Introducing Try Snowplow: a free BDP Cloud trial experience

When users first try Snowplow, there is often a delay before they get that ‘a ha’ moment.

The reason for this is that we structure data in a unique way, which many users may not be familiar with, but which makes working with data far easier. It also makes it easier to conduct advanced analytics and AI to answer more challenging business questions.

The data contains well over 100 additional contextual fields out of the box and can be further enhanced in real time to suit your business needs.

To allow more people to realise the power of this ultra-granular data, we introduced ‘Try Snowplow‘ – a free trial.

You can collect data from your websites and mobile apps within 30 minutes.

A new way to experience Snowplow

Try Snowplow is a small version of the Snowplow technology that can be setup quickly and easily. It’s the simplest way to trial Snowplow and experience its best-in-class data collection!

With Try Snowplow you can collect granular, well-structured data from your digital products and model, analyse and visualize it in your BI tool of choice. You can also explore the recipe library and see how Snowplow approaches common data use cases such as marketing attribution, product analytics or building a single customer view. You can try these recipes using real data from your digital products and pilot how Snowplow can empower you to solve your data use cases.

Why did we develop Try Snowplow?

We have known for a long time that there are a large number of people, especially data practitioners, who are interested in learning more about Snowplow and understanding how it was different to other approaches to collecting behavioral data. However, the only options for getting started were either long (Snowplow Open Source), expensive (Snowplow BDP) or very limited in what you can do with the data (Snowplow Mini and Snowplow Micro). Specifically, we wanted to create something small like Mini, but that would give the person trying the technology the opportunity to work with the data in SQL, to model the data and actually try out different use cases with it, to “bring the data to life”.

What do I need to get started?

A website or digital product to instrument tracking on

You’ll also need to decide where you want to deploy the Snowplow tracking. There is a tutorial for setting up web tracking, but you can use any of Snowplow’s web, mobile or server side trackers! And once you are collecting data, you can then decide how you want to access the data;  you can use any BI tool of your choice or you can connect with a SQL GUI.

Setting up Try Snowplow

The whole setup should take less than 30 minutes and follows some simple steps that the experience will guide you through:

1. Install the infrastructure – you’ll start by deploying Snowplow technology into your cloud account, this step is mostly automated and we’ll email you once it’s complete.
2. Instrument tracking – add tracking using any Snowplow trackers to your website, mobile application or digital product to start tracking user behaviour.
3. Connect to your database – next you’ll connect your BI or query tool of choice to your database to access your data.
4. Run queries and model your data – finally run some sample queries to explore the richness and granularity of Snowplow data.
5. Explore the recipe library – once your collection is up and running you can instrument further tracking and work through some of the Snowplow use-case recipes to learn more about the power of Snowplow data.

Understanding the difference between Try Snowplow and Snowplow BDP

While Try Snowplow uses the same core technology as Snowplow BDP and Snowplow Open Source, there are a few key differences. 

Specifically, it is a minified version of the Snowplow BDP technology that is:

• fast to set up, 
• cheap to run (minimal infrastructure costs), 
• non-scalable (unsuitable for production workloads). 

An overview of the key differences is given in the table below:

	Try Snowplow	Snowplow BDP
Hosted in your own cloud	AWS (GCP coming)	AWS, GCP
First-party server cookies	✗	✓
Unlimited sources	✓	✓
Custom data structures	✗	✓
Available enrichments	3	16
Custom enrichments	✗	✓
Bad rows	✓ (no UI)	✓ (with UI)
Load data into warehouse	Postgres	Redshift, Snowflake, BigQuery
Load data into lake	✗	S3, GCS
Data available in-stream	✗	Kinesis, PubSub
Maximum throughput	50 events per second*	Unlimited
Autoscaling	✗	✓
SLAs	✗	✓
Time limit	30 days	Unlimited