> For the complete documentation index, see [llms.txt](https://docs.bloomanalytics.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.bloomanalytics.io/dashboard.md). # Dashboard The Dashboard benefits your Shopify data analytics with an array of key performance indicators (KPIs), brought to life through dynamic and straightforward explanations for clear data-driven business decisions. ### :slot\_machine: Overview The Metrics Library contains these vital metrics, categorized for easy navigation: * **Sales Metrics** Keep tabs on critical sales information like order volumes, average order value, and net sales across customer bases. Tracking refunds also offers insights into customer satisfaction levels. * **Profit Metrics** Displays profitability indicators like gross profit, gross margin, and contribution margin across customers segments and marketing channels (paid and organic). Includes overall Shopify margins and app-specific margins. * **Marketing Metrics** Analyze conversion rates, advertising expenditure, customer acquisition cost (CAC), and return on ad spend (ROAS) across various customer segments and channels for market campaign effectiveness. Also, gauge the marketing efficiency ratio (MER) and breakdowns of revenue and profitability by channel. * **Customer Metrics** Uncover patterns in customer behavior with metrics on total customer counts, ratio of new customers, and counts of new and returning customers. ### My Metrics ### :1234:Understanding KPIs Each KPI within the Metrics Library is accompanied by these elements to facilitate easier understanding: * **Definition** A straightforward explanation of what the metric represents. * **Significance** Why the metric is crucial for your ecommerce success. * **How to Use** Directions on how to interpret and apply the metric for strategic decision-making. ### :sparkle:Visualizing and Interpreting the Data The Metrics Library offers intuitive Spline Area charts for user-friendly visualizations of sales, profit, marketing, and customer metrics. It’s designed to help monitor store performance by analyzing data patterns for improved marketing strategies, inventory management, and allied operations. ### :wrench:Customizing Your Analysis Bloom provides merchants the choice to alter their metric viewing experience with multiple customization options. * **Date-range Selection** Select your metric analysis period for a focused view of your data with custom daily, weekly, monthly, or yearly. * **Comparisons** Benchmark metrics against values in any year or same period in the past. * **Cumulative Analysis** Evaluate overall performance over your selected timeframe. ### Use Cases of the Metrics Library The Metrics Library supports Shopify store owners by facilitating: * **Informed Decision-Making:** Lean on solid metrics for strategic decisions across marketing and inventory projects. * **Customer Acquisition and Retention:** Gauge the impact of marketing campaigns and loyalty initiatives through relevant customer metrics. * **Profitability Focus:** Prioritize profitable outcomes by identifying high-return channels and customer segments. * **Marketing ROI Assessment:** Evaluate the efficiency of marketing spend across various channels for optimal budgeting. * **Identifying Improvement Opportunities:** Uncover performance trends for optimization and address potential issues. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.bloomanalytics.io/dashboard.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.