

Sell-through rate is the heartbeat of your inventory. It tells you how quickly stock is converting to revenue and whether you are overbuying, under-ordering, or pricing poorly. A simple calculator built on the formula units sold ÷ units received helps you spot winners, clear slow movers, and protect cash flow. Track this weekly or monthly and you will see patterns by product, channel, and campaign that your P&L alone will never reveal.Now imagine you never have to pull those numbers again. An AI agent logs into your dashboards, copies raw sales and inventory into Google Sheets and Excel, refreshes formulas, flags SKUs below your target sell-through, and emails a summary before your standup. Instead of chasing exports and fixing broken spreadsheets, your team just reads the story the data tells and acts on it.
## 1. Manual ways to calculate sell-through### 1.1 Basic Google Sheets calculator1. Create a new sheet (or tab) for your products.2. Add columns: `A: SKU`, `B: Product Name`, `C: Units Received`, `D: Units Sold`, `E: Sell-Through %`.3. Enter your data for the chosen period (e.g., last month): total units received in column C, total units sold in column D.4. In cell `E2`, add the formula: `=IF(C2=0, 0, D2/C2)`5. Format column E as percentage.6. Drag the formula down for all rows.7. Optionally add conditional formatting (Format → Conditional formatting) to highlight low sell-through SKUs.For help with formulas in Google Sheets, see Google’s guide: https://support.google.com/docs/answer/3093480### 1.2 Basic Excel calculator1. Open a new workbook.2. Create the same columns: `A: SKU`, `B: Product Name`, `C: Units Received`, `D: Units Sold`, `E: Sell-Through %`.3. Paste or type your inventory and sales data.4. In `E2`, enter: `=IF(C2=0,0,D2/C2)`5. Format E as Percentage with 1–2 decimal places.6. Fill the formula down.7. Insert a table (Ctrl+T) so formulas stay consistent as you add rows.See Microsoft’s overview of formulas in Excel: https://support.microsoft.com/en-us/office/overview-of-formulas-in-excel-ecfdc708-9162-49e8-b993-c311f47ca173### 1.3 Weekly sell-through summaries1. Create a second sheet called `Weekly Summary`.2. In Google Sheets or Excel, list weeks in rows (e.g., `2025-W01`, `2025-W02`).3. Use `SUMIFS` to aggregate units sold and received per week, then compute sell-through. * Sheets example in `C2` for weekly units sold: `=SUMIFS(Detail!$D:$D,Detail!$A:$A,$A2)` * Repeat for units received, then compute sell-through.4. Plot a line chart to visualize trends.### 1.4 Channel-level sell-through1. Add a `Channel` column (e.g., Web, Amazon, Retail).2. Use PivotTables (Excel) or Pivot tables (Sheets) to group by SKU + Channel.3. Show sum of Units Received and Units Sold.4. Add a calculated field (in Excel’s PivotTable) or extra column in source data with the formula `Sold / Received`.### 1.5 Manual CSV imports1. Export sales data from your ecommerce platform or POS as CSV.2. Import into Google Sheets (File → Import) or Excel (Data → From Text/CSV).3. Clean column names and ensure numeric types for quantities.4. Link this raw tab to your calculator tab using `SUMIFS` or `VLOOKUP`/`XLOOKUP`.**Pros of manual methods*** Full control and transparency.* Zero extra tools, just Sheets or Excel.**Cons*** Easy to forget weekly updates.* Error-prone copy-paste.* Does not scale when you have many channels or SKUs.---## 2. No-code automation with tools### 2.1 Use Google Sheets + scheduled importsIn Google Sheets, you can reduce manual work by connecting data sources.1. Use built-in connectors (Extensions → Add-ons) or partner add-ons that sync orders or inventory.2. Schedule refreshes where supported so your raw data tab stays up to date.3. Keep your sell-through formulas on a separate tab so reports update automatically whenever new data arrives.4. Learn more about connected Sheets here: https://support.google.com/docs/### 2.2 Power Query in ExcelPower Query turns Excel into a lightweight ETL tool.1. In Excel, go to Data → Get Data → From File or From Web, and connect to your sales exports or API.2. Use Power Query to clean, filter, and shape the data (remove duplicates, ensure numeric columns for units).3. Load the query into a table called `Sales_Raw`.4. Build your sell-through formulas on top of `Sales_Raw` using structured references.5. Refresh data with one click or on open.See Microsoft’s Power Query overview: https://support.microsoft.com/en-us/excel### 2.3 No-code automation platformsTools like Zapier, Make or n8n can push data into Google Sheets or Excel (via OneDrive).Example flow:1. Trigger: New order in your ecommerce platform.2. Action: Append a row to your Google Sheet orders tab.3. Your sell-through calculator references that orders tab with formulas.Pros:* Reduces manual exports.* Works across many apps.Cons:* Zap counts or scenario limits.* Logic still lives in formulas you maintain.---## 3. Scaled automation with AI agentsThis is where an AI computer agent like Simular Pro changes the game. Instead of stitching together many point automations, you let an agent operate your desktop, browser, Google Sheets, and Excel like a power analyst.### 3.1 Agent as your inventory analystA typical workflow for a retailer or agency:1. The Simular AI agent logs into your ecommerce platforms, marketplaces, and WMS via the browser.2. It downloads the latest order and inventory CSVs.3. It opens Google Sheets, pastes raw data into a `Raw_Imports` tab, and checks for schema changes.4. It refreshes pivot tables and sell-through formulas, then copies key metrics into a `Summary` tab.5. It opens Excel, updates your master workbook for finance, and ensures formulas calculate correctly.6. Finally, it exports a PDF dashboard or writes a short narrative explaining what changed and emails it to sales and merchandising.**Pros*** End-to-end automation across browser, Sheets, Excel and email.* Handles thousands to millions of steps with production-grade reliability.* Every action is visible and editable, so you can inspect and improve the workflow.**Cons*** Requires initial setup and onboarding of the agent.* You need to design guardrails (e.g., where files are stored, which tabs to touch).### 3.2 Agent for exception alertsInstead of just refreshing numbers, the agent can search for risk.1. Define business rules, such as: "Any SKU with monthly sell-through under 30%" or "Over 90% for three weeks straight".2. The agent runs your calculator in Google Sheets and Excel, applies those rules, and writes an `Alerts` tab.3. It drafts outreach for your team: for slow movers, suggest discounting or bundling; for fast movers, flag reorder urgency.**Pros*** Turns raw data into prioritized action.* Saves sales and marketing teams from digging through spreadsheets.**Cons*** Needs regular tuning of thresholds as your business evolves.By pairing solid spreadsheet models with a capable AI agent, you keep the flexibility of Google Sheets and Excel while escaping the grind of manual updates and endless CSVs.
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In Google Sheets, start by deciding on the time window you care about, such as weekly or monthly. Create a sheet called 'Sell Through' with columns: A: SKU, B: Product Name, C: Units Received, D: Units Sold, E: Sell-Through %. Import your data from your ecommerce or POS system into columns C and D for that period.In cell E2, enter the formula:`=IF(C2=0,0,D2/C2)`This divides units sold by units received and protects you from divide-by-zero errors. Format column E as a percentage. Drag the formula down for all rows. If you have multiple receipts and sales per SKU, add a raw data tab and use `SUMIFS` to aggregate by SKU before applying the formula. For help building formulas, see Google’s official docs: https://support.google.com/docs/answer/3093480
First, separate your data into 'Raw' and 'Report' layers. In either Google Sheets or Excel, keep all detailed transactions (orders, receipts, returns) on raw tabs. Add helper columns such as SKU, Channel, Date, Units Received, Units Sold. Next, build a summary table where each row is a SKU or SKU+Channel, and each column aggregates a metric using `SUMIFS` (Sheets) or `SUMIFS`/`XLOOKUP` (Excel).Once you have aggregated Units Received and Units Sold, add a Sell-Through % column using units sold ÷ units received. Then insert charts: bar charts for sell-through by SKU, line charts for sell-through over time. In Google Sheets: Insert → Chart. In Excel: Insert → Recommended Charts. Optionally add slicers (Excel) or filter views (Sheets) so sales and marketing teams can explore by category and campaign.
To track trends, you need two ingredients: clean dates and consistent time buckets. In your raw data tab, ensure each transaction has a proper date field. In a new tab called 'Trends', create a column listing each week or month you want to analyse (for example, the first day of each week or month).Use `SUMIFS` to aggregate units sold and received into each period. For example, in Google Sheets, weekly units sold formula might look like:`=SUMIFS(Sales!$D:$D,Sales!$A:$A,">="&A2,Sales!$A:$A,"<"&A2+7)`Do the same for units received, then divide to get sell-through rate. In Excel, the logic is identical. Once calculated, select the date and sell-through columns and insert a line chart to visualize how quickly items move over time. This helps you spot seasonality, marketing lift, or stock issues.
Start by using your calculator to segment problem SKUs instead of reacting to averages. Filter your sell-through table to show items below your target threshold, for example 30% monthly. Add columns for margin, stock on hand, and days since launch. This lets you distinguish new tests from true laggards.For each low-performing item, use your data to choose a lever: discounting (track impact by comparing sell-through before and after a promo), repositioning (changing imagery or copy and tracking click-through vs sell-through), or channel shift (moving from one marketplace to another). Also look at units received; sometimes the issue is overbuying rather than weak demand. Your calculator should highlight SKUs where receipts greatly exceed sales. Use those signals to cut reorders and free up cash. Over a few cycles, your data-driven adjustments will show up as higher average sell-through.
An AI agent can act like a tireless analyst who owns the entire reporting loop. You first define where your raw data lives (ecommerce exports, WMS, ad platforms) and where your models live (Google Sheets or Excel). The agent logs into your tools, downloads or syncs the latest data, and pastes it into the correct raw tabs. It then checks that formulas and pivot tables are recalculated correctly and that no columns have shifted.From there, the agent can generate summaries: top and bottom SKUs by sell-through, channels with inventory risk, and products with rapidly improving velocity. It can write a short narrative and email it to stakeholders or update a dashboard. Because Simular-style agents provide transparent execution, you can inspect every step, refine the playbook, and trust the automation at scale. The result: your team stops wrestling CSVs and starts acting on insights.