How to Generate Product Bullet Points with AI in conbase.ai
Introduction
- The Goal:
- By the end of this guide, you’ll be able to whip up clear, punchy bullet points for hundreds or even thousands of products in minutes, bringing order and consistency to your catalog.
- The Problem:
- Typing bullet points by hand for every product is slow, dull, and prone to mistakes. Merchandising teams waste hours re-writing specs, and shoppers get mixed messages.
- The Solution:
- Conbase.ai lets you build a custom AI pipeline that turns raw product data into polished bullets. You control the prompt, format, and output columns, so every line matches your brand’s style.
- Prerequisites:
- A Conbase.ai account
- A CSV with product data (name, description, key specs, etc.)
- Basic knowledge of what makes a good e-commerce bullet list
Are you here for the first time ? Then watch a full conbase.ai workflow in action
This video walks you through a complete conbase.ai workflow, from input to final output, so you can see exactly how the platform works and how to get the most out of its features.
Step 1: Set Up Your Project and Import Data
Create a New Project
Log in, click New Project, and call it “Generate Product Bullet Points – 2025”. This keeps everything tidy and easy to find later.
Upload Your Products CSV
Drag your CSV into the uploader. Conbase.ai shows a preview so you can double-check column headers.
- Use clear column names like product_name, description, specs
- Clean out odd symbols or blank rows before import
- Add any extra context columns you think the AI might need (for example, brand or material)
Step 2: Build Your AI Generation Pipeline
Add an Action Step
Click Add Step, choose Create New, and name it Generate Bullet Points.
Write Your Prompt
The prompt has three parts: instruction, context, and expected output.
Instruction (static):
You are an e-commerce copywriter. Write five concise bullet points that highlight key benefits, important specs, and materials. Use sentence case and start each bullet with an action verb. Do not repeat the product title. Avoid hype words like amazing or ultimate.
Context (dynamic):
Product name: {product_name}
Description: {description}
Specs: {specs}
Output (target column):
- Create a new column called generated_bullets
- Add one sample so the AI sees what good looks like:
• Fits true to size for most customers
• 100 percent organic cotton for soft feel
• Pre-shrunk so it stays the same after wash
• Ribbed neck keeps its shape
• Printed in eco-friendly inks
Step 3: Configure and Run the Pipeline
Select Settings
- Model: "GPT-4o"
- Processing Mode: "Instant" for test runs and fast execution, "Scheduled" for big jobs that can wait up to 24h and for 50% less api costs
- Integration: "Fill if empty" keeps already available data
Test, Review, and Scale
- Select ten rows and click Run Pipeline
- Read the bullets. Check tone, length, and accuracy
- Tweak the prompt if needed, then run on the full dataset
Step 4: Review and Export
Quality Check
- Open random rows and compare bullets to source data
- Look for repeated info or filler words
- Fix any outliers by re-running those rows with a refined prompt
Export Your CSV
Hit Export. You’ll get a CSV that includes the new generated_bullets column. Keep a backup of the original file before importing into your store.
Conclusion and Next Steps
You’ve turned a time-consuming chore into a quick, repeatable workflow. Use the same approach for product summaries, SEO tags, and more.
- Track how much faster listings go live
- Measure conversion lifts from clearer bullets
- Share this guide with teammates so everyone works from the same playbook
Ready to boost more workflows? Book a free demo and explore what else you can automate.
