Segment vs. Hightouch: Choosing the Right Customer Data Platform

Today, businesses need a Customer Data Platform (CDP) to manage their customer information. A good CDP should fit easily with your current tools, make customer experiences better, and be simple to set up. When picking a CDP, Segment and Hightouch are the top two contenders. Our CDP guide takes a closer look at these platforms, explaining how they solve customer identity, track user actions, create customer groups, and move data around.

Key Takeaways

• Integration: Segment’s pre-configured, real-time integration saves time, while Hightouch’s customization offers high precision but requires more resources.
• Identity Resolution: Segment is known for real-time identity resolution and dynamic customer profiling, while Hightouch provides precise, warehouse-based profiling.
• Pricing: Segment offers a scalable, user-based pricing model; Hightouch’s usage-based model may lead to higher costs for growing data needs.
• Staffing: Segment reduces operational costs with minimal technical resource requirements. Hightouch demands specialized engineering expertise.
• Reverse ETL: Segment provides comprehensive and flexible capabilities, whereas Hightouch specializes in efficient warehouse-to-tool data transfers.

Segment vs. Hightouch: Which CDP is Best for Your Business?

Segment is a top leader in Customer Data Platforms (CDPs). It can connect to over 150+ different data sources and delivers customer data quickly with little need for technical help. Segment is great for marketers because they can use the data easily without requiring a giant data engineering team.

 

 

Hightouch is known for its strong Reverse ETL (RETL) features and its ability to handle data from data warehouses. It’s great at turning raw data from warehouses into useful information for different business tools.

 

Let’s take a closer look at each platform.

Data Source Diversity: In practice, Segment supports JavaScript (analytics.js), iOS, Android, server-side libraries (Node, Python, Go, Ruby), and well over 150+ data sources. This library ecosystem speeds up and simplifies integration.

Segment can send data from these tools to your data warehouse, or pipe it directly between systems to support real-time tracking and integrations.

Moreover, Segment can also import non-event data, such as campaign spend data from Google or Meta Ads, into a data warehouse, effectively acting as an ETL tool.

Hightouch has recently added the ability to collect data from websites and a handful of other sources, and send them to some key destinations; however, this is only available on the “Business” plan and isn’t truly real-time in that syncs happen sub-hourly. For most use cases, Hightouch really only takes data from your databases and warehouses.

Deployment Models: If your team already has a mature data lake or data warehouse and wants to limit adding another data-collection layer, Hightouch’s model could be more attractive. Conversely, if you want real-time streaming from apps or websites, Segment’s event-based approach fits better.

High-Level Functional Capabilities

Segment:

Segment manages everything from data collection to audience activation. It seamlessly integrates marketing, operational systems, custom integrations, and warehouse-sourced data for a 360-degree view of customer interactions.

Hightouch:

Hightouch operates within a warehouse-first paradigm. It necessitates custom data preparation by data engineers, adding steps to data ingestion, preparation, and transformation, which can affect real-time data processing. There is little or no data collection capability.

Key Takeaway: For businesses seeking speed and flexibility with limited data engineering support, Segment offers a streamlined approach. Hightouch is only appropriate for companies with robust data engineering resources or who require precise control over warehouse data.

 

For Developers:

• Event Ingestion Methods: In Segment, events can be ingested via client-side libraries (e.g., analytics.js), server-side (e.g., Node.js) or Cloud Object sources (e.g. Google Ads). Hightouch doesn’t ingest events in real time; it primarily syncs pre-existing data from your warehouse to marketing tools.
• Engineering Resource Usage: With Hightouch, data engineers often define transformation logic in the warehouse using SQL or dbt. Segment offers a GUI-based approach to transformations, as well as optional code-based “Functions” and “Protocols” for advanced use cases.

Data Capture and Real-Time Integration

Segment:

Supports over 150+ data sources and 400+ destinations. It facilitates real-time data activation, audience building, and analytics. Most integrations are pre-configured, allowing CDP admins to connect sources quickly without additional coding.

Hightouch:

Each new data source integration requires developer and data engineer involvement, making it resource-intensive for teams handling high data variability. The challenge with a data warehouse first strategy is that the data needs to get into the data warehouse in the first place. This means creating event streams either manually, or via ETL tools like FiveTran; something that Segment can handle entirely.

Key Takeaway: Segment’s plug-and-play integration is perfect for fast-paced environments. Hightouch is better suited for businesses with consistent data sources and dedicated engineering teams.

Data Preparation and Flexibility

Segment:

Can capture data from diverse sources without extra preparation. Segment streamlines data workflows, so teams don’t have to take extra, time-consuming steps to prepare data. As for warehouse data, Segment’s preparation is on par with Hightouch’s.

Hightouch:

Demands extensive data preparation from engineers, making it less accessible for non-technical teams and slower to implement new data sources.

Key Takeaway: Segment’s low-preparation data capture saves time and is more accessible for non-engineering users. Conversely, Hightouch’s reliance on prepared data ensures precision but reduces agility.

Identity Resolution and Customer Profiling

Segment:

• Advanced Identity Resolution: Segment excels in real-time identity resolution, seamlessly merging customer data from multiple sources to create a unified customer profile. It leverages deterministic and probabilistic matching techniques to ensure accuracy and completeness.
• Client-Side Eventing: Segment provides robust client-side tracking capabilities, allowing businesses to capture detailed user interactions directly from their websites and applications. This includes tracking page views, clicks, form submissions, and other user behaviors in real-time, enabling a granular understanding of customer journeys.
• Customer Profiling: With automatic and real-time updates, Segment builds comprehensive customer profiles that include behavioral data, transactional history, and engagement metrics. These profiles are continuously enriched and can be segmented dynamically for targeted marketing campaigns.

Hightouch:

• Manual Identity Resolution: Hightouch’s identity resolution requires significant engineering effort each time a new data source is integrated or when data models are adjusted. This process involves configuring mappings and ensuring consistency across various datasets.
• Client-Side Tracking Limitations: While Hightouch can handle client-side data, it typically relies on the data already ingested into the warehouse. This means that real-time client-side eventing needs to be pre-processed and may not be as instantaneous as Segment’s native capabilities.
• Customer Profiling: Hightouch builds customer profiles based on the data prepared and managed within the data warehouse. This offers high precision but lacks the real-time dynamism seen with Segment’s approach.

Key Takeaway: Segment’s advanced and real-time identity resolution, combined with robust client-side eventing, provides a competitive edge for businesses requiring immediate insights and comprehensive customer profiling. Hightouch offers precise identity resolution within a controlled warehouse environment but demands more labor-intensive setup and maintenance.

 

For Developers:

• Matching Logic: In Hightouch, identity resolution might rely on custom SQL joins (e.g., email or user_id fields). Segment automatically merges user traits via track, identify, and alias calls.
• Event vs. Profile Stores: Segment maintains a centralized profile store for each user, which updates automatically. In Hightouch, the “profile” concept is purely derived from warehouse tables/views.

Audience Creation Comparison

Segment:

• User-Friendly Audience Builder: Segment offers an intuitive interface for creating and managing audiences without needing extensive technical knowledge. Users can define segments based on various customer attributes and behaviors, facilitating targeted marketing and personalized experiences.
• Dynamic Segmentation: Audiences in Segment can be dynamically updated in real-time as new data flows in, ensuring that marketing campaigns always target the most relevant segments.
• Integration with Marketing Tools: Segment seamlessly integrates with a wide range of marketing tools, allowing audiences to be pushed directly to advertising platforms, email marketing systems, and more with minimal configuration.

Hightouch:

• Engineering-Driven Audience Creation: Hightouch’s audience creation is tightly integrated with the data warehouse, requiring data engineers to define and manage segments. This approach ensures high precision and customizability but can slow down the process of audience definition and iteration.
• Static Segmentation: Audiences in Hightouch are typically based on pre-defined queries and data models, making them less dynamic compared to Segment’s real-time segmentation capabilities.
• Direct Data Activation: Hightouch excels in pushing data directly from the warehouse to business tools, ensuring that audiences are always based on the most up-to-date and accurate data available within the warehouse.

For Developers:

• Custom Query Logic: With Hightouch, you can define a segment with raw SQL or dbt. This is excellent for teams that want granular control, but it requires SQL knowledge. In Segment, you can build “Traits” or “Audiences” via a GUI or programmatically via an API.
• Real-Time Updates: Segment can push new user data in seconds to your chosen destinations. Hightouch typically updates on a schedule (though near-real-time syncs are possible at a higher cost or with specialized setups).

 

 

Key Takeaway: Segment’s user-friendly and dynamic audience creation tools empower marketing teams to swiftly define and leverage customer segments without heavy reliance on engineering. Hightouch provides highly customizable and precise audience creation through engineering-driven processes, ideal for teams that prioritize data accuracy and have the resources to manage complex setups.

 

Reverse ETL and Data Delivery

Segment:

• Comprehensive Reverse ETL: Segment supports Reverse ETL, allowing data to flow from the warehouse back to operational tools. This includes zero-copy delivery, which minimizes data storage costs by avoiding redundant data copies.
• Flexible Data Delivery: Segment can handle both real-time data streams and batch data processes, offering a mix of database and real-time user information. This flexibility ensures that businesses can tailor data delivery to their specific needs.
• Built-In Profile Databases: Segment includes built-in profile databases that facilitate easy data synchronization and reduce the need for additional data management infrastructure.

Hightouch:

• Focused Reverse ETL: Hightouch specializes in Reverse ETL, efficiently transferring data from warehouses to various business tools. However, it lacks built-in profile databases, which can restrict its flexibility in certain use cases.
• Data Dependency: Hightouch relies heavily on the data already present in the warehouse, making it less adaptable to scenarios requiring real-time data adjustments or profile enrichment.
• Operational Constraints: The absence of built-in profile databases means that businesses need to manage data synchronization and profile updates separately, potentially increasing complexity and operational overhead.

For Developers:

• Segment “Warehouse Syncs”: You can have data flow from Segment into a cloud warehouse (Snowflake, BigQuery, etc.) and then use Segment again to push that data to other tools (bi-directional sync).
• dbt Integration: Hightouch pairs well with dbt to orchestrate transformations and tests before data is sent to marketing tools. Segment’s focus is on real-time forwarding, though you can incorporate dbt if you store Segment data in a warehouse.

Key Takeaway: Segment’s comprehensive and flexible Reverse ETL capabilities, combined with built-in profile databases, make it an ideal choice for companies seeking scalable and cost-effective data delivery solutions. Hightouch’s focused Reverse ETL is powerful for warehouse-centric data strategies but may require additional infrastructure for profile management and real-time data needs.

Schema and Data Modeling

Segment:

• Dynamic Schema Management: Segment provides dynamic grouping and data modeling capabilities, accommodating both warehouse and direct sources. This flexibility allows businesses to adapt their data schemas as their needs evolve without extensive reconfiguration.
• Automated Data Mapping: Segment automatically maps incoming data to predefined schemas, reducing the need for manual data modeling and ensuring consistency across different data sources.

Hightouch:

• Pre-Defined Schemas: Data schemas to be prepared within the data warehouse prior to ingestion. Any changes in data sources or structures necessitate schema redefinition and data model adjustments.
• Structured Data Focus: This approach ensures high data integrity and consistency but limits flexibility, making it less suitable for rapidly changing data environments.

For Developers:

• Segment Protocols: For advanced governance, you can define a “tracking plan” in Segment’s Protocols to ensure incoming events match expected fields, data is formatting accurately, and flag errors as soon as they arise. This is helpful for large engineering teams that want standardization.
• Warehouse Modeling: Hightouch typically integrates with your existing warehouse schema. If you rename columns or change table structures, you must also update Hightouch syncs accordingly.

Key Takeaway: Segment’s dynamic schema management and automated data mapping offer significant advantages for growing businesses that require adaptable and scalable data models. Hightouch’s structured, pre-defined schemas provide robust data integrity, making it suitable for environments where data sources and structures remain relatively stable.

Cost Structure and Optimization

Segment:

• Scalable Pricing Model: Segment’s pricing is based on active users or tracked events, independent of the number of data sources or destinations. This model allows businesses to scale their CDP usage without incurring additional costs for expanding data integrations.
• Cost-Effective Scaling: As CDP needs grow, Segment remains cost-effective, enabling businesses to add more users and events without worrying about escalating costs tied to data sources or syncs.

Hightouch:

• Usage-Based Pricing: Hightouch charges based on data usage and warehouse operations. As the number of data sources and syncs increases, costs can rise significantly, especially for larger datasets.
• Potential for Higher Costs: Businesses with extensive data needs or those rapidly expanding their data sources may face higher operational costs with Hightouch’s pricing model.

For Developers:

• Event vs. Table Sync Costs: Segment costs can spike if your monthly tracked events climb sharply. Hightouch costs can climb if you’re syncing large tables with tens of millions of rows to multiple destinations.
• Optimization Strategies: Use Segment’s “Selective Sync” or event filtering to control which events and properties get forwarded. In Hightouch, refine your SQL or dbt models to reduce unneeded columns/rows.

Key Takeaway: Segment’s user-based pricing model offers efficient scalability, making it a cost-effective choice for businesses anticipating growth in user base and event tracking. Hightouch’s usage-based pricing may lead to higher costs as data requirements expand, making it better suited for organizations with stable or predictable data needs.

Staffing and Operational Costs

Segment:

• Minimal Technical Resources Needed: Segment requires fewer technical resources, enabling CDP administrators and marketing teams to handle most functions without extensive engineering support.
• Lower Staffing Costs: By empowering non-technical teams to manage core CDP functions, Segment reduces the need for large data engineering teams, lowering overall staffing and operational costs.

Hightouch:

• Engineering-Dependent Operations: Hightouch necessitates a dedicated data engineering team to manage data capture, preparation, and integration processes. This increases the complexity and cost of staffing.
• Higher Operational Investment: The requirement for specialized technical expertise can lead to higher operational costs, making Hightouch a more resource-intensive option.

For Developers:

• Team Roles: A “Segment admin” could be a marketing ops or product manager with moderate technical skills. A “Hightouch admin” is often a data engineer with SQL/ELT knowledge.
• Maintenance Overhead: Hightouch syncs can break when warehouse schemas evolve. Segment typically auto-adjusts unless your tracking plan is extremely strict.

Key Takeaway: Segment’s operational ease and minimal reliance on technical expertise make it a cost-effective solution for businesses looking to reduce staffing expenses. Hightouch’s model, requiring significant engineering involvement, suits organizations that can invest in specialized data teams to manage their CDP infrastructure.

Detailed Comparison: Operational Needs and Expertise

Segment:

• User-Centric Data Handling: Allows business users to manage data capture while CDP administrators oversee audience building and identity resolution. Developers are only needed for API integrations, simplifying the overall operational workflow.
• Real-Time Data Ingestion: Ensures that even with partial data availability, Segment can fill gaps through real-time ingestion, providing a comprehensive and up-to-date dataset seamlessly synced with your data warehouse.

Hightouch:

• Engineering-Driven Workflow: Requires mid-level developers for data capture, senior data engineers for data preparation, and business users for audience building. This multi-tiered approach ensures precision but increases the complexity of operations.
• Dependency on Data Warehouse: If a data warehouse is not already in place, implementing Hightouch can be challenging and time-consuming, often requiring a multi-year initiative. However, for businesses with mature data warehouse strategies, Hightouch can offer immediate value through seamless data activation.

For Developers:

• Workflow Automation: With Segment’s UI and API, you can automate environment management (dev, staging, prod) for each source. Hightouch typically relies on your data warehouse’s environment (development, staging, production schemas).
• Time to Value: Setting up a new tracking plan or source in Segment can take hours or days. For Hightouch, you need to ensure your warehouse data is fully modeled and tested first, which might take weeks for new data sets.

 

 

Final Verdict: Segment’s operational simplicity reduces dependency on extensive technical expertise, making it accessible for a broader range of businesses. In contrast, Hightouch’s engineering-centric model demands more specialized resources, making it suitable for organizations with established data engineering capabilities.

Which CDP is Right for You?

Both Segment and Hightouch bring unique advantages to the table:

Choose Segment if:

• Your business requires flexible data sources and dynamic schema management.
• You prefer low-preparation data handling with minimal technical dependencies.
• Easy access to reporting and analytics for non-technical users is a priority.
• You seek a scalable and cost-effective pricing model based on active users or events.
• You aim to minimize staffing and operational costs by empowering non-technical teams.

Choose Hightouch if:

• You have a dedicated engineering team with robust data engineering resources.
• Precise data control within a warehouse-first environment is essential.
• Your data sources are stable and require meticulous preparation and transformation.
• You need advanced Reverse ETL capabilities tailored for warehouse-sourced data.
• Your organization can manage the higher operational and staffing costs associated with Hightouch’s model.

 

Let McGaw Help You Decide

Selecting the right CDP is a major decision. It’s one that can significantly impact your data strategy and business outcomes. So, if you’re not sure which platform aligns best with your needs, we’re here to help. Our experts will help you assess your data requirements, budget constraints, and technical resources to identify the ideal CDP that maximizes your data operations and drives your business forward.

Contact McGaw today to discover the perfect CDP for your business and elevate your data strategy to the next level.