SKU Naming Cleanup — AI workflow for Malaysian SMEs
SKU Naming Cleanup turns product master list into standardised SKU naming. AI writes the first draft. You check it before it goes out.
Ready-to-use prompts for SKU Naming Cleanup
Create prompt
Create prompt
Create a first-pass deliverable
Setup · same in all four
You are helping a small or medium Malaysian business in [industry]. Write in plain English. Use short sentences. If customers will read it in Bahasa Malaysia, add a natural BM version. Do not invent numbers, prices, laws or customer details. If something needs a human to check, say so.
Replace [industry] with yours — “F&B”, “construction”, “retail”.
The task
Create standardised SKU naming. You will get product master list from me. Treat this as SKU naming cleanup for retail, distribution, F&B, manufacturing and e-commerce businesses. Keep every section short and concrete. End with the one action to take next. Give me a clean copy-paste version too.
Replace “product master list” with your real data.
Analyse prompt
Analyse prompt
Analyse the input and identify the highest-impact insights
Setup · same in all four
You are helping a small or medium Malaysian business in [industry]. Write in plain English. Use short sentences. If customers will read it in Bahasa Malaysia, add a natural BM version. Do not invent numbers, prices, laws or customer details. If something needs a human to check, say so.
Replace [industry] with yours — “F&B”, “construction”, “retail”.
The task
Study the product master list I provide and analyse the SKU naming cleanup picture. Surface the top five insights, with numbers where the data supports them. Spell out the business impact. Deliver standardised SKU naming. End on the three highest-impact actions for inventory data quality.
Replace “product master list” with your real data.
Optimise prompt
Optimise prompt
Improve an existing version for better business results
Setup · same in all four
You are helping a small or medium Malaysian business in [industry]. Write in plain English. Use short sentences. If customers will read it in Bahasa Malaysia, add a natural BM version. Do not invent numbers, prices, laws or customer details. If something needs a human to check, say so.
Replace [industry] with yours — “F&B”, “construction”, “retail”.
The task
Review and upgrade my SKU naming cleanup. Input: product master list, plus what we currently produce. Tell me where it loses accuracy, clarity or conversion. Remove work that adds nothing. Hand back a better standardised SKU naming, with each improvement mapped as before-issue, change, expected inventory data quality movement.
Replace “product master list” with your real data.
Automate prompt
Automate prompt
Turn the task into a repeatable AI-assisted workflow
Setup · same in all four
You are helping a small or medium Malaysian business in [industry]. Write in plain English. Use short sentences. If customers will read it in Bahasa Malaysia, add a natural BM version. Do not invent numbers, prices, laws or customer details. If something needs a human to check, say so.
Replace [industry] with yours — “F&B”, “construction”, “retail”.
The task
Automate SKU naming cleanup for me. Trigger event: product master list. Deliverable: standardised SKU naming. Stack: POS, inventory system, e-commerce, accounting. Lay out the trigger, required inputs, AI step, decision rules, where humans sign off, fallback behaviour, what to log, and inventory data quality tracking. A two-person Malaysian team must be able to keep this running.
Replace “product master list” and the listed systems with what you actually run.
New here? How the four prompts work together
They are one sequence, not four options. Run them in order on the same piece of work, feeding each answer into the next.
Create
Paste your real data. You get a first draft. Most people never need to go further than this.
Analyse
Paste that draft back in. It tells you what is weak, missing or wrong before a customer sees it.
Optimise
Paste the draft again with what Analyse found. You get a stronger version.
Automate
Only once the output has been good five times running. This is the one people reach for too early.
Nothing forces you through all four. A good Create draft that you edit yourself is a finished job. The longer version.
Specification
- You give it
- Product master list
- You get back
- Standardised SKU naming
- Moves
- Inventory data quality
- Run it
- Daily/Weekly
- Priority
- P2
- Works with
- POS, inventory system, e-commerce, accounting
- Tool guides
- Accounting software, POS systems
Is this for you?
- Pick it for
- Retail, distribution, F&B, manufacturing and e-commerce businesses. No setup needed. If you can copy and paste, you can run it.
- What you get
- Drafted in minutes, not built from scratch. It aims at cost control. Watch one number: inventory data quality.
- Reach for it when
- Most SMEs run it daily to weekly. If you are doing it by hand more often, automate it first.
How to run it
- 01Collect the input: product master list.
- 02Copy the Create prompt and paste it into ChatGPT, Claude or Gemini.
- 03Replace “product master list” in the prompt with your real data, then run it.
- 04Read the output against what you already know and correct anything the model guessed at.
- 05Track inventory data quality. Only wire up the Automate prompt after five useful runs in a row.
The tools you will need
The prompts run in any chat assistant — ChatGPT, Claude or Gemini. These are what you need around them to get the input in and the output somewhere useful.
- inventory system
- inFlow Inventory
- KatanaAimed at makers and light manufacturing.
- SortlyFree tier for a small catalogue.
- Zoho Inventory
- e-commerce
- Any tool you already use is fine.
- accounting
- AutoCountMalaysian, widely used for SST and e-Invoice.
- QuickBooks
- Xero
Check the rules yourself
This workflow touches rules set by someone else. Check the current requirements yourself before you act on the output.
- KPDN
- How you display a price, run a discount and word a promotion is regulated, and a claim about savings has to be true. AI writes persuasive promotional copy very easily — this is the body that decides whether it was misleading.
Links go to each authority’s own site. See all Malaysian authorities.
Data & privacy
If you paste customer or staff details into an AI tool, your business stays responsible for them under the PDPA. Replace names and numbers with initials or references first.
Using customer data with AI tools in Malaysia covers what to check with any provider before you paste.
For this website, it works differently.
Nothing you type here is sent to us or to an AI model. The prompts are static content, and the copy button works directly inside your browser.
Related workflows
- Slow-Moving Stock DetectionTurns SKU inventory and sales into slow-moving list.
- Reorder RecommendationTurns stock, lead time and sales into reorder plan.
- Stockout RiskTurns stock and sales velocity into reorder risk list.
- Dead Stock Action PlanTurns aged inventory into clearance/transfer/bundle plan.
All inventory & stock management workflows: Inventory & Stock Management
Maintained by Naven Pillai