Seller Picks Selection Strategy — AI workflow for Malaysian SMEs
Seller Picks Selection Strategy turns your product performance data into a Seller Picks selection strategy. AI writes the first draft. You check it before it goes out.
Ready-to-use prompts for Seller Picks Selection Strategy
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. Platform context: Lazada mechanics, fees and programme requirements change often — treat every rule as current-per-Seller-Center, to be confirmed there before committing money.
Replace [industry] with yours — “F&B”, “construction”, “retail”.
The task
Build me a Seller Picks selection strategy. Input from my side: your product performance data. This is a Seller Picks selection strategy for Lazada sellers running Malaysian stores, so keep it grounded and usable. Structure it in tight sections. Close with the single next action. Include a copy-ready version.
Replace “your product performance data” 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. Platform context: Lazada mechanics, fees and programme requirements change often — treat every rule as current-per-Seller-Center, to be confirmed there before committing money.
Replace [industry] with yours — “F&B”, “construction”, “retail”.
The task
I need analysis on a Seller Picks selection strategy. You get your product performance data. Find the five findings worth acting on, rank them, and attach the likely business impact to each. Turn the result into a Seller Picks selection strategy. The last section: three concrete steps to move picks-driven traffic.
Replace “your product performance data” 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. Platform context: Lazada mechanics, fees and programme requirements change often — treat every rule as current-per-Seller-Center, to be confirmed there before committing money.
Replace [industry] with yours — “F&B”, “construction”, “retail”.
The task
Review and upgrade my Seller Picks selection strategy. Input: your product performance data, plus what we currently produce. Tell me where it loses accuracy, clarity or margin. Remove work that adds nothing. Hand back a better a Seller Picks selection strategy, with each improvement mapped as before-issue, change, expected picks-driven traffic movement.
Replace “your product performance data” 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. Platform context: Lazada mechanics, fees and programme requirements change often — treat every rule as current-per-Seller-Center, to be confirmed there before committing money.
Replace [industry] with yours — “F&B”, “construction”, “retail”.
The task
Turn a Seller Picks selection strategy into an automated workflow. It starts when your product performance data arrives. It must end with a Seller Picks selection strategy. Available systems: Lazada Seller Center, Sponsored Solutions, Excel/Google Sheets. Map out: trigger, fields to capture, AI step, decision rules, where a human approves, what happens on failure, data to store, and picks-driven traffic tracking. Keep the whole thing maintainable by a small team.
Replace “your product performance data” 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
- Your product performance data
- You get back
- A Seller Picks selection strategy
- Moves
- Picks-driven traffic
- Run it
- Monthly
- Priority
- P2
- Works with
- Lazada Seller Center, Sponsored Solutions, Excel/Google Sheets
- Tool guides
- Excel & Google Sheets, Lazada Seller Center
Is this for you?
- Pick it for
- Lazada sellers running Malaysian stores. 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 growth. Watch one number: picks-driven traffic.
- Reach for it when
- Most SMEs run it monthly. If you are doing it by hand more often, automate it first.
How to run it
- 01Collect the input: your product performance data.
- 02Copy the Create prompt and paste it into ChatGPT, Claude or Gemini.
- 03Replace “your product performance data” 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 picks-driven traffic. 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.
- Lazada Seller Center
- Any tool you already use is fine.
- Sponsored Solutions
- Any tool you already use is fine.
- Excel/Google Sheets
- Any tool you already use is fine.
Check the rules yourself
This workflow touches rules set by someone else. Check the current requirements yourself before you act on the output.
- LHDN
- e-Invoice arrived in phases set by turnover. LHDN's published timeline puts Phase 4 at businesses up to RM5 million from 1 January 2026, and exempts those under RM1,000,000 a year. Check which phase you are in before you change how you invoice. Read from LHDN in August 2026; confirm it is still current.
- RMCD
- Cross the registration threshold and you must charge SST and file returns on time. Whether a service is taxable or exempt is decided here, and getting it wrong is expensive to unwind later.
- JPDP
- Pasting customer or staff records into an AI tool is a transfer of personal data. Consent, notice, retention and cross-border rules still apply when the tool is not yours.
Links go to each authority’s own site. See all Malaysian authorities.
Data & privacy
This workflow involves buyer names, addresses and order history. Under the PDPA your business stays responsible for it, and pasting it into an AI tool may be a disclosure to a third party. Replace names and numbers with initials or references first — the prompt works just as well on “Customer A”.
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.
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Maintained by Naven Pillai