Trends — day-over-day comparisons

Trends answers: “are things up or down lately, and by how much?” It lives on Reports → Trends.

What’s on the chart

• Daily revenue bars — one bar per day in the date range.
• Daily orders overlay — a second axis for order counts.
• 7-day moving average line — smoothed revenue. Reveals the underlying trend when daily bars are spiky.

The 7-day moving average

Each point is the average of the prior 7 days of revenue. It’s useful because:

• Weekends reliably dip on most DTC stores; the moving average absorbs that.
• Single-day promo spikes don’t distort your sense of “normal.”
• Comparing the moving average endpoint today vs. 30 days ago is a cleaner signal than comparing a Monday today to a Monday last month.

Compare to prior period

Under the main chart, a second chart shows the same metric for the prior equal-length period (30-day ranges compared to the previous 30 days, week-to-week, etc.).

Use the delta readout at the top to quantify:

• “Revenue is up 18% week-over-week”
• “Orders are down 6% but AOV is up 25% — we sold fewer but higher-ticket items”

Common uses

• Promo pre/post — was the promo’s incremental lift real, or did it just pull forward demand from the following week?
• Ad campaign rollout — did the new campaign actually move the baseline, or just consume budget?
• Product launch — did the new drop raise the trend, or was it a one-day spike that reverted?

What it doesn’t model

• Attribution — this is store-wide revenue, not channel-attributed. For per-channel trends, use the attribution report’s date range comparison.
• Seasonality decomposition — we don’t strip out annual seasonal patterns. If you’re comparing Nov to Oct, expect apples-to-oranges.

Related articles

• Dashboard — reading your home page — shows a simplified version of this chart.
• Attribution reports for per-channel trend detail.