you're going to
(20:02):
get results immediately. See, thisis about return on investment. This is
about getting results, not just creatingcontent. And then, of course this
list could go on forever about whatyou do when you have a score,
and I want to get into someof the advanced ways. So just the
main thing is is you want tofigure out what you should keep doing and
what you should stop doing. Nowthere's an advanced way, and I kind
(20:23):
of touched on it, and manyfolks that have followed so far and are
still listening can benefit from this advancedway right away. And what it does
is it directs your new content inthe direction of more leads and more sales.
Now, as I've shown you,it's difficult to measure in a lot
of these podcasting platforms anything other thanthe number of downloads because we don't necessarily
(20:48):
have cookie tracking from the listener inApple podcast or the listener on Spotify.
All the way to our e commerceplatforms. And so what we're going to
do here is we're going to optimizeon the sales side using similar concepts,
and then once we better understand thetopic that leads to conversion and the types
(21:11):
of customers that lead to conversion,we're going to apply that new information back
in the optimization of our front end, which is the podcast itself. Now
again the concept works blog posts,podcasts, video logues, content on social
media networks. But again with thisexample, because you're listening in a podcast,
we're going to talk specifically podcast.So the advanced way is to figure
(21:33):
out how do we drive maximum returnon investment, and we do this by
clustering up the episode topics. Soif you have a report that has episode
topic, the episode title, ithas the published date, and it has
the downloads, we can feed thatto either a Python script or artificial intelligence
or some kind of statistical measurement todo what's called topic clustering, to take
(22:00):
the headlines, the titles and figureout which of these titles have a representationally
high score. Because see the scoreis the foundation. The score normalizes the
data set. And now with anormalized data set, we can say Okay,
well, these types of content arein the top one percent or the
top what we use quint tiles,so in the top twenty percent of performance
(22:22):
for number of downloads. What issimilar about these topics? That's very important
because if they're already performing high andthey got a high score, we can
figure out what is similar and createnew content around what is similar, and
it's likely to generate similar volumes oftraffic. Now, there's a lot of
(22:44):
factors involved. Of course, we'vealready touched on that the giant aging population
could have things that were just publisheda couple of days ago, and so
we may need to cut out theyoung content and make sure that our report
only has everything over the that's thirtydays or older, but within the same
three hundred and sixty five day period, which then means in the math formula,
(23:07):
you don't have a three hundred andsixty five day period, and so
we have to adjust their numbers.So again, this is why marketing analysts
and business analysts. What I'm basicallydoing is taking my almost thirty years of
experience doing business analytics and business development, adding my IT experience to be able
to show you how to effectively andconsistently identify what works and what doesn't.
(23:32):
Are you still with me, Doyou want that return on investment? Do
you want to be able to turnover your marketing dollars and your content creation
dollars to get them back as quicklyas possible. Well, then stick with
me here, because when we talkabout these advanced methods, they are easy
to implement. Once you have aprocedure, so you log into the platform.
(23:52):
The person who does that follows thesesteps, They plug it into whatever
calculating tool you're using. It spitsout what you've got to do. If
that's set up, then things area lot smoother. But again, the
big problem with aging is that notevery episode in the sample has the same
lifespan or the same life There couldbe events in the you know, it
(24:14):
could be a war that broke out, there could be other things and stuff
that you published years ago may notbe reporting in this period because it's not
creating customers, because it's not followingbest practices, it's no longer ranking,
or it was written poorly, orthe content episode itself was just fine,
but it didn't have an offer.And so it takes in the analysis to
(24:37):
understand this and what We then dois layer additional weighting other than aging to
determine which content's best. So Imentioned earlier there's a source medium in a
separate system such as your content library. You may have that podcast episode tied
to the source and medium used inthe description tied to the source and medium's
(24:59):
generating traffic on your Google analytics.Now we can have a full pass through
from the episode published to the conversionat lead generation and the conversion at sale.
Now it might take somebody auditing thatwhole thing to make sure it's all
set up correctly, because a lotof stuff can go wrong. But now
we know from the score which podcastepisodes are getting the most traffic from the
(25:26):
conversion rate, which potential. Sowe now know these episodes have traffic score.
We can now score for conversion,and then we have our sale on
the sale side, we can scorefor sales. Now we use a weighted
average, and we teach this inour topic testing methods. We now use
(25:48):
a weighted average to know which ofthis content is converting. Then from there
we go through all the podcast episodes, build out topic clusters where the things
that are converting leads the way,so that might become a content hub,
and then all this other podcasting episodeson the same topic become leafs and nodes
(26:11):
and stuff off that content hub.And now we've taken our podcast from a
podcast world and where now it's contentin the blog post world. And now
we can see from different perspectives whetherour test and our measures were valid.
Now this is so important because nowwe haven't created new content. We're basically
(26:33):
recycling content we already know as popularin these podcasting networks or on YouTube or
on Rumble or on Spotify, andthen we're putting it on our website to
bring the traffic directly to the websitethrough social media, through search engines,
through pay per click advertising, andwe have better measurements on our website,
So now we're amplifying for the samesource and mediums. Well, it's the
(26:56):
same source and campaign at this point. Now we're amplified that, and we
now have better measures to determine whichtopics work and which topics don't. Now,
our content is not just content.Our content is marketing campaigns that can
be measured, that can be tested, that can be split tested. So,
for example, one of the excitingthings that we do with word press
(27:18):
sites is we have certain plugins thathelp us do in page ab split testing,
and so now we know which offersare the best offers, and then
we can take what we know aboutthe best offers, and when we record
the next podcast, we make thatoffer. See, it's possible for your
content to have load downloads because it'snot being promoted. It could have technical
(27:40):
issues, it could be missing adescription, it could have a bad title,
it could be not old enough tohave enough traffic to be measured accurately.
But I'm looking for the evergreen content. I've got podcast episodes from twenty
eighteen. Right now it's twenty twentythree. I got podcast episodes from twenty
eighteen that have had the same traficevery month, the same counter traffic.
(28:03):
But again, because the listeners weknow their real life humans, the same
human isn't going to listen to thepodcast every month. They might listen to
it twice, but they aren't gonnacome listen to it every month. So
if I'm getting from twenty eighteen totwenty twenty three, let's say there's a
solid four year period there, andI'm getting five hundred listeners every year for
(28:23):
four years, that is two thousandlisteners. So now the work I put
in one time has the potential toconvert that one percent or two percent of
listeners into leads, and I'm nowputting on twenty leads, two hundred leads.
Well, what if the optimization thatI'm teaching you right now could be
(28:45):
used to get ten, fifteen,twenty, thirty, even forty episodes.
It could be out of one hundredor out of five hundred episodes, but
but forty episodes that consistently month overmonth, year every year bring you leads
to your website. Now, byintegrating these similar measures measures on your back
end, you can start working outconversion and you can identify which of those
(29:06):
people are likely to become customers andthen apply what you learn in other platforms
while testing against the podcast medium.This is very important. Other content could
be underrepresented for other reasons. Thatcould have it could have published the same
date that there was a war inIraq, It could have been the same
(29:26):
published the same date that we withdrewfrom Afghanistan. And there's also issues where
we want to look at the cohorts. So we won't go into cohorts right
now. But when we have thisscoring that has been enhanced by leads generated,
which has been enhanced by sales converted. And by the way, not
every technical platform can do this,but I need you to know that this
(29:48):
is possible because now we can buildout cohorts, these quintiles, and we
can say this number one quintile,this h by performing quintel don't touch it
no matter what you do, copywriters, no matter what you do, editors,
no matter what you do, webmaster, don't touch this cohort. And
we can essentially lock down that contentso that we can keep getting the benefits
(30:11):
of content that already performs. Next, we can study that content, and
by studying that content, we canfigure out best practices, build checklists,
build out procedures that we now handto the copywriters with a list of topics,
and those copywriters will go out andwrite new copy, new content and
test it against what we've got now. And so now we're ratcheting up the
(30:33):
results that we're getting. And sothe main takeaway of this is that is
you can make decisions on downloads,click throughs, and other measures, but
they aren't going to tell you anythinguseful. They're going to feel useful,
but they aren't going to direct thereturn on investment. They aren't going to
direct the new content, they aren'tgoing to identify new tests even support product
development. Many of the publishers Iwork with find that they can develop new
(30:56):
products using this information. What Ido for publishers, by the way,
is I help them build, takeit their strong backlog, and identify what's
making money and what doesn't. NoticeI didn't say what generates traffic and what
doesn't, because again, listeners arenot customers, and we want to grow
our customer base, not necessarily ourlistener base, because if you're able to
(31:18):
create and keep profitable customers without havinga popular podcast, or without being a
YouTube creator, or without having agiant channel, and I've seen giant channels
that are not making any money.But again, applying this optimization, we
help basically the publisher or the businessnot have to increase their content budget.
(31:41):
They're not concerned about the Google slab, they're not concerned about YouTube demonetization,
They're not concerned about a lot ofthings because again we're recycling their existing content.
And so whether that content is apodcast or YouTube video, a blog
post, we help them increase theirreturn on investment by knowing what works and
what doesn't. And I've given youin this mini training session, I've given
(32:04):
you some of the ideas and conceptsthat help you use scoring measures. So
remember we're scoring, we're ranking,and then we're making decisions. Now,
for many clients, I've written testingprotocols that significantly increase sales. Now,
why do testing protocols increase sales?So, first off, this does rely
on statistically accurate measures. For manylistening to this you may not even know
(32:28):
what that means, but it meanswhat do we know about this measure that
makes it highly likely to be repeatable? How accurate is it? How likely
is it to continue those types ofresults? And so again, like I
said, I'm combining my technical backgroundwith my business analysts experience to help you
find new revenue sources. And sowe also understand that there's a bridge.
(32:49):
You know, the Apple podcast theGoogle podcasts are not telling you anything about
end user conversion. Plus, whenyou start layering in pay per click campaigns
and other things, we do haveto make sure that all the analytical tools
are integrated. So the testing protocolsI often build per application, and then
on the back end we start buildingin the repeat purchase. We want repeat
(33:15):
purchases across idiverse implementational marketing tools.What does that mean? It means we
want to know if it's the sameperson buying or different people buying. We
want to know their names and theiremail address. And you might have an
email marketing program where you're capturing theemails, but your e commerce platform is
somewhere completely different. Now, alot of organizations will try to integrate all
(33:36):
that. They'll spend hundreds of thousandsof dollars trying to get the perfect platform,
when the important thing about business isgetting the perfect customer, the most
profitable customers. So what I dois I use my background to help you
get the most out of what you'vegot right now, while standardizing the operations
so somebody can sit in an office, pull up a report, dump the
(33:58):
report into a spreadsheet, turn toreport into something useful, and then now
you're building out your editorial calendar withtopics that are most likely to generate customers.
They may not get the most traffic, but you know if they get
any traffic of the right customer groupthat you're going to start making sales.
And then ultimately, to help yourecycle the copy and content that you already
(34:22):
have because if you're going to keepthe budget the same size, because a
lot of you folks out there aretelling me how your budgets keep growing every
year and it's getting tough, andyou're spending so much money on content that
doesn't work anymore. Again, I'msaying, let's not only freeze the marketing
budget, let's not only freeze thecontent budget, but let's get maximum return
(34:43):
on investment, so that you're gettingthat money back as quickly as possible.
You're replacing the dollars you've invested inyour marketing the dollars you've invested in content.
And by the way, I reallythink content marketing done right is marketing.
So you really only have a marketingbudget. But we can talk about
that another time. So one exampleof this is how to optimize a podcast
(35:05):
episode even with limited analytics. That'swhat I've given you here. And so
there are other factors. Though youmight be generating revenue per episode, you
might have direct purchases in the episodeor in so for example, vlogs on
YouTube can have merch opportunities at thebottom. Somebody buying a T shirt about
a certain topic is a great indicatorthat they're a potential customer, and so
(35:30):
we want to build that back in. There's also in channel engagement that is
useful for increasing the reach of yourcontent. So in YouTube for example,
and I just wrote a big programon YouTube optimization because we're really working with
clients on that right now. Butfor examples, the viewers on YouTube who
(35:50):
stay on your video for more thansixty percent of the video significantly increases the
amount of times that YouTube will recommendyour video. And podcast is syndicating to
video, and so for example,all my audio podcasts end up on YouTube,
but they're just audio. I canidentify which ones I should probably invest
(36:13):
money in turning into like a headlessvideo because I know that they convert on
another platform for the specific audience thatI have. Does this makes sense to
you? Can you see how yourback catalog of content can boost sales,
generate more leads, especially if youcan start feeding better conversion insights to your
(36:35):
creative teams, because you know thosefolks are just gonna write content because they
want to. They're going to researchkeywords, and they're looking for the potential
traffic Google AdWords in ad sense wantspotential traffic YouTube advertisement wants potential traffic.
You need customers who pay, stayand refer. So I've shared with you
today a scoring methodology to use withpodcasts and so you can use take limited
(37:00):
information and get a better idea ofwhat works and what doesn't because you've added
offers and those offers have coding,and then we can test these new content
ideas that are based on conversion inother platforms that have better tracking as well
as we can build the new contentwith better tracking, you know, unique
(37:21):
offers, AD codes, specialized links, coded links, and so I'm open
for questions. If you're on thecall today, I'm gonna when I stopped
the recording, we're going to dowith the Q and a session. But
if you're going to write with yourquestions or discover or schedule a discovery call,
you want to visit www dot adbriefingsdot co dot uk. That is
(37:44):
www dot adbriefings dot co dot uk. There's no obligation to go to the
contact page and ask your questions.I know I covered this topic very quickly
and it's a complex topic. Butif you're my typical client has ten thousand
dollars or more on a content budget, and if you're walking around signing the
checks for ten thousand dollars in content. It is best if we can help
(38:06):
you gain a return on investment inninety days or less. That means the
ten thousand dollars you spent today,you can demonstrate to your boss or to
an executive, or to stakeholders thatyou got back the ten thousand dollars.
The original ten thousand dollars is backin your pocket ninety days or less.
Very often that is the most importantpart, not what new content we're going
(38:28):
to do and what new creative ideawe're going to try. And I am
overly analytical in a lot of thisstuff, but again, when I'm able
to help clients create millions of dollarson top of what they were producing before,
literally double businesses because now we're focusingon profitable customers. Do you think
you might want to pay attention?Do you think you might want to listen
to this episode again? Now?Of course, after I've done recording the
(38:50):
episode, we're going to do ourquestion answer session with coaching clients here.
And by the way, when youvisit www dot adbriefings dot co dot uk,
you can look at coaching programs andjoin these types of calls and influence
these types of calls so that wecan focus on content that helps you transform
business relationships into profits. And sowhile I'm giving you a couple seconds to
(39:10):
get together your questions, if you'renot on the live call, you can
of course ask these questions at thewebsite in the comments, or find me
on the internet. I'm justin hitwith ad briefings, copyrighting tips. But
the key here to understand is thatwhen you have proper measurements and you have
a normalization scoring, which you maynot have heard before, but it's an
(39:31):
important fact. And these are thingsyou can ask your people that are doing
analytics right now. By the way, this is kind of a way to
audit the people you've got. Howare the creative people coming up with topics,
what are they informing their decisions withAnd if it's about traffic, well,
remember listeners traffic, they're not customers. If they're not informing the decisions
(39:53):
on actual customers, then there arebetter ways to not only invest in marketing,
invest in content, but to geta return on investment, a measurable
return on investment in ninety days orless. And that means that we're recovering
the content investment with sales by focusingon driving meaningful and profitable customers into the
(40:17):
business. I'm gonna leave you withthat. I'm gonna stop the recording.
We're gonna answer your guys questions onthe call. I see the chat starting
to come through. Thank you verymuch for being a part of this micro
training session. I'm always happy toanswer your questions again. I'm just in
hit with ad Briefings, copywriting tipsand if you'd like to join some of
these live calls, you're going towant to visit www dot Adbriefings dot co
(40:40):
dot uk. Go to the contactpage and ask about how to get on
the live calls, or simply justask your questions about this particular topic.
Do you guys see what I justdid. I made an offer. I
can show you how to measure that. Thanks for listening, See you the
next one.
Remember, every podcast episode, everyvideo view, every interaction with your newsletter
is a real life person. NowI'm going to share a little bit about
how to optimize podcast episodes to reachthe maximum amount of audience, to create
the maximum number of leads. Andit's just one example of how I help
clients get more from their content.I hope this will be informative to you
(00:25):
because I'm going to give you aspecific technique that shows you where to measure,
how to measure, and then ultimatelyhow to optimize for conversion. I'm
justin hit with ad briefings copyrighting tipsin today's podcast episode is kind of a
micro course. I really want youto take notes and to make sure you're
listening carefully to what's going on here. And since we're in the podcast format,
(00:46):
I want to share these insights inthat context so that you can understand
what's necessary to help your clients orto help your business convert more from podcasts.
First off, podcasts are easy toproduce. I simply wrote an outline,
fleshed out an article, and nowI'm going to do the podcast.
But just because they're easy to producedoesn't mean the topics that you cover are
(01:10):
topics that your audience wants to hear. And so what we need to do
is to drive forward a means ofmeasuring to optimize for longevity, for conversion
rate, and then ultimately for sales. So we have to understand that we
want more listeners, we want alarger audience. But as a marketer,
(01:33):
our goal is to reach customers asmany customers as possible. Now we're buying
customers by investing time and effort incontent creation, and in this particular format,
the podcast, we're creating audio,video and other content that's wrapped around
this audience video. So every podcastepisode has a title, it has a
description, it has a call toaction, it may have hashtags, it
(01:56):
may have all these other elements.And so what we need to figure out
when looking at analytics is what isthe combination of these things that best generates
maximum number of leads and the maximumnumber of sales. Now, some mistake
to worry about engagement, number ofdownloads, and a lot of other factors
because we can't control those things.All we can do is once a customer
or once a potential prospect has engagedin our content, we can only control
(02:21):
the offer of the action that theywill take. Now, when they take
the behavioral action, we'll see that, and we can now see that someone
who is a listener, and thatwe might not really know whether it listens
to the whole episode or just partof the episode, but that listener then
becomes a prospect in our system.Whether it's a click to our website and
now tracked in some kind of analyticsplatform, or actually a lead on the
(02:45):
website. We don't really know anythingabout that episode until that kind of conversion
happens. So if we want tomaximize that conversion, we need to make
offers in the podcast that give ussome means of tracking. So we're want
to turn the listeners into prospects.Now, how do we do that Because
(03:06):
we're now acknowledging the truth that listenersare not customers, and so we need
to measure so that we can targetthe customers and create more listeners who are
potentially customers. So there's two conversionevents. The first conversion event would be
in show, and that's inviting alistener to ask questions or to invite a
website for a free gift. Now, the in show offer is going to
(03:29):
show up in your analytics on thewebsite as a unknown traffic or unassigned traffic
or direct traffic, and that's okay. It is difficult to measure and is
difficult to know that they came froma specific podcast episode. So that offer
will be typically be consistent. It'llbe something simple. We don't necessarily want
(03:51):
to ask them to like and subscribebecause people who are subscribing in a platform,
because our podcasts are syndicated, wedon't necessarily want them to subscribe an
Apple podcast because that doesn't really tellus anything unless our analytics can show us
that they subscribed in that platform.Now, before I talk about the next
conversion opportunity, you have to understandthat a properly implemented podcast is going to
(04:16):
syndicate. So this podcast syndicates acrosstwenty seven different channels. Every one of
those channels has their own analytics.So I promise you I'll give you a
measure you can do in some centrallocation, and then indicators of measurements that
you can do in multiple platforms thattend to be regular platforms like Google Analytics
or the podcast recording location. Sothe next conversion opportunity that you can give
(04:44):
to the listener of a podcast isactually in your description, and so in
the description, you can invite themto a special offer, you can invite
them to a free newsletter, somethingthat's going to get you that opt in.
So the first offer or the firstconversion opportunity is going to show up
as unassigned or direct traffic in youranalytics. It's hard to track. But
again, if you're driving them tosome kind of a capture of a lead,
(05:08):
and that offer is tied to alead, then you now have a
behavioral or conversion event that we cannow have some context to move and you
will see if someone clicked through onthe description from a certain platform, whether
or not they are you know wherethey're coming from, but that's not as
(05:28):
important as you can always go backand look at the episode popularity, and
then on the back end you cansurvey and to find out what topics they're
interested in, because we're really developingcontent around topics, whether it's a podcast
or a video or it's a writtenblog post. That is not as important.
So let's continue. If you makeyour conversion opportunity in the description,
(05:51):
now you can use your Google UTMparameters, whether it be sourced, well,
it's going to be sourcing medium atall times, but depends on how
much you fill that out out.You now have context to know that that
individual clicked through the description to thewebsite that tells you the activity behavioral change
moving from one platform to another,and then when they opt in, of
(06:11):
course you're now going to know thelead attribution. Can you see how this
works? Now, the question becomeswhich episodes are most popular and most likely
to send prospects to our website.We're going to find that out in two
different ways. The first way isthose people who convert the leads who also
(06:33):
become customers. We can look attheir demographics, survey them and determine what
topics they're interested in. That iswhere we're going to start driving the new
content creation. On the metric side, there are three factors in play.
So this is your podcasting platform whichhas the highest potential to reach new customers.
(06:53):
It's not necessarily the podcast episode withthe most downloads. So we have
to ask the question which episodes arepopular as indicated by the number of downloads
in a specific period. Because ifwe know there are a certain number of
downloads in a specific period, wecan look at the number of leads generated
in the same period, and wecan say, out of all of our
(07:13):
podcast traffic, here's all the leadswe've created, and then you can segment
it by whether you have the UTMperimeters or not. The next is what
episodes are populatdor as indicated by leadattribution since published date. So now we
can look at a wider range,a longer time period, and we know
since the source and medium attributions arethere, we can look in the Google
(07:36):
analytics and you can see how manyleads in total versus how many impressions or
downloads in total do we have.This is actually a more more accurate measure,
and so now you can look atthe conversion rates by episode by lead
attribute. But remember none of thisanalytics is it's all representational. None of
(07:57):
this analytics is perfect. So thelast bit is we want to make sure
that we're coding in our source andmedium, and we want to see which
source and medium that's in the poolof sources and mediums used on our podcast
episodes is now contributing to a salestransaction. So this is the most accurate
measure. I want to make sureeverybody's with me still, because this of
(08:18):
course is a mini training course onapplying methodology for conversion rate optimization, specifically
two podcasts. But here's a problem. It's a problem that every publisher faces,
is that no one episode gets enoughtraffic in short periods of time to
be statistically accurate. And so thishas been a problem. Podcast with hundreds
(08:41):
of thousands of viewers could have onlyfive or six thousand impressions or downloads on
a specific episode. Now, thatmight be the episodes that are tracked inside
of the publishing platform for your podcast, whether you're using spreaker or Spotify or
whatever platform you're using. Maybe that'sthe oppressions that are tracked there, or
(09:03):
the downloads that are tracked there,and there could be other downloads elsewhere.
Because the content got syndicated, itgot reused, the offer still remained in
a reuse, Like I let peoplecreate shorts out of my videos all the
time, but because it builds thedrive for my directs, but I can't
measure the directs. Now. Thesecond factor is is that the same podcast
(09:26):
listener may listen to multiple podcasts.Now, a lot of the podcast platforms
don't have that analytics in there,so we can know how many times the
same person listened, and that's becausethe different players don't track back that information
accurately. I know, I've gotan iPhone and an Android phone, and
I'm using different players on each phone, and they're not passing back the data.
(09:48):
And that's okay though, because themeasure I'm going to teach you in
this is useful at the head whereyou're publishing, and it's a representative and
feeds advanced techniques that we can talkabout at the into this program. So
again, the publisher doesn't know forsure how many downloads happen, but we
are assuming that the inaccuracy of theanalytics is consistent, and therefore we can
(10:13):
start doing relative measures to identify whatis likely to be most valuable in generating
leads and generating sales. And whenour attributions are correct and our linking are
correct, and there's an offer inevery episode and there's an offer and a
description, we can then start justfiguring out which hashtags and headlines and stuff
we start testing in order to increasethe traffic for particular campaigns. And by
(10:39):
the way, every episode is acampaign. That's the right way of doing
content marketing. So let's get backon track. How do publishers solve this
problem. How does a business solvethis problem, Well, you turn to
marketers, not just the people writein the copy, but you turn to
marketing analysts to figure out what works. They're going to look at the podcast
as a series of messages, justlike a series of email messages or a
(11:01):
series of direct mail letters, andwe're going to apply similar methodology to figure
out what was attribution for the sale. And then based on the attribution of
the sale, we're going to figureout what topics led up to that sale.
And so we don't know which listenerlistened to multiple podcasts. We don't
know that they didn't just Google andthen go to that podcast and listen to
(11:24):
it on a platform that they're noteven loyal to, and then they heard
your offer in the message, andthen they went directly typed in in a
different browser your website, and thenthey took action and became a lead,
and then from there they became acustomer. We don't necessarily have the ability
to track all that, and that'sokay, because again, we're going to
look for evergreen content. Now,when I'm working with clients, they don't
(11:46):
always agree, but I want tolook for evergreen content and then standardize the
downloads to factor in aging in orderto determine which types of content consistently draws
traffic. So we're in our podcastingplatform. We've pulled up the analytics and
it gives you the title of thepodcast episode, it gives you the data
(12:07):
was published and the number of downloads. And you might think that doesn't tell
you very much to make a decision, but that's why we use a formula,
and you gonna want to write thisdown. We're developing a score that
is going to give us the potentialvalue of that podcast over time. But
we're normalizing the score to compare episodesthat have different aging. This is very
(12:31):
important to understand. These episodes havedifferent aging. You publish something last week
it has twelve listeners, and youpublish something three years ago that has five
hundred listeners, which is better.What we don't know necessarily unless we have
a way of scoring. And thescore, again is a normalization here.
So let's talk about the formula scoreequals aging times and then we have a
(12:56):
parenthesis here for a fraction downloads divideup a period. So we're gonna pull
up a report of the last ninetydays. We're gonna pull up a report
of the last three hundred and sixtyfive days, and then we're gonna use
this formula, and I'll tell youa little bit more about the formula in
order to develop a score that allowsus to relatively compare different aged episodes to
(13:18):
determine which episode has the best performance. Now, this is only the performance
of downloads. This is not youknow your sales and leads performance. But
you need to know what's getting trafficconsistently in order to make sure that those
things have offers in them that cannow pull off the back end opportunity,
(13:39):
which would be a lead generated onyour website. Now, remember, some
of these platforms will let you putin offers as an add on, so
you can end up with the sameoffer in every podcast episode. Some of
them will let you do av splits. Some of them you can't change the
original audio, but you can changethe descriptions. And then, most importantly,
things that score really well well,we don't want to come back and
(14:01):
do headline testing and optimization of keywordsand optimization of hashtags and standardization of content,
because that could mess up something that'salready working the way it was presented.
So again, your score is aweighted measure of potential traffic over time,
and it gets more accurate as agingincreases. So the older the video
(14:22):
is, the more likely This scoreis representational of seasonal variations. It takes
into account seasonal variations, It takesinto account changes in the economy, It
takes into account news headlines, soagain it's more evergreen content. Now,
the aging is the number of dayssince the podcast episode was published, and
this is the number of days sincefirst published date. But it should reset
(14:45):
if you've changed the episode title ordescription significantly, And so that's something you
have to keep in mind. Ifevery ninety days you're optimizing the poor performers,
you may need to look at ashorter time period in order to know
whether the optimization has made a difference. There are times I'll just put a
headline on it because I've recorded apodcast and I just need to get it
(15:07):
out there. But I might comeback later and use a different headline,
and when I'm doing my headline testing, and that episode that was like eight
listeners is now all of a sudden, three hundred listeners because the headline caught
their attention. It broke them outof that droneness or the doom scrolling they
were doing, and they've started todownload. Now. In this measurement,
(15:28):
downloads is the count of downloads duringtheir reporting period. And this is very
important and this number is representational.We talked about how the number is not
very accurate. There's a lot ofreasons, ad blockers, different devices,
there's a lot of reasons why thedownload count is not your most accurate count.
One of the problems that I havewith this podcast and the other podcasts
(15:50):
who manage, is it because wedo such a great job on syndication.
And syndication means the podcast is onGoogle podcasts and Apple podcasts and Spotify and
a bunch of these directories, andit's pretty much everywhere. But are the
more places the podcast shows up,the less accurate it is to know the
number of actual downloads. When itcame to who listened to the podcast.
(16:11):
Now, I know there are toolsthat can help with that, but ultimately,
the we can get the bid,we can get the podcast in the
hands of listeners faster than we canget the tools to register how those people
are. Now. Finally, theperiod. The period is the number of
days in the reporting period. Soa low volume podcast is going to want
to have like three hundred and sixtyfive days. You're going to want to
(16:32):
look at all these traffic over thethree hundred and sixty five days and do
your performance measure. And a highPI volume podcast, which whatever depends HIW
for you, might be ninety days. But the key is we need enough
samples to come up with something statisticallyaccurate because what I've just described here.
Now, using a scoring system allowsus to rank, and then from ranking
we can take specific actions to improveperformance. Like, for example, if
(16:57):
you've got an episode that has alot of views but it's not generating traffic,
you might look into it. Andso the first thing we're gonna do
is gon we're gonna audit the offers. You might say, oh my gosh,
I'm so excited. This got fivehundred and seventy six listeners in the
last twenty days or twenty eight days, but why am I not getting any
leads? Well, you might golook at it and find out there's no
(17:19):
offer in the description. You mightgo look at it and there's no offer
in the audio. Now can wefix that? Yes? Should we fix
that? Probably because we don't careso much about the downloads. Remember,
listeners are not equal to customers,and so even though it gets high traffic,
we'll make a note that the topicgot high traffic, but we need
(17:41):
to do something with that traffic byhaving an offer. And so what we're
doing here is the scoring approach allowsus to focus on those things that have
the potential for an offer to dosomething, and then we're just going to
look at it. We're not changingstuff, but we're going to look at
it and say, oh, waita second. We've got a good description,
we've got good hashtags, we've gota good headline, but there's no
(18:02):
offer in the description. So we'regoing to add an offer at the end
of the description. Now, arepeople going to find the offer at the
end of the description? Is thatoffered? Tech's going to syndicate across all
the different channels that are showing outyour podcast. Probably not, But what
if that five hundred and seventy sixlisteners that month one percent of them two
percent of them could become leads onyour website. You don't want to miss
(18:26):
that opportunity. Next, the scoringsystem helps us figure out what we should
study as controls. If you goin and do this scoring and then you
rank the stuff that's at the bottomof the rank. You don't want to
do more of that. You wantto do the stuff that's at the top,
the stuff that got the highest traffic. Now we're going to talk about
a little bit later how to inform, because again traffic doesn't equal customers.
(18:51):
How to inform yourself. But youdon't want to mess with the podcasts that
have high traffic. If you wereusing this method with a video log podcast
that's all on YouTube, you wantthe impressions because YouTube will spread your content
out more So, if you starttouching headlines and descriptions for high performing,
high scoring content, you're gonna,you know, we're gonna kick yourself in
(19:14):
the butt and hurt yourself because itcould cause an evergreen video to drop out
of YouTube recommendations. Every time youmodify something, by the way these platforms,
uh, you know, stop therecommendations and then reassess it and then
put them back in. Next.You may find content that is scoring okay,
but if you put a but ifyou look at your analytics, you
(19:37):
see that the source and medium orthe specific offer that was in that episode
is going like gangbusters, and sonow we've identified which podcast episode already creates
sales and might need to be promoted. So instead of writing new content,
you take a few dollars and doa pay per click campaign and you amplify
the podcast episode that's already doing well. And then from there you're going to
(20:02):
get results immediately. See, thisis about return on investment. This is
about getting results, not just creatingcontent. And then, of course this
list could go on forever about whatyou do when you have a score,
and I want to get into someof the advanced ways. So just the
main thing is is you want tofigure out what you should keep doing and
what you should stop doing. Nowthere's an advanced way, and I kind
(20:23):
of touched on it, and manyfolks that have followed so far and are
still listening can benefit from this advancedway right away. And what it does
is it directs your new content inthe direction of more leads and more sales.
Now, as I've shown you,it's difficult to measure in a lot
of these podcasting platforms anything other thanthe number of downloads because we don't necessarily
(20:48):
have cookie tracking from the listener inApple podcast or the listener on Spotify.
All the way to our e commerceplatforms. And so what we're going to
do here is we're going to optimizeon the sales side using similar concepts,
and then once we better understand thetopic that leads to conversion and the types
(21:11):
of customers that lead to conversion,we're going to apply that new information back
in the optimization of our front end, which is the podcast itself. Now
again the concept works blog posts,podcasts, video logues, content on social
media networks. But again with thisexample, because you're listening in a podcast,
we're going to talk specifically podcast.So the advanced way is to figure
(21:33):
out how do we drive maximum returnon investment, and we do this by
clustering up the episode topics. Soif you have a report that has episode
topic, the episode title, ithas the published date, and it has
the downloads, we can feed thatto either a Python script or artificial intelligence
or some kind of statistical measurement todo what's called topic clustering, to take
(22:00):
the headlines, the titles and figureout which of these titles have a representationally
high score. Because see the scoreis the foundation. The score normalizes the
data set. And now with anormalized data set, we can say Okay,
well, these types of content arein the top one percent or the
top what we use quint tiles,so in the top twenty percent of performance
(22:22):
for number of downloads. What issimilar about these topics? That's very important
because if they're already performing high andthey got a high score, we can
figure out what is similar and createnew content around what is similar, and
it's likely to generate similar volumes oftraffic. Now, there's a lot of
(22:44):
factors involved. Of course, we'vealready touched on that the giant aging population
could have things that were just publisheda couple of days ago, and so
we may need to cut out theyoung content and make sure that our report
only has everything over the that's thirtydays or older, but within the same
three hundred and sixty five day period, which then means in the math formula,
(23:07):
you don't have a three hundred andsixty five day period, and so
we have to adjust their numbers.So again, this is why marketing analysts
and business analysts. What I'm basicallydoing is taking my almost thirty years of
experience doing business analytics and business development, adding my IT experience to be able
to show you how to effectively andconsistently identify what works and what doesn't.
(23:32):
Are you still with me, Doyou want that return on investment? Do
you want to be able to turnover your marketing dollars and your content creation
dollars to get them back as quicklyas possible. Well, then stick with
me here, because when we talkabout these advanced methods, they are easy
to implement. Once you have aprocedure, so you log into the platform.
(23:52):
The person who does that follows thesesteps, They plug it into whatever
calculating tool you're using. It spitsout what you've got to do. If
that's set up, then things area lot smoother. But again, the
big problem with aging is that notevery episode in the sample has the same
lifespan or the same life There couldbe events in the you know, it
(24:14):
could be a war that broke out, there could be other things and stuff
that you published years ago may notbe reporting in this period because it's not
creating customers, because it's not followingbest practices, it's no longer ranking,
or it was written poorly, orthe content episode itself was just fine,
but it didn't have an offer.And so it takes in the analysis to
(24:37):
understand this and what We then dois layer additional weighting other than aging to
determine which content's best. So Imentioned earlier there's a source medium in a
separate system such as your content library. You may have that podcast episode tied
to the source and medium used inthe description tied to the source and medium's
(24:59):
generating traffic on your Google analytics.Now we can have a full pass through
from the episode published to the conversionat lead generation and the conversion at sale.
Now it might take somebody auditing thatwhole thing to make sure it's all
set up correctly, because a lotof stuff can go wrong. But now
we know from the score which podcastepisodes are getting the most traffic from the
(25:26):
conversion rate, which potential. Sowe now know these episodes have traffic score.
We can now score for conversion,and then we have our sale on
the sale side, we can scorefor sales. Now we use a weighted
average, and we teach this inour topic testing methods. We now use
(25:48):
a weighted average to know which ofthis content is converting. Then from there
we go through all the podcast episodes, build out topic clusters where the things
that are converting leads the way,so that might become a content hub,
and then all this other podcasting episodeson the same topic become leafs and nodes
(26:11):
and stuff off that content hub.And now we've taken our podcast from a
podcast world and where now it's contentin the blog post world. And now
we can see from different perspectives whetherour test and our measures were valid.
Now this is so important because nowwe haven't created new content. We're basically
(26:33):
recycling content we already know as popularin these podcasting networks or on YouTube or
on Rumble or on Spotify, andthen we're putting it on our website to
bring the traffic directly to the websitethrough social media, through search engines,
through pay per click advertising, andwe have better measurements on our website,
So now we're amplifying for the samesource and mediums. Well, it's the
(26:56):
same source and campaign at this point. Now we're amplified that, and we
now have better measures to determine whichtopics work and which topics don't. Now,
our content is not just content.Our content is marketing campaigns that can
be measured, that can be tested, that can be split tested. So,
for example, one of the excitingthings that we do with word press
(27:18):
sites is we have certain plugins thathelp us do in page ab split testing,
and so now we know which offersare the best offers, and then
we can take what we know aboutthe best offers, and when we record
the next podcast, we make thatoffer. See, it's possible for your
content to have load downloads because it'snot being promoted. It could have technical
(27:40):
issues, it could be missing adescription, it could have a bad title,
it could be not old enough tohave enough traffic to be measured accurately.
But I'm looking for the evergreen content. I've got podcast episodes from twenty
eighteen. Right now it's twenty twentythree. I got podcast episodes from twenty
eighteen that have had the same traficevery month, the same counter traffic.
(28:03):
But again, because the listeners weknow their real life humans, the same
human isn't going to listen to thepodcast every month. They might listen to
it twice, but they aren't gonnacome listen to it every month. So
if I'm getting from twenty eighteen totwenty twenty three, let's say there's a
solid four year period there, andI'm getting five hundred listeners every year for
(28:23):
four years, that is two thousandlisteners. So now the work I put
in one time has the potential toconvert that one percent or two percent of
listeners into leads, and I'm nowputting on twenty leads, two hundred leads.
Well, what if the optimization thatI'm teaching you right now could be
(28:45):
used to get ten, fifteen,twenty, thirty, even forty episodes.
It could be out of one hundredor out of five hundred episodes, but
but forty episodes that consistently month overmonth, year every year bring you leads
to your website. Now, byintegrating these similar measures measures on your back
end, you can start working outconversion and you can identify which of those
(29:06):
people are likely to become customers andthen apply what you learn in other platforms
while testing against the podcast medium.This is very important. Other content could
be underrepresented for other reasons. Thatcould have it could have published the same
date that there was a war inIraq, It could have been the same
(29:26):
published the same date that we withdrewfrom Afghanistan. And there's also issues where
we want to look at the cohorts. So we won't go into cohorts right
now. But when we have thisscoring that has been enhanced by leads generated,
which has been enhanced by sales converted. And by the way, not
every technical platform can do this,but I need you to know that this
(29:48):
is possible because now we can buildout cohorts, these quintiles, and we
can say this number one quintile,this h by performing quintel don't touch it
no matter what you do, copywriters, no matter what you do, editors,
no matter what you do, webmaster, don't touch this cohort. And
we can essentially lock down that contentso that we can keep getting the benefits
(30:11):
of content that already performs. Next, we can study that content, and
by studying that content, we canfigure out best practices, build checklists,
build out procedures that we now handto the copywriters with a list of topics,
and those copywriters will go out andwrite new copy, new content and
test it against what we've got now. And so now we're ratcheting up the
(30:33):
results that we're getting. And sothe main takeaway of this is that is
you can make decisions on downloads,click throughs, and other measures, but
they aren't going to tell you anythinguseful. They're going to feel useful,
but they aren't going to direct thereturn on investment. They aren't going to
direct the new content, they aren'tgoing to identify new tests even support product
development. Many of the publishers Iwork with find that they can develop new
(30:56):
products using this information. What Ido for publishers, by the way,
is I help them build, takeit their strong backlog, and identify what's
making money and what doesn't. NoticeI didn't say what generates traffic and what
doesn't, because again, listeners arenot customers, and we want to grow
our customer base, not necessarily ourlistener base, because if you're able to
(31:18):
create and keep profitable customers without havinga popular podcast, or without being a
YouTube creator, or without having agiant channel, and I've seen giant channels
that are not making any money.But again, applying this optimization, we
help basically the publisher or the businessnot have to increase their content budget.
(31:41):
They're not concerned about the Google slab, they're not concerned about YouTube demonetization,
They're not concerned about a lot ofthings because again we're recycling their existing content.
And so whether that content is apodcast or YouTube video, a blog
post, we help them increase theirreturn on investment by knowing what works and
what doesn't. And I've given youin this mini training session, I've given
(32:04):
you some of the ideas and conceptsthat help you use scoring measures. So
remember we're scoring, we're ranking,and then we're making decisions. Now,
for many clients, I've written testingprotocols that significantly increase sales. Now,
why do testing protocols increase sales?So, first off, this does rely
on statistically accurate measures. For manylistening to this you may not even know
(32:28):
what that means, but it meanswhat do we know about this measure that
makes it highly likely to be repeatable? How accurate is it? How likely
is it to continue those types ofresults? And so again, like I
said, I'm combining my technical backgroundwith my business analysts experience to help you
find new revenue sources. And sowe also understand that there's a bridge.
(32:49):
You know, the Apple podcast theGoogle podcasts are not telling you anything about
end user conversion. Plus, whenyou start layering in pay per click campaigns
and other things, we do haveto make sure that all the analytical tools
are integrated. So the testing protocolsI often build per application, and then
on the back end we start buildingin the repeat purchase. We want repeat
(33:15):
purchases across idiverse implementational marketing tools.What does that mean? It means we
want to know if it's the sameperson buying or different people buying. We
want to know their names and theiremail address. And you might have an
email marketing program where you're capturing theemails, but your e commerce platform is
somewhere completely different. Now, alot of organizations will try to integrate all
(33:36):
that. They'll spend hundreds of thousandsof dollars trying to get the perfect platform,
when the important thing about business isgetting the perfect customer, the most
profitable customers. So what I dois I use my background to help you
get the most out of what you'vegot right now, while standardizing the operations
so somebody can sit in an office, pull up a report, dump the
(33:58):
report into a spreadsheet, turn toreport into something useful, and then now
you're building out your editorial calendar withtopics that are most likely to generate customers.
They may not get the most traffic, but you know if they get
any traffic of the right customer groupthat you're going to start making sales.
And then ultimately, to help yourecycle the copy and content that you already
(34:22):
have because if you're going to keepthe budget the same size, because a
lot of you folks out there aretelling me how your budgets keep growing every
year and it's getting tough, andyou're spending so much money on content that
doesn't work anymore. Again, I'msaying, let's not only freeze the marketing
budget, let's not only freeze thecontent budget, but let's get maximum return
(34:43):
on investment, so that you're gettingthat money back as quickly as possible.
You're replacing the dollars you've invested inyour marketing the dollars you've invested in content.
And by the way, I reallythink content marketing done right is marketing.
So you really only have a marketingbudget. But we can talk about
that another time. So one exampleof this is how to optimize a podcast
(35:05):
episode even with limited analytics. That'swhat I've given you here. And so
there are other factors. Though youmight be generating revenue per episode, you
might have direct purchases in the episodeor in so for example, vlogs on
YouTube can have merch opportunities at thebottom. Somebody buying a T shirt about
a certain topic is a great indicatorthat they're a potential customer, and so
(35:30):
we want to build that back in. There's also in channel engagement that is
useful for increasing the reach of yourcontent. So in YouTube for example,
and I just wrote a big programon YouTube optimization because we're really working with
clients on that right now. Butfor examples, the viewers on YouTube who
(35:50):
stay on your video for more thansixty percent of the video significantly increases the
amount of times that YouTube will recommendyour video. And podcast is syndicating to
video, and so for example,all my audio podcasts end up on YouTube,
but they're just audio. I canidentify which ones I should probably invest
(36:13):
money in turning into like a headlessvideo because I know that they convert on
another platform for the specific audience thatI have. Does this makes sense to
you? Can you see how yourback catalog of content can boost sales,
generate more leads, especially if youcan start feeding better conversion insights to your
(36:35):
creative teams, because you know thosefolks are just gonna write content because they
want to. They're going to researchkeywords, and they're looking for the potential
traffic Google AdWords in ad sense wantspotential traffic YouTube advertisement wants potential traffic.
You need customers who pay, stayand refer. So I've shared with you
today a scoring methodology to use withpodcasts and so you can use take limited
(37:00):
information and get a better idea ofwhat works and what doesn't because you've added
offers and those offers have coding,and then we can test these new content
ideas that are based on conversion inother platforms that have better tracking as well
as we can build the new contentwith better tracking, you know, unique
(37:21):
offers, AD codes, specialized links, coded links, and so I'm open
for questions. If you're on thecall today, I'm gonna when I stopped
the recording, we're going to dowith the Q and a session. But
if you're going to write with yourquestions or discover or schedule a discovery call,
you want to visit www dot adbriefingsdot co dot uk. That is
(37:44):
www dot adbriefings dot co dot uk. There's no obligation to go to the
contact page and ask your questions.I know I covered this topic very quickly
and it's a complex topic. Butif you're my typical client has ten thousand
dollars or more on a content budget, and if you're walking around signing the
checks for ten thousand dollars in content. It is best if we can help
(38:06):
you gain a return on investment inninety days or less. That means the
ten thousand dollars you spent today,you can demonstrate to your boss or to
an executive, or to stakeholders thatyou got back the ten thousand dollars.
The original ten thousand dollars is backin your pocket ninety days or less.
Very often that is the most importantpart, not what new content we're going
(38:28):
to do and what new creative ideawe're going to try. And I am
overly analytical in a lot of thisstuff, but again, when I'm able
to help clients create millions of dollarson top of what they were producing before,
literally double businesses because now we're focusingon profitable customers. Do you think
you might want to pay attention?Do you think you might want to listen
to this episode again? Now?Of course, after I've done recording the
(38:50):
episode, we're going to do ourquestion answer session with coaching clients here.
And by the way, when youvisit www dot adbriefings dot co dot uk,
you can look at coaching programs andjoin these types of calls and influence
these types of calls so that wecan focus on content that helps you transform
business relationships into profits. And sowhile I'm giving you a couple seconds to
(39:10):
get together your questions, if you'renot on the live call, you can
of course ask these questions at thewebsite in the comments, or find me
on the internet. I'm justin hitwith ad briefings, copyrighting tips. But
the key here to understand is thatwhen you have proper measurements and you have
a normalization scoring, which you maynot have heard before, but it's an
(39:31):
important fact. And these are thingsyou can ask your people that are doing
analytics right now. By the way, this is kind of a way to
audit the people you've got. Howare the creative people coming up with topics,
what are they informing their decisions withAnd if it's about traffic, well,
remember listeners traffic, they're not customers. If they're not informing the decisions
(39:53):
on actual customers, then there arebetter ways to not only invest in marketing,
invest in content, but to geta return on investment, a measurable
return on investment in ninety days orless. And that means that we're recovering
the content investment with sales by focusingon driving meaningful and profitable customers into the
(40:17):
business. I'm gonna leave you withthat. I'm gonna stop the recording.
We're gonna answer your guys questions onthe call. I see the chat starting
to come through. Thank you verymuch for being a part of this micro
training session. I'm always happy toanswer your questions again. I'm just in
hit with ad Briefings, copywriting tipsand if you'd like to join some of
these live calls, you're going towant to visit www dot Adbriefings dot co
(40:40):
dot uk. Go to the contactpage and ask about how to get on
the live calls, or simply justask your questions about this particular topic.
Do you guys see what I justdid. I made an offer. I
can show you how to measure that. Thanks for listening, See you the
next one.
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