Instead of writing them manually, I wrote a Python script that uses a simple keyword extraction method to pull key terms from product descriptions and combine them into a template. Here's a snippet:
python
import re
from collections import Counter
def extract_keywords(text, top_n=5):
words = re.findall(r'\b[a-z]{3,}\b', text.lower())
return [word for word, _ in Counter(words).most_common(top_n)]
def generate_meta(description):
keywords = extract_keywords(description)
return f"Shop our {', '.join(keywords[:3])} collection. {description[:100]}..."
It's not perfect, but it saves a ton of time. For more complex SEO tasks, I've been using a tool that automates keyword research and meta tag generation. What's your workflow for bulk meta descriptions?
Top comments (1)
Interesting approach! I've tried something similar but found that keyword stuffing can hurt readability. Have you considered using TF-IDF instead of simple frequency to get more contextually relevant terms?