Pertama Partners

AI Inventory Analysis and Merchandising Reports

Use AI to generate inventory analysis narratives, merchandising recommendations, and sell-through reports that help retail teams make faster, data-driven decisions. Built for multi-channel retailers managing stock across physical stores, warehouses, and marketplace fulfillment centers.

RetailIntermediateWorkflow Automation & Productivity2-4 weeks

Transformation

Before & After AI

What this workflow looks like before and after transformation

Before

Inventory reports are raw spreadsheets that require hours of manual interpretation. Merchandising decisions rely on gut feel and outdated weekly summaries. Slow-moving stock goes unnoticed until it becomes dead stock. Stockouts during peak periods (11.11, Hari Raya) happen because teams lack timely sell-through visibility across channels.

After

AI transforms raw inventory data into narrative reports with clear recommendations: what to markdown, what to reorder, and where to reallocate stock between channels. Weekly sell-through analysis is automated, and merchandising briefs are generated with actionable next steps. Dead stock is flagged within 2 weeks instead of 2 months.

Implementation

Step-by-Step Guide

Follow these steps to implement this AI workflow

1

Connect Inventory Data Sources

3-5 days

Consolidate inventory data from your POS, warehouse management system, and marketplace fulfillment dashboards (Shopee, Lazada). Standardize fields: SKU, location, quantity on hand, quantity sold, days in stock, cost, and retail price. Establish a weekly data export routine.

Inventory Data Consolidation Prompt
You are a retail inventory analyst. I will provide inventory snapshots from [NUMBER] sources: [SOURCE_LIST]. Help me design a unified inventory data template that standardizes SKU naming, location codes, and status fields across all sources. Include a data validation checklist to catch common discrepancies like duplicate SKUs or mismatched quantities.
Adapt the source list to your actual systems. This template works with any combination of POS, WMS, and marketplace platforms.
2

Generate AI-Powered Stock Analysis Narratives

1 week

Feed consolidated inventory data into AI to produce narrative summaries that translate numbers into plain-language insights. Focus on sell-through rates, aging stock, reorder signals, and channel-level stock distribution imbalances.

Inventory Narrative Report Generator
You are a retail merchandising analyst. Based on the following weekly inventory data for [CATEGORY], generate a narrative analysis covering: overall sell-through rate, top 5 fastest and slowest moving SKUs, stock aging alerts (items over [DAYS] days), reorder recommendations, and channel distribution imbalances. Write in clear business language for a non-technical audience.
Feed in your weekly data export as a CSV summary or paste key metrics. Run every Monday for consistent weekly rhythm.
3

Create Merchandising Recommendation Reports

1 week

Use AI to generate merchandising briefs that recommend product placement, bundling opportunities, markdown timing, and seasonal assortment adjustments. Incorporate marketplace trending data from Shopee and Lazada category insights.

Merchandising Strategy Brief Prompt
You are a retail merchandising strategist. Based on the following sell-through data and upcoming [EVENT/SEASON], generate merchandising recommendations for our [CATEGORY] assortment. Include: product bundling opportunities, markdown candidates with suggested timing and depth, hero product nominations for marketplace featuring, and assortment gaps to fill. Context: SE Asian market.
Run this analysis 4-6 weeks before major sales events. Combine with marketplace trending reports from Shopee/Lazada seller tools.
4

Automate Reporting Cadence and Review Process

1 week

Establish a weekly and monthly reporting rhythm where AI-generated reports feed into team review meetings. Define ownership, escalation triggers (e.g., stockout risk, dead stock threshold), and continuous improvement of report templates based on team feedback.

Reporting Cadence Design Prompt
You are a retail operations consultant. Design a reporting cadence for a [TEAM_SIZE]-person merchandising team managing [SKU_COUNT] SKUs. Include: weekly report schedule, monthly deep-dive agenda, escalation triggers and thresholds, and a template improvement feedback loop. The team currently spends [HOURS] hours per week on manual reporting.
Customize escalation thresholds based on your category margins and stock turn targets. Start conservative and tighten over time.

Get the detailed version - 2x more context, variable explanations, and follow-up prompts

Tools Required

AI assistant for narrative generation and analysisInventory management or POS system with data exportSpreadsheet tool for data consolidationMarketplace seller analytics (Shopee, Lazada)

Expected Outcomes

Reduce weekly inventory reporting time by 70%, from manual spreadsheet analysis to AI-generated narrative reports

Identify slow-moving and dead stock 4-6 weeks earlier, enabling timely markdowns that recover 15-20% more margin

Improve stock allocation across channels, reducing stockouts during peak events by 20-30%

Solutions

Related Pertama Partners Solutions

Services that can help you implement this workflow

Operations Automation Clinic

Learn more

AI Readiness Audit

Learn more

Common Questions

AI excels at pattern recognition in structured data like inventory levels, sell-through rates, and aging. It does not replace your merchandising judgment, but it surfaces insights faster than manual analysis. Think of AI as a junior analyst that processes the data and writes the first draft, while your experienced team makes the final decisions on markdowns, reorders, and allocation.

Start with a data cleanup sprint as part of Step 1. Most retailers find that 80% of their inventory data is usable after standardizing SKU codes and reconciling quantities. AI can work with imperfect data if you flag known issues in the prompt. Begin with your best-quality category and expand as data hygiene improves.

For stock committed to Shopee or Lazada fulfillment centers (FBL, SBS), AI reports should flag it separately with channel-specific sell-through analysis. Reallocation recommendations apply only to stock in your own warehouses. Over time, use AI insights to optimize how much stock you commit to each marketplace fulfillment program based on historical channel demand.

Ready to Implement This Workflow?

Our team can help you go from guide to production — with hands-on implementation support.

Get Implementation SupportBrowse All Guides