Sold by: SnowplowÂ
Deployed on AWS
Unlock the full potential of your data with Snowplow's Customer Data Infrastructure (CDI) for AWS - the key to eliminating data silos, optimizing costs, and leveraging AWS's powerful ecosystem for advanced analytics, real-time operations, and AI workloads.
Overview
Snowplow on AWS allows you to leverage your behavioral data in any lake, real-time stream, or analytical workload. Snowplow Customer Data Infrastructure is a privacy-centric solution deployed in the client's VPC and Amazon sub-account. It offers comprehensive behavioral data collection, enrichment, and governance capabilities, eliminating data silos by gathering information from various first-party data sources (websites, mobile apps, etc).
Snowplow offers cost-effective data management by storing diverse data sets (structured, unstructured, semi-structured) in S3 object storage and leveraging AWS Glue as a cataloging method. Snowplow CDI also leverages Amazon Kinesis to process and operationalize large streams of data into other AWS services and/or external platforms, focusing on interoperability and scale. The solution democratizes access to data across analytics, data science, and other workstreams.
In storing and processing your most valuable asset, first-party customer data, businesses can rely on a Snowplow + AWS foundation within their data stack, avoiding downstream vendor lock-in for various workloads, and ultimately future-proof their business for an AI-centric architecture.
Highlights
- Thousands of companies like Burberry, Strava, and Auto Trader use Snowplow to generate AI-ready data to uncover deeper customer journey insights, predict customer behaviors, personalize customer experiences, and detect fraud.
Details
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Delivery method
Deployed on AWS
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Features and programs
Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
Pricing is based on the duration and terms of your contract with the vendor, and additional usage. You pay upfront or in installments according to your contract terms with the vendor. This entitles you to a specified quantity of use for the contract duration. Usage-based pricing is in effect for overages or additional usage not covered in the contract. These charges are applied on top of the contract price. If you choose not to renew or replace your contract before the contract end date, access to your entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/12 months |
|---|---|---|
BDP Enterprise | Guide price is dependent on event volumes, SLAs & support requirements | $37,500.00 |
Dimension | Cost/unit |
|---|---|
Additional Overage Fees | $0.10 |
Vendor refund policy
All fees are non-cancellable and non-refundable except as required by law.
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA)Â .
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Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
Software as a Service (SaaS)
SaaS delivers cloud-based software applications directly to customers over the internet. You can access these applications through a subscription model. You will pay recurring monthly usage fees through your AWS bill, while AWS handles deployment and infrastructure management, ensuring scalability, reliability, and seamless integration with other AWS services.
Resources
Vendor resources
Support
Vendor support
Additional support information available at https://docs.snowplow.io/docs/ Support offered 24/7 via support@snowplow.io .
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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Sentiment is AI generated from actual customer reviews on AWS and G2
Functionality
Ease of use
Customer service
Cost effectiveness
Positive reviews
Mixed reviews
Negative reviews
AI generated from product descriptions
Data Collection Infrastructure
Comprehensive behavioral data collection from multiple first-party sources including websites and mobile applications
Data Processing Framework
Supports processing of structured, unstructured, and semi-structured data sets using AWS Glue for data cataloging
Stream Processing Capability
Utilizes Amazon Kinesis for real-time data processing and operationalization across AWS services and external platforms
Privacy-Centric Architecture
Deployed within client's VPC and Amazon sub-account with built-in data governance and privacy controls
Data Storage Optimization
Leverages S3 object storage for cost-effective and scalable data management across diverse data types
Data Source Integration
Native connectors to multiple data sources with API integration capabilities and pre-built workflows
Data Processing Engine
Advanced data processing capabilities including decoding, normalization, data quality verification, aggregation, and correlation
Workflow Management
Flexible technical building block assembly with user-friendly interface and data flow lifecycle visualization
Kubernetes Deployment
Cloud-native architecture designed for deployment and operation on Kubernetes infrastructure
Data Enrichment
Capability to correlate, bind data to subscriber profiles, and enrich information based on defined business criteria
Data Platform Architecture
Unified platform integrating data engineering, analytics, business intelligence, data science, and machine learning on a single architecture
Open Source Foundation
Built on open source data projects with support for open standards and data formats
Lakehouse Infrastructure
Provides a common data management approach using a lakehouse architecture running on Amazon S3
Data Intelligence Engine
Advanced engine capable of interpreting organizational data context and enabling broad data access across teams
Collaborative Workflow
Native collaboration capabilities enabling cross-functional data and AI workflow integration
Standard contract
No
No
Customer reviews
0 ratings
0 AWS reviews
|
6 external reviews
Star ratings include only reviews from verified AWS customers. External reviews can also include a star rating, but star ratings from external reviews are not averaged in with the AWS customer star ratings.
Darren H.
A great product to help you with user event collection and tracking
Reviewed on Apr 24, 2019
Review provided by G2
What do you like best about the product?
- Access data in real time
- It's an open platform
- Snowplow as a company is great to work with
- It's an open platform
- Snowplow as a company is great to work with
What do you dislike about the product?
- You need to work on creating the reporting layer. It's understandable but it still puts ownership onto the team using it.
What problems is the product solving and how is that benefiting you?
- User analytics
- Experimentation
- ML-based products such as recommender systems.
- Experimentation
- ML-based products such as recommender systems.
Recommendations to others considering the product:
- Engage with Snowplow as a provider, they really know their product and the surrounding ecosystem really well.
Jeroen V.
Best event analytics platform
Reviewed on Mar 28, 2019
Review provided by G2
What do you like best about the product?
The scalability and full control of collected event data. As a Snowplow partner we enable our customers to gain full control of their data collection and store massive amounts of behavioral event data in their own data warehouse for further analysis. Unlike analytics platforms as GA(360) or Adobe Analytics, Snowplow is able to scale to the volume and variety of data with keeping the size and data strategies companies who work with Snowplow in mind.
What do you dislike about the product?
Snowplow can be complex in setup. It can be hard to make the right decisions for collector, enrichment, etc based on requirements.
What problems is the product solving and how is that benefiting you?
With implementing Snowplow we enable customers to work with comprehensive data, collected, transformed and stored in their own data platform like AWS. Using this rich data we help companies to answer all sorts of data challenges, from basic marketing intellegence to data science models
Frode J.
Up and running in hours
Reviewed on Mar 14, 2019
Review provided by G2
What do you like best about the product?
Great open source project for a streaming data pipeline. It only took a couple of hours to get running on Google Cloud Platform. A few more hours and we are setup with several trackers for webpages and ad units, including custom events.
There were public guides on how to setup the system and that made the process a lot easier than if we would have to follow just the documentation.
The system comes with some data enrichments and most of our needs were covered. With their API enrichment option we can also enrich the data from our internal API´s.
There were public guides on how to setup the system and that made the process a lot easier than if we would have to follow just the documentation.
The system comes with some data enrichments and most of our needs were covered. With their API enrichment option we can also enrich the data from our internal API´s.
What do you dislike about the product?
We have GDPR requirements and it does not look like we can have IP anonymization that triggers before events are dumped in storage. But this is being worked on according to some issues.
This is not your plug and play saas solution with rich UI and one-click installers. You need to get your hands dirty, but you alos
This is not your plug and play saas solution with rich UI and one-click installers. You need to get your hands dirty, but you alos
What problems is the product solving and how is that benefiting you?
We wanted to do custom event tracking of ad units and webpages and get a faster and more precise output of the data. This allow our clients to see their performance in near realtime and for us to run analysis across clients.
Recommendations to others considering the product:
Solid open source project that was easy to test, and that met our criteria.
Robert K.
A highly extensible event analytics platform you can trust
Reviewed on Mar 06, 2019
Review provided by G2
What do you like best about the product?
- High fidelity, comprehensive web tracking out of the box
- Create new types of events & enrichments to use (not forced into using GA's limited custom dimensions or messy schema-less JSONs of other platforms)
- Great documentation & community backing
- Own your data
- Able to retroactively apply business logic to data and reports
- Create new types of events & enrichments to use (not forced into using GA's limited custom dimensions or messy schema-less JSONs of other platforms)
- Great documentation & community backing
- Own your data
- Able to retroactively apply business logic to data and reports
What do you dislike about the product?
- Lack of well supported Google Ads integrations
- Slow release cycle on some enrichment data (e.g. custom referrers, user agents)
- Difficulty of working within Scala to customise the pipeline (no one in our organistaion knows Scala)
- Amazon EMR runner slow & expensive to start for batch processing flows
- Slow release cycle on some enrichment data (e.g. custom referrers, user agents)
- Difficulty of working within Scala to customise the pipeline (no one in our organistaion knows Scala)
- Amazon EMR runner slow & expensive to start for batch processing flows
What problems is the product solving and how is that benefiting you?
We help companies plan, build, run and analyse large experiments on their properties - Snowplow is a fundamental part of what we do.
Many testing companies limit themselves to tracking experiments in tools like Optimizely and constrict their analysis to what they track inside that tool. With Snowplow Analytics we've expanded our experiment metrics to optimize for highly bespoke things for our clients such as:
- Decreasing delivery distance for an ecommerce site
- Increasing the variety of fields and values interacted with on a financial institution's calculators
- Measuring site speed impacts of experiment variants on actual users
It also enables us to build and run personalisation experiments for clients which we wouldn't be able to easily build in other platforms (like GA):
- "This place is popular with 24 sales in the last day."
- "We noticed you left this product in your cart, return to checkout?"
Many testing companies limit themselves to tracking experiments in tools like Optimizely and constrict their analysis to what they track inside that tool. With Snowplow Analytics we've expanded our experiment metrics to optimize for highly bespoke things for our clients such as:
- Decreasing delivery distance for an ecommerce site
- Increasing the variety of fields and values interacted with on a financial institution's calculators
- Measuring site speed impacts of experiment variants on actual users
It also enables us to build and run personalisation experiments for clients which we wouldn't be able to easily build in other platforms (like GA):
- "This place is popular with 24 sales in the last day."
- "We noticed you left this product in your cart, return to checkout?"
Recommendations to others considering the product:
You'll need to have analysts familiar with SQL, R and Python to make the most of it.
Consider a good dashboarding tool like Superset to help non-technical stakeholders to make use of the data.
Keep Google Analytics around because agencies and even many internal users will be familiar with GA.
If you encounter errors or issues, you can most likely Google the answer or get a speedy response back from the community forums.
Consider a good dashboarding tool like Superset to help non-technical stakeholders to make use of the data.
Keep Google Analytics around because agencies and even many internal users will be familiar with GA.
If you encounter errors or issues, you can most likely Google the answer or get a speedy response back from the community forums.
Mike R.
Must have for scaling your product with confidence
Reviewed on Feb 23, 2019
Review provided by G2
What do you like best about the product?
Complete control over the data/pipeline and the ability to model the data in any way you see fit. The support team is fantastic, responsive, and knowledgeable.
What do you dislike about the product?
No true drawbacks. Moving from Segment or Mixpanel you might have to adjust to the structure in which event data is transmitted, but that's to be expected when transitioning to almost any analytics platform.
What problems is the product solving and how is that benefiting you?
Full funnel optimization, looking for user trends based on marketing/campaign/ad source, A/B test result validation. Also enhances the ability to help resolve customer support requests. Snowplow data is used in almost every product decision.
Recommendations to others considering the product:
Make sure to have a plan/convention when implementing any of the trackers. This will make your life much easier when you start to analyze the data in Redshift with your BI tool.