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The Science of Excel for PPC Marketers with Bing Ads

November 21, 2019

Welcome everyone to the Bing
ads webcast on the science of Excel for PPC marketers. My name is MJ DePalma and
I will be your host today. This is the third webcast in our
advertisers science series and we are excited to share concrete
methodologies of harnessing the power of Excel for
your marketing. Before we begin, let’s review
some housekeeping items to enhance your experience
with us today. The webcast console that you see
is customizable on your side. Where you can click the content
widgets that you see on your screen and move them around or
size them for your screen size. You can expand your slide
area by clicking on maximize icon the top right of
your slide area, or by dragging the bottom right
corner of the slide area. If you have any technical
difficulty please click on the help widget. It has a question mark icon and
covers common technical issues. We recommend if you can, to leave all the widgets as they
are, so you have the ability to see all the great
resources at the same time. This way. This cast is jam packed
with great information, and because of that we most likely
will not have time for Q and A at the end. However, feel free to tweet
your questions to Bing ads at Eric Couch if they go
unanswered, using the hashtag askbingads and Eric will do his
best to answer them for you. We will also be following
up with a blog post on any unanswered questions, so
be on the lookout for that and the follow up email
after the webcast. Also, you’ll see a resource
widget in the upper right hand corner we’ll refer
to during the webcast. Go ahead now and download
the Excel spreadsheet you see, so you’re ready to follow
along later with Eric. Also we found out that the PDF
of the actual presentation was not downloadable and that’s probably because
the presentation is so large. So we’ll fix that on
the on-demand portion. We’ll figure that out. It might be a PDF of two parts. So be on the lookout for that. Also, there’s a Twitter widget
that will enable you to tweet right from the webcast
with the hashtag Bing ads and hashtag Bing ads
webinar hashtag. That’s kind of redundant,
but that’s what it is. Which appears to your upper
right under resources. We will also provide all Twitter
handles of the speakers in the next slide. Let me introduce my, as I said,
my name is MJ DePalma and I will be your host and
monitoring all Q & A. And we also have Eric Couch,
who’s are client development and training manager. And as you can see, he’s also an Excel superhero,
in that picture.>>More of an Excel dork.>>[LAUGH]
>>But I appreciate the enthusiasm. Or I guess the, or yeah,
just a super hero designation. Fun fact, MJ’s actually the person
who took that photo of me.>>That’s right.>>It is, yeah. I just felt compelled to just
kind of like rip that open and just let my Excel flag fly, so.>>You’ve gotten a lot of
mileage out of that, Eric.>>I really have.>>[LAUGH]
>>A lot of interesting comments but all good things,
and I’m not ashamed.>>Well, you truly love Excel,
and it fits you really well.>>It’s true, it’s true.>>Also just to mention,
the on-demand version, just so you know, for you and
your colleagues, will be available approximately
two days after this webcast. And can be accessed using
the same link you registered at, which is If your colleagues or
friends could make it this time, be sure to share that
link with them and you’ll get it in the followup
email that I mentioned earlier. Last house keeping item,
we would love your participation in our survey at the end
of the webcast so that we can improve
in anyway possible. So lets get started,
what’s on the agenda?>>Well, I was gonna ask you
what’s on the agenda, but I guess I’m the one who
put this all together. So, I should probably know that,
right? So yeah, what we’re
gonna talk about today. We have a lot of
ground to cover. So, here’s what
we’re gonna cover. The power of conditional
formatting and pivot tables. We’re gonna talk about some
ways you can use Excel to turbo charge some insights you get
from the Bing ads interface. We’re also gonna talk about
how to combine Excel formulas like a mad PPC scientist. I’m gonna throw some new
formulas at the audience that you may not have heard before, especially because we
only just released them. I’m also gonna talk about how
you can use some plug ins like solver, to rearrange and incrementally add budget
within your ROI goals. So does that sound good?>>That sounds awesome, Eric.>>All right.>>I do wanna touch on that,
we’ve being doing a lot of client trainings and
doing a lot of events. And from those events,
we’ve heard over and over again, this is where this web cast and
this content actually came from, is that our customers really
wanted to know, how can I be more data driven simply by
using the tools that I have? How can I be more powerful? How can I be more insightful? And so, being at Microsoft and having Excel is such
an amazing magical win-win.>>Yeah, I mean if you wanna
work with spreadsheets, you might as well work on
the program that is the best spreadsheet tool
in the universe.>>[LAUGH] That’s right.>>So let’s get started, right? So yeah, the tools MJ mentioned,
so the one’s we’re gonna be talking about today,
three in particular, Excel. So hopefully, everybody [LAUGH]
here has that, I know I do. It’s getting kinda critical so
we’ll walk through this. But we’re also gonna talk
about Auction Insights, the Campaign Planner and
the one we’ll see here. It’s grayed out. It’s Bing Ads Intelligence. It’s another plugin for Excel. We’re not gonna talk
about it today but->>We will be doing another web cast coming soon that
will be dedicated to Bing Ads Intelligence.>>Absolutely, it’s kind of like the hidden
gem of search marketing. So it’s just kinda there
to wet your appetite. So if you wanna follow along,
at any point you can go to the upper right corner of
the webcast console and download the file. It’s the I Simply
Excel Demo Workbook. That has pretty much everything
we’re gonna talk about in there with some pretty
detailed instructions. So if you missed what
we’re talking about or you wanna revisit it at any
time, just download that and it’ll be there at your
fingertips ready to go.>>Awesome.>>All right, we ready?>>We’re ready.>>Got a lot of ground to cover,
so we’re gonna fly. So our first thing to
talk about is let’s avoid spreadsheet blindness with the
power of conditional formatting. So, what is
spreadsheet blindness? Well, spreadsheet blindness
is an affliction that unfortunately affects about 90%
of search engine marketers. Basically it’s when you’re
staring at a spreadsheet full of rows and columns that go beyond counting
and you kind of go blind. Your eyes feel like
they got set on fire. It’s just you are not
enjoying looking at it. You are not able to figure
out what kind of insights you are able to derive from
these spreadsheets, and we wanna help you out. There are some tools and some tactics you can
employ to help you. So what is conditional
formatting? Well, conditional formatting is
an Excel function that allows you to format things
conditionally. Well, the non-sarcastic
answer of that is conditional formatting is a function that
allows you to automatically change the format of
a cell based on values and parameters that you dictate. And you can actually change a
lot of different things with it. Like it’s not just limited to, well, it’s really
not limited at all. So you can change text color and
format. You can also change cell colors. Now, that’s gonna be one
we’ll talk about at length. You can also add some bar
graph overlays to your data. And then insert some
very pretty graphics. So, I’m going to warn you now, that’s about as fancy as
my design know-how gets. So, if you’re expecting anything
prettier, you’re probably gonna be disappointed, but
how do you find it? So it’s not really
hiding anywhere. It’s one of the default functions in Excel
in the home ribbon. You can find it kind of
on the right-hand side, kind of squished between
the general settings and also like the format
of table stuff. Now, if you’re not seeing it, maybe your Excel window’s
not quite long enough. But once you do have it there,
and you click on it, and you get the drop down menu, you
have a lot of different options. You can highlight cells according to
values that you set. So things like greater than,
less than, between, equal to, you can also get fancy and
look at. Certain text things, like
look at things with text that contains certain characters or
certain things that you maybe want to highlight,
like maybe an add copy. You can also look at things
with predefined rules. So if you don’t wanna do
things by custom nature, do just the top ten, or top 10%,
or bottom 10% of things, or above and
below average items. So maybe if you wanna look at
your keywords, and conditionally format the ones that are above
or below certain thresholds for conversioning, right,
or the top ten. Just isolate certain
themes there. You can also layer data
bars over your spreadsheet. So this can be very useful for
quantitative metrics, things that aren’t
necessarily good or bad. You just need to know how
many of them that you have, things like impressions. Whereas, this other one
is really great for qualitative metrics,
which are color gradients. So spoiler alert, if you wanna
create things like a heat map, this is where you wanna go. If you wanna look at things,
whether they’re good or bad based off of how high or
low they are on a scale, you can use this to
figure that out. And then you can also insert
some icon sets in-line with your data. If you’re not a big fan of
just some of the color things, instead you’re more visual,
you wanna do some arrows or some other color coded icons,
do that instead. And even below that, you’re not just limited to the
ones we have highlighted here. You can also create
custom rules. So believe me, creating custom
conditional formatting rules is probably a webinar unto itself,
because you can get very, very, very in depth with
the color gradient and all of the different types
of options in there. So we are not going to
dive into that today, but you have the option to
customize any of these rules in a way you see fit
with those custom rules there, and just highlight new rules. So, how can we
actually use this? So what’s an easy way that you
can get started using this function in kind of
a scientific way? And the easiest way is creating
a dayparting heat map, doing it by campaign, or
even to the account level. So to use conditional
formatting properly, so you want to download it, and so, it looks like we’re a little
bit out of order here. So what you want to do is, you
actually create an account from the report center, making sure
that the unit of time is hour of day ,and then you download
that report to Excel. And if you want to, you can
make it a campaign report, not just an account report. And so, what you wanna do is, this is like the raw
output that you get. So this is like spreadsheet
blindness personified. So MJ,
what am I supposed to do here?>>Well you’re supposed to
do conditional formatting.>>[LAUGH]
>>Yeah, exactly, because you really can’t tell. Unless you want to stare at
these numbers and try and figure out what it is
you’re supposed to do.>>I have no idea
where to look here.>>Exactly. So to use conditional
formatting properly, all you have to do is highlight
each column individually, and select the scale
that you wanna use. So in this case, I’ll show you
the wrong way of doing it. So if you highlight every single
column and just do one scale for all of it, it actually
gets kinda thrown off, and it looks sort of like a mess,
like this. So this doesn’t actually
tell us anything. All it’s really telling me here
is that, no kidding, or no duh, impressions are the highest
value on this spreadsheet. That’s not actually
helping us at all.>>No.
>>Instead if we highlight each column individually and apply
the appropriate color scale, so for
things like cost per conversion, making sure that lower
numbers are better, or for click-through rate, making sure
higher numbers are better. Well if we do that correctly,
then it’s actually, we get a more accurate picture
of account performance by time of day,
visualized in heat map form. And then if we’d layer
some gradient bars to these quantitative metrics, it actually provides
even more insight. We know what the even flow of
traffic is over the course of this day in terms of both
impressions, clicks, spend, and conversion volume. And then we see our qualitative
metrics with this red and green contrast immediately
highlighting some opportunities here. So MJ,
just looking at the contrast, so the red versus the green, what
are some of the opportunities I have here to maybe you bid more?>>So the green, where it says,
line number seven.>>Yeah, so
we’re really well there.>>Eight.>>11.>>Exactly.>>Where it’s not as green you
can probably gain more there.>>Yeah, exactly. And so when you look at
something like average position, like where I’m doing
the worst in the day, so I have that one midnight
hour that’s pretty bad, but I also have those hours from
about like 4 p.m to 6 p.m in the afternoon for
this particular account. My average position
is pretty bad, and my cost per conversion number
is actually pretty good, right?>>Yeah.>>Exactly.
So looking at those contrasts, I can pretty much immediately
see an opportunity to implement a dayparting bid modifier.>>I see.
>>To be a little more competitive there. So that’s the big thing when
working with heat maps, is to look at the contrasts
if you’re looking at this sort of dayparting thing, but
that’s not the only use for it. So this is a dayparting heat map
just looking at time of day, but you get a little more advanced. So this is the same kind
of heat map here, only now, we’ve added in days in
addition to time of day. So we’re seeing the entire week,
and we can see some pretty
clear general themes. So early morning hours, pretty much regardless of day,
probably not good for us. But Sundays, pretty terrible for
this account, as is some of the evening hours. Those are the dinner hours
from about 5 to 7 PM. So we can get some pretty clear
directional insights from what I’m supposed to do here,
but it’s not even just
limited to dayparting. That’s not the only use case for
this. So this is a super slick ad
copy, ad performance heat map. This is an older version of it. So you can actually get this
if you have Bing Ad’s account managers, they can run this
through your own accounts, or I can teach you how to do this, which we’ll go over to
this in just a second. But can you imagine
trying to figure out what the best combination was
of your ad title and ad description if these were
all just raw CTR numbers?>>No.>>Exactly. Yeah, it’d just be a bunch
of numbers on a big white spreadsheet, totally incapable
of figuring anything out. But, if you use this conditional
formatting and look for the greenest cells,
you’re able to figure out pretty quickly what your best
combinations are, and for this particular industry. So this is for auto insurance,
and what we’ve done here is we’ve looked at what we’re
using in the ad title, and then also the calls to action,
or the features, or the benefits in the ad description line, and
pit those against one another to figure out what’s the highest
click-through rate. And we found that mentioning
free and safe, go figure, for auto insurance, that’s
the most popular combination.>>As well as, I see fast and
safe, and quote and safe.>>Yeah, and
also quote and safe.>>Safe is pretty-
>>Yeah, safe seems to be the universal
best performer there. We add in a couple of other
extra elements there for flavor, but safe, particularly in that
ad title, that’s the key. Now, MJ, there is one common
theme that these two heat maps, they had one thing in common. Do you have any idea
what it might be?>>Tell me.
>>Tell me, okay. Well, I guess you didn’t read
ahead on the presentation.>>[LAUGH]
>>I didn’t.>>Okay, so the one common theme
that they had is that they both came from pivot tables.>>Awesome.
>>So yeah, the ad performance heat map, if you know how to make a pivot
table already, I’m gonna go in to it just now if you don’t,
but if you already do know that ad copy performance heat
map came from a pivot table. So when you use something like
conditional formatting on a pivot table, it kinda amplifies the power
that a pivot table already has, like to isolate or to look at
specific segments of your data. Conditional formatting
just makes it that much easier to read. So, I guess it’s time
to kinda dive in to talking about your
new best friend, or maybe rediscovering your
old claim, the pivot table. I put this picture here because
it’s man’s best friend. Well, pivot table is really
the Excel user’s best friend, especially when it comes to PPC. The pivot table is one of the
very first things That I ever looked at,
when it came to learning Excel. So let’s go through
a hypothetical situation here. So let’s say you needed to
pull the following report. So we need to look at
a pure performance report, a six month performance broken
out by month, match type, devices, and conversions. So if I go to
the Bing Ads Report Center, I can download a keyword report
with all that stuff in there. But the problem is,
it looks like this. And so it’s too much data. You have the same metrics
that are repeated over and over again. So if you look at,
we have the Ad Group and the Account Name and
all that stuff. It’s really hard to
simplify this or to figure out what this report
is actually supposed to tell me. I’m looking at a specific
thing here, and it’s not giving me anything. So the issue here is that
this report on its own isn’t really actionable. Or I mean, it’s actionable but you have to take some time to
really dive into it, right? Now, enter the pivot table. So I’m probably preaching
to the choir here. So let’s all kind of have
a mutual love fest for the pivot table. But just for those of you not
in the know, well, now you are. A pivot table is a program tool
that allows you to aggregate and compare data from selected
columns and rows. And then you can manipulate that
to obtain a desired report. But in English, it’s a reporting
tool that you can do a bunch of crazy stuff with. Although, the short answer
is that it’s awesome. It’s my favorite tool in Excel,
pretty much. So let’s kinda give
the comparison here. So the standard Excel table,
so it’s a raw output. It’s not really actionable or
obvious and it requires some adjustments to
actually use this as a report. You wouldn’t wanna send that giant white Excel spreadsheet
to a client, or to a boss, or to anybody who cares about what
it is you’re doing, right? Whereas the pivot table, you can summarize that data
in easy-to-digest formats. You can also quickly compare
those subsets updated together and then reveal patterns and
relations in that data. And really, it just allows for
faster analysis. So if we look at our
original problem here, so considering that question we
had, so which keywords get the most clicks broken out
by match type on computers? Well if we focus on these four
elements of the pivot table, Rows, Values, Columns,
and Filters, well, we can actually see that. So if you wanna look at
what it actually looks like when you’re manipulating
these pivot tables. So there are four elements,
Filters, Columns, Rows and Values. Those build and
define your pivot table. And so by dragging and
dropping those elements into these different fields, you can
create a pretty robust report. Though I wanna say this, you can
get there in many different ways with a pivot table, either by
rearranging stuff in the rows or the values or
columns or filters. There are a million different
ways to get this data there. So it’s really flexible. Now, there are a few steps to
performing a perfect pivot. So one is determining what
the table should display. Selecting all of the data
you wanna pivot. Navigate to Insert
>Pivot Table. You choose the location for
your table and create it, and then drag and drop Field List
elements into place. And just for
those of you still on the line, we are gonna go into some more
advanced applications of this. We just need to kinda
set the foundation. Now, let’s determine
what the table displays. So the most basic level, so the
basic most formative question is, which keywords
get the most clicks? Well to figure that out, we put
keywords in our rows field and values in our clicks field,
right? So now we’re just looking
at clicks per keyword, so pretty simple. And we layer on another
element to that. So match type,
we put match type in columns. And now we’re looking at
clicks by keyword, but also broken up by match type. So again,
getting a little more advanced. And then adding in
that device filter, and now we’re looking at
computers specifically. So now we’re looking at exact
clicks by device, like on PC, phrase clicks on PC,
like on a keyword level. So once we do all that, so
how to actually create it, selecting the data? Well, make sure you select it. So select all the data because
you never know what you might wanna add into your pivot table. So that’s just kind of
a common best practice and there are some quick keyboard
shortcuts I’ll share with you in a second that’ll
actually kind of, basically teach you how
to do it much faster. Go to Navigate,
Insert>Pivot Table. This will prompt you to choose
a location for the new table. And so as a best practice here,
once you get that option to insert the pivot table
somewhere, just create it in a new spreadsheet or
on a new worksheet. Don’t create it in the actual
sheet that contains all the data, cuz that’s gonna
make things kinda messy. And then drag and
drop your fields into place. So you just physically move
them into the proper quadrant. So make sure device, you drag
and drop it over into filters. And do the same thing for the rest of those in the order
that we talked about. And so what that does is once
you’ve kinda got that all arranged, is it tells
you pretty specifically. So you’re looking at which
keywords get the most clicks, broken up by match
type on computers. And right now because of
this pivot table that we’ve manipulated, we can find out
that it’s this modified broad scrubs discount keyword that’s
getting the most clicks. Now, some of you might say
that’s fairly basic, right? So fine, fine, I hear you. So I’ll show you my very
favorite application for pivot tables which is
normalized quality score. So this came to me. I learned this a couple of years
ago from a really smart guy by the name of Brad Geddes. So if you don’t already
follow this guy on Twitter, he’s @bgtheory. He’s somewhat of a PVC genius,
good friend of ours. He’s an ad copy guru. So if you wanna know about, not
just Excel stuff but ad copy, he’s the guy to follow. And he taught me how to do this. So this is normalized
quality score. So what’s the big
deal about this? So the problem with the normal
pivot table is when you look at something like quality score,
is that it uses averages. And averages lie. So if you think about like, we have five key words
in this ad group. Well, if we think about the
average quality score of this, well, technically it’s got
an average quality score of 8.6. Now, I don’t know about you but
clearly there’s a problem here, right? I’m just highlighting it for
everybody to see. It’s that big 3. It’s just standing out,
it’s kinda like a sore thumb. And it’s especially problematic
if we have a situation like this, where that quality score
3 keyword is actually driving the majority of the impression
volume in this ad group. Now, if you’re just looking at
the average quality score of this ad group, like you’re not
gona be able to see that there’s this one outlier here dragging
the whole thing down. It’s kind of masked by
that average, right? So how do we actually
account for this? Well, I’ll show you how. So luckily, we can tweak pivot
tables to identify this issue in our account. So we just need to add some
columns to our data sheet, use a calculated field, and
then sort and filter the result. How you do that? Well, it goes a little
bit something like this. So if you wanna create
this yourselves, go to keyword report
from the Report center. Make sure it includes Spend,
Impressions and Quality Score. And then make the date range for
the last 30 days. Now, one thing, I’m gonna share some of my
favorite pro tips with you. So your Excel spreadsheet
was not carved in stone. You may download it. You may seem to think so,
but it’s not. So you’re more than welcome and
free to change it or add to it. Add some columns to it,
it’s okay. Which is exactly what
we’re gonna do here. So for
this particular spreadsheet, add a column to the end of it
and title it QS*Impressions. And so what you wanna do is for
each of your keywords, multiply your impressions by your
quality score in that column. And then pivot table it. And then just another
quick pro tip here. Ctrl+Shift and the arrow keys
makes selecting your pivot table data way easier. If you’re working with
a lot of rows and columns of data,
don’t drag and drop it. Just use the Ctrl+Shift and the arrow keys to select
just those populated cells. And it makes your
life much simpler. Now, put your ad groups
in the row field. So you create your pivot table
in a new spreadsheet Put your Ad Groups in the Row field. Put Average of Quality Score,
Sum of Impressions, and Sum of Spend in
the Values field. And it’s gonna look
something like this. Now, you use calculated fields
when you’re working with aggregate derived metrics
in a Pivot Table. Because again, if you try and
take something like average of Quality Score or sum of CPC for
your Ad Groups, it’s not gonna calculate correctly, or
especially not the averages. You wanna make sure you’re
creating at calculated field for these, so it’s calculating
that actual honest CPC. Otherwise it’s gonna take the
average CPC of all the elements inside that Ad Group. So make sure you use
a calculated field for that kind of stuff or when you wanna calculate
something very interesting. So I’d actually make use
of calculated fields. So when you’re in your Pivot
Table, you can find it under Fields, Items and Sets in the
Pivot Table tools Analyze tab. And so for
this calculated field, name it
Normalized Quality Score. And for that formula,
make it the Quality Score times Impressions column
divided by Impressions. So make sure
the quotations are there, that’s the important part. Make sure you’re selecting that
column, and not just trying to make it multiply your Quality
Score times Impressions here. That’s not what we’re
trying to measure. The reason this works is because
we’re looking at this at the Ad Group level,
not just the keyword level. So what we’re gonna do here
is that by weighting for these Impressions, we’re able to
quickly identify Ad Groups that have poor Quality Score keywords
driving all the traffic. So if you remember
this issue here, so this Ad Group had an average
Quality Score of 8.6. Well if we go through this map,
this extra map here, it actually shows us that if we
wait for impressions, it’s got a Quality Score of a 4.3,
a weighted Quality Score of 4.3. Which if you know your
Quality Scores, that’s bad. So, what it does here is you can
now analyze your Ad Groups by their true Quality Score, and quickly determine where you
should break out your keywords. So this is a really great way
to figure out where structural changes need to happen in your
account, because you have some keywords in it like a specific
Ad Group dragging things down. So, break those keywords out
into their own Ad Groups to try and improve the Quality Score. Now, another pivot table pro
tip, you can actually, and this is one not
many people know. You can actually sort and filter a Pivot Table by more
than just the row value. Now this might actually
be some kind of bug or just something not intended, because sometimes it
will break things. But you can actually
use sort and filter on the cell right next to
the top row in your Pivot Table to create filter buttons
next to every single or at the top of every single
row in your Pivot Table. So in this case, like you want to highlight that
cell, hit sort and filter. And then you can start sorting
and filtering by the actual values, and the sum of
Normalized Quality Score. And so, if you do this, you
could actually start looking for the following things,
which are the big red flags. So look for a Normalized
Quality Score of 4 or below, or even 5 or below. That’s when you know you
have really big issues. Sort descending by spend because
you can do that with that sort filter in place now. Even though, well again,
start to make your Pivot Table, get a little bit funky. Don’t do this too often,
but it definitely helps. And then look for a large difference between your
Average Quality Score and then your Normalized Quality Score,
because that’s when you know that’s where the biggest
structural issues are. So if you’re not at all
impressed by that or satisfied, well, I hope you are,
but if not, I will come back. And this is either a threat, or a promise, depending on how
much you like Pivot Tables. I’ll come back and talk another
hour about how to Pivot Table 100,000 lines of
Salesforce lead data, with monthly campaign
performance reports. So, sound good?>>Sounds awesome, Larry.>>All right. So that’s kind of Pivot Tabling. And again, so if you wanted to do something
with your ad copy performance heat map, you’ll create a Pivot
Table based off an ad report. So just create an extra
couple of lines like one for ad titles and one for
ad descriptions. And then manually enter in
the elements that you wanted to Pivot Table. And so then just use
a calculated field for CTR, and then layer conditional
formatting on top of it to create that heat map. Sounds fairly simpleish, right?>>It does.
>>Kind of, kind of?>>Hopefully.>>Hopefully, well,
the instructions are all there. So again, once you guys get
access [INAUDIBLE] presentation. It might come in two parts, but you should be able to reverse
engineer the process from that.>>Yeah, in the next couple
of days, this deck will be available in a couple parts for
download at the same URL that you use to register and
log in for today’s presentation. It was way too big. I didn’t realize that until
a few minutes before we started. Unfortunately, I apologize for
that. But it will be available. Everybody was asking for
it, so thanks very much.>>All right, so let’s jump
on to, cuz we have, again, we’ve got a lot of ground to
cover, so let’s talk about how to turbocharge the Bing
Ads Interface with Excel. We have a lot of really cool
tools that none of people know about especially ones that are
fairly unique to our platform. So the first one that
I wanna talk about is the Campaign Planner. So if you wanna go find
the campaign planner, so we have it in
the resources list, but it’s also at just planner. And the reason we like this so
much, the reason we think it’s really
cool is that this is a way for you to plan campaigns
with better insights. This is really
a great way to plan overall campaign strategy at
an industry or a vertical level. Cuz you can monitor
marketplace changes, traffic trends across
your industry. And then also discover new
campaign, ad group, and keyword ideas. But the big reason that we’re so
excited about it, I mean, yeah, you get performance and
traffic data and vertical and product insights. But the thing that really sets
us apart here is we give you competitive insights by
keyword and industry. So if you wanna look at specific
keywords you’re not even advertising for yet, we give you competitive
insights about the domains, the types of advertisers you’re
gonna be going up against. So if you want to look at
something like running shoes or video game consoles,
you’ll see you’ll be going up against and, and also start to get an idea
of their ad coverage. Like how often are they
showing for this term? What’s their position coverage? Where are they at on the page? Average position,
sidebar, mainline? We give you all those insights. And then you can also pin and
favorite these terms for later use. You can also see these trends
by keyword and over time. So you get keyword,
vertical trends, and performance data by
looking at this Summary tab. So you’re gonna have to
look at it per month, or also year over year. And then, again, you can see these competitive
marketplaces before you even start advertising by using
the Competition tab. So as an example here, we just
have this MacBook Air term. So this is usually
a video that we show, but we’re just gonna paint
a picture for you. So we saw a really cool
use case here, where looking at this MacBook Air term
like we saw all the trends. So we saw a spike,
it’s actually going. So we’re gonna look at it,
look at the trends here. And so for this MacBook Air
term, we’re looking at basically what’s the traffic
like over the course of a year. And so, no surprise here, it really spikes going
into those winter months. So that’s like Black Friday,
Christmas, Thanksgiving shopping. And so we can also really
see when it happens, but also on which devices. So we have this device
break down, and so we can see that this spike is
really happening on desktops. And then we can also take a look
at just device performance in aggregate too. Because maybe, this is
a really good way to help you pitch a mobile strategy. We need more time than this,
so I’m gonna kind of move on. But the big thing that we’re
gonna see here is that when we go to this Competition tab, you’ll see that
we’re advertising. Let’s say, for the sake of
argument, don’t tell anybody, MJ, that I’m Apple. And I’m seeing that
on the Results page, this Microsoft Surface Pro 3 or Pro 4 ad is showing up
above us on our core term. This might be a problem, right? Especially, if I’m Apple’s SCM
manager, maybe my boss sees this and they start blowing up my
phone asking, what’s going on? Are you actually doing your job? Well this report can
help you circumvent that. It can help you say okay,
yes, this is happening, but it’s only happening
maybe one in five searches, because Microsoft’s ad
coverage is only about 20%. Their top of page rate is
only about 8% of the time, so this happened to be the once in
a lifetime showing on the surf, that caused this
to be a problem. And you can export all of this
to Excel at any time, too. So you’re not just limited
to looking at the UI. But we also have some
more insights here. So we can look at
the Seahawks’ jerseys term. So once it actually
advances here. We also get location
insights too. So I used to sit in front of a
guy who’s name was Tony Austin, a really good friend. Also a rabid Seahawks fan and, I
had a working theory that maybe Seahawks fans were somewhat
newer to football fandom. Like maybe they were kind of
more of a bandwagon fandom. And I kept on giving a hard
hard time about this, they say they call themselves
the 12th man because none of them were fans until 2012.>>[LAUGH]
>>That’s how we stepped over the line a little bit but, that
was kind of the breaking point. Like, okay,
you can’t prove this. And I was like,
can’t I Tony, can’t I? And so using this tool, you can
see that there was a pretty significant spike,
in Seahawks Jersey traffic. In Washington, when they went to the Superbowl
it is in January 2015. But this just used for winning
dumb office place arguments. You can also use this for
campaign planning. So you can use this for
budget forecasting. Because we give you
the impression volume month over month, and with a little Excel
know-how, you can actually plot this out and figure out what
those numbers actually mean. So, this is what it looks like
when you hover over each one of those data points, and record
the impression volume, and then put this in Excel. And with a little bit of
conditional formatting, you can then figure out how does
this compare to the average traffic volume in this industry? This is where education and
training, and what we found was, is that numbers wise, there was
actually about a 40% dip in the summer months and a 20%
rebound in the fall months. How this can help you, is that this can actually
influence a budget discussion. So if you’re planning
out your monthly budget, like month by month by month,
and the person who’s making the decision has that
expectation that you’re gonna be able to spend as much in the
summer months that you were in the early winter months,
then they might be disappointed. So you can kind of get ahead
of that conversation by saying look, traffic volume is
gonna dip by about 40%, so we should probably account for
that. And then you can also take the
same tactic with overall budget increases year over year, because we provide you with
those year over year numbers. And so the mean traffic volume, like on a monthly basis is about
20% higher year over year. So you can also translate that
to say, okay maybe your budget should also increase if we want
to capture all that traffic. So that’s one
particular use case. So this is all
conditional formatting, but there’s another tool that
I’m also a big fan of, and it’s auction insights. So auction insights, we used to have this in
Bing ads intelligence, but it’s not there anymore, but you can still find it
in the user interface. We actually just released this,
so we released a Bing ad academy cheat sheet about this,
it’s all at YouTube channel now. So I just tweeted about it, so you can probably just
find it to my history or I’ll retweet it
after this Webinar, because we talked
about this there too. And so this helps you
get some actual insights about your competition. So you get comparisons to other
advertisers on the auctions in which you took part, you can also monitor
the competition over time, so auction insights is not a static
snapshot of your account. It changes with what ever
date range you’re looking at. And you can discover
opportunities and also issues, by looking at 5 key metrics. So the key metrics you’ll
look at are impression share, average position and overlap
rate, those are the first three. Overlap rate is actually
a really good one to focus on, because this is how often did
you compete against other advertisers. So if you see specific
changes in this overlap rate, this is how you know
somebody is gunning for you specifically, especially
if it’s on a brand turn. If you see a really big spike
in your overlap rate on a brand turn, you know somebody
is gunning for you. It’s also kind of a backdoor
insight into budget strategy, or keyword strategy. Because if you’re seeing
an increase in overlap rate, it means they’ve either
specifically added this keyword and it’s no longer just
matching in a broad sense or phrase match sense like they’re
targeting this specifically. Or they’ve increased the budget
in which that keyword, to the campaign in which
that keyword was located. We can also have position above
rate, which is how often did other advertisers show up above
you and then top of page rate. Now, position above rate is also
kind of backdoor insight into their bid strategy
relative to yours. Because you’re seeing an
increase of position above rate, you know, in some
advertiser relative to you, that means they really increase
their bids on that term too. So if you’re seeing an increase
in position above rate, and then also,
overlap rate on a brand term, that means they’re gunning for
you specifically. So let’s talk about
a theoretical use case here, an actual use case to
troubleshoot this. So let’s troubleshoot this
account versus our competitors. So this is for
a real life example here for a very popular diet keyword for
an advertiser. They were dominating
on this term, running pretty much unopposed
for the first half of January. Go figure, diet terms,
very popular in the new year. Not a big surprise there. But we saw some performance
issues pop up with this guy. Like their average CPC
started like it spiked, their CPA spiked too. And looking at the change
history, there was nothing that this advertiser did
to account for that. But if we look at their
Auction Insights report, we might find some more. So this is like the before and
after snapshot. So before, this advertiser was
pretty much running unopposed. So normally there is
an animation there, but I will give you the cliff
notes version of it. They have an average
position of 1.5. And the closest Overlap
rate was about 46% and the Position above rate,
the closest one, was about 38%. Now that’s about to change. So this is the after snapshot. So they had 5 new competitors
enter this space and then the Overlap rate End up
increasing from 4 to 6%, to 70%. And then position above rate
went from 38% to 81 and 91%. Meaning that they’re no longer
running unopposed here, and that’s what accounts for the big difference in
their performance here. Now, because this is
an Excel webinar, I’m gonna tie back in to
Auction Excel Insights here. So you can run a pivot table. Like downloading auction
insights reports over time like for the monthly segment in place
from some other platforms. Or just look at it from a month,
by month, by month in Bing ads and
download that report and then pivot table it and
you can actually see how your competitive landscape
changes over time. So what we’re looking at
here is a pivot table of overlap rate over about a siz
month span and we’re seeing how seasonality influences our
advertisers campaign strategy. And so this is for
a bridal keyword, like there is a wedding
dress keyword. And so
we’re seeing of their in gray. I’m not sure if I can
say their name out loud, I can’t say it out loud but
they were a big bridal retailer. And we so that as they actually
did the wedding season which is allegedly like peaks in July and
tapers off after that, well, I guess, right? It was tapering off and we’re seeing a drastic decrease
on their overlap rates because they’re no
longer spending as much. Make sense?>>Makes sense.>>All right, well we also have
some other things to go through. So you can also go through
position above rate which is, again, kind of analysis
of their bid strategy. Seeing how competitors’ bids
change relative to yours. And in this case,
that orange line may or may not belong to a giant
Seattle based e-commerce retailer who really decreased
their bids going into December. And so this is some things
you can do with it. Again, this came from
a pivot table, and this is just data that you can
get from the Bing Ads interface. But let’s really nerd out here. So we talked about like all
these other interface stuff, so let’s really get to the nuts and
bolts of Excel. Let’s talk about
how you can use and combine some formulas
like a mad scientist. Sounds good?>>Sounds great.>>All right, so we already know Excel is
an incredibly versatile tool and almost every formula can have
unique PPC applications. So I’m going to run through
some of my favorites here and then maybe throw some
curveballs at you too. So we have IF, which is for
making conditional if/then statements like if my
conversions are greater than 1, then increase my bid by 10%. [INAUDIBLE] Make it 15%, and that’s kinda what it would
look like in practice, it’s just a really
basic bid formula. But you can also make use of
nested if/then statements for more power. Like if my conversions are
greater than 1, and it’s below position 3, and it’s exact, then
do all that stuff I just said. And this is kind of what that
formula would look like. Again, so you can also see this on the
demo sheet if you download that. Now, I’m gonna throw
a curveball at you, because we have
some new formulas. We just released a couple of new
formulas that have some actually pretty relevant PPC applications
in the latest release of Excel 2016. And so one of those is ifs. So, if you’re not comfortable
with multiple if statements in a row, use this formula. So, if you wanna increase
your bids by 10% for multiple conversions, but only
5% for poor average position. So this is what that looks like. And so this is really great
if you’re not wanting to make multiple ifs like in a row. Because sometimes there’s some
logic to it that isn’t intuitive to some people. So this can be a really great
way to make use of those nested formulas without having to
actually know how to do it. Now the weakness here is
that this is only for true statements. With the regular IF formula,
you can make a value for if it’s true or if it’s false. You can’t do that here,
it’s only it it’s true, so you’re not gonna be able to make
super complicated ones the way you could with a really
complex if then statement. But it is a way to make
something a little bit more advanced. And that’s brand spanking new,
so if you have Excel 2016, give that a shot. Cuz there are some variants on
that too, there’s like max ifs min ifs, so you can kind
play around with them. But we’re not done yet,
so we also have LEN. I’m pretty sure I couldn’t
do this job without LEN, or really post to Twitter for
that matter. Because it’s for counting the number of
characters used in a cell. Which is really useful for
things like ad copy. When you’re working with
a limited number of characters. And so the nice thing about
LEN is that it also works with formulas. So if you’re concatenating
something together, I could actually count the results
of the concatenate, not just the number of characters used
in that concatenate formula. So it behaves,
how you’d expect it to. So I definitely
recommend you use this, if you haven’t already. But I also have a few others,
so Correll or Pearson. So this is really useful for
analyzing the positive or negative correlation
in the dataset. So you can use this to determine
how fluctuating campaign spend is impacting your
overall business. Like, take a look at the impact,
like the correlation of non-branded spend
on brand spend, or non-branded impression volume
and brand conversions. Try and fit some of these
metrics against one another using correlate to figure
out how they’re related. We also have standard deviation,
which provides the standard deviation, or variance,
in a dataset. This is also found in pivot
tables, which can be really useful in comparing your
bids versus the competition. So if you really wanna have
your mind blown at some point, run an hour of day
report on your keywords. And take a look at the
difference between your average CPC, and your max CPC. And then also, look at
the standard deviation there. Because I guarantee you, the
larger the standard deviation, the bigger the gulf is
between your max CPC and your average CPC. And in that difference is where
your advertisers are bidding you up and
down over the course of the day. It’s where your bids
are a little bit more unstable. Now, we also have LINEST, which
calculates the statistics for a line by using
the least squares method. So you can use this to project
future performance based on past metrics. I’ll show you an example
of this a little bit later. We also have=CONCATENATE,
which is for combining the contents of
one cell with another. Like we’re using this for
our ad copy, creating some Bing friendly
ads from an AdWords ad, right? There are two
description lines there, we’re combining them together
to create one Bing ad. It also can combine the contents
of any cell with the text string contained in quotation marks. So if you wanna create some
modified broad match keywords, You would concatenate
that together. We’re just concatenating a plus
symbol to the beginning of the cell we’re targeting. Now we have another new
formula here which is probably gonna blow your
minds a little bit. Again, Excel 2016 or later. It’s the formula TEXTJOIN, which is a more powerful
form of CONCATENATE. And so why is this so cool? It allows you to
automatically add delimiters. It also ignores empty cells and you can join arrays
of cells together. So if we have that same
example from before, but we have an empty cell
in the middle and then we also have this
delimiter in place. So we’re using TEXTJOIN, we’ll
say ignore this empty cell, put a period or put a space
in between the cells I’m concatenating and also do this
across an entire array of cells. So if you have multiple cells to
join, you can use TEXTJOIN to do it way faster than CONCATENATE
and in a much simpler formula. So give that one a shot. Now we also have one
more to talk about, well a couple more to go through
but SUBSTITUTE is useful for substituting one character for
another. Which again is kind
of also useful for creating modified
broad match keywords. So if you remember that
concatenate formula I showed you, this is the other
half of that. So if you look at SUBSTITUTE,
now we’re just substituting any instance of space with space
plus to finish off the formula. But while each formula is useful
on its own, if you combine them in nested formulas,
you can achieve more faster. So in this previous example, you
can combine, concatenate, and substitute to create modified
broad match keywords in one formula. Or you can also combine IF,
CONCATENATE and SUBSTITUTE to say if this is my
modified broad match ad group then do the concatenate and
substitute. So you can get really in depth
the kind of stuff you’re targeting. Now, let’s go through
a theoretical problem here. Let’s say you need to generate
about 350,000 keyword-level destination URLs. And let’s say that they have
unique locations, ad groups and project identifiers. Do you think you could
do that manually, or would you even
really want to MJ?>>No not at all.>>Not at all.>>I have too many other
things that I’d like to do.>>Exactly, so the solution
here is something like VLOOKUP. So VLOOKUP is one of
my favourite formulas, it stands for vertical lookup. If you need to cross
reference a lot of data, this is really how you do it. Or you can also use
index match two. But this is probably
a controversial opinion to voice in an Excel webinar, but INDEX
MATCH has always kind of struck me as the hipster
version of VLOOKUP, in that it’s like vinyl. It’s just as good,
or it sounds better, it’s just way more complicated. Like not many people
know about it. That’s probably
a harsh version of it. It’s actually like a little
bit more flexible and it’s not quite as taxing
on your Excel spreadsheets. But for most people, VLOOKUP is
gonna get you what you need. But if you know how
to use INDEX MATCH, I’m not trying to throw shade
at INDEX MATCH, great function, we’re not gonna
go into it today. Now this is the VLOOKUP formula. So it looks a little
bit intimidating, so I’m just gonna break it down for
the newbies in the group. So LOOKUP_VALUE is what
you’re trying to look up. The TABLE_ARRAY is the array
of cells you’re targeting for this search. So it contains what you’re
trying to look up as well as any corresponding values you
might wanna pull in. The column index number is the
specific column you wanna pulled in on this search, and then
RANGE_LOOKUP, you just ignore. And so some small reminders
here is CONCATENATE or TEXTJOIN combines cells. So if you want to combine
multiple cells, and here’s a hint, cells that you might
have populated with VLOOKUP, cuz remember, we have this overall
problem we wanna solve for. Well, this is how you do it. And then that’s
the CONCATENATE formula, so it can refer to a cell or
strings of text. So it’s easy enough, right? So it’s a quick walk-through of
just how you might use VLOOKUP in a real use case to solve
that one problem of mine So we have six ad groups,
six keywords, with a need for six different destination URLs. And so, first off you’ll want to
prepare a master list of URLs to cross-reference with
your adverts, right. Then you can also pull those in,
so cross-reference it with that first spreadsheet to get
the URLs into our new sheet. Then do you observe yourself
with the substitute format to prepare our campaign and
keyword columns for use with our tracking tags,
and then also concatenate all of that together in order
to create six destination URL’s, but wait, hold on, hold on,
hold the phone here. I thought that just
said combining, so do you not want to take five
steps to accomplish one task? Well in that case, don’t. Just do it in one formula, because everything
I’ve just talked about, can all be done in
one single formula, to concatenate these
formulas together, doing this entire process in
one step rather than five. So we’re concatenating a VLOOKUP
with text, with substitute, and all that in just one formula,
to do this in one single step. And so, and
it sounds super complicated, and it’s anybody in the history
of planet earth or PPC ever actually used
something like this. Well yeah, actually. Like I use this. Back in my agency days,
by the way, that says 18,388. So we were generating a unique
keyword level destination URLs for an automatically generated
report from a tool provider. So it was for a Canadian client. So if you do the math there we
had to do it for 8 provinces and 11 cities. So you multiply like 18,000
keywords each of those modifiers equals 350,000 unique
keyword URLs generated in about a half hour, and
if I’m being honest, most of that was spent waiting
for the formula to compute, and also brushing the smoke away
from my poor laptop at the time, because it’s really struggling
with that amount of data. But all of that was just done
through VLOOKUP, SUBSTITUTE, and CONCATENATE. Now, I’ve one more question for
you. So MJ, is there a way to use
Excel to intelligently determine how to best spend our
advertising budgets and can you do it across
multiple accounts?>>Believe it or not, yes.>>Yes?
>>I’ve seen you do it.>>Yeah, she’s seen me do it. So, yeah, she saw me do that.>>And it’s a magical
moment when you see it for the first time. [LAUGH]
>>Exactly. So you actually can do this. Just not with regular Excel. So, I do this with a plug-in
called Excel Solver. So Excel Solver, it’s a plug-in. It solves things. The last little sarcastic thing
I’m going to throw in here is, the real answer to this is,
that it solves equations that you give it according to
parameters that you set. Equations like what is my most
efficient budget allocation to maximize conversion volumes. I found this is really useful,
especially for you agency guys out there. If you’re working with
a lot of accounts, across a lot of
different platforms. I know how working in those
things can go on a day to day basis. You’re making budget tweaks, like spending on some
display campaigns. Because you have
to make budget for the month and once you are no
longer in that position like you forgot about that. You didn’t forget to tweak it. So you’re still spending
that same amount on those less efficient campaigns. This is a judgement free zone,
so I’m not calling you out for
it but that’s just life. So I mean especially for you guys out there who work
with a lot of accounts, this might be able
to help you out. And so how can you do it? Well, so how do you find it? Well first things first,
it’s not included by default but you can find it by going to
your Excel options menu and then going to add-ins. So you find it right here. And so once you have it enabled,
it’s actually in the data tab found right there in
the data ribbon in Excel. Once you have it enabled you can
do super cool stuff like this. The genesis of this idea started
with a good buddy of mine. His name is Samo and
he works at Netflix now. On twitter he’s @samonppc. Super smart guy, he first
showed me the thing, and then I figured out you could do
this across multiple accounts. And so what we have here
is a mix of Bing and Google campaigns.>>And we found the average daily spend
across all these campaigns and then calculated the optimal
budget as found by Excel Solver. Cuz we’re not just asking
how much can I spend, but how much can I spend given the
fact that I still need to worry about conversion volume? Cost per conversion. Makes sense, right? So how do we actually do that? So again, if you download
the Excel demo sheet. All of these instructions
are in there. So you can do this in
your own accounts. But for the very, very short version of how
to do this, basically, you download a campaign report
from the report center. Make the date ranged
the last 30 days, and make sure to include
the following columns. Average CPC, cost, conversions,
and conversion rate. And then also, make sure to include impression
share lost to budget. And this is just kinda what
that report looks like. You can also include the same
metrics from other accounts for this cross account optimization. Just make sure you include your
impression share lost to budget metrics all in the same column. So if you wanna try this with
your AdWords data, download that same report from AdWords and
include it’s lost IS parentheses budget, and there’s probably
some percentage in there too. And then you can also
do the same thing for your AdWords display campaign,
and just use the column display lost
impression share to budget. And make sure all of those
columns are in the same spot. Make sense so far, kind of? Well again, the instructions
are on that demo sheet. So what I wanna do here, is find
our average daily spend for each campaign. And so again, remember the date
range you looked at here. So we looked at last 30 days, so our formula is gonna be
cost divided by 30 days. And then we find the maximum
possible daily spend for each campaign. And so that’s when we pull
in the lost impression share numbers. So that formula is your average
daily spend that you just made, divided by one, minus your
lost impression share. So that’s gonna tell us, not just what we spend on
average but what we could’ve spent on average given our lost
impression shares numbers. So again,
we’re just kind of figuring out how much we could have
theoretically spent. Now, we sell several campaigns
here that are limited by budget. But I know like one of the
biggest pain points I always had when I worked in an agency is
get like reports, especially my ad works account rep and they’d
send me something like, hey, these accounts are limited by
budget and they always tell me. No duh. So the question here is we know
we can grow our budget here but is it a good idea to do it. So this is where excel
solver comes in. So we add in three columns. Solve budget, solve clicks,
and solve conversions. And so what goes in each of
those, well I’ll tell you. So Solved Budget is left
entirely to solve for itself, so we leave it blank. Solve Clicks is where we
take our average CPC and what our Solved Budget will be. And basically kind of reverse
engineer what our new click total would be. And you’re probably seeing
where this is going. The solved conversions column
takes our conversion rate, multiplies it by that
solved clicks amount, and figures out what our new
conversion volume would be. And then, we use Solver to
the highlight a cell in there. So again,
follow the instructions and you’ll kind of figure
out what to do there. Basically what we’re asking
Solver to do you say, give me as many conversions as possible,
we’re highlighting one cell to say make this as
large as you can. Then telling solver to do this
by changing your budget, so you’re highlighting
the solved budget column. And then, you would say,
make sure my campaign can actually spend that,
by putting in some constraints, by saying this can’t exceed
my maximum possible spent. We’re putting in some
constraints on it. Cuz otherwise it’s just
gonna funnel all you spend towards some brand campaigns. Even though that brand campaign
might not be able to actually spend it. So what it’ll do
is it’ll actually give you some stuff to do. So the highlighted
campaigns on this screen, they’re actually getting paused. Because from an efficiency
standpoint we’re losing money. Based on my budget constraints I should not be
spending money here. There are better places to spend
that money because I am looking for as many conversions
as possible. So, the highlighted campaigns
are getting paused and then it is also providing us some
opportunities to boost budget. So reallocate that
spend somewhere else. It might be a brand campaign. In Bing ads. It might be like a generic
campaign in ad words. Just giving you a more
intelligent way to spend this money. And so the one thing here is
that you’re not limited to calculating your
existing budget either. So using both solver in Linest, you can chart out the potential
gains from increased spend and even see the point of
diminishing returns. Because the directions will
show you how to do this, but you can tweak the values in one
of the constraint fields to play around with values, and
see the incremental conversion games as you go,
like spending in this account. And so that’s an array
that it gives you. So I tweak it to say,
I’m spending 3,000 a month, 9,000 a month, at 18,000 and
even beyond that. And it’s giving me a conversion
volume for all of that. And using Linest to
target that array, it gives me basically the line
or like the equation for what I could be
spending going forward. But the upshot here is that just
by reallocating our budget and doing nothing else. No bids, no budget, no bids,
no keyword additions. I can get 1.2 more conversions
per day which was 36 more conversions a month,
which for this advertiser was a 17.6% increase with no
change except budgets which, I don’t know about you I’ll
take that any day, right?>>I would.>>All right.
>>I’m sure everyone on the call would too.>>So you excel, therefore you
rock because today you learned about how conditional formatting
can make your data easy to read. Also, learn how you use pivot
tables to get insights you can’t find any other way. Insights like normalized
quality score or and an ad copy performance hit map. And you also learn how
to use features like the Campaign Planner and
Auction Insights with Excel. You also learn how to use
some formulas like V-lookup, Text Join and
ifs to get things done. And learned about plug
ins like X-Solver to just do things a little
bit more intelligently, spend your budget
more intelligently.>>Fantastic, Eric.>>Whoo!
>>That was a whole lot of information.>>It was, it was a marathon. This’ll be recorded, so you can
come back to this at any time.>>Absolutely, I definitely wanna thank
everyone who joined us today. I apologize if we did not get a
chance to answer your question. But we will follow up with
a blog post on any unanswered questions. There are some great questions
that we do want to answer. So we will be sending out
an email to everyone who joins with the replay link. Please if you could,
take a little bit of time and give us your feedback
on this webinar. We would love to improve
hearing your feedback, please also if you’d like you
can tweet hashtag AskBingAds. Also if you want your question
answered that way as well, Eric is happy to get your
tweets @ecouch11, and you see my handle as well there. So thank you, everyone,
look forward to having you on our next webcast, and
until then, talk to you soon.>>Thanks guys.


  • Reply Kirti Sinha April 19, 2016 at 10:28 am

    The transcript of this webinar is available here:

  • Reply Sagbee C September 17, 2019 at 4:32 pm

    Where i can download the spreadaheet?

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