In Retail Analytics, unlocking the full potential of our platform begins with connecting your data sources. Whether you choose to leverage our existing connectors or manually import your own data, this guide will walk you through the process and highlight the key information we pull from each source.
Connecting Data Sources
Existing Connectors: You have the option to seamlessly connect to one of our existing connectors or manually import your data. Refer to our guide for detailed instructions on connecting to our pre-existing connectors.
Recommended Data Sources: We strongly advise connecting at least your Store, Google Analytics, and one Marketing connector. This ensures you can fully leverage the capabilities of Retail Analytics.
Why We Need This Data
Shopify/BigCommerce: We pull essential data such as Revenue, COGS (Cost of Goods Sold), and Stock from your store. This data forms the foundation of our analysis, empowering you to make informed decisions on marketing spend, stock optimization, and pricing strategies.
Google Analytics: Google Analytics data is crucial for providing the source of the transactions and customers. This also feeds key marketing KPIs like Product Views, Product Conversion Rate, and Click-Through Rate (CTR).
Marketing Platforms (e.g., Google Ads, Meta Ads, TikTok): We extract Ad Spend data from your marketing platforms, providing valuable insights into your advertising efforts. Retail Analytics currently supports integration with Meta, Google Ads, and TikTok.
Enhancing Analysis with Additional Data
Manual Data Import: For enhanced accuracy and flexibility, we offer the option of manually importing additional data, including:
Additional Marketing Costs: Perfect for incorporating offline marketing expenses, agency fees, influencer spending, and other marketing costs not covered by existing connectors.
Shipping/Handling/Fulfilment Costs: Unless stored in Shopify, these costs require manual importation. Refer to our guide for detailed instructions.
Additional Product Costs: If product costs vary over time or are not stored in Shopify, manually import this data to ensure accurate analysis.
Additional Product Attributes: Add custom attributes such as color or size to your products for deeper analysis and categorization.
Maximizing Accuracy and Insight
Including as much data as possible ensures accurate metrics like Contribution Margin and empowers you to analyze your data in various ways. Our platform utilizes this data to calculate complex metrics such as Customer Lifetime Value (LTV), repeat rates, ad spend per SKU, and contribution per SKU.
With Retail Analytics, connecting your data sources unlocks a wealth of insights to drive informed decision-making and optimize your business strategies. Start leveraging your data today for enhanced profitability and success.