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Description

Peel offers an intuitive and automated analytics platform that enables you to assess your data effectively, enhancing both customer acquisition and retention strategies. By simply connecting your Shopify store(s), you can witness a remarkable transformation in your data within just a few hours. Peel curates and delivers the most critical data, KPIs, and trend analyses to your e-commerce team, ensuring that everyone has quick and easy access to vital insights. You'll find a variety of visual representations, including graphs, tables, cohorts, and charts, all showcasing your historical data for comprehensive exploration. With just a few clicks, you can unlock this information, make informed decisions, and drive significant business growth, paving the way for a data-driven future.

Description

Gain practical insights for your direct-to-consumer brand with a personalized, comprehensive overview that requires no engineering expertise. With just a single click, you can integrate all your marketing data and analyze it directly within the application. Real-time detection of insightful trends and anomalies becomes effortless, eliminating the need for tedious spreadsheets filled with numerous tabs. Centralize your marketing data sources seamlessly, as we support all major connectors utilized by D2C brands. You won’t have to worry about maintaining a data pipeline or setting up a data warehouse; we take care of that for you. Instantly compute and analyze key performance indicators with ease. Our pre-defined dashboards allow you to visualize crucial metrics such as Customer Acquisition Cost, Lifetime Value, and Retention Cohorts, which are essential for monitoring and enhancing your store's performance. Furthermore, you have the freedom to customize these charts to fit your unique metrics and definitions, as all visualizations are constructed using SQL, enabling your team or ours to tailor them as needed. The flexibility and user-friendliness of our platform empower you to make informed decisions faster than ever before.