In this modern era, most organizations have websites and they recognize the importance of having a digital presence. However, simply having a website is not enough, you must also ensure that it is maintained and designed in a way that attracts customers and adds value to your company. Here comes the role of Web Analytics.
Snowplow Analytics is one of the popular Web Analytics platforms that help you to manage and analyze the traffic of your website. It can also assist businesses in determining the top sources of user traffic and evaluating the success of their Marketing Campaigns. Moreover, it has gained wide acceptance in the market because of its unique features and pricing models.
This article will give you a comprehensive guide to Snowplow Analytics and its key features. You will explore the key products of Snowplow Analytics available in the market and its processing pipeline. You will also get to know about the Snowplow Analytics Pricing in the further sections. Let’s get started.
Table of Contents
- Introduction to Snowplow Analytics
- Key Features of Snowplow Analytics
- Key Products of Snowplow Analytics
- Snowplow Analytics Processing Pipeline
- Snowplow Analytics Pricing
Introduction to Snowplow Analytics
Snowplow Analytics is one of the popular alternatives to Google Analytics with some key differences. It is a Data Collection Platform that enables data teams to manage and analyze collections of data across all platforms in real-time. You can run it on Amazon Web Services (AWS) or Google Cloud Platform (GCP), depending on your preferences.
Snowplow can collect a wide range of telemetry data, but clickstream data holds a special place with many functionalities that are useful for web monitoring. In Snowplow Analytics, there are modules called Trackers that are responsible for sending data to Collectors. These Collectors are simple web servers that accept HTTP requests and then encrypt and publish all incoming data.
Once data is received by the Collector, these data can be reviewed and enriched before being loaded into the user’s Data Warehouse via the ETL (Extract, Transform, and Load) process. Some of the companies that use Snowplow Analytics include Capital One, Dollar Shave Club, Weebly, etc.
Key Features of Snowplow Analytics
Snowplow Analytics has gained wide popularity in the market because of its unique key features. Some of the key features include:
1) Complete Ownership of your Data
Snowplow provides you with complete control over the data. You can use Snowplow to include your own business rules and requirements. Moreover, when you run a query or wish to pull a report, you don’t have to send the data to Google or Adobe. Thus, giving you complete ownership of your data.
2) Collection and Warehousing of Data in Real-Time
Integrating Snowplow with Amazon Kinesis can help you to achieve a Real-Time event data platform. Real-Time data applications built on top of Snowplow data for activities like Fraud Detection, Personalization, Defect Tracking, and Short-Term Forecasting can be a game-changer.
3) Consistency Across Platforms
Because you aren’t bound by the data models of Google or Adobe, you may easily track websites, mobile applications, games, software, and even hardware based on the business logic. This configuration makes it easier to identify your users across multiple properties and analyze their behavior using data.
4) Open Source
One of the key features of Snowplow Analytics is that it is Open Source. It can make use of cutting-edge cloud services such as Amazon Kinesis, Amazon Redshift, and Elastic Map Reduce to deliver an analytics platform that scales linearly and in real-time.
5) Easy Integration
Snowplow provides a single customer view by combining data from each channel and platform. You can easily integrate Snowplow with Zendesk, Marketo, Mailchimp, etc.
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Key Products of Snowplow Analytics
Snowplow Analytics has released 2 key products. They are:
1) Snowplow Insights
Snowplow Insights is a paid Snowplow offering that comes with a fully managed Snowplow pipeline, a user interface console, and 24/7 tech support. Some of the key features of Snowplow Insights include Data Pipeline Maintenance, Autoscaling, Data Processing, and Compliance Management. Moreover, it includes a Data Quality Management tool that lets users validate lost data, identify data quality issues, and restore redundant data.
2) Snowplow Open Source
The below image depicts the features provided by Snowplow Insights and Snowplow Open Source:
Snowplow Analytics Processing Pipeline
Snowplow gathers a variety of event data, analyses it, and saves it by allowing it to flow through a Pipeline. Below is the diagram representing the Snowplow Analytics Processing Pipeline.
Snowplow Analytics Processing Pipeline consists of 6 major components. They are:
- Snowplow Tracker
- Collector Component
- Enrichment Component
- Storage Component
- Data Modeling
- Snowplow Analytics
1) Snowplow Tracker
Trackers are client-side or server-side libraries that send Snowplow events to a Snowplow collector to track customer behavior. You can also use one of Snowplow’s sixteen trackers to collect data from third parties on your website, app, or server.
2) Collector Component
After the Collector receives data from one or more trackers, it encrypts and broadcasts all data received on a message bus. Thus, the collector is a simple web server that can accept HTTP requests and then encrypts and publishes all incoming data.
3) Enrichment Component
During the Enrichment phase, Snowplow verifies incoming data to ensure it is stated in a protocol that it recognizes and then extracts and enriches event properties. The Enrichment component of Snowplow is without a doubt the most difficult and exciting part of Snowplow Pipeline.
4) Storage Component
The Storage Component is responsible for storing the messages in blob storage or a queryable Data Warehouse like Google BigQuery or Amazon Redshift. In case, the target storage is a Database, event properties map to columns.
5) Data Modeling
The basic setup of Snowplow Analytics is completed once the messages are stored in the blob storage or a Data Warehouse like Google BigQuery or Amazon Redshift. In the Data Modeling process, the following operations are performed:
- Data at the event level can be merged with data from other sources.
- Data at the event level can be aggregated into smaller data sets.
- Business logic can be applied.
The main objective of Data Modeling is to make querying easier.
6) Snowplow Analytics
This is the last stage in the Snowplow Analytics Processing Pipeline. In the Snowplow Analytics phase, the integration of modeled data and stored data takes place with:
- BI tools like Tableau, Looker, etc. for visualization and analysis purposes.
- Languages like Python and R to create statistical models.
- Search services like ElasticSearch for real-time dashboards.
Snowplow Analytics Pricing
Snowplow Analytics is an open-source platform, and the sole cost is the cost of running it on Amazon Web Services. The cost will vary based on how much data you have used and which pipeline you used. Moreover, Snowplow has launched their Total Cost of Ownership Model (TCO Model) that helps users to estimate their Snowplow Analytics Pricing based on the usage of AWS (Amazon Web Services).
This model predicts that at low volume, the Snowplow Analytics Pricing will cost $1000 per year, which reflects the cost of hosting a server to host a PostgreSQL Database for your Snowplow data. However, in the case of higher volumes, the savings are significant. For organizations recording between 10k and 100k events per month, Running Snowplow Analytics is at least an order of magnitude less expensive than GA (Google Analytics) Premium and Adobe SiteCatalyst.
Even at a billion events per month Snowplow Analytics Pricing comes out to be half of what Google Analytics Premium costs. Moreover, Snowplow Analytics Pricing comes out to be less expensive than Mixpanel, Kissmetrics, or Keen IO for anyone capturing 500K or more events. Additionally, it was observed that Snowplow Analytics Pricing is 25% less expensive to run than Mixpanel at 20 million events per month.
This article provided an introduction to Snowplow Analytics and its key features. You got a deeper understanding of the Snowplow Analytics Processing Pipeline that can help you to create an optimized pipeline. You also got to know about the Snowplow Analytics Pricing. Snowplow Analytics is an excellent tool for assisting your business in transitioning from data adolescence to data maturity.Visit our Website to Explore Hevo
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