Analytics for Node.js

Our Node.js library lets you record analytics data from your node code. The requests hit our servers, and then we route your data to any analytics service you enable on your integrations page.

This library is open-source, so you can check it out on Github.

All of our server-side libraries are built for high-performance, so you can use them in your web server controller code. This library uses an internal queue to make identify and track calls non-blocking and fast. It also batches messages and flushes asynchronously to our servers.

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Getting Started

Install the Module

Run:

npm install --save analytics-node

This will add our Node library module to your package.json. The module exposes an Analytics constructor, which you need to initialize with your Segment source’s Write Key, like so:

var Analytics = require('analytics-node');
var analytics = new Analytics('YOUR_WRITE_KEY');

Of course, you’ll want to replace YOUR_WRITE_KEY with your actual Write Key which you can find in Segment under your source settings.

This will create an instance of Analytics that you can use to send data to Segment for your project. The default initialization settings are production-ready and queue 20 messages before sending any requests. In development you might want to use development settings.

Identify

identify lets you tie a user to their actions and record traits about them. It includes a unique User ID and any optional traits you know about them.

We recommend calling identify a single time when the user’s account is first created, and only identifying again later when their traits change.

Example identify call:

analytics.identify({
  userId: '019mr8mf4r',
  traits: {
    name: 'Michael Bolton',
    email: 'mbolton@initech.com',
    plan: 'Enterprise',
    friends: 42
  }
});

This call is identifying Michael by his unique User ID (the one you know him by in your database) and labeling him with name, email, plan and friends traits.

The identify call has the following fields:

userId String or NumberThe ID for this user in your database.
traits Object, optionalA dictionary of traits you know about the user. Things like: email, name or friends.
timestamp Date, optionalA Javascript date object representing when the identify took place. If the identify just happened, leave it out and we’ll use the server’s time. If you’re importing data from the past make sure you to send a timestamp.
context Object, optionalA dictionary of extra context to attach to the call. Note: context differs from traits because it is not attributes of the user itself.
anonymousId String or Number, optionalAn ID to associated with the user when you don’t know who they are (eg., the anonymousId generated by analytics.js)

Find details on the identify method payload in our Spec.

Track

track lets you record the actions your users perform. Every action triggers what we call an “event”, which can also have associated properties.

You’ll want to track events that are indicators of success for your site, like Signed Up, Item Purchased or Article Bookmarked.

To get started, we recommend tracking just a few important events. You can always add more later!

Example track call:

analytics.track({
  userId: '019mr8mf4r',
  event: 'Item Purchased',
  properties: {
    revenue: 39.95,
    shippingMethod: '2-day'
  }
});

This example track call tells us that your user just triggered the Item Purchased event with a revenue of $39.95 and chose your hypothetical ‘2-day’ shipping.

track event properties can be anything you want to record. In this case, revenue and shipping method.

The track call has the following fields:

userId String or NumberThe ID for this user in your database.
event StringThe name of the event you’re tracking. We recommend human-readable names like Song Played or Status Updated.
properties Object, optionalA dictionary of properties for the event. If the event was Product Added, it might have properties like price or product.
timestamp Date, optionalA Javascript date object representing when the track took place. If the track just happened, leave it out and we’ll use the server’s time. If you’re importing data from the past make sure you to send a timestamp.
context Object, optionalA dictionary of extra context to attach to the call. Note: context differs from traits because it is not attributes of the user itself.
anonymousId String or Number, optionalAn ID to associated with the user when you don’t know who they are (eg., the anonymousId generated by analytics.js)

Find details on best practices in event naming as well as the track method payload in our Spec.

Page

The page method lets you record page views on your website, along with optional extra information about the page being viewed.

If you’re using our client-side setup in combination with the Node.js library, page calls are already tracked for you by default. However, if you want to record your own page views manually and aren’t using our client-side library, read on!

Example page call:

analytics.page({
  userId: '019mr8mf4r',
  category: 'Docs',
  name: 'Node.js Library',
  properties: {
    url: 'https://segment.com/docs/libraries/node',
    path: '/docs/libraries/node/',
    title: 'Node.js Library - Segment',
    referrer: 'https://github.com/segmentio/analytics-node'
  }
});

The page call has the following fields:

userId String or NumberThe ID for this user in your database.
category String, optionalThe category of the page. Useful for things like ecommerce where many pages often live under a larger category.
name String, optionalThe name of the of the page, for example Signup or Home.
properties Object, optionalA dictionary of properties of the page. A few properties specially recognized and automatically translated: url, title, referrer and path, but you can add your own too!
timestamp Date, optionalA Javascript date object representing when the track took place. If the track just happened, leave it out and we’ll use the server’s time. If you’re importing data from the past make sure you to send a timestamp.
context Object, optionalA dictionary of extra context to attach to the call. Note: context differs from traits because it is not attributes of the user itself.
anonymousId String or Number, optionalAn ID to associated with the user when you don’t know who they are (eg., the anonymousId generated by analytics.js)

Find details on the page payload in our Spec.

Group

group lets you associate an identified user with a group. A group could be a company, organization, account, project or team! It also lets you record custom traits about the group, like industry or number of employees.

This is useful for tools like Intercom, Preact and Totango, as it ties the user to a group of other users.

Example group call:

analytics.group({
  userId: '019mr8mf4r',
  groupId: '56',
  traits: {
    name: 'Initech',
    description: 'Accounting Software'
  }
});

The group call has the following fields:

userId string or numberThe ID for the user that is a part of the group.
groupId string or numberThe ID of the group.
traits dict, optionalA dict of traits you know about the group. For a company, they might be things like name, address, or phone.
context dict, optionalA dict containing any context about the request. To see the full reference of supported keys, check them out in the context reference
timestamp datetime, optionalA datetime object representing when the group took place. If the group just happened, leave it out and we’ll use the server’s time. If you’re importing data from the past make sure you send timestamp.
anonymousId String or Number, optionalAn ID to associated with the user when you don’t know who they are (eg., the anonymousId generated by analytics.js)
integrations dict, optionalA dictionary of integrations to enable or disable

Find more details about group, including the group payload, in our Spec.

Alias

alias is how you associate one identity with another. This is an advanced method, but it is required to manage user identities successfully in some of our integrations.

In Mixpanel it’s used to associate an anonymous user with an identified user once they sign up. For KISSmetrics, if your user switches IDs, you can use ‘alias’ to rename the ‘userId’.

Example alias call:

analytics.alias({
  previousId: 'old_id',
  userId: 'new_id'
});

The alias call has the following fields:

userId StringThe ID for this user in your database.
previousId StringThe previous ID to alias from.

Here’s a full example of how we might use the alias call:

// the anonymous user does actions ...
analytics.track({ userId: 'anonymous_user', event: 'Anonymous Event' })
// the anonymous user signs up and is aliased
analytics.alias({ previousId: 'anonymous_user', userId: 'identified@gmail.com' })
// the identified user is identified
analytics.identify({ userId: 'identified@gmail.com', traits: { plan: 'Free' } })
// the identified user does actions ...
analytics.track({ userId: 'identified@gmail.com', event: 'Identified Action' })

For more details about alias, including the alias call payload, check out our Spec.


Configuration

The second argument to the Analytics constructor is an optional dictionary of settings to configure the module.

var analytics = new Analytics('YOUR_WRITE_KEY', {
  flushAt: 20,
  flushAfter: 10000
});
flushAt NumberThe number of messages to enqueue before flushing.
flushAfter NumberThe number of milliseconds to wait before flushing the queue automatically.

Development

You can use this initialization during development to make the library flush every time a message is submitted, so that you can be sure your calls are working properly before pushing to production.

var analytics = new Analytics('YOUR_WRITE_KEY', { flushAt: 1 });

Selecting Integrations

The alias, group, identify, page and track calls can all be passed an object of integrations that lets you turn certain integrations on or off. By default all integrations are enabled.

Here’s an example with the integrations object shown:

analytics.track({
  event: 'Membership Upgraded',
  userId: '97234974',
  integrations: {
    'All': false,
    'Vero': true,
    'Google Analytics': false
  }
})

In this case, we’re specifying that we want this track to only go to Vero. All: false says that no integration should be enabled unless otherwise specified. Vero: true turns on Vero, etc.

Integration flags are case sensitive and match the integration’s name in the docs (i.e. “AdLearn Open Platform”, “awe.sm”, “MailChimp”, etc.).

Note:

  • Available at the business level, filtering track calls can be done right from the Segment UI on your source schema page. We recommend using the UI if possible since it’s a much simpler way of managing your filters and can be updated with no code changes on your side.

  • If you are on a grandfathered plan, events sent server-side that are filtered through the Segment dashboard will still count towards your API usage.

Historical Import

You can import historical data by adding the timestamp argument to any of your method calls. This can be helpful if you’ve just switched to Segment.

Historical imports can only be done into integrations that can accept historical timestamp’ed data. Most analytics tools like Mixpanel, Amplitude, Kissmetrics, etc. can handle that type of data just fine. One common integration that does not accept historical data is Google Analytics since their API cannot accept historical data.

Note: If you’re tracking things that are happening right now, leave out the timestamp and our servers will timestamp the requests for you.

Batching

Our libraries are built to support high performance environments. That means it is safe to use our Node library on a web server that’s serving hundreds of requests per second.

Every method you call does not result in an HTTP request, but is queued in memory instead. Messages are then flushed in batch in the background, which allows for much faster operation.

By default, our library will flush:

  • The very first time it gets a message.
  • Every 20 messages (controlled by options.flushAt).
  • If 10 seconds has passed since the last flush (controlled by options.flushAfter)

There is a maximum of 500kb per batch request and 15kb per call.

If you don’t want to batch messages, you can turn batching off by setting the flushAt option to 1, like so:

var analytics = new Analytics('YOUR_WRITE_KEY', { flushAt: 1 });

Batching means that your message might not get sent right away. But every method call takes an optional callback, which you can use to know when a particular message is flushed from the queue, like so:

analytics.track({
  userId: '019mr8mf4r',
  event: 'Ultimate Played'
}, function(err, batch){
  if (err) // There was an error flushing your message...
  // Your message was successfully flushed!
});

You can also flush on demand. For example, at the end of your program, you need to flush to make sure that nothing is left in the queue. To do that, call the flush method:

analytics.flush(function(err, batch){
  console.log('Flushed, and now this program can exit!');
});

Multiple Clients

Different parts of your application may require different types of batching, or even sending to multiple Segment sources. In that case, you can initialize multiple instances of Analytics with different settings:

var Analytics = require('analytics-node');
var marketingAnalytics = new Analytics('MARKETING_WRITE_KEY');
var appAnalytics = new Analytics('APP_WRITE_KEY');

Troubleshooting

If you’re having trouble we have a few tips that help common problems.

No events in my debugger

  1. Double check that you’ve followed all the steps in the Quickstart.

  2. Make sure that you’re calling one of our API methods once the library is successfully installed—identify, track, etc.

No events in my end tools

  1. Double check your credentials for that integration.

  2. Make sure that the integration you are troubleshooting can accept server-side API calls. Compatibility is shown on the integration docs pages and on the sheets on your Segment source Integrations page.

  3. Check out the integration’s documentation to see if there are other requirements for using the method and integration you’re trying to get working.


If you have any questions or see anywhere we can improve our documentation, please let us know or kick off a conversation in the Segment Community!