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The Top Segment Alternatives and Competitors

Looking for a Segment alternative? Read on to learn more about Segment customer data platform competitors. Prefer to talk it out? Request a demo to chat with our team about the best CDP for your use case.

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Introduction

Researching and weighing the pros and cons of Customer Data Platforms can be a tedious, time-consuming task, taking hours of time that could be better spent shipping data products and making progress toward your business goals. Chances are, you have already heard of Segment, the historical leader in the legacy CDP market, and are looking for a better alternative.

In this article, we do a lot of the heavy lifting for you, providing context into the CDP landscape, giving a brief history of how Segment started, and comparing modern customer data platform competitors and Segment alternatives.

CDP overview

What is a Customer Data Platform?

A Customer Data Platform (CDP) is a software system built for customer data collection and customer data management. Its purpose is to collect customer data from various sources, unify that data by building a customer 360 with comprehensive customer profiles, and activate these profiles in downstream tools managed by marketing, product, and other organizations within a business.

The CDP adds value across a company by enabling all sorts of use cases like advanced product analytics, personalized marketing campaigns, enriched customer data in sales CRMs, and deeper customer journey analysis to enhance the customer experience from end-to-end. Many CDPs like Segment and RudderStack operate in real-time, offering immediate action and optimization to enhance customer engagement.

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What is a CDP used for?

CDPs were built for collecting first-party data (user behavior data, transactional data, etc) using event streams and ETL data pipelines, creating a deduped, 360-degree view of customers with out-of-the-box identity resolution tools, and enabling marketing and product teams to build audiences and segment users based on features they define.

From there, these audiences and segments can be analyzed in product analytics tools like Amplitude or Mixpanel, activated in marketing automation tools, and sent to advertising platforms so that digital marketing teams can ship targeted advertising campaigns, product teams can deliver personalized user experiences, and email marketing teams can send the right emails at the right time to the right users.

In short, we can think of CDPs as API integration platforms that enable businesses to collect, unify, and activate first-party data, improving the ROI of ad campaigns, increasing conversion rates on their marketing websites, and improving efficiency by decreasing customer acquisition costs and reducing churn.

Following the $3.2 billion acquisition by Twillio in 2020, Segment has become one of the most popular CDPs on the market, giving marketers the ability to make customer experiences across every channel more personalized, timely, and impactful. Since then, customer data platforms have proliferated and today, there are several competitors and alternatives to Segment to weigh before deciding on which CDP is right for your business.

Segment overview

How did Segment start?

Believe it or not, Segment (previously segment.io) started as a classroom lecture tool that CEO Peter Reinhardt and his roommates had the idea to build while studying aerospace engineering and computer science at MIT.

Founded in 2011, the idea was that the tool would allow students to signal to a professor that they were lost or confused during a presentation, then the professor could see a graph that would let them know the overall status of the class’ comprehension and thus if the lecture was missing the mark.

In December 2012, after some funding, a couple pivots, and near failure, the roommates decided to open-source a JavaScript library they had developed that offered a workaround to deal with the frustration the team had finding a single analytics platform that could deliver all the insights they wanted.

The JavaScript library gathered all the data being collected on the Segment website and then funneled it simultaneously to several analytics services. They posted the JavaScript library, dubbed simply “analytics.js”, to GitHub, began pitching it to developers, and shared it to Hacker News. The rest is history–Segment as we know it was born.

What is Segment?

Despite its humble beginnings, Segment has grown into a multi-billion dollar Customer Data Platform (CDP) for marketers that simplifies collecting and using data from the users of a company’s digital properties like marketing websites, mobile apps, web apps, etc. Segment simplifies the process of collecting data and integrating with new tools, allowing marketers to spend more time finding value in customer data, and less time trying to collect it.

Beyond collection, Segment also allows marketing teams to enrich the customer data collected by connecting data from other tools, aggregating it to monitor performance, inform decision-making processes, and create uniquely customized user experiences. You can also use other tools like Unify, Segment’s identity resolution tool, to unify data from individual users to gain a wholistic understanding of their actions.

Who Uses Segment?

Pre-Twilio acquisition, Segment was a tool built for software engineers and developers. Since the acquisition, Segment has focused primarily on the marketing persona. Segment appeals to marketers because it gives them an easy way to collect and merge different data sets to create customer profiles, enrich audiences, and activate campaigns across various tools.

Historically, engineering teams have been drawn to Segment because they don't have to spend time creating their own event tracking library and building custom integrations to all of their downstream SaaS tools.

Using Segment, developers and engineers don't have to build and maintain API integrations and data pipelines, and marketing teams can experiment quickly and launch marketing campaigns without being slowed down by data team requirements.

How Does Segment Work?

Segment solves for many use cases, but its product and features are centered around Connections, Protocols, Warehouses, Personas, Functions, and Journeys.‎

Segment Connections

Segment's Connections feature enables configurable routing of collected customer data to over 300+ platforms such as databases, analytics tools, CRMs, and more. It provides an integration layer that transforms and controls data flow to destinations through an easy-to-use UI rather than complex code setup. Connections scales to any data volume across real-time and batch transfers with built-in reliability mechanisms.

Segment Protocols

Segment's Protocols feature provides the data collection layer to bring customer data into the Segment platform across various channels. It offers tailored APIs, SDKs, libraries, and ingestion methods to capture event data from sources like web, mobile, server, CRM, and more. Protocols handles mapping, validation, idempotency, and reliability to flexibly integrate data sources using the best approach for each.

Segment Warehouses

Segment's Warehouses feature allows loading your customer data from Segment into cloud data warehouses and lakes such as Snowflake, BigQuery, and Redshift. Though Segment still stores a copy of your data in its own black box, it also provides the pipeline for efficiently moving customer data from Segment into storage optimized for analysis, machine learning, and integration with business intelligence tools. Warehouses gives flexibility to leverage your preferred warehouse provider while handling large volumes of data ingestion reliably.

Segment Personas

Segment's Personas feature automatically creates detailed profiles of your customers by unifying event data, contact profiles, and behavioral signals into a single view. It enriches profiles with over 250 pre-built traits and allows creating custom attributes to build robust customer segments and audiences. Personas serves as the customer profile management layer on top of raw data collection to drive personalized experiences.

Segment Functions

Segment's Functions feature allows transforming, augmenting, and analyzing raw customer event data within Segment before sending it downstream to other tools. It provides a serverless environment to run JavaScript code that executes business logic, profile enrichments, analytics metrics, and data formatting on customer events. Functions gives engineering teams flexibility to customize dataflows before routing to destinations.

Segment Journeys

Segment's Journeys feature enables creating multi-channel customer experiences by mapping out triggers, conditional logic, delays, data lookups, and actions across web, mobile, email, etc. It provides a visual workflow builder to model cross-channel lifecycles and orchestrate personalized messaging without engineering resources. Journeys simplifies automation of complex customer interactions tailored to each user's journey.

Segment alternatives

What are the alternatives to Segment?

Since 2012, several competitors to Segment have emerged as customer data has multiplied and the CDP space has started to gain traction in organizations from SMBs to the enterprise. The top Segment alternatives include ActionIQ, Amperity, Lytics, mParticle, RudderStack, Simon Data, Snowplow, and Tealium, each with its own benefits and differentiators. Here is what we know about each in comparison to Segment.‎

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ActionIQ

Both ActionIQ and Segment consolidate customer data from multiple sources into unified customer profiles. However, ActionIQ offers more extensive analytics capabilities like attribution modeling and prediction, while Segment focuses on data routing and workflows.

ActionIQ provides enterprise-scale customer data infrastructure for advanced use cases, whereas Segment serves broader business users. ActionIQ emphasizes insights from historical customer data while Segment powers real-time customer experiences.

Ultimately, ActionIQ suits analytics experts and data scientists while Segment appeals to marketers and business teams.

Amperity

Both Amperity and Segment ingest data to create unified customer profiles used to power experiences. However, Amperity leverages machine learning for automating customer stitching and segmentation, while Segment focuses on workflows.

Amperity provides enterprise customer data management suited for personalization, while Segment offers an easier platform for marketers. Amperity emphasizes processing historical data into actionable insights, whereas Segment routes real-time data events.

Ultimately, Amperity appeals to sophisticated users wanting advanced analytics while Segment serves broader business teams with workflows.

Lytics

Both Lytics and Segment ingest customer data from various sources to create unified profiles and power customer experiences. However, Lytics includes more built-in segmentation, personalization, and predictive modeling capabilities versus Segment's focus on data routing.

Lytics leverages first-party customer data with third-party data enrichment, while Segment relies solely on first-party data.

Overall, Lytics provides more out-of-the-box analytics for targeting and personalization while Segment offers better workflow automation across marketing channels.

mParticle

Both mParticle and Segment provide tools to collect, unify, and activate customer data from websites, mobile apps, and other sources. Segment offers an intuitive workflow builder for marketers while mParticle emphasizes the underlying data infrastructure and data quality.

mParticle focuses more on real-time data routing to various endpoints whereas Segment powers customer experiences via workflows. While both are built with marketers in mind, mParticle caters more to technical users and real-time use cases while Segment targets less technical users and workflow automation.

Simon Data

Both Simon Data and Segment consolidate customer data from disparate sources into unified profiles. However, Simon Data is focused on managing real-time customer data streams while Segment specializes in routing data to various marketing and analytics tools.

Simon Data provides an enterprise customer data engine with advanced machine learning capabilities, while Segment offers prebuilt workflows and connections. Simon Data is suited for complex real-time use cases like personalization, while Segment powers marketing workflows and analysis.

Ultimately Simon Data appeals to advanced practitioners optimizing streaming data, whereas Segment serves a broader business user base.

Snowplow

Both Snowplow and Segment collect data to create unified customer profiles. However, Snowplow is open source software suited for technical teams wanting greater control, while Segment is a proprietary SaaS platform designed for less technical users.

Snowplow involves managing your own infrastructure, while Segment handles this behind the scenes. For identities, Snowplow has configurable first-party storage options, whereas Segment uses a proprietary identity graph.

Ultimately, Snowplow appeals to engineers wanting customization despite more complexity, while Segment prioritizes ease of use for marketing teams.

Tealium

Both Tealium and Segment collect customer data from websites, mobile apps, and more to create unified customer profiles. However, Tealium offers more enterprise-scale data management capabilities while Segment is better for simpler marketing workflows.

Tealium provides robust analytics functionality out-of-the-box, while Segment requires adding separate tools for advanced analytics. Tealium is self-hosted software, whereas Segment is a multi-tenant SaaS platform.

Ultimately Tealium suits companies wanting greater control over customer data infrastructure while Segment meets basic workflow and routing needs.

Disadvantages

The Disadvantages of Legacy CDPs

Many legacy CDP vendors face challenges in flexibility, scalability, and advanced use cases. Solutions like Segment and mParticle can have complex implementation and configuration for multi-channel workflows. Tealium and Lytics may lack robust machine learning capabilities for cutting-edge personalization and segmentation.

Black-box platforms like Segment provide less control compared to warehouse-native solutions and introduce risks of vendor lock-in and limitations for customization. Legacy CDPs also tend to focus on specific capabilities like analytics (ActionIQ) or marketing (Lytics) rather than serving diverse needs.

While early CDPs solved basic data consolidation challenges, modern enterprises now require more advanced and adaptable customer data infrastructure. Legacy vendors have gaps when it comes to enterprise-grade scalability, flexibility, and machine learning capabilities compared to modern customer data platforms.

Warehouse Native CDP

Introducing the Warehouse Native CDP

RudderStack offers an innovative new approach to customer data management with the Warehouse Native CDP. This allows companies to build a flexible and secure end-to-end customer data platform directly within their cloud data warehouse.

The key advantage of the Warehouse Native CDP is it gives you full control and transparency over your customer data while leveraging the scale of your data warehouse. Rather than using a legacy CDP that stores your data in a black box, you can manage data pipelines, build unified profiles, and activate customer data all from your own Snowflake, BigQuery, or Redshift instance. This eliminates vendor lock-in and provides advanced functionality like real-time streaming, reverse ETL to data destinations, and machine learning-powered personalization.

Leading brands like Crate and Barrel and Joybird are already using RudderStack's Warehouse Native CDP to reduce costs while accelerating their ability to deliver personalized, real-time customer experiences.

The Segment Alternative: RudderStack

RudderStack's key advantages over Segment include its pricing structure, open source architecture, warehouse-native approach, and greater transparency and control. RudderStack allows you to build your customer data infrastructure directly within your own data warehouse or lake, rather than relying on Segment's proprietary database. This eliminates vendor lock-in, reduces costs, and provides full data ownership.

Additionally, RudderStack enables faster warehouse sync times, real-time data transformations, more advanced identity resolution, and reverse ETL capabilities compared to Segment. RudderStack also has more flexible pricing based on event volume rather than per monthly tracked users (MTU).

For enterprises concerned about data security and compliance, RudderStack is the clear winner. It never stores customer data, avoiding GDPR and CCPA risks. RudderStack offers more advanced monitoring, alerting, and troubleshooting features as well. With its warehouse-native architecture, RudderStack unlocks more value from data teams' existing infrastructure investments.

Overall, RudderStack provides greater openness, performance, transparency, and flexibility compared to Segment. Data teams looking to take control of their customer data choose RudderStack over Segment.

Learn more about Rudderstack vs Segment.

Learn more about Segment alternatives.

Have more questions about Segment alternatives? Meet with our team of CDP experts and find the Customer Data Platform that works for your company's needs.