Why Eppo
FEATURED CASE STUDY
Coinbase Saves Millions, Reduces Experiment Analysis Time by 40%, and Restores Trust in Experimentation with Eppo
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Eppo Vs. Optimizely
Maximize experiment velocity across teams, and master cause/effect relationships
Drive an experimentation culture
Empower all teams with experimentation
Eppo empowers all teams with experimentation, whether in product and engineering, or in go-to-market such as sales and marketing.
Maximize decision-making velocity
Eppo’s intuitive user interface (UI) and mature, proven features ensure maximum experimentation velocity.
Understand causal impact of drivers and outcomes
Empower smart decision-making with best-in-class, rigorous statistical methods built by experts.
Why customers choose Eppo vs. Optimizely
- Vision
Empower all teams with experimentation.
Including both technical and non-technical audiences.
Broad perspective: Eppo’s deep experience handles a broad range of industries and scenarios.
Build the best marketing team user experience
Not accommodating to technical staff such as data science and engineering.
Limited perspective: Sees experimentation primarily with a marketing lens and focus elsewhere (e.g., content management and customer data).
- Achieving the VisionMaximize decision-making velocity
Build a comprehensive solution from the ground-up
Warehouse Native: Integrates with all the leading cloud data warehouses. Provides transparency, trustworthiness, control, and security.
Plan right: Includes team-level organization and performance scorecards, a full experiment report builder, as well as a knowledge repository so that learnings from past experiments may be referenced, compared, and re-used.
Self-serve with intuitive UI: From simple on-off flags to gradual rollouts & full-blown experiments.
Build trust by understanding causation of outcomes: Measures are made with purpose. Underlying calculations are transparent, well-documented.
Collaborative customer success help: White glove service, to ensure maximum value.
Growth through
acquisitionAcquisition strategy
Not Warehouse Native: Requires you to send your data externally to a warehouse for analysis. That’s inefficient and dangerous.
No planning capabilities: No comprehensive experimentation planning to build and manage a comprehensive experimentation strategy holistically.
Inadequate experimentation features
No experiment health diagnostics
No analysis tools
Can’t use metrics that matter.
Inflexible: Proprietary stats engine (Harvard & Stanford, sequential testing), not flexible. 3rd-party integrations are cumbersome to set up.
Expensive to get help: Required to purchase add-on services of data scientists and professional services.
Why is Warehouse-Native Critical?
- Self-Serve Analysis
Decrease analysis time with Eppo using same-day analysis, translating to a faster decision-making process.
- Secure data
Shipping key business metrics to a 3rd party is a non-starter. As Eppo is warehouse-native, that’s not an issue.
- Minimize Costs
Eppo eliminates redundancy in storage, reduces pipeline development and management, and reduces experimentation run-times.
- Transparency, trustworthiness, & control
Optimizely’s data processing is opaque, creating trust issues. Eppo instills trust with powerful controls and a single source of truth for both business reporting and experimentation data.
- Discern the signal from the noise
Eppo’s enterprise-scale Performance Scorecards let you measure aggregate impact, align teams around inputs and outputs, and more.
Eppo ensures cost-effectiveness
- 1Storage
Eppo doesn’t store your data separately. It’s already in your cloud data platform.
- 2Reduces pipeline costs by 90%
Eppo is hyper-optimized to your warehouse.
- 3Reduce experiment operational costs
Eppo shortens experiment runtime with CUPED++
The brands that use Eppo
Ready to go from knowledge to action?
Talk to our team of experts and see why companies like Twitch, DraftKings, and Perplexity use Eppo to power their experimentation programs.
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