Case Study: Lovepop achieves democratized analytics and faster insights with Sisense for Cloud Data Teams

Lovepop’s Accessible Data Builds Magical Moments

Lovepop, a fast-growing Boston startup that designs and handcrafts intricate pop-up greeting cards, needed a way to aggregate and analyze data from multiple lines of business—ecommerce, retail, wholesale and B2B—so teams could plan production, measure ad spend, and scale operations as the company expanded. The challenge was providing fast, SQL-friendly analytics that a broad set of users could access and act on without creating a bottleneck for the data team.

Lovepop implemented Sisense for Cloud Data Teams to keep analysis close to the SQL layer, enable dynamic filtering, and connect quickly to Redshift; about 80 employees now use the platform (10 writing SQL) to access the “Magical Moments” dashboard, build visualizations, and share controlled views with external partners. The result: faster self-service insights, hours saved for the data team, more dynamic forecasting with Python/R integrations, improved operational decisions around production and retail, and stronger data governance for third parties.

Lovepop

Michael Prentice

Principal Data Engineer