Getting the Most out of App Analytics

Session 303 WWDC 2015

App Analytics is the powerful new tool inside iTunes Connect. Get a walk through of the metrics related to user engagement, marketing campaigns, monetization and more. Gain valuable insights from data that only Apple provides, so you can build better iOS apps and a more informed app business.

TRYSTAN KOSMYNKA: Thank you.

Thank you.

My name is Trystan Kosmynka.

I'm in iTunes Engineering.

Myself and my colleague David Hopkins are excited today to help you get the most out of App Analytics.

App Analytics today is publicly available for all developers with a valid developer account.

Sales admin or finance role inside iTunes Connect.

There are no restrictions to your use of App Analytics.

It's available to all developers.

Because there are no restrictions and it's publicly available, we are excited to tell you that as of today it is no longer in beta.

[Applause]

Thanks. So why does this matter?

Why do we care about App Analytics?

Why is Apple excited to bring this product to you?

We care because App Analytics provides answers.

There are a lot of big questions that you have as app developers or marketers.

Are customers finding your app?

Are they installing the app?

Are they purchasing goods inside of your application, and are they returning?

Our goal with App Analytics is that we can provide some of these insights so you can make great decisions going forward.

Through these answers, we also reveal missed opportunities.

A good example of this is if your application is available across all storefronts but you have not yet localized in a particular country, with App Analytics what you can see is you can see that you have really high App Store page views in a particular country but the conversion rate isn't so good.

If you maybe localize your store presence to that language, you make it more accessible to more customers.

This is the type of data that we deliver with App Analytics.

With all of these, our ultimate goal is to help you build a better app.

You are here to learn tips and tricks from experts so you can build a better app.

That's on the development cycle.

We want you to know that your responsibilities do not stop after launch.

There is a whole new set of things to focus on, marketing your app, advertising your app, adding more content, new versions, maybe there's price changes.

Your Store presence is important as well.

All of that goes back into your product development life cycle, and it's really important to creating a successful app in a successful app business.

We do all of these things with Analytics data.

Analytics has three key data sources.

We have App Store data, sales data, and usage data.

These three data sources are combined to tell a single story across acquisition to engagement.

We answer those key questions with this.

Are customers finding your app, are they purchasing it, and are they using it and returning?

To understand these measures better, let's take Trip Guider 2.0.

We updated this this year for WWDC.

Don't download it.

It is not real.

Here we are seeing our App Store views.

What App Store views are is a potential customer visits your product page in the App Store.

That triggers an App Store view.

This is an example of our Store measure.

Next ,we have app units and app sales.

This is an example of our sales measures.

In this example, I have $2.99 for Trip Guider.

That's going to generate $2.99 of sales.

This is what the customer spent on your app.

App units registers the transaction, a single app unit would be present in this case.

Let's move along to the usage measures.

We have installations.

Installations is different than app units.

This is a common question we get: What is the difference between these two?

If I was to purchase Trip Guider for $2.99, that's one app unit, but it may generate multiple installs.

It's one to many.

I could have purchased it and installed it on my iPhone and my iPad.

That generates two installations.

Additional usage measures that we have available: sessions, active devices, and active devices in the last 30 days.

What is important with these is that it is again one to many.

I may have opened this app, Trip Guider, and visited Pigeon Point in the morning.

That's one session.

I came home and shared the experience with family and friends.

That's two sessions.

But all of this was from my iPhone, and that's one active device.

So sessions is an overall idea of engagement, and active devices is, how large is your device base?

Active devices in the last 30 days is the same as active devices; however, the time period is longer.

I'm not using Trip Guider every single day.

But if I used it in the last 30 days, I register a 1 in the active in last 30 days.

The last measure we're going to share with you is in-app purchases.

This is again a Store or sales measure.

In-app purchases is like units where it's the transaction itself, not the price.

In this case I bought Northern California maps for 99 cents.

What this will do is it will take 99 cents and adds it to the app sales.

So it's app sales and in-app purchases combined, but it will generate a1 for the in-app purchase measure.

Combining all these measures, we get to tell that story of acquisition to engagement.

App Store views all the way down to in-app purchases gives you the idea of the entire customer life cycle.

That's great.

But how do you actually get started?

We have good news.

This is probably the easiest session in terms of work generated for you, the developer.

There is nothing you need to do to get started.

No code you need to write.

There is no SDK that you need to integrate, no iOS framework you need to hook in.

This is something completely built into the operating system and that you get for free.

You have to have a valid developer license.

Sales admin or finance role.

Not a lot involved to get going with this.

It is available for the App Store, iOS apps only.

And it's available for iOS 8 and above.

That means that data is available when it is generated from apps on iOS 8.

Another important point is that privacy is built in.

With App Analytics, we wanted to provide developers with a powerful functionality, powerful feature and tool, and we wanted to do so in a way that we would not compromise customer privacy.

This is built all the way from the operating system to the UI.

iOS has privacy constraints built in.

This means that our usage measures, customers are prompted with this display where they can choose to share sessions and active devices.

We believe that customers should have a choice, and this is built into App Analytics.

Data is available in aggregate form and not personally identifiable, it's completely anonymous.

What this means for you as the developers, in the App Analytics UI you see counts.

You do not see the raw data.

It is all available in iTunes Connect.

It's available today, it's no longer in beta.

Once you log into iTunes Connect, you'll see the App Analytics module show up here.

That's it for the static part of this.

I'll turn it over to David Hopkins, and he'll show you an overview of some key features within App Analytics in an actual demo.

[Applause]

DAVID HOPKINS: Hi, I'm David Hopkins, and I'm going to give you a quick demo of the App Analytics product.

When you log into iTunes Connect, you'll see App Analytics alongside your other modules, such as Sales and Trends and Users and Roles.

When you click on App Analytics, you will be taken to the app list.

That's the entry point to the App Analytics product.

From here you can see a snapshot across all of your apps across four key measures, again measuring all the way from acquisition with App Store views down to engagement with sessions.

You'll see the value for the current period as well as a percentage change from the previous period to help provide some context as to whether that value is good or bad.

If you hover over the percentage change, you'll see the value for this period and the value for the previous period as well as the date ranges associated with each.

The default time period here is the last 30 days, but you can change which time period you're looking at from the date picker in the top right.

You can select from any predefined ranges or select a custom range as well as selecting any day, week, or month.

Now I'm showing you the app list where you can view all of your apps.

Let's dive into one of the apps.

For those of you who build lots of great apps, the easiest way to find your app in here is to search.

We can search for our app Trip Guider.

When we click on the app Trip Guider, we will be taken to the app overview page.

The app overview page is designed to give you a high-level overview of your app.

The first thing you are going to see is your all time data for your app since it has been in App Analytics.

Again we are seeing across the same four measures we saw in the app list with App Store views, app units, sales, and sessions.

Now is a good time to call out that Trystan mentioned that we take privacy very seriously.

All of our usage data is available only for the customers who have agreed to opt in and share their data with developers.

You'll see this text that says "opt in only" below these usage measures.

If you want to know your opt-in rate specific to your app, click on the question mark next to About App Analytics Data.

We click on that, and we can see for our app Trip Guider that in the last 30 days, 23 percent of users that installed Trip Guider agreed to share their data.

As you move down the page, the next thing you'll see is a breakdown by day across six measures.

Again, we are looking at the last 30 days here.

You can see the value for the current period as well as the percentage change from the previous period, but now we have a little bit more granularity.

We can see the graphs by day.

So for example, we knew that our app Trip Guider 2.0 is killing it in terms of App Store views.

We are up 82 percent.

But what we didn't know is that the majority of this increase came over this five- or six-day period here.

We can also hover over any day to find out the value for that day.

We can see that on May 15 we had our peak in terms of App Store views, when we had around 160,000 App Store views.

As you move down the page, the next thing you'll see is a map.

This is a map of your app units by storefront.

Here we are looking at which territories have the most app units.

For Trip Guider, you can see that most of the app units came in the United States, followed by Thailand.

Again, here we are revealing missed opportunities.

Maybe we didn't know that our app was so popular in Thailand, and there's an opportunity for us to go in and localize our app to Thai to really optimize the experience for the customers in Thailand.

You can change which measure you're looking at, so this default's app units, but you can select any other measure that Trystan mentioned.

Choose sales, and now we have a map of our top sales by territory.

As you move down the page, the next thing you'll see is on the left-hand side.

You'll see a graph of your users' retention.

Retention is designed to show you whether your newly acquired customers are staying engaged with your app.

On the right-hand side, you'll see a breakdown of your app units by platform.

Again, you can change which measure you are looking at here to select from any of these measures.

You can see that for our app Trip Guider we have 68 percent of our app units coming on the iPhone, followed by 29 percent on the iPad.

Now I'm showing you the app list where you can see your list of apps as well as the app overview, where you can see a high-level view of your app.

I'm going to hand it back over to Trystan, who will walk you through how we can dive into some of this data.

[Applause]

TRYSTAN KOSMYNKA: Thank you, David.

Gave a quick overview of App Analytics.

We had the app list.

This is the best way to see all of your apps at a single view.

And the app overview, the best way to look at a single app, you can see all of the key measures in one place.

We have the beautiful map, the beautiful chart, and you can see it broken down by platform.

That's just touching the surface.

As a developer or marketer, you want to see and explore and discover new trends.

And you can do this with a feature called Metrics.

What Metrics does, we take those key indicators, all of the measures we talked about, and we add in another layer called dimensions.

These dimensions can be used multiple ways.

First, as filters.

If you wanted to answer the question: How many sessions am I getting on my iPhones or my iPads?

I can do that by filtering sessions by platform.

What if you wanted to see users, are they coming back?

You can filter by purchase date.

Is my app version being adopted?

You can do this by filtering by app version as well.

Dimensions are a great way to see certain measures filtered by certain things.

You also can group the data.

If you wanted to see the composition of your units by a particular platform, you can view by that data as well.

We will show these things.

So we have the measures.

We have the dimensions.

You can tell interesting stories by combining these two things.

We are excited that as of today there are new measures available as well.

You can tell all-new stories.

The first one we are introducing is Crashes.

This is a crash rate.

This will show up just like sessions and installs.

It's a usage measure.

What it will allow you to do is you can improve the overall stability of your app.

If you've really focused on quality on the next version of your app, once the app is in the Store, you can filter crashes by 2.0 of your app and see if you made the impact you intended to make.

Next, we have a new sales measure.

This is Paying Users.

If we look at sales, sales is a number that hopefully is increasing over time.

But if you have users that are purchasing multiple times within the app, Paying Users can give you that visibility.

It is the unique count of how many users have purchased within your app on a given day, week, or month.

It's really powerful.

Now, on the topic of power, we have all of our measures.

We have the two new measures we are excited about.

There's also power in comparing things.

I'll give you some practical examples before David demos of things you should be commonly comparing as you are marketing your app, as you are making product decisions as well.

The first is product page conversion rate.

This is the overall effectiveness of your product page.

It is important to focus on quality screenshots, using app video previews, making sure your text sounds great.

You do this by comparing app units in App Store views.

It will give you an overall score, so to speak, of how that page is doing.

And you can compare this across all of your apps.

Next is average revenue per paying user.

We take that new measure, Paying Users, and compare it to sales.

This gives me an apples-to-apples comparison across all my apps.

Are my users in app A spending more than my users in app B?

This is a really important metric that you can use to grow your overall sales and grow the overall health of your app.

Next, crashes per session.

Again, Crashes is a measure you want to use to improve the stability of your app.

You can use crashes per session as a comparison to see how you are doing against your other apps.

The last example we'll share is sessions per active device.

This is taking the Sessions metric and Active Devices metric, and by using these two I get a comparison across all of my apps.

I will turn it over to David, and he's going to demo the power of the metrics view.

And again, these new measures, Paying Users and Crashes, this is data that you do not integrate to SDK for, and it's data that only Apple can provide.

Paying Users comes straight from the sales data.

It is something that is unique to App Analytics.

DAVID HOPKINS: Thanks, Trystan.

So when we left off, we were looking at the app overview.

As Trystan mentioned, if you want to dive into your data, the best place to do it is in the metrics view.

The metrics view is a tab within the context of your app.

We can click that, and it will take us to the metrics view.

You can click on any of the data in the overview, and it will take you to the metrics view that data selected.

For example, we are looking at our app units broken down by platform.

Say we wanted to take a deeper look at our iPhone users and our app units.

We can click on that, and now we are taken to the metrics view with our app units selected, and we're looking at just our users on the iPhone.

What you'll see in the metrics view is in the top left you'll see the value for the period as well as a chart where we break down your app units by day.

If you hover over a day, you'll see the value for that day.

If you scroll below the chart, you'll see a table that contains the value for each day.

And if you scroll to the top, the next thing we will talk about are your measures.

On the left-hand side you can see that we have app units selected.

Your measures are broken down by sales and usage.

If you have any questions about any of these measures at any time, you can hover over the measure and you'll see a question mark.

If you click on that question mark, you'll get the definition of the measure.

So we talked about this new measure, Paying Users.

You can see it says the number of unique users that paid for the app or an in-app purchase.

Great. I talked about how we are looking at just our app units on the iPhone.

To do this, we have a concept of filters.

To add a filter, click on the top right, and you can add up to two filters.

Right now you can see that we are looking at just our users on the iPhone.

We can click to add a second filter.

So let's look at our users on the iPhone in the United States.

And now we are looking at just those users on the iPhone in the United States.

You can also change which version you're looking at.

If you want to switch between platforms, select from iPhone and switch to iPad.

Great. Now I've shown you how to look at a specific value within any given dimension.

Oftentimes, you want to instead compare the values within a given dimension.

To do this, we have a feature called View By.

If we remove our filters, and let's say we want to look at all of our top territories for our app units and see which ones rank the highest.

We can select View By, and select territory, and now you'll see all of your top territories plotted over time for app units.

Again, if you hover over the graph on any given day, you can see the value for each of your top territories.

If you scroll down below the chart, you'll see a table that contains the total value for each territory.

And you can see here that we have five territories selected by default.

These are the top territories.

But you can also deselect any of these.

We can deselect Brazil and then plot Japan.

Now the graph will update.

The default view here is as a line chart, but you can also change this to an area chart or a bar chart.

We can switch to area.

That gives us a nice view of the overall curve as well as a breakdown for each dimension.

Okay. So now I've shown you how to compare the values within a given dimension.

But sometimes you're more interested in the relationship between two measures.

One example of this that Trystan talked about is the relationship between app units and App Store views.

You'll call this your product page conversion rate.

What percentage of users are landing on your App Store page and going on to purchase your app?

To do this, we have a feature called Compare To.

From here, we're looking at app units, and we can select another measure.

So we'll select App Store views.

Now you'll see both your app units and App Store views plotted on the same chart.

The default view here, we're looking at a dual-axes graph.

You can hover over any day and see the value for each of those measures.

In the top-left corner you can see the total value for each of those measures.

This is a really nice way to view the relationship between these measures, see how they trend over time.

We are excited to announce some new enhancements that we're bringing to Compare To as of today.

Instead of just being able to view this on a dual-axes chart, we added the ability to view this rate over time with the new feature we call Ratios.

So from here, you can select new chart types, from Single Access and Ratio.

We'll select Ratio.

And now you can see the ratio between your app units and App Store views plotted over time.

That gives you a nice picture of that product page conversion rate that Trystan talked about.

You can see here that we're at around 18 percent for the last 30 days, but a few weeks ago for Trip Guider 2.0 we made some updates to our description of the app on the App Store page.

And thanks to App Analytics, we are able to see the product page conversion rate drop off right here.

We got down to about 6 percent.

So what we did is we went and updated the copy to the description of our App Store page, and we saw that product page conversion rate rise over time.

As you go on you can see that now we are back up to around 30 percent conversion rate.

Great. Now I've shown you how to use some of the power features in the metrics view, and I'll hand it back over to Trystan.

TRYSTAN KOSMYNKA: So David went through metrics.

This is the best way to explore and discover things and reveal those missed opportunities within App Analytics.

If you want to dive deeper than the overview, this is that feature.

One question we have not answered yet is, how do people find your app?

This is a question that is hard without App Analytics.

To do this, we have a feature called Sources.

App Analytics has two types of sources.

The first is completely organic and free.

You do not need to do any work to take advantage of this.

This is websites.

If you are actively marketing your application on websites, forums, maybe it's getting picked up by the press as well.

Websites, any time a link to your App Store page is present, we capture the web-referring URL and present that to you in App Analytics.

It is important that these, both websites and campaigns, they slice across your entire data set.

You are able to filter App Store views, in-app purchases, the new measures such as Paying Users.

You can filter these by the website and see how effective those apps are at increasing these metrics.

Next we have campaigns.

So websites is something that you don't need to do anything to take advantage of.

If you log in today, you should be pleasantly surprised that there are websites available for your apps.

Campaigns: you do need to create them, and we will talk about this.

The easiest way, the vanilla way, to create them is your App Store URL, you add a provider token.

In our example, we have one, two, three, four.

That is not your provider token.

If you use 1234, you won't get campaigns in your dashboards.

You can then add a campaign token.

My recommendation to you is that we take an event and placement approach with this.

Think of WWDC as the event and placement as newsletter or forums or home page.

You combine these in a single string, and that way when you see it in App Analytics, you know what it was for and where it was running.

There are all kinds of ways you can do this, and we want you to experiment with it.

We think it's really important.

The next way to create a campaign is StoreKit.

If you're using StoreKit today, all you need to do is add two parameters.

Add the Provider Token parameter, it's a constant in this dictionary, and you add your Campaign Token parameter.

If you are not using StoreKit, it's an easy way to create an in-app App Store-type experience.

You can cross-promote your own titles within StoreKit, and it's the best way to get a nice conversion rate for installs within your own app.

It is designed by Apple.

You don't need to create your own mimicked App Store within an app.

The last way to create campaigns is smart app banners.

If you have a home page on which you're advertising your apps today, you've probably seen this already.

If you're creating an app and this is the first time you're here, you can add a meta tag to your home page and that meta tag, you can add a provider token and campaign token to your affiliate data, and that campaign will be attributed to all of the traffic coming through.

To demo this, David will come up again.

He's going to walk through sources, how you see it.

He's also going to talk about how you create a campaign and how you can get that provider token from the UI.

DAVID HOPKINS: Great.

So as Trystan mentioned, there's two types of sources we track in App Analytics.

You have your top websites and your top campaigns.

Websites are tracked any time a user follows a link in mobile Safari to your App Store page.

For example, we have our website for Trip Guider, which is Trip Guider.apple.com, and we've implemented a smart banner that links to our App Store page.

Any time a user follows that link, it's going to generate a App Store view.

Any time the user goes on to purchase the app, it will generate an app unit.

And so on for sales, and sessions, and all of your measures.

This view should be familiar.

It's the same view we saw for our app list.

Now we are looking at our top websites.

You can click on any of the websites, and you'll be taken to the source overview for that website.

Again, this view is going to be familiar to you.

It is the same view you saw for your app overview.

Now you are looking at just your users who came from Trip Guider.apple.com.

So the great thing about websites is that you get them for free.

You don't have to do anything to implement your websites.

They just show up automatically.

Any link that goes to the App Store page will just show up.

The other type of source we have is campaigns.

Campaigns are great because you can use them anywhere.

They are not just working on mobile Safari.

Anywhere on iOS.

We can send out an email, put them on social media, but they require setup.

So for most of you, when you log in you'll see something like this like we have for Trip Guider.com, which is an empty list of our campaigns.

I'll walk you through how to set up a campaign.

For Trip Guider, we want to promote the use of Trip Guider in order to find things to do for WWDC.

I'll show you how to set up that WWDC campaign.

As Trystan mentioned, all you have to do is add a provider token and campaign token to your URL.

But to make this even easier, we have a tool that generates the campaign link.

When you follow this link, you'll see here that you have a tool and all you have, is you have your app selector, so you can switch between apps, we have Trip Guider selected.

And that will populate your app's app ID as well as that provider ID that Trystan talked about.

And here we can enter the campaign name, so we'll say WWDC whoops, there we go.

2015. It generates a campaign link.

Now you can copy this campaign link and you can put it anywhere, in an email, on your social media.

You'll start to see your campaigns show up.

It is also important to note that generating the campaign link does not mean that you'll see the campaigns in your top campaigns list.

Campaigns will only start to show up once you have five users.

Follow that link and then go and purchase your app.

So now that I've shown you how to generate a campaign, let's take a look at an app where we've already started use campaigns.

The easiest way to switch between apps is to use the app switcher in the top left.

So we switch from Trip Guider to our other app, Tide Minder.

And now we can see the list of campaigns that we set up for Tide Minder.

So, for example, we set up a campaign to track our home page here.

So we have our display home page campaign that is showing up in the list.

Similar to what you saw in the app overview and the top websites overview, you can click on this and you will be taken to your campaign overview where you can see a high level of how this campaign is doing.

So now I've shown you how to track these two different types of sources.

We hope that you go out and start setting up campaigns right away.

I'll hand it back over to Trystan.

[Applause]

TRYSTAN KOSMYNKA: All right.

Thank you, David.

David covered the campaign list, the website list.

Very familiar to the app list as well.

It filters all of your data by a particular website.

We show the top campaigns and the top websites here, and then we have the overview so you can see all of it in a single shot.

If you're running a campaign, perhaps you're paying for the campaign as well.

This is a great view to just look at and see, how is it actually doing?

Is it money well spent?

Last question we'd like to answer is, are customers returning to the app?

David mentioned there's a retention widget inside the overview.

We will go into this in some more detail, go over the retention feature.

Before we do that, before we show the UI, I want to give a lesson on how this actually works.

We have a purchase date.

And what makes sense is that 100 percent of the customers who purchase the app are customers on their purchase data.

They've remained customers.

They are retained.

What isn't as obvious is that a couple days later and all the way up to 30 days later, less of them are actually active customers.

So here we see day two, 45 percent are remaining customers, and then on day 30, we see 10 percent.

So what we're looking at here is a single purchase date, and then seven days later, 20 percent of the customers are retained.

We're going to bring this down, and we see that June 1 is our real example here.

So June 1, two days later, 45 percent of the customers were retained.

One purchase date is great to look at, but you want to compare this because you are making many changes over the course of time and you want to compare multiple purchase dates in a single shot.

We added June 2.

We have June 1 and 2 now.

Let's expand that even more.

That is not enough.

Now I see June 1 to June 9.

I'm looking at nine purchase days.

We've changed the numbers now as well.

At the top I have 45 percent for two days after June 1.

At the bottom, June 9, I have 60 percent.

So it's a little hard to read because it's a single color.

So what we've also done to this heat map is we've added colorization, so I can see that 10 percent of my customers 30 days later have returned on the June 1 purchase date.

That's a lighter color indicating that the retention is not so good at that point.

Go down to the bottom right, and I see a darker color indicating there's a hotspot there, those improvements we made.

Maybe it was my App Store presence, but likely it was the new version of the app or new content to the app to get people to come back and use it, and I have a 60 percent retention rate two days after June 9.

That's how retention works.

The easiest way to understand it is to do a demo.

So we are going to do another demo here.

David will walk through retention.

DAVID HOPKINS: Great.

So retention is available as another tab within the context of your app.

We are looking at the retention for our app Trip Guider.

The first thing I'll talk about is the retention grid, which Trystan introduced.

On the left-hand side, you'll see the purchase date for each of the last 30 purchase days.

Next to that, you'll see a number of devices.

That's the number of devices that installed on that purchase date.

On the top of the grid you'll see a number.

That is the number of days since the purchase date.

So when we look at this number one, it means we are looking at one day after the purchase date.

The easiest way to understand the retention grid if you are getting lost is to hover over any cell, and it gives you a nice explanation.

So we'll hover over this 32 percent, and it says, "32 percent of the devices that installed the app on May 13 were active two days later."

So oftentimes you'll hear people talk about their day seven retention.

And as an app developer, you know that people will purchase your app and a lot of times they come back on day one or day two, but then the usage starts to fall off.

We like to measure a day that is a little further out.

That's why day seven retention is important.

We make this easy to see within App Analytics.

All you need to do is click on the seven and you can see your day seven retention over time.

As the app developer, your goal should be to keep the users engaged and try to drive up the day seven retention over time.

You can see that we start out around 18 percent.

As time goes on, we are increasing a little bit, but our goal should be really to keep our users engaged for day seven and beyond.

You can also look at any single purchase date and look at the retention for that date.

So, for example, if we want to look at our retention on May 12, we can click on that.

You can see in the top left, now we have a graph of our retention for our users who purchased on May 12.

It starts at around 48 percent on day one and goes on as time goes on and goes to around 8 percent.

Again, we want to focus here on driving up our retention.

The last thing I want to point out on the retention view is the ability to add a filter.

Just like you saw on the metrics view, we can also filter by any dimension and look at the retention for just that dimension.

We can add a filter and look at just our retention for our users on the iPad.

Now the retention updates.

Great, that's the end of my demo.

I hand it back to Trystan who will wrap up our session on App Analytics.

[Applause]

TRYSTAN KOSMYNKA: Great, thank you, David.

That was retention.

This is answering the question, are users returning to the app?

We covered a lot today, first thing was the app list.

This is bird's eye view of all of your iOS apps.

We also support bundles.

So we have page views, units, and sales for app bundles.

These are storefront and sales measures.

Next, he covered the overview.

This is your app at a glance.

All of the measures are available.

There's the nice retention widget.

You have the map as well as the pie chart for the platforms as well.

Metrics, you use this to explore and discover new trends within your app.

You can see the dimensions are available.

We have the new metrics as well.

We have Paying Users and Crashes, those are new as of today.

Sources answers that question of, how are customers finding my app?

Are they actually turning into real customers?

We have the page views, which are potential customers.

Are they turning into engaged and purchasing customers?

Finally, are customers returning to your app?

We answer this question with retention.

We are excited about App Analytics.

We hope you use it to build better apps.

We hope this conference has been a great week for you.

For more information, look at the App Analytics Developer Guide and look at the developer forums.

We encourage you to talk to the Evangelist as well, Mark Malone.

We will be downstairs after this in a lab for a short amount of time.

We also will be available for Thursday's lab as well.

There are a couple related sessions, Promoting Your App with an IAd.

This already aired, so we encourage you to look on the video afterwards, and the What's New in iTunes Connect that occurred this morning.

This is a great session.

We walked through new metrics that will be available in the fall for TestFlight, and there's How to Manage Your Store Presence as well.

The labs again this afternoon and tomorrow, we will be available, the analytics team will be there to answer your questions.

Have a great week.

Thank you very much.

[Applause]

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