A glossary for eCommerce analytics 

Eric Chuk

Words used to talk about eCommerce and analytics are usually clear to those who have a long tenure in the industry, but in some cases the terminology isn’t obvious—especially considering that different words are used to refer to the same or similar things and that the industry changes quickly. To establish a better understanding of some of the core concepts, here is a list of terms found in data-driven eCommerce that are closely related but indicate important distinctions.

Assortment: the set of products made available for sale by a retailer

Automated vs. manual: a computerized system designed to perform tasks consistently at increased scale and speed is automated, whereas a manual approach is less systematic and more prone to human error

Brand/manufacturer: the maker (not necessarily the seller) of a product

Business intelligence vs. competitive/market intelligence: the difference between internal company information that is critical for decision-making versus information about the space the company operates within, including other businesses with similar goals or customers

Crawling/extracting/scraping: often used interchangeably to mean the process of copying data from websites and other online sources to a database (to crawl the web is to navigate various pages of interest while collecting relevant data through extracting/scraping tools and processes)

Data vs. analytics: data is information that has been gathered, standardized, and structured to enable processing; analytics is the discovery or interpretation of meaningful patterns in data

Data science vs. machine learning: data science is a broad field concerned with obtaining knowledge from large amounts of data (often through statistical analysis); machine learning consists of computational methods for pattern recognition (such as classification, regression, and clustering)

Data-driven: focusing on the use of data and metrics to make business decisions, instead of intuition or guesswork

Distributor vs. wholesaler: a distributor has an inventory of products from various brands that it often sells to retailers in smaller amounts and at a faster delivery speed than a brand; a wholesaler is a brand or distributor that sells to retailers

eCommerce: the selling and buying of products online

Gray market: the selling of products by those unauthorized to do so, who may violate pricing agreements or other policies of the original manufacturers

Omni-channel: the phenomenon of retailers having to sell in a consistent, competitive manner across all channels or platforms (online, including websites and mobile devices, as well as offline, such as brick-and-mortar stores)

Optimization: adjustment of parameter settings (based on data) to improve performance

Price vs. value: price is the amount a seller expects to be paid for a product (usually not considered negotiable by buyers, but it is affected by supply/demand) and reflects a brand’s intended market; value is an assessment of worth determined by both price and desirability (good value often means high desirability or quality at a below-average price)

Pricing elasticity: flexibility in the amount that can be charged for a product while still maintaining a desired level of profit

Product vs. SKU (stock-keeping unit): a product is an item sold, which can have various combinations of attributes such as size or color—each combination is a stock-keeping unit and has its own unique identification number for tracking

Promotion: a price reduction or incentive offered by a seller for certain products, including not only discounts or markdowns (percentages off and dollar amounts off) but other types (free shipping, free gift with purchase, and “buy one, get one”)

MSRP (manufacturer’s suggested retail price) vs. MAP (minimum advertised price): both are forms of retail price maintenance or control; MSRP is the amount that the maker of a product would like it to be sold for (the baseline price that determines how much resellers pay the manufacturer to get the product in the first place), while MAP is a limit set by brands for compliance by retailers (the final selling price for a product may be below MAP, but resellers cannot advertise a price below it)

Repricing: adjustment of product prices in response to specific criteria, either automatically (using specified rules or dynamically) or manually

Retailer/merchant: the seller/reseller (not necessarily the maker) of a product (some merchants also have their own self-generated brands or product lines)

SEO (search engine optimization) vs. SEM (search engine marketing): SEO is part of SEM, which aims to increase the visibility of a website in the results pages of search engines (by optimal use of keywords and links to drive organic traffic as well as through pay-per-click advertisements)

Taxonomy vs. classification: a taxonomy is a system of knowledge organization stricter than classification, since it specifies a hierarchal relationship between categories and category members and establishes standardized labels for the concepts it covers

White space: a gap or unfulfilled area in a market, whether defined by price range, product assortment, or other factors

Recap: Using this newfound vocabulary

From the perspective of savvy retailers and brands, modern eCommerce relies on data and analytics to deliver actionable competitive intelligence. Such intel is the result of data science, which automates the classification and comparison of various products sold across the web. It also assists in tracking their prices over time, at scale. This goes beyond search engine optimization/marketing by extracting and cleaning raw data about products to make it usable in answering key questions.

Common concerns that can be addressed by this approach include the optimization of assortment, pricing, and promotions, as well as the enforcement of MAP compliance (even in the gray market). Strategic opportunities to expand or differentiate your business based on unfulfilled white spaces can also be identified. As eCommerce players are increasingly expected to provide a consistent omni-channel experience, turning to platforms such as Quad’s can help you make data-driven decisions to win customers, no matter how big the competition or how fast things change.

What are some other foundational concepts or terms you’ve encountered as a brand or retailer conducting eCommerce in the era of big data? Let us know your thoughts or questions.

Eric Chuk

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