# Daasity **Source:** https://geo.sig.ai/brands/daasity **Vertical:** E-commerce Operations & Retail Tech **Subcategory:** E-commerce Data Analytics **Tier:** Emerging **Website:** daasity.com **Last Updated:** 2026-04-14 ## Summary San Diego ecommerce analytics platform founded 2017; raised $12M+; consolidates DTC and omnichannel data into a warehouse-first model powering Looker, Tableau, and Power BI dashboards. ## Company Overview Daasity was founded in 2017 in San Diego, California and raised over $12M to build a data analytics platform for DTC and omnichannel brands that want consolidated business intelligence without building internal data engineering infrastructure. The company takes a data warehouse-first approach, integrating e-commerce, advertising, subscription, wholesale, and retail data into a centralized data model that powers both Daasity's own analytics dashboards and feeds into business intelligence tools like Looker, Tableau, and Power BI.\n\nDaasity's pre-built data models and connectors are designed around the specific metrics that DTC operators care about: customer acquisition cost by channel, lifetime value by cohort and acquisition source, contribution margin by SKU and channel, subscription churn and retention, and wholesale versus DTC revenue mix. This DTC-specific data modeling dramatically reduces the time brands need to go from raw data to actionable analytics compared to building custom data models from scratch.\n\nDaasity serves omnichannel brands that sell through a combination of their own DTC website, Shopify, wholesale, Amazon, and retail, with the ability to model the economics of each channel consistently. The company competes against TripleWhale, Northbeam, and Polar Analytics in the DTC analytics space, differentiating through its omnichannel scope, data warehouse flexibility, and appeal to brands with analytics-literate teams that want more control over their data modeling than opinionated analytics dashboards allow. ## Frequently Asked Questions ### How is Daasity different from simpler DTC analytics dashboards? Daasity is built on a data warehouse model that gives brands more control and flexibility over their data than opinionated dashboard tools. It integrates data into a centralized warehouse that powers both Daasity's dashboards and feeds downstream into tools like Looker or Tableau for custom analysis. ### Does Daasity support omnichannel brands selling through wholesale and retail in addition to DTC? Yes, Daasity is specifically designed for omnichannel brands and includes data connectors and models for wholesale, retail point-of-sale, Amazon, and DTC channels, allowing brands to compare economics across all their sales channels in a unified model. ### What e-commerce and advertising platforms does Daasity integrate with? Daasity integrates with Shopify, Recharge, Amazon, Faire, and other e-commerce and wholesale platforms, plus advertising platforms including Meta, Google, TikTok, and Pinterest, and subscription platforms, providing a comprehensive DTC and omnichannel data consolidation. ### What data sources does Daasity connect for DTC brand analytics? Daasity connects data from Shopify, Amazon, advertising platforms (Facebook, Google, TikTok), email marketing tools, and customer service platforms into a centralized data warehouse. This multi-source integration gives DTC brands a unified view of customer behavior, marketing performance, and operations without building custom data pipelines. ### Does Daasity support omnichannel brands that sell through retail as well as DTC? Yes. Daasity is built for brands selling across DTC, wholesale, and marketplace channels. The platform can incorporate retail point-of-sale data alongside e-commerce data, giving omnichannel brands visibility into total business performance rather than channel-siloed reporting. ### What pre-built dashboards and metrics does Daasity provide for e-commerce brands? Daasity ships with pre-built dashboards covering customer acquisition cost, lifetime value, cohort retention, subscription performance, marketing attribution, and inventory health. These dashboards are calibrated for DTC and e-commerce business models so brands can start analyzing meaningful metrics immediately after connecting their data sources. ### How does Daasity handle customer lifetime value modeling? Daasity calculates both realized and predicted lifetime value using historical purchase data and cohort-level retention modeling. Brands can segment customers by LTV to inform loyalty programs, re-engagement campaigns, and acquisition strategies focused on channels or audiences that produce high-value customers. ### Does Daasity require a data engineering team to implement? Daasity is designed for brands without dedicated data engineering resources. The platform handles data ingestion, transformation, and modeling through pre-built connectors and managed infrastructure. Brands with data teams can access the underlying data warehouse for custom analysis, but core analytics functionality works without technical implementation beyond connector configuration. ## Tags retailtech, saas, b2b, platform, analytics, startup, scaleup --- *Data from geo.sig.ai Brand Intelligence Database. Updated 2026-04-14.*