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Using date range and comparison filters

How to use date pickers, comparison periods, and grouping options across all dashboards.

Updated today

Overview

Every dashboard in Datadrew comes with date range and comparison filters at the top of the page. These filters let you control what time period you are analyzing and compare it against a previous period to spot trends, growth, or decline.

Setting a date range

The date picker lets you choose the exact start and end dates for your analysis. You can:

  • Select a custom range: Click the date picker and choose any start and end date. All dashboard metrics will update to show data only for that window.

  • Use preset ranges: Quick options like "Last 7 days," "Last 30 days," "This month," or "Last quarter" are available for fast selection.

  • Change at any time: Switching the date range instantly recalculates all metrics, charts, and tables on the page.

Enabling comparison mode

Comparison mode lets you see how the current period stacks up against a previous one. When enabled:

  • Each metric card shows a percentage change (green for improvement, red for decline).

  • Trend charts overlay the comparison period so you can visually compare patterns.

  • The comparison period is automatically calculated based on your selected range. For example, if you select "Last 7 days," the comparison period is the 7 days before that.

To enable comparison, toggle the comparison option in the date picker. You can also select a custom comparison period if the automatic one does not fit your needs.

Group By filter

The Group By filter controls how data points are aggregated on trend charts:

Option

What it does

Best for

Day

Each data point represents one day

Short-term analysis (last 7-14 days). Spot daily fluctuations and day-of-week patterns.

Week

Each data point represents one week

Medium-term analysis (last 30-90 days). Smooths out daily noise while showing weekly trends.

Month

Each data point represents one calendar month

Long-term analysis (last 3-12 months). Best for seeing seasonal patterns and month-over-month growth.

Quarter

Each data point represents one calendar quarter

Strategic analysis (last 1-2 years). Useful for board-level reporting and annual planning.

How date ranges apply across dashboards

The date range and Group By settings you select carry over as you navigate between different dashboards in the same session. This means:

  • Set your date range once on the Store Performance page, and it stays active when you switch to the Ads or Customer dashboards.

  • Each dashboard may show slightly different date behavior based on data availability. For example, ad platform data may have a 1-2 day lag compared to Shopify order data.

Data time limits by plan

Depending on your Datadrew plan, you may have limits on how far back you can look:

  • Free plan: Last 3 months of data.

  • Starter plan: Last 12 months of data.

  • Pro plan and above: Unlimited historical data.

If you try to select a date range beyond your plan's limit, the date picker will show a notice explaining the restriction. You can upgrade your plan to unlock more historical data.

Tips for effective date analysis

  • Always use comparison mode when reviewing performance. Absolute numbers without context can be misleading β€” a revenue of $50,000 means different things depending on whether the previous period was $40,000 or $60,000.

  • Match the Group By to your date range. Using daily grouping on a 12-month range creates too many data points and makes charts hard to read. Use weekly or monthly instead.

  • Account for seasonality. When comparing periods, consider whether holidays, sales events, or seasonal patterns might explain changes. Compare year-over-year when possible for seasonal businesses.

  • Check data freshness. Datadrew syncs your Shopify data daily. Today's data may not be fully available until the next sync cycle. Ad platform data (Meta, Google) may have an additional 1-2 day delay due to reporting windows.

Need help?

If you have questions about date ranges or comparison filters, reach out to us at support@datadrew.io or use the in-app chat widget.

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