Segment logo
A single hub to collect, translate and send your data with the flip of a switch.

What is Segment?

Segment is a single hub for customer data. Collect your data in one place, then send it to more than 100 third-party tools, internal systems, or Amazon Redshift with the flip of a switch.
Segment is a tool in the Analytics Integrator category of a tech stack.

Who uses Segment?

Companies
826 companies use Segment in their tech stacks, including Optimizely, ZeroCater, and UserVoice.

Developers
77 developers use Segment.

Segment Integrations

Google Analytics, Sentry, Mixpanel, Intercom, and HubSpot are some of the popular tools that integrate with Segment. Here's a list of all 63 tools that integrate with Segment.

Why developers like Segment?

Here’s a list of reasons why companies and developers use Segment
Segment Reviews

Here are some stack decisions, common use cases and reviews by companies and developers who chose Segment in their tech stack.

Julien DeFrance
Julien DeFrance
Full Stack Engineering Manager at ValiMail · | 16 upvotes · 66.6K views
atSmartZip
Amazon DynamoDB
Ruby
Node.js
AWS Lambda
New Relic
Amazon Elasticsearch Service
Elasticsearch
Superset
Amazon Quicksight
Amazon Redshift
Zapier
Segment
Amazon CloudFront
Memcached
Amazon ElastiCache
Amazon RDS for Aurora
MySQL
Amazon RDS
Amazon S3
Docker
Capistrano
AWS Elastic Beanstalk
Rails API
Rails
Algolia

Back in 2014, I was given an opportunity to re-architect SmartZip Analytics platform, and flagship product: SmartTargeting. This is a SaaS software helping real estate professionals keeping up with their prospects and leads in a given neighborhood/territory, finding out (thanks to predictive analytics) who's the most likely to list/sell their home, and running cross-channel marketing automation against them: direct mail, online ads, email... The company also does provide Data APIs to Enterprise customers.

I had inherited years and years of technical debt and I knew things had to change radically. The first enabler to this was to make use of the cloud and go with AWS, so we would stop re-inventing the wheel, and build around managed/scalable services.

For the SaaS product, we kept on working with Rails as this was what my team had the most knowledge in. We've however broken up the monolith and decoupled the front-end application from the backend thanks to the use of Rails API so we'd get independently scalable micro-services from now on.

Our various applications could now be deployed using AWS Elastic Beanstalk so we wouldn't waste any more efforts writing time-consuming Capistrano deployment scripts for instance. Combined with Docker so our application would run within its own container, independently from the underlying host configuration.

Storage-wise, we went with Amazon S3 and ditched any pre-existing local or network storage people used to deal with in our legacy systems. On the database side: Amazon RDS / MySQL initially. Ultimately migrated to Amazon RDS for Aurora / MySQL when it got released. Once again, here you need a managed service your cloud provider handles for you.

Future improvements / technology decisions included:

Caching: Amazon ElastiCache / Memcached CDN: Amazon CloudFront Systems Integration: Segment / Zapier Data-warehousing: Amazon Redshift BI: Amazon Quicksight / Superset Search: Elasticsearch / Amazon Elasticsearch Service / Algolia Monitoring: New Relic

As our usage grows, patterns changed, and/or our business needs evolved, my role as Engineering Manager then Director of Engineering was also to ensure my team kept on learning and innovating, while delivering on business value.

One of these innovations was to get ourselves into Serverless : Adopting AWS Lambda was a big step forward. At the time, only available for Node.js (Not Ruby ) but a great way to handle cost efficiency, unpredictable traffic, sudden bursts of traffic... Ultimately you want the whole chain of services involved in a call to be serverless, and that's when we've started leveraging Amazon DynamoDB on these projects so they'd be fully scalable.

See more
Yonas Beshawred
Yonas Beshawred
CEO at StackShare · | 10 upvotes · 9.6K views
atStackShare
Segment
Rails
FullStory
Sentry
#Bug-squashing
#Sessionrecording
#Reproducing-bugs
#UserFeedbackAsAService

One of the challenges we've had to deal with as our product surface area has grown, is identifying and reproducing bugs. We use Sentry for exception monitoring, however, it's usually difficult to try to reproduce bugs. I first heard about FullStory from our friends over at Flexport (check out the Stack Story and you'll hear them mention it: https://stackshare.io/posts/how-flexport-builds-software-to-move-over-1-billion-dollars-in-merchandise). FullStory let's you record user sessions, and play them back to help you identify bugs and UX issues. You're even able to view the console errors live as they happen during the sessions!

We were pretty blown away at how comprehensive the product was at first, and it seems to be getting better every time I use it. Only complaint is that it's super expensive once you're in the hundreds of thousands of sessions so we had to stop trying to record logged out sessions, we only use it for auth'd sessions. We also started out using it via Segment but once we needed to watch out for the number of sessions we were recording we realized that it was impossible to restrict FullStory recordings on a per-page basis without ripping it out of Segment, so we ended up just using their JS snippet and putting that in the Rails views that we wanted to monitor closely.

The ability to share specific portions of sessions, speed them up, skip inactivity, and all sorts of other little features all add up to a really solid product that helps both our PMs and engineers improve our own product much quicker. I officially requested a Sentry + FullStory integration a while back https://twitter.com/yonasbe/status/871987738777616384, still waiting on this! #UserFeedbackAsAService #reproducing-bugs #sessionrecording #bug-squashing

See more
Yonas Beshawred
Yonas Beshawred
CEO at StackShare · | 4 upvotes · 4.5K views
atStackShare
Google Analytics
Segment
Amplitude
#Analyticsstack
#Analytics
#FunnelAnalysisAnalytics

Adopting Amplitude was one of the best decisions we've made. We didn't try any of the alternatives- the free tier was really generous so it was easy to justify trying it out (via Segment). We've had Google Analytics since inception, but just for logged out traffic. We knew we'd need some sort of #FunnelAnalysisAnalytics solution, so it came down to just a few solutions.

We had heard good things about Amplitude from friends and even had a consultant/advisor who was an Amplitude pro from using it as his company, so he kinda convinced us to splurge on the Enterprise tier for the behavioral cohorts alone. Writing the queries they provide via a few clicks in their UI would take days/weeks to craft in SQL. The behavioral cohorts allow us to create a lot of useful retention charts.

Another really useful feature is kinda minor but kinda not. When you change a saved chart, a new URL gets generated and is visible in your browser (chartURL/edit) and that URL is immediately available to share with your team. It may sound inconsequential, but in practice, it makes it really easy to share and iterate on graphs. Only complaint is that you have to explicitly tag other team members as owners of whatever chart you're creating for them to be able to edit it and save it. I can see why this is the case, but more often than not, the people I'm sharing the chart with are the ones I want to edit it 🤷🏾‍♂️

The Engagement Matrix feature is also really helpful (once you filter out the noisy events). Charts and dashboards are also great and make it easy for us to focus on the important metrics. We've been using Amplitude in production for about 6 months now. There's a bunch of other features we don't use regularly like Pathfinder, etc that I personally don't fully understand yet but I'm sure we'll start using them eventually.

Again, haven't tried any of the alternatives like Heap, Mixpanel, or Kissmetrics so can't speak to those, but Amplitude works great for us.

#analytics analyticsstack

See more
Jordi Mon Companys
Jordi Mon Companys
PM at Códice Software · | 3 upvotes · 6.8K views
atPlastic SCM
Intercom
Segment
Amplitude
C#
.NET
Plastic SCM
#VersionControlSystem

I use Plastic SCM because I can handle, via Gluon, non-text or non-code assets in the same repo as the programmers I work with, regardless of the size, if I have to lock those or files or anything. It is a point and click interface that keeps version control for me in the background will keeping me away from all its complexities. It's the perfect #VersionControlSystem to do distributed or centralized version control when you don't like any of those.

Plastic SCM is built using .NET, C# and Mono. In Product we decided to go for Amplitude and Segment to track usage and monitor activation as well as Intercom to communicate news, updates and tips. The reasons to pick all of those are pretty similar: scalability and ease of use.

See more
Julien DeFrance
Julien DeFrance
Full Stack Engineering Manager at ValiMail · | 2 upvotes · 5.1K views
atSmartZip
Intercom
Zapier
Segment
AutopilotHQ

Achieving #MarketingAutomation using AutopilotHQ

Some of the key aspects evaluated here: - Ability to integrate with Segment or Zapier - Being multi-channel (Not just Email automation) - Dozens of integrations and capabilities: SFDC, In app messages, SMS, Push Notifications, Direct Mail, Segment Events... - Allowing teams to operate outside of engineering dependencies - Segmentation against user attributes / user traits - Static or Dynamic segments - Concept of user journeys - And more

Combined with Segment and its own sets of integrations and capabilities, AutopilotHQ ended up being a very powerful tool for Product Marketing to use at SmartZip.

Couple of years later, there certainly were some overlap with the features offered by Intercom 's engagement module , but our team kept on using this tool given the greater range of functionality / capabilities.

See more
Matthias Posch
Matthias Posch
Making YouTube work for business. · | 2 upvotes · 2.2K views
atTubics
Mixpanel
Segment

We needed something to send our user events to. With Segment it's super easy to get started and now we can change to whatever data destination we want. Currently Mixpanel, but now the product team can change that, without any source code change!

See more

Segment's features

  • A single API to integrate third-party tools
  • Data replay that backfills new tools with historical data
  • SQL support to automatically transform and load behavioral data into Amazon Redshift
  • More than 120 tools on the platform
  • One-click to install plugins for WordPress, Magento and WooCommerce
  • Mobile, web and server-side libraries

Segment Alternatives & Comparisons

What are some alternatives to Segment?
Google Tag Manager
Tag Manager gives you the ability to add and update your own tags for conversion tracking, site analytics, remarketing, and more. There are nearly endless ways to track user behavior across your sites and apps, and the intuitive design lets you change tags whenever you want.
Astronomer
Astronomer is a data engineering platform that collects, processes and unifies enterprise data so you can get straight to analytics, data science and insights. Astronomer Clickstream captures valuable user events and routes them straight to all your favorite tools or a data warehouse for analytics. All in real time.
Avo
A code-generated, type-safe tracking library to accurately implement analytics events that are defined and maintained in a single-source-of-truth web app. Built to optimize the experience of maintaining and version controlling complicated event schemas.

Segment's Stats

- No public GitHub repository available -