Joao Correia
Driving Growth & Innovation With Data

With the rise of AI, ML and data science, the importance of owning and having full control over your data has increased, as data is one of the crucial ingredients to these disciplines.

In this post, we'll explore the top reasons why an increasing number of companies are looking to Snowplow as an alternative/complement to conventional SaaS analytics providers like Google Analytics 360, Adobe Analytics, Segment, and Heap.

Top 7 reasons for adopting Snowplow Analytics

  1. 1. Analytics Maturity
  2. 2. Current vendor fatigue
  3. 3. Savings and balance between people and tools
  4. 4. Unsustainable pricing with current solution
  5. 5. Avoid vendor lock in
  6. 6. Technologically sophisticated
  7. 7. Compliance with regulations

1. Analytics Maturity

As companies evolve in their analytics maturity and continue hiring for "head of analytics," "data scientist," and "data engineer" roles they often realize that getting the raw event-level data from analytics SaaS is more complex than it should be.

Data Scientists want data as raw as possible, and have a hard time dealing with arbitrary product limitations and complexity (n dimensions, eVars, scopes, etc.); they need the raw event-level data.

For Data Engineers, Snowplow comes as a logical choice, sometimes as a complement to existing analytics software, as it provides full control over all aspects of the data collection, processing, and storage.

2. Current Vendor Fatigue

These companies are usually tired of silver bullet promises that never materialize, and spending months/years in implementation and training, chasing the elusive dream of self-service analytics.

A platform can be frustrating to use for many, but data scientists and data engineers now they have a choice, build their own or use Snowplow.

In many of these cases, companies continue to use vendor X (because of legacy or bureaucracy) and add Snowplow to empower their data science team or incorporate that data into products.

3. Savings and balance between people and tools

I've seen companies spend $150k/year for Google Analytics 360 and not even blink. The "Nobody ever got fired for choosing IBM" is back, this time with Google and Adobe.

Companies realize there are no silver bullets; whatever platform they choose will require people to leverage the data. Opting the open-source route makes sense because it allows a more balanced investment in people vs. tools.

4. Unsustainable pricing with current solution

We've found certain analytics vendors pricing models are incompatible with some companies business models.

An example is B2B companies where their customers are B2C, and their services are exposed to the consumers of the B2C company. If the B2C company has 40 million monthly visitors that is the traffic the B2B company will have to pay for.

Example: For 40 million visitors with one session each.
On Heap using the startup plan: $0.02495 / session = $998k / month
On Segment $0.01129 / User = $451k / month

Even with significant pricing discounts, companies are effectively bleeding money with each customer they win because each can bring thousands or millions of their customers.

5. Avoid vendor lock-in

When you buy into certain vendors, expect to be pushed to buy into their complete range of products, in fact, you won't have much of choice, as their products won't play well with products other than their own.

Prepare to pay vast sums of money and be locked-in for the next decade, the inertia and cost of change are just too big to change.

Companies trying to avoid or get out of vendor lock-in choose Snowplow because it's open-source, it plays well with other tools, and provides them with full control over their data.

6. Technologically sophisticated

Companies with a strong technological base, often avid users of rising cloud services understand that paying more than $100k/year in licensing fee to have access to event-level data is a weak value proposition.

These companies already use cloud technology extensively and adopting Snowplow is a straightforward and logical step.

7. Compliance with regulations

Some companies are subject to a higher degree of scrutiny or need for transparency in data collection, processing, and storage, especially with GDPR and similar regulations.

Snowplow allows highly regulated industries to own and control all aspects of their event-data collection, processing, and storage.

Conclusion

Snowplow adoption has been steadily growing among analytically mature companies who want to do more with their data. We believe this trend will continue with the democratization of data science, AI, and ML.

Looking for Snowplow Consulting?. Contact us.

Share your comments below

Share your view in the comments section below.