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Reactive SDP is built to get retail buyers from raw sales data to a purchase-ready forecast as fast as possible — without requiring a data analyst or a multi-week onboarding project. This guide covers exactly what you need to do from the moment you sign in for the first time.

1 Prepare your sales data CSV

The most important step — and the one that takes the most time if your POS export is messy — is getting your data into the right format. Reactive SDP reads a weekly sales history CSV.

Required columns

Column name	Format	Required?	Example
style_id	Text	Required	WMJKT-001
name	Text	Required	Wool Blazer
category	Text	Required	Outerwear
week_start	Date (YYYY-MM-DD)	Required	2025-01-06
units_sold	Integer	Required	14
eop_inventory	Integer (end-of-week on hand)	Required	218
msrp	Decimal (MSRP / retail price)	Required	89.00
cost	Decimal (unit cost)	Required	22.50
sub_category	Text	Optional	Denim, Knits, Wovens
size	Text (size label)	Optional	S, M, L, XL or 28, 30, 32
color	Text	Optional	Black, Navy
sell_price	Decimal (current listed price)	Optional	74.99
avg_unit_retail	Decimal	Optional	79.00
units_returned	Integer	Optional	2
vendor	Text	Optional	Factory A
image_url	URL	Optional	https://…/blazer.jpg

Each row represents one style × one week (or one style × size × color × week, if you're providing SKU-level data). Use the "Download Template" button on the upload screen for a pre-formatted example.

Separate PO data upload

Purchase order data (units on order, expected delivery dates) is uploaded as a separate PO CSV — you don't need to include any PO columns in your historical sales file. This keeps your sales export clean and lets you update PO data independently. Use the "Upload PO CSV" option after loading your sales history.

How to export from common systems

• Shopify: Use the "Sales by product" report, export to CSV, and use a lightweight script or spreadsheet to pivot from daily to weekly. (The Shopify API also supports weekly aggregation directly.)
• Lightspeed / Square: Both provide sales history exports. You'll need to add on-hand inventory columns from a separate stock report.
• NetSuite / SAP / Microsoft Dynamics: Standard saved search / query export. Your IT or finance team will have an existing template — ask for "weekly unit sales and end-of-week on-hand by style."
• Custom ERP: The raw SQL is almost always straightforward: GROUP BY style_id, DATETRUNC('week', sale_date) for sales; join to inventory snapshot for on-hand.

2 Upload and verify your data

Once your CSV is ready, drag and drop it onto the Reactive SDP upload area, or click "Upload CSV" to browse for the file. The tool will:

1. Parse all columns and validate the format
2. Display a summary: number of styles detected, number of weeks of history, categories found
3. Flag any rows with missing required data or unexpected values

If the parse summary looks right — correct number of styles, correct date range — you're ready to proceed. If a column is missing or misnamed, the error message will tell you exactly which column is expected.

3 Read the forecast output

After upload, you'll see the main planning dashboard. The top-level KPIs — including Gross Sales, units, and margin — give you a snapshot of where things stand. Here's what each metric means:

Demand forecast

The projected unit demand for each style over the forecast horizon (default 13 weeks, configurable up to 52 in Settings). This is a seasonally-adjusted forecast based on your historical sell rate, not a naive average. The forecast accounts for the seasonal pattern of each product category — if outerwear historically spikes in weeks 38–45, that's reflected automatically.

Sell-through rate

The percentage of available inventory expected to sell by end of season, given current trajectory. A target of 65–75% by week 8 is a common benchmark for healthy in-season performance. Styles below target may need markdown action; styles well above may need reorder.

Weeks of cover

Current on-hand inventory divided by the forecasted weekly demand rate. This tells you how many weeks your current stock will last. A style with 4 weeks of cover and a 10-week vendor lead time needs to be on order immediately.

Reorder signal

Red, yellow, or green indicator. Red means the style is projected to stock out before its end date given current trajectory and lead time. Yellow is a watch item — cover is adequate but thinning. Green is healthy.

Style Planning table

Below the KPI cards, the Style Planning table is where you do most of your detailed work. Use the lookback and lookforward controls to adjust the time window — for example, set lookback to 8 weeks to focus on recent velocity, or extend lookforward to 26 weeks for a longer planning horizon. Key columns include:

• Week Age — how many weeks since the style's first sale
• ST% — sell-through percentage to date
• Turns — inventory turns over the lookback period
• GMROI — gross margin return on investment
• Lost Revenue — estimated revenue lost to stockouts
• Sizes in Stock — count of sizes currently available vs. total offered

All columns are draggable — rearrange them to match your workflow. The sticky totals row at the bottom keeps aggregate numbers visible as you scroll through styles.

4 Configure planning parameters

Open Settings (gear icon) to configure the inputs that drive your plan. Settings are grouped into collapsible sections — start with General and expand from there.

• General → Lead time (weeks): How many weeks from placing an order to receiving goods. If you have multiple vendors with different lead times, use the longest one as your default, or set per-style overrides in your CSV.
• General → Safety stock: Extra coverage buffer expressed as weeks of cover or absolute units. A common starting point is 2–4 weeks.
• General → MOQ: Default minimum order quantity applied to all PO recommendations.
• Sell-through target: The percentage of a style's opening inventory you're targeting to sell by a given week. Identifies styles behind pace.
• Tags: Configure the thresholds that trigger status badges on style cards — including the margin floor, which excludes low-margin styles from replenishment.
• Demand Quality Filters: Controls which historical weeks feed into the velocity baseline. The trailing demand cutoff automatically detects styles winding down and excludes their weak tail from the forecast. Optional filters for size breakage and low-margin weeks are also available.
• Data Window → Forecast horizon: How many weeks forward to forecast. Default is 13 weeks, configurable up to 52.
• OTB budget: Optional. Enter your open-to-buy budget to see which reorders are within budget.

5 Review reorder alerts

The Reorder Alerts view shows all styles sorted by urgency — styles projected to stock out soonest appear first. For each alert you can see:

• The projected stockout date (if no reorder is placed)
• The recommended reorder quantity, accounting for lead time and safety stock
• The size and color breakdown of the reorder (if size/color data was provided)
• The estimated cost at your last unit cost (if cost data was included)

Use this view as your weekly work queue. Clear the red alerts first. Investigate the yellow alerts. The goal is to never be surprised by a stockout.

6 Export your purchase order

When you're ready to act on reorder recommendations, click "Export PO." This generates a CSV with:

• Style number and name
• Category and sub-category
• Reorder quantity by size and color (if applicable)
• Estimated cost (if cost data provided)
• Week needed by (based on lead time from today)

This CSV is formatted to be pasted directly into most vendor order templates or uploaded to most B2B buying portals. You can also filter the export to include only specific categories, only styles above a minimum order value, or only styles with red-level urgency.

What to do your first week

1. Upload your CSV and verify the summary numbers match what you'd expect
2. Check 5–10 styles you know well — does the forecast feel right?
3. Adjust lead time and safety stock to match your actual vendor situation
4. Look at the top 3 red-alert styles. Are these real concerns you were already tracking?
5. Export a PO for one category to see the format before using it in a live order

If the forecast seems directionally right on the styles you know best, you're calibrated. From there, it's a weekly rhythm: upload the latest data, review alerts, place orders.