E-commerce Product Title Optimizer

Problem

Product titles affect search exposure, click-through, and conversion, but small and mid-sized e-commerce teams often lack stable rules. Copying competitors can introduce banned terms, manually written titles may miss high-weight keywords, and generated titles may not improve with real performance. The e-commerce product title optimizer turns title creation into a checkable workflow instead of a one-shot writing task.

Capabilities and workflow

It works from category keyword banks, platform length rules, banned-word dictionaries, and platform ranking signals, covering Taobao, Tmall, JD, Pinduoduo, and Douyin, with v2.1 support for English titles on Shopee and Lazada. Key capabilities include:
- Title generation: produce Top-N candidates from category, selling points, and target keywords, with compliance checks and cold-start fallback.
- Diagnosis and scoring: score titles on keyword weight, length, structure, and CTR triggers, then provide actionable rewrite suggestions.
- Banned-word screening: detect extreme claims, false promises, off-site promotion, brand-risk terms, and efficacy violations.
- Competitor benchmarking: compare the user’s title against rivals and identify missing keywords.
- Low-friction parsing: extract category, selling points, and target keywords from product descriptions or links.
- Feedback loop: ingest impressions, clicks, and orders to reweight keywords and write high-performing terms back to the keyword bank.

Boundaries

It is useful for bulk title drafting, compliance pre-checks, and iterative operations, but it does not replace official platform data. Sparse categories are limited by keyword-bank coverage, so discover is needed to expand terms; demand scoring depends on an external keyword-metrics.json; final publishing still requires platform rules and legal review. For more natural copy, use prompt templates and validate the output with score.