What the data for this category looks like
Personal care product marketing data primarily comes from brand internal product manuals, e-commerce platform detail page copy, live marketing scripts, ingredient test reports, and offline promotional materials. The data update rhythm changes with new product launches, compliance requirement adjustments, or marketing campaign cycles, with no fixed schedule. Document formats include long text manuals, short copy for individual products, ingredient/specification tables with structured data, and mixed text-image files embedded with product images and usage effect images. Core fields include product name, active ingredients, specifications (such as milliliters, grams, piece count), skin type suitability, usage methods, and marketing selling points. Units mostly follow common measurement standards in the care industry, such as ml, g, and pieces.
What constraints these characteristics impose on the document parsing and chunking process
Diverse document sources require parsing tools to support multiple formats including docx, pdf, and excel. They must also handle layout differences inherent to each format, such as nested tables in excel and embedded images in pdf. Frequently updated promotional materials need parsing workflows that support fast batch processing, to avoid delays in overall efficiency caused by overly long parsing times for individual documents. Structured ingredient tables and specification parameter tables require chunking logic to preserve semantic units, so related product names and corresponding ingredients are not split into different chunks. Mixed text-image documents need parsing tools to extract image alt text or embedded descriptions, to ensure visual selling points in marketing content can be fully converted into retrievable text information. Specific measurement units and skin type descriptions also require retaining contextual connections during chunking, to avoid separating units from their corresponding ingredients.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
PARSE_ENABLE_IMAGE | Enabled | Personal care marketing documents often include product images and usage effect images. Enabling this setting extracts image alt text or embedded descriptions, adding additional retrieval dimensions |
PARSE_TABLE_MODE | Retain cell structure | Personal care documents frequently contain ingredient tables and specification parameter tables. Retaining structure prevents related information from being split apart |
CHUNK_SIZE | 800–1200 characters | Adapts to the semantic integrity of long manuals and short copy, avoiding excessive splitting of key information |
PARSE_FILE_TIMEOUT_SECONDS | 120 seconds | Balances batch processing efficiency and long document parsing needs, preventing single tasks from being interrupted by timeouts |
CHUNK_OVERLAP_RATE | 10–15% | Reduces semantic boundary breaks, ensuring key information in long paragraphs or tables can be linked across chunks |
ENABLE_METADATA_EXTRACT | Enabled | Can extract metadata such as product name and skin type suitability, to assist subsequent retrieval and result correlation |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing settings.
Three common mistakes
- Symptom: After uploading a PDF document, the parsing result contains no image-related text, and embedded images cannot be displayed in the front-end preview. Cause: The
PARSE_ENABLE_IMAGEconfiguration item is not enabled, or the backend components required for image parsing are not deployed correctly. - Symptom: After uploading a docx format product manual, the chunking result splits the ingredient table into multiple independent segments, and the corresponding product name cannot be linked. Cause:
PARSE_TABLE_MODEis not set to retain cell structure, and the chunk length is set too small, causing table semantics to be split. - Symptom: Parsing tasks frequently trigger timeout errors when batch processing excel format product specification tables. Cause: The
PARSE_FILE_TIMEOUT_SECONDSsetting value is lower than the actual required parsing time, orPARSE_BATCH_SIZEis not configured to limit the number of concurrent tasks.
How to confirm configurations are correct
- Upload a single typical personal care marketing document, such as a 10-page product manual, and check the parsed chunk list to confirm that structured content such as ingredient tables and specification parameters is not split.
- Enter the document parsing configuration interface, and verify that the values of core configuration items such as
PARSE_ENABLE_IMAGEandPARSE_TABLE_MODEmatch the preset requirements. - Submit a batch parsing task, and check system logs to rule out timeout or format exception errors.
- Retrieve specific keywords in the document, such as the core ingredient of a product, to confirm that the search results contain complete related information, with no semantic breaks.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.