Sprucely

Provides a visual query builder interface that translates drag-and-drop widget selections into underlying data queries without requiring SQL knowledge. Users select metrics, dimensions, and filters through a point-and-click interface that abstracts the complexity of query construction, enabling non-technical marketers to compose custom dashboards in minutes rather than hours.

Connects to marketing platforms (Google Analytics, Facebook Ads, Shopify, etc.) via OAuth and API integrations, automatically normalizing disparate data schemas into a unified internal schema. The system maps platform-specific fields (e.g., 'fb_campaign_id' vs 'google_campaign_id') to canonical dimension names, enabling cross-platform analysis without manual ETL configuration.

Enables team members to add comments and annotations to dashboard widgets, creating a discussion thread around specific metrics or insights. Comments are persisted with timestamps and user attribution, allowing asynchronous collaboration and knowledge sharing without leaving the dashboard interface.

Manages scheduled data synchronization from connected sources at configurable intervals (hourly, 4-hourly, daily), updating dashboard visualizations asynchronously without blocking user interactions. The system queues sync jobs, handles API rate-limit backoff, and caches query results to minimize latency between data availability and dashboard display.

Implements fine-grained access control allowing dashboard creators to assign view-only, edit, or admin permissions to team members and external stakeholders. The system enforces permissions at the dashboard level and underlying data level, preventing unauthorized access to sensitive metrics while enabling secure client or partner sharing via time-limited public links.

Provides a curated library of pre-calculated marketing metrics (CAC, LTV, ROAS, conversion rate, etc.) with standardized definitions and calculation logic. Users select metrics from the library rather than defining calculations manually, ensuring consistency across dashboards and reducing errors from incorrect aggregation logic.

Automatically calculates and visualizes period-over-period comparisons (YoY, MoM, WoW) for selected metrics, displaying both absolute and percentage changes. The system handles calendar alignment, leap year adjustments, and partial period calculations, enabling quick identification of trends and anomalies without manual date range selection.

Enables users to filter dashboard data by multiple dimensions (campaign, channel, product, geography, etc.) and drill down into segments to explore underlying data. The system maintains filter state across dashboard widgets, allowing users to apply a single filter set to all visualizations simultaneously while supporting independent filters on individual widgets.

Provides a selection of chart types (line, bar, pie, table, heatmap, etc.) for visualizing metrics, with limited customization options for colors, labels, and axes. The system automatically selects appropriate chart types based on metric and dimension selections, though users can override the recommendation.

Allows users to export dashboard snapshots (PDF, PNG, CSV) and schedule automated email delivery of reports on a recurring basis (daily, weekly, monthly). The system captures dashboard state at export time, includes metadata (export date, data freshness), and supports email distribution lists for batch delivery.

Monitors the health of connected data sources, tracking sync success/failure rates, latency, and data freshness. The system displays status indicators on dashboards, logs sync errors with diagnostic information, and alerts users when data is stale or sync failures occur.