Quickstart: analytics-java
This tutorial helps you start sending data from your program to Segment and any of our destinations, using our analytics-java library. As soon as you’re set up you’ll be able to turn on any new destinations with the flip of a switch!
If you want to dive deeper at any point, check out the analytics-java reference.
Step 1: Create a Source in the Segment app
Before you begin, you need a Workspace (which is a container that holds all of the sources and destinations which are billed together for an organization). If you already created one, great! If not, you can sign up for a free Segment account and create one.
Next, create a Java source from your Workspace:
- Click Add Source.
- From the source catalog page, click Java.
- Click Add Source again from the informational panel that appears to the right.
- Give the source a display name, and enter the URL the source will collect data from.
When you create a Source in the Segment web app, it tells the Segment servers that you’ll be sending data from a specific source type. When you create (or change!) a Source in the Segment app, Segment generates a new Write Key for that source. You use the write key in your code to tell the Segment servers where the data is coming from, so Segment can route it to your destinations and other tools.
Step 2: Install the Library
The recommended way to install the library for Java is with a build system like Gradle or Maven. This makes it simple to upgrade and swap out destinations. The library is distributed using Maven Central as a jar
dependency.
Here’s what it would look like with Maven:
Add to pom.xml
:
<dependency>
<groupId>com.segment.analytics.java</groupId>
<artifactId>analytics</artifactId>
<version>LATEST</version>
</dependency>
or if you’re using Gradle:
implementation 'com.segment.analytics.java:analytics:+'
Step 3: Initialize the SDK
Before you can send us events, you need to initialize an instance of the Analytics class. To do so, you must use the Analytics.Builder
class.
Analytics analytics = Analytics.builder(writeKey).build();
The Builder can also be used to customize behaviour of the Analytics instance.
Note: There is an internal AnalyticsClient
class. Do not confuse this class with the public Analytics
class and do not use this class directly.
The Analytics class has a method called enqueue
that takes a MessageBuilder
. Each message class has a corresponding builder that is used to construct instances of a message.
Although not enforced at compile time, make sure you provide either of userId
or anonymousId
for each message. Failing to do so will raise an exception at runtime.
The following examples use Guava’s immutable maps, but feel free to use plain old Java maps instead.
Step 4: Identify Users
Good to know: For any of the different methods described in this quickstart, you can replace the properties and traits in the code samples with variables that represent the data collected.
The identify
message is how you tell Segment who the current user is. It includes a unique User ID and any optional traits you know about them. You can read more about it in the identify reference.
Here’s what a basic call to identify
a user might look like:
Map<String, String> map = new HashMap();
map.put("name", "Michael Bolton");
map.put("email", "mbolton@example.com");
analytics.enqueue(IdentifyMessage.builder()
.userId("f4ca124298")
.traits(map));
Note: The enqueue method takes a MessageBuilder
instance and not a Message
instance directly. This is to allow you to use a MessageTransformer
that applies to all incoming messages and transform or add data.
That’s identifying Michael by his unique User ID (the one you know him by in your database) and labeling him with name
and email
traits.
Fun Fact: if you only want to use a basic CRM setup, you can call it a day right now. Just switch on Salesforce, Intercom, or any other CRM you’d like to use from our interface and we’ll starting send all of your user data to it!
Of course, lots of analytics tools record more than just identities… they record the actions each user performs too! If you’re looking for a complete event tracking analytics setup, keep reading…
Step 5: Track Actions
The track
method is how you tell Segment about which actions your users are performing on your site. Every action triggers what we call an “event”, which can also have associated properties. You can read more about track
in the track reference.
Here’s what a call to track
might look like when a user signs up:
analytics.enqueue(TrackMessage.builder("Signed Up")
.userId("f4ca124298")
.properties(ImmutableMap.builder()
.put("plane", "Enterprise")
.build()
)
);
That’s just telling us that your user just triggered the Signed Up event and chose your hypothetical 'Enterprise'
plan. Properties can be anything you want to record, for example:
You’ll want to track events that you’re interested in, such as Signed Up, Item Purchased or Article Bookmarked.
To get started, we recommend tracking just a few important events. You can always add more later!
Once you’ve added a few track
calls, you’re done! You successfully installed Analytics tracking. Now you’re ready to turn on any destination you fancy from our interface, margarita in hand.
What’s Next?
We just walked through the quickest way to get started with Segment using our Java library. You might also want to check out our full reference to see what else is possible, or read about the Tracking API methods to get a sense for the bigger picture.
If you’re running an Ecommerce site or app you should also check out our Ecommerce API reference to make sure your products and checkout experience are instrumented properly!
This page was last modified: 11 Mar 2022
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