Snowplow vs. Segment

How does Segment – a Customer Data Platform (CDP) – compare to a Snowplow Behavioral Data Platform (BDP)?

What’s the difference
between Snowplow and
Segment?

Segment is a useful tool for the right user – however, it is struggling to keep pace with trends in the data space. Notably the emphasis on data privacy and ownership, the demand for transparency and OS tech, and the wide adoption of Cloud Data Warehouses.

As such, it is on the verge of being branded a legacy technology. Its value proposition of harnessing the complexity of customer data amidst the explosion of SaaS platforms over the last couple of decades – while initially compelling – is now showing its age with the emergence of best-in-class tooling across the Modern Data Stack.

Implicit in Segment’s focus on sending data to hundreds of downstream apps is that the data warehouse becomes just one of many destinations. As organisations have coalesced around cloud data warehouses as their central source of truth, they have begun to feel frustrated with Segment’s limitations. The data it delivers is not fit for purpose, and in many cases serves as an active blocker to aspirations for behavioural data.

If you are building for complexity and growth, Snowplow is definitely the better option.

“I’ve never seen engineers and marketing people talk to each other as much as they are right now. We’ve just touched the surface with Hightouch, Snowplow and Braze. I am super excited to see what’s possible.”

DARREN HAKEN | HEAD OF ENGINEERING, AUTO TRADER

Key Snowplow Features

True real-time latency
Get data to your storage destination in as little as 5 seconds to create use cases such as real-time recommendations.
Quality assurance
Trial tracking in a sandbox environment – like software testing. Data is also pre-validated with JSON schemas to ensure quality.
Easy to query
Create a single, unified table, which can be easily queried.
Private SaaS deployment
Deploy our technology directly into your own cloud environment – customer data is not stored by Snowplow.
True first-party cookies
Snowplow allows you to understand your customers’ behaviour during their anonymous journeys, maximising the efficiency of your marketing funnel.
AI & BI ready data
Snowplow lands data in your storage destination in an AI- and BI-ready state, saving an enormous amount of time cleaning and wrangling data to get it to operational quality.

Snowplow vs Segment Overview

Choose Snowplow for:
  • Future proofing your modern data stack
  • Advanced analytics and AI use cases with a composable CDP
  • A strong focus on data ownership, compliance and governance
Choose Segment for:
  • Marketing teams simply looking to get data from A to B
  • Small companies unaffected by the monthly-tracked-user pricing
  • Sending data immediately to 3rd-party tools – often unfiltered and without adopting centralized storage

Warehouse and lake-first analytics

The warehouse is becoming the center of data gravity, with the global data warehousing market set to be worth $30 billion by 2025 (Global Market Insights).

In terms of data modeling in the warehouse, Snowplow is the third-largest publisher of dbt models on the planet, after dbt and Fivetran.

Companies are realizing the benefits of centralized data storage in order to create trust in data and build sophisticated data applications.
Snowplow was built for this purpose from the ground up – we get the highest quality data from any source into your cloud storage destination – lake or warehouse.
While Segment can load to centralized storage, the structure and quality of the data are not good enough to effectively scale up your data projects and create a reliable source of truth – it is designed to forward data not store it.

Compliance

Segment stores your data
The best practice for first-party data is to be stored in a warehouse, not a third-party SaaS platform. The fact that your data is kept on Segment’s servers means you do not have complete control over your data.
Data-subject requests
The fact that Segment stores your data presents a potential risk around responding to data-subject requests. Customers have to rely on Segment to delete data on their behalf.
Understanding your data
Snowplow is designed to achieve the structure and flexibility needed to operate effectively in an increasingly complicated era for data compliance. Segment creates confusion by producing poorly understood data, potentially leading to compliance issues.

Composable CDPs are replacing CDPs

A Composable CDP consists of the same components as an off-the-shelf CDP like Segment: Data Collection, Data Storage/Modeling, and Data Activation, however, each stage is provided by a best-in-class tool, avoiding many of the issues with packaged CDPs.

Sophistication: by implementing a best-in-class product at each layer of the Composable CDP, organizations can achieve a far more extensible CDP solution that can solve problems well beyond the common use cases of off-the-shelf CDPs.
Customization: with a Composable CDP, you can determine the events and entities that match your business and decide how your data is modeled for activation, rather than relying on a ‘paint-by-numbers’ approach.
Future-proofing: composable CDPs are future-proof by design, allowing you to avoid the vendor lock-in and one size fits all approach associated with off-the-shelf CDPs by hand picking every element in your data stack.

Avoid Segment MTU pricing

There are many benefits to event-based pricing

Fairness

MTU-based pricing: highly engaged and monetizable users cost the same to track as users that have interacted with your product just once.

Event-based pricing: cost scales with the value of the user. Low-value users (e.g., that bounce) generate few events and so cost little to track.

Predictability

MTU-based pricing: browser restrictions – e.g., ITP – disrupt joining the customer journey and favor the Vendor by inflating the number of monthly tracked users.

Event-based pricing: more predictable due to wide event bands and less likely to incur the cost of unfair overages.

Scalability

MTU-based pricing: customers can suffer punitive averages or huge contract value increases on renewal.

Event-based pricing: cost per event decreases with volume as the bands get wider (1m-5m, 5m-10m and so on).

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