Analytics for Go v2 (Deprecated)
Segment’s Go library lets you record analytics data from your Go code. The requests hit Segment’s servers, and then are routed your data to any analytics service you enable on your destinations page.
This library is open-source, so you can check it out 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 a tunable buffer to batch messages, optimized for throughput and reduced network activity.
Getting Started
Install the Package
Install analytics-go
using go get
:
go get github.com/segmentio/analytics-go
Then import it and initialize an instance with your source’s 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.
package main
import "github.com/segmentio/analytics-go"
func main() {
client := analytics.New("YOUR_WRITE_KEY")
}
That will create a client
that you can use to send data to Segment for your source.
The default initialization settings are production-ready and queue 20 messages before sending a batch request, and a 5 second interval.
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:
client.Identify(&analytics.Identify{
UserId: "019mr8mf4r",
Traits: map[string]interface{}{
"name": "Michael Bolton",
"email": "mbolton@example.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 label him with name
, email
, plan
and friends
traits.
The identify
call has the following fields:
message map[string]interface{} |
Identify message. A userId or anonymousId is required. |
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:
client.Track(&analytics.Track{
Event: "Signed Up",
UserId: "f4ca124298",
Properties: map[string]interface{}{
"plan": "Enterprise",
},
})
This example track
call tells us that your user just triggered the Signed Up event choosing the “Enterprise” plan.
track
event properties can be anything you want to record. In this case, plan type.
The track
call has the following fields:
message map[string]interface{} |
Track message. An event name and userId or anonymousId is required. |
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 set up in combination with the Go 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:
client.Page(&analytics.Page{
UserId: "f4ca124298",
Category: "Docs",
Name: "Go library",
Traits: map[string]interface{}{"url": "https://segment.com/libraries/go/"},
})
The page
call has the following fields:
UserId string |
The ID for this user in your database. |
Category string, optional |
The category of the page. Useful for things like ecommerce where many pages often live under a larger category. |
Name string, optional |
The name of the of the page, for example Signup or Home. |
Traits map[string]interface{}, optional |
A few traits about the page that are specially recognized and automatically translated: url , title , referrer and path , but you can add your own too! |
Timestamp string, optional |
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 . Timestamp should be in iso8601 form. |
Context map[string]interface{}, optional |
Extra context to attach to the call. Note: context differs from traits because it is not attributes of the user itself. |
AnonymousId string, optional |
An 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:
client.Group(&analytics.Group{
UserId: "019mr8mf4r",
GroupId: "56",
Traits: map[string]interface{}{
"name": "Initech",
"description": "Accounting Software",
},
})
The group
call has the following fields:
message map[string]interface{} |
Group message. An event name and userId or anonymousId is required. |
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 destinations.
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:
client.Alias(&analytics.Alias{
PreviousId: anonymousUser,
UserId: "019mr8mf4r",
})
The alias
call has the following fields:
UserId string |
The ID for this user in your database. |
PreviousId string |
The previous ID to alias from. |
Here’s a full example of how we might use the alias
call:
// the anonymous user does actions ...
client.Track(&analytics.Track{
Event: "Anonymous Event",
UserId: anonymousUser,
})
// the anonymous user signs up and is aliased
client.Alias(&analytics.Alias{
PreviousId: anonymousUser,
UserId: "019mr8mf4r",
})
// the identified user is identified
client.Identify(&analytics.Identify{
UserId: "019mr8mf4r",
Traits: map[string]interface{}{
"name": "Michael Bolton",
"email": "mbolton@example.com",
"plan": "Enterprise",
"friends": 42,
},
})
// the identified user does actions ...
```go
client.Track(&analytics.Track{
Event: "Item Viewed",
UserId: "019mr8mf4r",
Properties: map[string]interface{}{
"item": "lamp",
},
})
For more details about alias
, including the alias
call payload, check out our Spec.
Development Settings
You can use the Size
field set to 1 during development to make the library flush every time a message is submitted, so that you can be sure your calls are working properly.
func main() {
client := analytics.New("YOUR_WRITE_KEY")
client.Size = 1
}
Logging
The DEBUG
environment variable can be used to enable logging during runtime, like so:
DEBUG=analytics go run test.go
Selecting Destinations
The alias
, group
, identify
, page
and track
calls can all be passed an object of context.integrations
that lets you turn certain integrations on or off. By default all destinations are enabled.
Here’s an example track
call with the context.integrations
object shown.
client.Track(&analytics.Track{
Event: "Membership Upgraded",
UserId: "019mr8mf4r",
Integrations: map[string]interface{}{
"All": false,
"Mixpanel": true,
},
})
In this case, we’re specifying that we want this 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 (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 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 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 analytics-go 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 flushed in batch in the background, which allows for much faster operation.
By default, our library will flush:
- every 20 messages (control with
FlushAt
) - if 5 seconds has passed since the last flush (control with
FlushAfter
)
There is a maximum of 500KB
per batch request and 32KB
per call.
HTTP Tracking API limits
Segment's HTTP Tracking API accepts batch requests up to 500KB. To avoid errors in event creation, ensure that individual event payload sizes remain below 32KB.
Sometimes you might not want batching (eg. when debugging, or in short-lived programs). You can turn off batching by setting the FlushAt
argument to 1
, and your requests will always be sent right away.
Options
If you hate defaults you can configure analytics-go with the following fields:
Size int |
The number of messages to queue before flushing. |
Endpoint string |
|
Troubleshooting
The following tips often help resolve common issues.
No events in my debugger
-
Double check that you’ve followed all the steps in the Quickstart.
-
Make sure that you’re calling a Segment API method once the library is successfully installed—
identify
,track
, etc. -
Make sure your application isn’t shutting down before the
Analytics.Client
local queue events are pushed to Segment. You can manually callAnalytics.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/oranonymousId
. If you send events without either theuserId
oranonymousId
, Segment’s tracking API responds with anno_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 amessageId
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.
This page was last modified: 30 May 2024
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