# Orders Analytics

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**Difficulty:** 🟡 Intermediate · **Reading time:** \~15 min
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**Open this page in your dashboard:** [**Go to Orders Analytics →**](https://dashboard.sellermagnet.com/dashboard/orders/analytics)
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## 📋 Overview

The **Orders Analytics** page provides a complete visual overview of your Amazon sales performance. Combining KPI cards, trend charts, geographic breakdowns, and heatmaps, it gives you actionable insights into when, where, and how your products sell.

Whether you are running a single-marketplace storefront or managing a pan-European portfolio, this page is your command center for understanding revenue patterns, spotting anomalies early, and making data-driven decisions about inventory, advertising, and pricing.

***

## 📊 Key Performance Indicators

![SellerMagnet Orders Analytics](/files/tecaoFQuC4A5PobzazBl)

At the top of the page, five KPI cards give you an instant pulse check on your business health.

| KPI                 | Description                              | Why It Matters                                               |
| ------------------- | ---------------------------------------- | ------------------------------------------------------------ |
| **Total Orders**    | Number of orders in the selected period  | Tracks demand volume independently of revenue                |
| **Total Revenue**   | Combined revenue across all marketplaces | Your top-line number for the period                          |
| **Avg Order Value** | Average revenue per order (AOV)          | Signals pricing health and cross-sell effectiveness          |
| **Total Units**     | Total units sold                         | Reveals whether revenue growth comes from volume or price    |
| **Refund Rate**     | Percentage of orders that were refunded  | Early warning for product quality or listing accuracy issues |

> **Pro tip:** Compare your AOV across different date ranges. A rising AOV with stable order count often means your upselling or bundling strategy is working. A falling AOV alongside rising order count may indicate you are discounting too aggressively.

### How to Read KPI Cards Effectively

Each KPI card displays:

* **Current value** for the selected date range
* **Percentage change** compared to the previous equivalent period (e.g., last 30 days vs. the 30 days before that)
* **Trend arrow:** green for improvement, red for decline

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**Warning:** A green arrow on Refund Rate means the rate went **up**, which is actually bad. Always read this KPI in context, for Refund Rate, lower is better.
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***

## 📈 Charts & Visualizations

### 1. Revenue & Profit Trend

A **full-width line chart** showing revenue and profit over time for the selected period. Hover over data points to see daily/weekly values.

**What to look for:**

* **Consistent gap between revenue and profit lines:** healthy margin stability
* **Narrowing gap:** rising costs (COGS, shipping, FBA fees) eating into profit
* **Sudden drops:** stockouts, listing suppressions, or Buy Box losses
* **Weekly patterns:** most Amazon categories see weekend dips; if yours does not, your niche may behave differently

> **Pro tip:** If you see a sharp revenue drop on a specific day, cross-reference it with Amazon Seller Central notifications. Common causes include listing deactivations, inventory receipt delays, or category-wide Buy Box suppressions during Prime events.

### 2. Orders Heatmap

A **7x24 grid** showing order volume by **day of week** and **hour of day**. Darker cells indicate higher order volume. Use this to identify peak selling times.

**How to use the heatmap strategically:**

1. **PPC dayparting:** Increase ad bids during your darkest cells (peak hours) and reduce spend during light cells
2. **Lightning Deals timing:** Schedule deals to start just before your peak hours
3. **Customer service staffing:** Align support hours with peak order windows
4. **Inventory planning:** High-volume days help predict when stock levels will drop fastest

#### Scenario: You Notice a Revenue Dip on Tuesdays

You open the Orders Analytics page and notice that Tuesdays consistently show 20-30% lower revenue than other weekdays. Here is how to investigate:

{% stepper %}
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#### Check the heatmap

Is Tuesday uniformly low, or is there a specific time block (e.g., morning hours) dragging it down?
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#### Compare marketplaces

Use the marketplace filter to check each market individually. Maybe your DE marketplace is fine but UK drops on Tuesdays.
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{% step %}

#### Cross-reference with PPC

Are your ad campaigns pausing or reducing budget on Tuesdays? Check your dayparting rules.
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#### Look at competitor activity

Competitors may be running Tuesday-specific promotions that steal Buy Box share.
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#### Review historical data

Switch to L6M or L12M to confirm this is a consistent pattern, not a one-time anomaly.
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**Action plan if confirmed:**

* Increase PPC bids by 15-20% on Tuesday mornings
* Schedule a Lightning Deal or coupon for Tuesdays
* Test a Tuesday-specific promotion ("Tuesday Deal") for 4 weeks and measure impact

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**Quick win:** Even a 10% improvement on your weakest day can translate to significant monthly revenue. If Tuesdays average EUR 800 instead of your daily average of EUR 1,100, closing that gap by half adds roughly EUR 600/month.
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### 3. Revenue by Marketplace

A **pie/donut chart** breaking down total revenue by Amazon marketplace (DE, US, UK, FR, IT, ES, etc.).

**What healthy marketplace distribution looks like:**

* If one marketplace accounts for more than 80% of revenue, you have concentration risk
* Ideally, your top marketplace is under 60% with meaningful contribution from at least 2-3 others
* Watch for marketplaces where revenue is declining quarter-over-quarter

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**Best practice:** If a marketplace contributes less than 5% of revenue but consumes significant management time, evaluate whether the ROI justifies the effort, or whether those resources could grow a mid-tier marketplace instead.
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### 4. Top Products by Revenue

A **horizontal bar chart** showing your best-selling products ranked by revenue.

**Strategic uses:**

* Identify your "vital few": typically 20% of products drive 80% of revenue (Pareto principle)
* Spot products dropping out of the top ranks over time
* Compare against your profit data: top revenue products are not always top profit products

### 5. Revenue by Country

A **bar chart** displaying revenue split by country for geographic performance analysis.

Use this to:

* Track expansion into new markets
* Identify countries where you may need localized listings or translations
* Spot geographic trends (e.g., Southern European markets growing faster in summer)

***

## 🔍 Filters

| Filter          | Options                                   | Default      |
| --------------- | ----------------------------------------- | ------------ |
| **Marketplace** | All Marketplaces, or select specific ones | All          |
| **Date Range**  | L7D, L30D, MTD, YTD, L6M, L12M, Last Year | Last 30 days |

### Date Range Guide

| Shortcode     | Meaning                | Best For                                         |
| ------------- | ---------------------- | ------------------------------------------------ |
| **L7D**       | Last 7 days            | Quick pulse check, spotting immediate issues     |
| **L30D**      | Last 30 days           | Standard performance review                      |
| **MTD**       | Month to date          | Tracking monthly targets                         |
| **YTD**       | Year to date           | Annual trend analysis, year-over-year comparison |
| **L6M**       | Last 6 months          | Medium-term trend identification                 |
| **L12M**      | Last 12 months         | Seasonality analysis, long-term growth tracking  |
| **Last Year** | Previous calendar year | Year-over-year benchmarking                      |

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**Tip:** When comparing periods, remember that L30D compares against the **previous** 30 days (days 31-60 ago). If a major sale event (e.g., Prime Day) falls in one period but not the other, the comparison may be misleading.
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***

## Weekly Analytics Review Checklist

Use this template every Monday to stay on top of your numbers:

* [ ] **Check Total Revenue vs. last week**: Are you trending up or down?
* [ ] **Review Refund Rate**: Any spike above your 30-day average?
* [ ] **Scan the heatmap**: Any new patterns or anomalies?
* [ ] **Check Top Products**: Did any product drop out of the top 10?
* [ ] **Review marketplace split**: Is any market growing or shrinking unexpectedly?
* [ ] **Compare AOV**: Has average order value shifted?
* [ ] **Cross-reference with PPC spend**: Is increased spend translating to proportional revenue?
* [ ] **Note any external factors**: Holidays, competitor launches, Amazon policy changes

{% hint style="success" icon="rocket" %}
**Pro tip:** Screenshot your KPI cards every Monday and paste them into a shared team document or Slack channel. Over time, this creates a visual history that makes quarterly reviews much faster.
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***

## 🔄 Before & After: Using Analytics to Drive Decisions

### Before (No Analytics Review)

> A seller notices revenue is "down" but cannot pinpoint why. They increase PPC spend across all campaigns by 20%, burning an additional EUR 1,200/month with no clear improvement. After 3 months, they have spent EUR 3,600 extra with marginal results.

### After (Weekly Analytics Review)

> The same seller uses Orders Analytics and discovers:
>
> * Revenue dip is isolated to **one marketplace** (IT) where a competitor launched a similar product at a lower price
> * The heatmap shows their peak hours shifted from 8 PM to 10 PM after a Prime Day algorithm update
> * Their #3 top product dropped to #7 due to a stockout two weeks ago
>
> **Actions taken:** Adjusted IT pricing by 8%, shifted PPC dayparting to match new peak hours, expedited restock for the #3 product. Result: Revenue recovered within 2 weeks with no additional ad spend.

***

<details>

<summary><strong>⚠️ Common Mistakes to Avoid</strong></summary>

<table><thead><tr><th width="260">Mistake</th><th>Why it matters &#x26; what to do</th></tr></thead><tbody><tr><td><strong>Mistake 1: Reacting to daily noise instead of weekly trends</strong></td><td>A single bad day does not make a trend. Always look at L7D or L30D before making pricing or advertising changes. One-day dips are normal and can be caused by Amazon search algorithm updates, CDN issues, or simply natural variance.</td></tr><tr><td><strong>Mistake 2: Ignoring the Refund Rate KPI</strong></td><td>A refund rate climbing from 3% to 5% may not look dramatic, but on EUR 50,000/month revenue, that is an additional EUR 1,000 lost. Monitor this weekly and investigate any increase above 1 percentage point.</td></tr><tr><td><strong>Mistake 3: Over-indexing on revenue without checking profit</strong></td><td>Revenue growth is meaningless if profit margins are shrinking. Always view the Revenue &#x26; Profit Trend chart together, not just the revenue line. A seller growing revenue 20% while profit drops 10% is heading for trouble.</td></tr><tr><td><strong>Mistake 4: Not segmenting by marketplace</strong></td><td>Aggregate numbers can hide marketplace-specific problems. A 5% overall growth could mean DE grew 15% while UK declined 10%. Always check the marketplace breakdown.</td></tr><tr><td><strong>Mistake 5: Comparing unequal periods</strong></td><td>Comparing a 30-day period that includes Prime Day against a normal 30-day period will show a misleading decline. Use YTD or L12M for fair comparisons around major events.</td></tr></tbody></table>

</details>

\## Use Case Scenarios

### Scenario: Seasonal Product Performance

You sell both evergreen products and seasonal items (e.g., garden furniture and Christmas decorations). Here is how to use Orders Analytics:

1. Filter by **L12M** to see the full annual cycle
2. Note which months show revenue peaks: these correspond to your seasonal products ramping up
3. Use **Top Products by Revenue** to confirm which products drive the seasonal spikes
4. Tag these products (see [Product Tags](/dashboard-and-analytics/dashboard-overview/product-tags.md)) as "Seasonal - Q4" or "Seasonal - Summer"
5. Next year, use this data to time your inventory shipments 6-8 weeks before the expected ramp-up

### Scenario: New Marketplace Launch Assessment

You expanded into Amazon FR two months ago. Here is how to evaluate performance:

1. Set the date range to match your launch period
2. Filter to **FR marketplace only**
3. Check if your order count is growing week-over-week (even small growth is positive in month 1-2)
4. Compare your FR AOV against your DE or UK AOV: if it is significantly lower, your pricing may need adjustment for the French market
5. Use the heatmap to identify when French customers shop: it may differ from your home market

***

## 🔧 Troubleshooting

| Issue                                | Possible Cause                              | Solution                                                            |
| ------------------------------------ | ------------------------------------------- | ------------------------------------------------------------------- |
| KPI cards show zero                  | No orders in selected period/marketplace    | Expand the date range or check marketplace filter                   |
| Revenue chart shows flat line        | Single day selected or very narrow range    | Switch to L7D or L30D for meaningful trends                         |
| Heatmap appears mostly empty         | Low order volume in selected period         | Use a longer date range (L6M or L12M) to accumulate data            |
| Marketplace chart missing a market   | No sales in that marketplace for the period | Confirm your listings are active in that marketplace                |
| Numbers do not match Seller Central  | Data sync delay (typically 2-4 hours)       | Wait for the next sync cycle; check your last sync timestamp        |
| Profit line missing from trend chart | Cost data not yet configured                | Ensure you have entered COGS (Cost of Goods Sold) for your products |

***

## ❓ FAQ

<details>

<summary><strong>How often is the data updated?</strong></summary>

Order data syncs from Amazon every 2-4 hours. KPIs and charts refresh automatically when new data arrives. You can see your last sync timestamp in the account settings.

</details>

<details>

<summary><strong>Can I export the charts?</strong></summary>

Currently, chart export is not available directly. You can take screenshots or use the Orders table export for raw data. Chart export functionality is on the roadmap.

</details>

<details>

<summary><strong>Why does my revenue here differ from Amazon Seller Central?</strong></summary>

Small discrepancies (under 2%) are normal and typically caused by timing differences in data sync, currency conversion rounding, or pending orders that have not yet settled. If the discrepancy is larger, check that all your marketplaces are connected.

</details>

<details>

<summary><strong>Can I see data for a specific product only?</strong></summary>

The Orders Analytics page shows aggregate data. To analyze a specific product, use the Product Tags feature to tag it and then filter your Orders table by that tag. Product-level analytics are available in the Products section.

</details>

<details>

<summary><strong>What timezone are the heatmap hours in?</strong></summary>

The heatmap uses the **buyer's local timezone** based on the marketplace. For example, Amazon DE orders show in CET/CEST, while Amazon US orders show in the timezone of the buyer's shipping address.

</details>

<details>

<summary><strong>How far back does historical data go?</strong></summary>

SellerMagnet stores your complete order history from the moment you connect your Amazon account. The "Last Year" filter shows the previous calendar year. For data before your account connection date, historical import may be available depending on your plan.

</details>

***

## 💡 Tips

{% hint style="success" icon="rocket" %}
**Pro tip:** Use the heatmap to identify your peak selling hours, then align your PPC dayparting strategy to maximize ad visibility during those windows. Sellers who align ad spend with peak hours report 15-25% better ACoS (Advertising Cost of Sale) on average.
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**Privacy mode:** If you are sharing your screen during team calls or presentations, toggle the privacy mode to blur all numeric values across KPIs and charts. This is especially useful when presenting strategies without revealing exact revenue figures.
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**Pro tip:** Bookmark the Orders Analytics page with your most-used filter combination (e.g., L30D + DE marketplace). The URL preserves your filter state, so you can jump straight to your preferred view.
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**Team collaboration:** If multiple team members manage different marketplaces, have each person set up their own bookmarked view filtered to their assigned marketplace. This speeds up daily check-ins and ensures accountability.
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***

## ➡️ What's Next?

{% content-ref url="/pages/QUfddxcjTGMwmLVQVH0o" %}
[Refunded Orders](/dashboard-and-analytics/dashboard-overview/refunded-orders.md)
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{% content-ref url="/pages/5vsXtaqLonaWayeTIHV6" %}
[Reports](/dashboard-and-analytics/dashboard-overview/reports.md)
{% endcontent-ref %}


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