E-commerce Dictionary

A circular product identity is a unique digital record linked to a physical product that keeps its material, repair and recycling data available through resale, repair and end of life.

A cloud PIM is product information management software that runs online as a service, so your team works in a browser and the vendor handles hosting, updates and scaling.

Completeness refers to the extent to which all required and recommended product attributes, media, and translations are present and filled out for a product across all intended sales channels.

Product compliance data is the legal and safety information a product must show or carry to be sold, such as CE marking, warnings, ingredients and the responsible person.

Composable commerce is an approach where you build your online store from separate, best-fit services such as checkout, search and PIM, connected through APIs.

A composable PIM is an API-first product information management system that works as one replaceable building block in a composable commerce stack.

Computer vision for DAM is AI that analyzes images and videos in a digital asset management system to tag, describe and organize them automatically.

A content delivery network (CDN) is a group of servers in many locations that stores copies of website files and serves each visitor from a nearby server.

A content editor in a PIM is the person who writes, checks, translates and completes product content such as titles, descriptions and attributes before it goes to sales channels.

A content gap analysis compares the content you have with the content your audience needs or competitors offer, to find missing topics, pages and product information.

Content governance is the set of roles, rules and processes that decide who creates, reviews, publishes and updates content, and to which standard.

A content model is a structured plan of the content types you manage, the fields each type has and how the types relate to each other.

Content syndication in ecommerce is sending product titles, descriptions, attributes and images from one source to retailers, marketplaces and comparison sites in each channel's format.

Contextual commerce lets people buy a product right where they discover it, such as in a social post, video, article, chat or AI assistant, without going to a separate webshop first.

Contextual product information is current product data adapted to where and how a shopper sees it, such as channel, device, language or location.

Conversion rate (CR) is the share of visitors or sessions that complete a goal, usually a purchase, calculated as conversions divided by sessions times 100.

Product page CRO is the practice of testing and improving product detail pages, such as images, titles, specs, reviews and the buy box, so more visitors add to cart.

Country of origin is the country where a product was manufactured or last substantially transformed, stored as a product attribute for customs, labels and sales channels.

Cross-border trade (CBT) attributes are product fields needed to sell abroad, such as HS code, country of origin, weight and customs value.

Cross-channel content consistency means a product shows the same core facts, such as name, specs, price and images, on every channel where you sell it.

Cross-functional collaboration is when people from different departments work toward one shared goal with clear roles, such as a complete and correct product launch.

Cross-selling in ecommerce is suggesting complementary products, such as accessories or matching items, to a shopper who is viewing or buying a related product.

A customer data platform (CDP) collects customer data from every source, such as your webshop, email and ads, into one profile per customer that other tools can use.

Customer reviews and ratings are buyer feedback on a product: a star score plus a written review that helps other shoppers decide.

Customer-centric product data is product information written and structured around what shoppers need to decide, not only around internal specs.

Customer-led product development is building and improving products based on direct customer input, such as reviews, returns, support questions and interviews.

Data cleansing is finding and fixing errors, duplicates, gaps and inconsistent formats in data. For ecommerce, it means cleaning product data before it reaches your channels.

Data consolidation is combining data from several sources, such as supplier files, an ERP and webshops, into one cleaned and consistent dataset in a single system.

A data contract is an agreement between the producer and the consumer of data that defines its structure, allowed values, quality rules and ownership.

Data decay is the gradual loss of accuracy in stored data, such as product details that become outdated as prices, specs and suppliers change.

Product data deduplication finds and removes duplicate product records by matching on identifiers, names and attributes, so each product exists once.

Data governance is the set of rules, roles and checks that decides who owns which data, how it is created and changed, and what quality it must meet.

Data ingestion is the process of collecting data from sources such as supplier files, ERPs and APIs and loading it into a central system for storage and use.

A centralized repository for storing large volumes of raw, unstructured, and semi-structured product data from various sources before it's processed or structured.

Data lineage is the record of where a piece of data came from, which steps changed it and where it went, from source to final destination.

Data mapping rules are instructions that link each field in a source, such as a supplier file, to a field in a target system and say how to convert the value on the way.

A data mesh is a decentralized data architecture where business domains own and publish their data as products, following shared governance rules.

A data model defines what data a system stores and how it relates; a PIM data model structures products, variants, attributes and categories.

Data orchestration in e-commerce coordinates how data moves between ERP, suppliers, PIM and sales channels, in the right order and format.

Data productization is turning raw data into a documented, owned and quality-checked data product that other teams and systems can use directly.

Data profiling is analyzing an existing dataset to see what it contains: how complete each field is, which values and formats occur, and where errors sit.

Data quality is how accurate, complete, consistent and current your data is. In e-commerce it covers specs, attributes, images and values on every channel.

Data quality monitoring is the ongoing checking of data against rules for completeness, accuracy and consistency, with alerts when quality drops.

A data quality rules engine checks every record against rules you define, such as required fields, allowed values and formats, and flags or blocks data that fails.

A data quality score is a number, often 0 to 100, that shows how complete, correct and consistent a product record or catalog is against the rules you set.

Data residency is the physical or geographic location where an organization's data is stored, often chosen to meet laws, contracts or customer expectations.