Case Study: Artifact Uprising achieves trusted, standardized analytics with Iteratively

How Artifact Uprising standardized their analytics and aligned teams to drive growth

Artifact Uprising, an ecommerce company selling photo books, cards, prints, and gifts, struggled with unreliable analytics data across Google Tag Manager and Segment. Their team faced inconsistent reporting across platforms and production analytics bugs, making it hard to trust the data used for business intelligence, marketing, personalization, and advertising. To solve this, they turned to Iteratively to help govern and standardize their tracking.

With Iteratively, Artifact Uprising rebuilt its analytics taxonomy, created standardized event templates, added QA checks to CI/CD, shared live documentation, and used Slack to keep teams aligned. Iteratively became a single source of truth for analytics, catching inconsistencies before production and improving collaboration between developers and analysts. The result was an estimated 6 hours saved per week for the team, fewer analytics bugs, and cleaner data the organization could trust.

Artifact Uprising

Carly Kaufman

Director of Business Intelligence