Analytics for Node.js Classic

Current Version:

Release Date: Aug 02, 2022

Segment’s Node.js library lets you record analytics data from your node code. The requests hit Segment’s servers, and then Segment routes your data to any destinations you have enabled.

The Segment Node.js library is open-source on GitHub.

All of Segment’s 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 Segment’s servers.

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Getting Started

Run:

npm install --save analytics-node

This will add Segment’s 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.

Regional configuration

For Business plans with access to Regional Segment, you can use the host configuration parameter to send data to the desired region:

1. Oregon (Default) — api.segment.io/v1
2. Dublin — events.eu1.segmentapis.com

An example of setting the host to the EU endpoint using the Node library would be:

var analytics = new Analytics('YOUR_WRITE_KEY', {
    host: "https://events.eu1.segmentapis.com"
  });

Identify

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

You should call identify once when the user’s account is first created, and then again any time their traits change.

Example of an anonymous identify call:

analytics.identify({
  anonymousId: '48d213bb-95c3-4f8d-af97-86b2b404dcfe',
  traits: {
    friends: 42
  }
});

This call identifies the user and records their unique anonymous ID, and labels them with the friends trait.

Example of an identify call for an identified user:

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

The call above identifies Michael by his unique User ID (the one you know him by in your database), and labels him with the name, email, plan and friends traits.

The identify call has the following fields:

Find details on the identify method payload in the Segment Spec.

Track

track lets you record the actions your users perform. Every action triggers what Segment calls 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, Segment recommends tracking just a few important events. You can always add more later.

Example anonymous track call:

analytics.track({
  anonymousId: '48d213bb-95c3-4f8d-af97-86b2b404dcfe',
  event: 'Item Purchased',
  properties: {
    revenue: 39.95,
    shippingMethod: '2-day'
  }
});

Example identified track call:

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

This example track call tells 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:

Find details on best practices in event naming as well as the track method payload in the Segment 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 Segment’s client-side set up in combination with the Node.js library, page calls are already tracked for you by default.

Example page call:

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

The page call has the following fields:

Find details on the page payload in the Segment 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:

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

Alias

The alias call allows you to associate one identity with another. This is an advanced method and should not be widely used, but is required to manage user identities in some destinations. Other destinations do not support the alias call.

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:

Here’s a full example of how Segment 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@example.com' })
// the identified user is identified
analytics.identify({ userId: 'identified@example.com', traits: { plan: 'Free' } })
// the identified user does actions ...
analytics.track({ userId: 'identified@example.com', event: 'Identified Action' })

For more details about alias, including the alias call payload, check out the 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,
  flushInterval: 10000,
  enable: false
});

Error Handling

Additionally there is an optional errorHandler property available to the class constructor’s options. If unspecified, the behaviour of the library does not change. If specified, when an axios request fails, errorHandler(axiosError) will be called instead of re-throwing the axios error.

Example usage:

const Analytics = require('analytics-node');

const client = new Analytics('write key', {
  errorHandler: (err) => {
    console.error('analytics-node flush failed.')
    console.error(err)
  }
});

client.track({
  event: 'event name',
  userId: 'user id'
});

If this fails when flushed no exception will be thrown, instead the axios error will be logged to the console.

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 Destinations

The alias, group, identify, page and track calls can all be passed an object of integrations that lets you turn certain destinations on or off. By default all destinations 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, Segment specifies the track to only go to Vero. All: false says that no destination should be enabled unless otherwise specified. Vero: true turns on Vero, etc.

Destination flags are case sensitive and match the destination’s name in the docs (for example, “AdLearn Open Platform”, “awe.sm”, “MailChimp”). In some cases, there may be several names for a destination; if that happens you’ll see a “Adding (destination name) to the Integrations Object” section in the destination’s doc page with a list of valid names.

Note:

• Available at the business level, filtering track calls can be done right from the Segment UI on your source schema page. Segment recommends 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 destinations that can accept historical timestamped data. Most analytics tools like Mixpanel, Amplitude, Kissmetrics, etc. can handle that type of data just fine. One common destination 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 Segment’s servers will timestamp the requests for you.

Batching

Segment’s libraries are built to support high performance environments. That means it is safe to use the Segment 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, Segment’s library flushes:

• 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.flushInterval)

There is a maximum of 500KB per batch request and 32KB 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!');
});

Long running process

You should call client.track(...) and know that events will be queued and eventually sent to Segment. To prevent losing messages, be sure to capture any interruption (for example, a server restart) and call flush to know of and delay the process shutdown.

import { randomUUID } from 'crypto';
import Analytics from 'analytics-node'

const WRITE_KEY = '...';

const analytics = new Analytics(WRITE_KEY, { flushAt: 10 });

analytics.track({
  anonymousId: randomUUID(),
  event: 'Test event',
  properties: {
    name: 'Test event',
    timestamp: new Date()
  }
});

const exitGracefully = async (code) => {
  console.log('Flushing events');
  await analytics.flush(function(err, batch) {
    console.log('Flushed, and now this program can exit!');
    process.exit(code);
  });
};

[
  'beforeExit', 'uncaughtException', 'unhandledRejection',
  'SIGHUP', 'SIGINT', 'SIGQUIT', 'SIGILL', 'SIGTRAP',
  'SIGABRT','SIGBUS', 'SIGFPE', 'SIGUSR1', 'SIGSEGV',
  'SIGUSR2', 'SIGTERM',
].forEach(evt => process.on(evt, exitGracefully));

function logEvery2Seconds(i) {
    setTimeout(() => {
        console.log('Infinite Loop Test n:', i);
        logEvery2Seconds(++i);
    }, 2000);
}

logEvery2Seconds(0);

Short lived process

Short-lived functions have a predictably short and linear lifecycle, so use a queue big enough to hold all messages and then await flush to complete its work.

import { randomUUID } from 'crypto';
import Analytics from 'analytics-node'


async function lambda()
{
  const WRITE_KEY = '...';
  const analytics = new Analytics(WRITE_KEY, { flushAt: 20 });
  analytics.flushed = true;

  analytics.track({
    anonymousId: randomUUID(),
    event: 'Test event',
    properties: {
      name: 'Test event',
      timestamp: new Date()
    }
  });
  await analytics.flush(function(err, batch) {
    console.log('Flushed, and now this program can exit!');
  });
}

lambda();

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

The following tips often help resolve common issues.

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 a Segment API method once the library is successfully installed—identify, track, etc.

3. Make sure your application isn’t shutting down before the Analytics.Client local queue events are pushed to Segment. You can manually call Analytics.Client.Flush() to ensure the queue is fully processed before shutdown.

Other common errors

If you are experiencing data loss from your source, you may be experiencing one or more of the following common errors:

• Payload is too large: If you attempt to send events larger than 32KB per normal API request or batches of events larger than 500KB per request, Segment’s tracking API responds with 400 Bad Request. Try sending smaller events (or smaller batches) to correct this error.

• Identifier is not present: Segment’s tracking API requires that each payload has a userId and/or anonymousId. If you send events without either the userId or anonymousId, Segment’s tracking API responds with an no_user_anon_id error. Check the event payload and client instrumentation for more details.

• Track event is missing name: All Track events to Segment must have a name in string format.

• Event dropped during deduplication: Segment automatically adds a messageId field to all payloads and uses this value to deduplicate events. If you’re manually setting a messageId value, ensure that each event has a unique value.

• Incorrect credentials: Double check your credentials for your downstream destination(s).

• Destination incompatibility: Make sure that the destination you are troubleshooting can accept server-side API calls. You can see compatibility information on the Destination comparison by category page and in the documentation for your specific destination.

• Destination-specific requirements: Check out the destination’s documentation to see if there are other requirements for using the method and destination that you’re trying to get working.