My name's Pete Frisella.

I'm a developer advocate on the Google Analytics team.

I'd like to introduce you to a new series we have called "Off

the Charts." This series is about getting into the deep

features of Google Analytics, understanding how it works,

things you can do with it, and how to use the feature itself.

So today, I'd like actually talk to you about getting

started with cost data upload, and this is all about

measuring non-Google paid campaigns.

So let's talk about what is cost data upload.

I'll kind of get into little bit more about what that means

and what cost data upload works, how it works and the

feature itself.

Then we'll go into the architectural overview, which

explains the deep details and also how you would actually go

about uploading data to Google Analytics.

And then finally, we'll talk a little bit about some

opportunities that are available from a developer

perspective and also from a business perspective.

So with that, we'll get started.

So what is cost data upload, and what does

cost data itself mean?

So this is all related to all the paid campaigns you may be

running out there, all the information that's related to

that paid campaign.

Whether it be ad costs, clicks, impressions, the name

of the campaign, all this itself relates to cost data.

It's what we refer to as cost data in Google Analytics.

So for example, if you are running a campaign, say with

Google AdWords, for example, you'll know this is pretty

familiar for you.

You've got cost data, and if you link that to Google

Analytics, which is what you should be doing, you actually

get these reports within Google Analytics that

highlight, for your paid campaigns, how they're

performing.

And they give you a lot more information around how to

optimize certain key words, maybe landing page

optimization.

Now, these things are important things, but to

really do this analysis, you need that cost data associated

with the campaigns that you're running in Google AdWords.

And this linking works really well today, and it takes care

of all that for you.

And it gives you some powerful tools to take care of analysis

around campaigns and user interaction, and how campaigns

are performing.

The thing is, though, for a lot of people, why we

encourage you to use Google AdWords, we love Google

AdWords, obviously.

There is other paid campaign services out there that people

obviously use, and that includes things like other

paid search services.

You might be running in a campaign on a social network.

You might be doing email marketing campaigns.

So all of these campaigns are running out there, and you're

getting users visiting your website or your property from

these paid campaigns, and that's great.

You're able to track what they're doing, the conversions

possibly that are taking place, goal completions.

And you're getting a good general sense of which paid

campaigns are driving traffic to your site.

This is great.

So a report like this, that I'm showing here right now, is

kind of common that you're looking at, for my particular

campaigns, how are they performing and what kind of

traffic is coming to my site because these campaigns?

Now, you see that first row there, row number one, is a

Google AdWords campaign.

And you'll notice while you have user interaction data

such as visits, and you have impressions and clicks cost

data, you don't get the same kind of visual in cost data

that you would have for AdWords.

You don't get the same data for the other paid campaigns

that you may have.

So for example, we have an AdWords network campaign

running, and we have an affiliate

network campaign running.

And you'll see, we know people are coming to the site, but we

don't have the cost data within GA to do that analysis.

There's kind of two things missing around this then.

For the particular paid campaign itself, being able to

analyze that in terms of the ROI and the metrics you might

be getting.

Click-through rate, cost per click, things like that, you

kind of miss out on that.

And then also, you don't really have the ability to

compare how these services are performing against each other.

So is the AdWords network driving more?

Better conversions, or is Google AdWords driving better

conversions?

So you're missing that kind of complete view, that complete

analysis, around your cost data across all your different

paid campaigns that you might be having for all online

advertising and digital marketing.

But cost data kind of solves that problem.

When we launched this feature about a month ago, we had some

success stories right off the bat with a couple customers,

working with partners of ours to get something in place and

a solution for them.

So, for example, we talked Next Analytics and Cardinal

Path, and they came up with a solution that

uses cost data upload.

And they worked with Natural Wellbeing.

And really, it was around fully automating this process

for them, so being able to take their cost data

automatically, export it, and upload it into Google

Analytics using this new feature.

And it worked really well for them in saving them a lot of

time and doing this full automation.

We also did the same thing with ShufflePoint and E-Nor.

They came up with a solution using cost data upload again

to help OEMPCWorld.

And this one was really about, again, fully automation.

And a lot of the analysis they were doing was kind of a

manual process where you had your Google AdWords data, you

had some other campaigns.

You had to manually bring that stuff together and do analysis

outside of GA.

So this new feature really allowed them to bring all that

into Google Analytics and to do that complete analysis

within the product itself.

So it saved them a lot of time, fully automated, a great

solution for them.

So I think it would be good just to start off with a quick

demo to show you how this actually works.

And then we're going to dive into details, and I can give

you a little bit more background on how these actual

steps that involved to do this.

Sometimes, it's just easier to show you how it works, so I'll

start off with a report.

This is within Google Analytics.

It's a custom report, and the example here is that I have a

paid search ad running, and it's for an ad network.

It's a CPC, and it's for the keyword

"dogbone." And I can see--

so I've tagged my URLs, and I'll get into that

a little bit later.

So I know that someone's clicked on the URL, and

they've visited my property, and I can see that there's

been two visits.

But just as how I described before, we don't have

any cost data here.

But the thing is, I actually do have the cost data.

The service provider that I'm using allows me to

export the cost data.

I just don't have it in GA, so that's really

what I want to do.

I want to have that same data available in GA so I can do

analysis and can carry out cost analysis.

So just something to note here, the source is Ad

Network, the medium is CPC, and the keyword is "dogbone."

So as I mentioned, I actually do have this cost data.

So you can imagine that I exported this from the paid

search provider and have it in CSV file.

And there's a header up here that has some dimensions that

I'll explain later.

But in row two, we can see the same values that I just showed

you in report are actually here.

We have Ad Network as a source, CPC is our medium, and

we have this keyword here, "dogbone."

And there's that cost data I was talking about.

We have impressions, we have clicks, and we have ad cost,

so I have this data.

It's there.

It's available, and there was a couple other

keywords that I ran also.

Now, let's actually upload it and see how this process

works, and then we'll see--

once it's available in the report, you'll see how it's

actually joined together.

So I have a little script.

It's a Python script, just to kind of test things and see

how it's working, how the feature works.

I'll start off with--

there's this new entity called custom data source.

I can also explain what this means in a little bit, but

basically, you upload the cost data to a custom data source,

and you specify which date you'd like to upload

the cost data for.

So, in this example, this cost data actually is from

yesterday, so I exported all of the cost data and metrics

from yesterday into a CSV file, and it's

available to upload.

So I'm going to select the custom data source that I want

to upload to.

And I'll show you how this process works.

So I have quite a few accounts here.

I want to upload to the My Store account.

I will select the web property, and then here's what

I'm talking about in terms of custom data sources.

I have three set up, and I'm just going to choose the first

one, the Ad Network custom data source.

So now I've selected it.

If I go back up, you'll see now that it's actually

selected, here, Ad Network, and then also the account and

the web property.

And then the upload data again is 2012, November 28.

So I will do an upload of cost data, which is

number three here.

I know the file that I showed you, what the name of it is.

Oops.

Spelled that wrong.

OK, so it's actually uploading right now to Google Analytics

to that customer data source, and if all goes successful,

we'll get a response back from the server

saying it was a success.

So it takes a little bit of time to process the data.

It's not going to show up instantly.

I will go back to the presentation.

It could take anywhere from a few minutes to up to 12 hours,

so you should see data within 12 hours.

Depending on the kind of load and your profile and web

property, it could take a little longer.

I'm going to actually go back to the presentation.

We've successfully uploaded cost data.

I'll come back a little bit later, and we'll see if it's

available in the report and if it's been joined

to our actual campaign.

In the meantime, let's talk about architectural overview,

how this feature works, and how you would actually go

about uploading cost data.

So there's quite a few steps involved, but they're all

pretty simple.

The first four are really around how to prepare for a

successful upload.

And the fifth is really around reporting and how you would do

analysis, the tools that are available for that within GA.

We'll start with tagging campaign URLS.

So obviously, the primary benefit to this feature is

that you're able to join that user interaction data that's

already in GA that you have, and you're able to join that

with the cost data that might sit somewhere externally.

So bringing those two together is really a huge benefit here.

But in order to do that, it's important that you use

campaign tracking parameters, so you should

be doing this anyways.