Use Case

Turn customer reviews into SEO-friendly proof blocks

Import your reviews. Batcher aggregates them by product, extracts key themes (pros, cons, recurring criteria), and generates structured summary blocks - ready to inject into your product pages or category pages.

Try it free
Hundreds of products enriched
Real customer vocabulary extracted
SEO-friendly HTML output

The problem

Your customers leave reviews on third-party platforms (Trustpilot, Google, Trusted Shops) loaded via JavaScript widgets. Google can't see them - they don't count for SEO. Meanwhile, your competitors have rich, native review content on their product pages that boosts their rankings.

Manually reading thousands of reviews, extracting themes, and writing summaries? Nobody has time for that.

How Batcher solves it

1

Import your reviews.

Export from your review platform, or use Jina to scrape them from your site. One row per review, or one row per product with all reviews concatenated.

2

Aggregate by product.

Batcher groups reviews by product or category.

3

Summarize and structure.

AI generates a structured block for each product: top 3 strengths, top 3 concerns, most mentioned criteria, overall sentiment. Output in HTML ready for injection into your CMS.

4

Extract real vocabulary.

Batcher pulls actual customer language from reviews - terms your customers use that you might not have in your descriptions. This enriches your pages' semantic field.

Who this is for

  • E-commerce managers wanting native review content for SEO
  • Agencies offering content enrichment services
  • Marketing teams mining customer insights from review data

Your reviews are hidden from Google. Fix that.