Snowplow vs. Adobe Analytics
“We would not have achieved our current level of self-serve data without Snowplow. It has enabled us to democratize our data culture, significantly improving our analytics coverage and deepening our insights”
DANIEL HUANG | DATA ENGINEER, STRAVA
Key Snowplow Features
Create a culture of trust in dataSnowplow has pioneered data validation and testing tech that creates full trust in the data across your business
Quality assuranceTrial tracking in a sandbox environment – like software testing. Data is also pre-validated with JSON schemas to ensure quality
Data optimized for AI & BIOur highly-curated behavioral datasets are granular and accurate enough to power advanced AI and BI use cases
Compliant first-party data creationMitigate against tightening regulatory requirements through ‘private SaaS’ deployment model – no customer data ever leaves your infrastructure
Gain a customer 360Understand your customers’ behavior during their anonymous journeys and across devices, maximizing the efficiency of your marketing funnel
Free your data teamData lands in your warehouse ready for use, freeing your data team from endless cleaning and wrangling and ensuring projects see production
Snowplow for warehouse-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.
While Adobe 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 single source of truth.
Adobe can create data quality issues
Adobe Analytics is presented as an Enterprise-grade advanced analytics tool, but the data quality simply doesn’t justify this.
Blocked by privacy controls Adobe has not kept up with the changes to browsers and adblockers over the last 5 years, limiting the lifetime of tracking cookies. There will be gaps in the data collected
Bad data cleaningOnce bad data has been collected by Adobe, there is no way to get it out or clean the data. One Snowplow customer migrated from Adobe after accidentally-collecting customer PII, forcing them to discard business-critical data
Lack of customizationAdobe forces everything to conform to a fixed model (‘name=value pairs’ of strings), when your tracking doesn’t naturally fit into this format, the result is lossy data that doesn’t accurately reflect your site/app
Inflexible to business requirementsOnce there’s live data in a dimension, you can’t use that dimension for something else in a new version without it intermingling with the existing data – i.e., data cannot evolve with your business
Misleading and incomplete dataWhen unique values in a dimension reach a certain threshold, Adobe hides a proportion of them, rendering the data incomplete
Adobe lacks flexibility and customization
Tools should adapt to the user, not the other way around. Adobe makes it hard for less linear use cases and business contexts.