How BARK Scaled Its Data Platform and Culture with Rittman Analytics

The Download

BarkBox is BARK's flagship monthly subscription, delivering themed boxes of toys and treats tailored to dogs' unique playstyles. Every month features an original collection that surprises and delights both dogs and their humans.

The company's success is built on deep customer insight, playful storytelling, and a commitment to a dog-first design. With a strong omnichannel strategy and data-driven approach to personalization, BARK has created a powerful emotional connection with its customers. This foundation, paired with exceptional customer service, maximizes lifetime value, achieves high retention and maintains its position as a leader in the pet industry.

The Challenge

As BarkBox scaled, its data capabilities struggled to keep up. The company found itself in a familiar situation of a rapidly growing business built on data infrastructure designed for a startup. What had once worked for a startup environment was now a limiting factor for a fast-growing, data-rich business.

• Fragmented and Inconsistent Data: Information was scattered across a legacy e-commerce platform, third-party systems and countless spreadsheets. Without a single source of truth, teams faced conflicting business definitions and unreliable reports.
• Manual and Inefficient Processes: The marketing team relied heavily on manual workflows to consolidate campaign data, track performance and report on customer engagement. Pulling insights from multiple sources including ad platforms, email systems and internal databases required hours of spreadsheet work each week not only slowed down decision-making but also made it difficult to react quickly to trends, optimize campaigns in real time and accurately measure ROI.
• Limited Access to Strategic Insights: The legacy data warehouse and complex data model made it difficult for teams to explore or analyze data independently. This lack of scalability and governance hindered self-service analytics and prevented BARK from unlocking the full potential of AI-driven insights.

BARK's legacy cloud analytics infrastructure was increasingly unable to keep pace with the company's growth and evolving data needs. Query performance had degraded as data volumes scaled, creating bottlenecks for analysts and slowing time-to-insight. The platform's cost structure made scaling prohibitive, while the absence of a true semantic layer meant metric definitions varied across teams—undermining confidence in reporting and making a "single source of truth" elusive.

The Solution

Rittman Analytics took a deeply collaborative, embedded approach to help BARK build a modern, scalable data platform using our proven Data Team Enablement Framework.

Phase 1: Confront the Hard Truths Through Discovery

We began with an in-depth discovery process, working closely with stakeholders across the business to fully understand the challenges of scaling BARK's data function. Through a series of collaborative workshops and technical deep-dives, we were able to uncover both strategic and operational barriers to growth.

This process included:

• Comprehensive stakeholder mapping across every business unit to understand data needs, dependencies and priorities.
• A full technical assessment of the existing infrastructure, conducted with complete transparency and access.
• Joint problem-solving sessions with internal teams to align on challenges and co-design potential solutions.
• A detailed capability gap analysis identifying where people, processes and technology needed to evolve to support a modern data organization.
• A comprehensive audit of BARK's existing legacy environment, documenting technical debt, performance constraints, and governance gaps. Following a structured multi-vendor evaluation, BigQuery and Looker were selected as the target platform—a decision aligned with BARK's broader strategic commitment to the Google Cloud ecosystem.

Phase 2: Create the Change

The team executed a full platform migration to Google BigQuery and Looker, systematically transitioning production workloads while maintaining business continuity. Over a twelve-month engagement, we delivered:

• Data Warehouse Migration: All historical data and active pipelines were migrated to BigQuery, with Hevo and custom integrations replacing legacy ingestion processes. dbt was implemented to power multi-layered transformations, creating a modern, scalable foundation for analytics.
• Semantic Layer Implementation: Looker replaced the legacy business intelligence platform, establishing a unified semantic layer with governed metric definitions. This provided the "single source of truth" that had been missing—enabling consistent, self-service reporting across the organization.
• Departmental Solutions Migration: Existing dashboards and reports were rebuilt and enhanced in Looker, starting with marketing and campaign analytics. Beyond immediate reporting needs, the semantic layer represents a strategic unlock: a governed data foundation that positions BARK to integrate AI and natural language interfaces directly with trusted enterprise data.

Phase 3: Manage the Change

Throughout the engagement, the Rittman Analytics team worked alongside BARK's data team, focusing on coaching, skills transfer and establishing best practices to ensure they could independently manage and scale the new platform long-term.

Migration Delivered On Time and On Budget: The complete platform migration—to BigQuery and Looker—was delivered within a 12-month timeline, on budget, and with zero disruption to business operations. Throughout the transition, BARK's teams maintained full access to analytics capabilities, with no gaps in reporting or data availability.

Business Benefits Delivered

The new analytics platform transformed BARK's data capabilities, empowering its teams and creating a foundation for continued growth.

• Established a Single Source of Truth: The modernized data platform provides consistent, reliable and democratized data access, enabling teams across Marketing, Finance and Customer Experience to make decisions with confidence from a unified version of the truth.
• Increased Operational Efficiency: Automating data pipelines and operational reporting eliminated manual bottlenecks, reduced overhead and saved significant time and effort for teams such as the Growth Marketing Team.
• Enabled Proactive, Data-Driven Decisions: With reliable, insightful dashboards, automated alerts and self-service analytics tools, business units can now monitor performance proactively, identify trends and uncover insights that were previously difficult to surface.
• Built a Scalable Foundation for Growth and AI: The new cloud-native architecture is designed to scale with the business and supports advanced capabilities, allowing BARK to integrate AI and machine learning models directly into its data environment to fuel future growth.
• Empowered the Internal Data Team: Through a deeply collaborative partnership and extensive knowledge transfer, BARK's data team is now equipped with the skills, processes and tools to independently manage, maintain and evolve its modern data platform.