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When revenue jumps 20%, your board, clients, or founders all ask the same question: why? Price volume mix (PVM) analysis is how you answer with precision instead of guesses.By decomposing growth into price, volume, and mix effects, you can see whether margin expansion came from smart pricing, successful campaigns, or a quiet shift toward high‑value products. The FTI and Zebra BI approaches both emphasize SKU‑level detail, consistent units of measure, and clear storytelling by product category or channel.This is exactly where an AI computer agent shines. Instead of analysts spending nights exporting CSVs, cleaning SKUs, and rebuilding formulas, you delegate the busywork. The agent logs into your tools, refreshes Google Sheets and Excel models, applies the PVM formulas, and highlights outliers. You stay focused on decisions: which products to push, where prices are too aggressive, and which segments quietly erode margin while the headline revenue still looks good.
### 1. Manual, traditional ways to run PVM analysisEven before automation, you can get a lot of value from a disciplined price volume mix workflow. Here’s how most teams do it today.#### Method 1: Classic PVM in Google Sheets1. **Structure your data** In a new Google Sheet, create columns for: `SKU`, `Product Name`, `Period`, `Units`, `Revenue`. Add two periods (e.g. Prior and Current) stacked in rows. See Google’s Sheets basics: https://support.google.com/docs/answer/60002922. **Calculate prices and totals** Add calculated columns: - `Price = Revenue / Units` using a formula like `=IF(E2>0,E2/D2,0)` - Use `=SUMIF` or `=SUMIFS` by period to get total revenue.3. **Compute Price Effect** For each SKU, use: `Price Effect = (Current Price – Prior Price) * Prior Volume` Example formula: `=(G2-H2)*D2` where `G2` is current price, `H2` prior price, `D2` prior units.4. **Compute Volume Effect** `Volume Effect = (Current Volume – Prior Volume) * Prior Price` Example: `=(E2-D2)*H2`.5. **Compute Mix Effect** The simple approach: `Mix Effect = Total Revenue Change – Price Effect – Volume Effect` After you sum price and volume effects by SKU, subtract from total variance.6. **Aggregate by product or channel** Use **Pivot tables** (`Insert → Pivot table`) to roll up PVM effects by product category, channel, or region.#### Method 2: Excel PVM with pivot tables1. **Import your data** Paste or import sales data into Excel with columns for `SKU`, `Period`, `Units`, `Revenue`. Import help: https://support.microsoft.com/excel2. **Add calculated columns** - `Price = Revenue / Units` - Prior vs current prices and volumes using structured references.3. **Apply PVM formulas** In three new columns: - `= (CurrentPrice - PriorPrice) * PriorVolume` - `= (CurrentVolume - PriorVolume) * PriorPrice` - `= RevenueChange - PriceEffect - VolumeEffect`.4. **Summarize with a PivotTable** `Insert → PivotTable`, then drag `Product` to Rows and the three effect fields to Values. This instantly shows which products drove price, volume, and mix.5. **Visualize the bridge** Use waterfall charts (https://support.microsoft.com/en-us/office/create-a-waterfall-chart-in-excel-8de1ece4-ff21-4c10-ae13-582ddc257f21) to tell the story from prior revenue to current, broken into price, volume, and mix blocks.#### Method 3: SKU-level deep dive1. Start from your Excel or Sheets PVM table. 2. Filter to **SKUs with negative mix effect but positive volume**, to find products that are selling more but dragging margin. 3. Filter to **high positive price effect with volume decline**, to detect over‑aggressive price hikes.These manual methods give you insight, but they’re time‑consuming and brittle when data changes.---### 2. No‑code automation with existing toolsFor growing teams, the next step is to reduce the repetitive glue work between systems.#### Method 4: Google Sheets + connectors1. **Connect your data source** Use a connector add‑on (e.g., your CRM or accounting tool’s official Sheets add‑on) so sales data auto‑refreshes into a dedicated tab. Learn about add‑ons: https://support.google.com/docs/answer/29422562. **Keep formulas in a separate model tab** Point your PVM formulas to the raw-data tab using `IMPORTRANGE` or direct references. When data refreshes, your price, volume, and mix calculations update automatically.3. **Add data validation and named ranges** Use named ranges (https://support.google.com/docs/answer/63175) for key cells like total revenue or selected period so marketers and founders can change the scenario without breaking formulas.#### Method 5: Excel + Power Query1. **Use Power Query to pull data** from databases, CSV exports, or online sources. Intro: https://support.microsoft.com/en-us/office/get-started-with-power-query-7104fbee-9e62-4cb9-a02e-5bfb1a6c536a2. **Transform once, reuse forever** Clean SKUs, map product groups, and unify units in Power Query steps. Refreshing the query rebuilds your PVM dataset automatically.3. **Link to a PVM model sheet** Your formulas for price, volume, and mix live in a separate sheet referencing the query output table. Click **Refresh All**, and the whole PVM story updates.These no‑code patterns eliminate copy‑paste, but you’re still the operator: opening files, clicking refresh, and exporting charts for stakeholders.---### 3. Scaling PVM with an AI agent (Simular)This is where you step out of spreadsheet babysitting and let an AI computer agent handle the workflow end‑to‑end.#### Method 6: Autonomous desktop workflow**Story:** Imagine your Monday used to start with two hours of CSV exports. Now, a Simular Pro agent does it before you wake up.1. **Record the ideal workflow once** In Simular Pro, you define a task: open your browser, log into your CRM or ERP, export sales by SKU, and save files.2. **Have the agent open Google Sheets and Excel** It uploads fresh data into your Sheets model, opens your Excel PVM workbook, refreshes Power Query, and recalculates price, volume, and mix.3. **Generate outputs you actually use** The agent can copy the latest PVM summary into a Google Sheet dashboard, export an Excel chart as PDF, and email or upload it to your team workspace.**Pros:** - End‑to‑end automation across web, desktop, and cloud. - Production‑grade reliability; handles thousands of UI steps. - Transparent logs so finance and RevOps can audit each step.**Cons:** - Requires one‑time setup and clear instructions. - Best for teams with recurring PVM needs (weekly, monthly).#### Method 7: Always‑on PVM copilot for sales and marketing1. **Centralize your Sheets and Excel models** so the agent knows exactly which files contain the canonical PVM logic.2. **Let the agent watch for new data** Trigger it via webhook when monthly books close or when a new campaign ends.3. **Ask higher‑level questions** Instead of manually digging, you can have the agent run the PVM, then summarize insights: which product mix changes improved ROI, where discounting destroyed margin, which regions deserve price tests.**Pros:** - Turns a technical analysis into a self‑serve narrative for non‑financial founders, agencies, and marketers. - Saves analysts from repetitive mouse‑clicking across tools.**Cons:** - Relies on the underlying spreadsheet formulas being correct. - Requires clear governance about which numbers are “official.”Once these AI agents are in place, price volume mix analysis stops being a monthly fire drill and becomes a quiet, always‑on signal you can trust.