Welcome! With this script you can transform CSV files into Segment API calls and send those calls locally from your machine. This script has been pressure-tested at volume and has sent over 100M events to some of Segment's largest customers. It's based on code originally published in https://github.com/brennan/segment-upload-scripts. Big thanks to https://github.com/brennan/ for the inspiration!

IMPORTANT DISCLAIMER IN PROVIDING THIS SCRIPT, SEGMENT MAKES NO REPRESENTATIONS ABOUT WARRANTY FOR A PARTICULAR PURPOSE OR USE. SEGMENT CUSTOMERS & EMPLOYEES USING THIS SCRIPT DO SO AT THIER OWN RISK. Please consult Segment's documentation, support, and success before sending large volumes of data into your workspace, and please test all data in a separate dev source before sending into production sources.

Getting Started

You can start sending CSVs to Segment by following 6 simple steps--also outlined in the comments of csv2segment:

1. Set the delimiter
2. Set write keys
3. Enable the API method(s)
4. Prepare column variables
5. Customize your API calls
6. Run csv2segment <filename.csv>

Let's explore each step in more detail!

1. Set the delimiter

Specify the character which separates your CSV columns. Consider pipe-delimiting (|) if you have JSON or commas in your column values

delimiter: '|',

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2. Set your write keys

It's important for you to test your CSV-to-Segment calls before pushing to a production write key. For that reason, this script supports two write keys. The default behavior of the script sends the data to the DEV/TESTING source.

//Send calls to a DEV/TESTING Segment Source (replace DEVELOPMENT WRITE KEY with your own!)
const segment = {
  devKey : "DEVELOPMENT WRITE KEY", 
  productionKey : "PRODUCTION WRITE KEY", 

Replace DEVELOPMENT WRITE KEY with the write key for your Segment testing source and replace PRODUCTION WRITE KEY with your Segment production source.

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3. Enable the API method(s)

Select which Segment method(s) you'll be using with your CSV by setting the values to true. Each of these methods will fire with EACH ROW of your CSV. Fun fact: you can select more than one method! In the example below, we're sending Track and Identify calls:

  // Select which Segment API method(s) you'll be using by setting the value to 'true'
  const fireIdentify = true;
  const fireGroup = false;
  const fireTrack = true;
  const firePage = false;
  const fireScreen = false;

And here we're sending only Page calls:

  // Select which Segment API method(s) you'll be using by setting the value to 'true'
  const fireIdentify = false;
  const fireGroup = false;
  const fireTrack = false;
  const firePage = true;
  const fireScreen = false;

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4. Prepare your column variables

Before we start writing calls to the Segment API, it's super helpful to define (and format) variables for each of your CSV columns.

To get started, let's define each of the columns in the CSV File files as an element of the fileCols object:

Sample CSV

User ID	First Name	Last Name	Email Address	Zip Code	Page Visited	IP Address	Campaign	Anonymous ID	Date Added
1	Test	User	[email protected]	90210	Home Page	127.0.0.1	New Product	null	10/3/2021

FileCols Object

const fileCols = {
    'User ID' : { trait : 'userID', datatype: 'Number', isUser: true},
    'First Name' : { trait : 'first_name' },
    'Last Name' : { trait : 'last_name', allowNull: true },
    'Email Address' : { trait : 'email', datatype: 'String' },
    'Zip Code' : { trait : 'zip_code', datatype: 'Number' },
    'Page Visited' : { trait : 'page_name', datatype: 'String', isPage: true},
    'IP Address' : { trait : 'id_address', context: true },
    'Campaign' : { trait : 'campaign', context: true },
    'Anonymous ID' : { trait : 'anonymousId', isAnonymous: true },
    'Date Added' : { trait : 'size', datatype: 'Date', isTimestamp: true }
}

Replace each of the column names above with the headers for your own CSV, and keep the following in mind when defining your variables:

• trait: "trait or property name" Optional defaults to snake case of column header
• datatype : "String" Optional - defaults to String
  • Number Cast numbers in the proper format with Number(data[n])
  • Boolean Cast booleans in the proper format with Boolean(data[n])
  • Date Cast (ISO-8601) datestrings in the proper format with new Date(data[n])
  • JSON Cast JSON in the proper format with JSON.parse(data[n])
• allowNull : false Optional - defaults to false, if true the column can be set to 'null'
  • The script treats all CSV values as strings by default--even null values! This element will allow replace the String with null
• isUser : false Sets column as the userId
• isAnonymous : false Sets column as the annonymousId
• isEvent : false Sets column as the event name REQUIRED for Track calls
• isGroup : false Sets column as the group name REQUIRED for Group calls
• isPage : false Sets column as the page name REQUIRED for Page calls
• isScreen : false Sets column as the screen name REQUIRED for Screen calls
• isTimestamp : false Sets column as the timestamp REQUIRED for loading historical data
• context : false Defines the value as a context variable

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5. Customize your calls (OPTIONAL)

Now all the basics are in place and the standard behavior will function without any additional changes. HOWERVER, you can customize any of the Segment calls you selected in Step 3, and map those calls against the columns you defined in step 4.

Remember the following when sending events to the Segment API:

• You MUST specify an anonymousId OR a userId in each call
• Group calls also require a groupId
• Track calls require an event value
• Timestamps MUST be in ISO-8601 format (e.g. 2017-03-12T15:15:41.029Z) and cast as Dates to work properly
• The integrations object controls where your data goes downstream
• The context object can set useful context on your event (e.g. ip address)

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Identify() calls

Here's what a basic identify call looks like in the script:

function sendIdentifies(col){
    let package = {};
    package.userId = col.userId;
    if ("anonymousId" in col) package.anonymousId = col.anonymousId;
    package.traits = col.properties;
    package.integrations = {};
    if ("timestamp" in col) package.timestamp = col.timestamp;

    // Send the package via identify call
    analytics.identify(package);
    console.log('// identify call ' + col.userId)
  }

By default all traits defined in the fileCols object are sent as properties to with the Identify call, however you can customize the call by changing updating the package object.

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Group() calls

WARNING: You MUST set a column as isGroup for the call to go through!

Here's the default Group call in our script:

function sendGroups(col){
    if ("groupId" in col) {
      let package = {};
      package.groupId = col.groupId;
      package.userId = col.userId;
      if ("anonymousId" in col) package.anonymousId = col.anonymousId;
      package.traits = col.properties;
      package.integrations = {};
      if ("timestamp" in col) package.timestamp = col.timestamp;
      analytics.group(package);
      console.log('// group call  ' + package.groupId + ' user ' + package.userId);
    } else {
      console.log('INVALID GROUP CALL - missing groupId');
    }
  }

By default all traits defined in the fileCols object are sent as traits to with the Group call, however you can customize the call by changing updating the package object.

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Track() Calls

WARNING: You MUST set a column as isEvent for the call to go through!

Here's the default Track call in our script:

function sendTracks(col){
  
    if ("event" in col) {
      let package = {};
      package.event = col.event;
      package.userId = col.userId;
      if ("anonymousId" in col) package.anonymousId = col.anonymousId;
      package.properties = col.properties;
      package.integrations = {};
      if ("timestamp" in col) package.timestamp = col.timestamp;
    
      // Send the package via track call
      analytics.track(package);
      console.log('// track call ' + package.userId);
    } else {
      console.log('INVALID EVENT CALL - missing Event Name');
    }
 }

By default all traits defined in the fileCols object are sent as properties to with the Track call, however you can customize the call by changing updating the package object.

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Page() or Screen() Calls

WARNING: You MUST set a column as isPage or isScreen for the call to go through!

Here's the default Page call in our script:

 function sendPages(col){
    if ("pageName" in col) {
      let package = {};
      package.name = col.pageName;
      package.userId = col.userId;
      if ("anonymousId" in col) package.anonymousId = col.anonymousId;
      package.properties = col.properties;
      package.integrations = {};
      if ("timestamp" in col) package.timestamp = col.timestamp;
      if ("context" in col) package.context =  col.context;
      
      // Send the package via page call
      analytics.page(package);
      console.log('// page call ' + package.name + ' by ' + package.userId);
    } else {
      console.log('INVALID PAGE CALL - missing Page Name');
    }
  }

By default traits defined in the fileCols object with context: false are sent as properties with the Page() or Screen() call and objects with context: true are sent as context

You can customize the call by changing updating the package object.

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6. Run the script

Once you've configured everything in your script, running it is super easy!

1. Open the script directory in your terminal
2. run npm install for the first time only
3. Make sure Node is version 7 or higher
4. run ./csv2segment <filename.csv> and the script should run!

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Troubleshooting

My calls aren't appearing in the debugger!

• Is there DEFINITELY an anonymousId OR userId defined for identify calls?
• Is there DEFINITELY an isGroup plus the above for Group calls?
• Is there DEFINITELY an isEvent value for Track calls?
• Are Node and NPM running on the latest version?
• Have you tried pipe-delimiting your CSV?

My timestamps are off in the debugger

Segment shows your timestamps in the debugger relative to the timezone set in your Segment settings. So if you send UTC timestamps into Segment but your workspace is set to EST, all timestamps will show up in the debugger 5 hours earlier than expected. This only happens in the Segment debugger, and the timestamps as reported in the actual event payload will be the one leveraged in your data warehouse and other downstream destinations.

5-10% of my events didn't show up in Segment

Are you connected via WiFi? Try Ethernet!

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Advanced Methods

Interested in doing some fancier things in your event payloads? Read on!

Backdated Events with Custom Timestamps

Timestamps are optional, and help you backdate your events--which is super handy for backfilling historical data! If you plan on doing so...

• Make sure your timestamps are in ISO-8601 format!! (e.g. 2017-03-12T15:15:41.029Z)
• Cast a timestamp appearing in column n using new Date(data[n])
• Transform timestamp values using string functions like var.concat()