Illustrative examples of ranking parameters

Quality of sitemap Page-loading speed Security (e.g. HTTPS) Images (e.g. type, number, quality) Consumer reviews (e.g. number, rating, recent) Trader-Consumer Interaction (e.g. answered queries, responsiveness) Dispute settlement history (e.g. number of consumer complaints, solutions found) Completed sales (e.g. number, recent) Price Internet traffic, performance in search ‘Offline’ service quality indicators (e.g. hotel star rating, delivery performance, the degree to which places, brands etc. are familiar or well known in society) Trust measures (e.g. participation in platforms' escrow services, registered identity, industry certification schemes/icons, data protection seals / certifications) Data protection ‘score’, e.g. based on reviewing the privacy policies of apps by an app store Web accessibility (Multi-)Device adaptability Content quality (e.g. based on website linking, richness, language quality, number of languages, etc.) Key word tagging (positive – number, level of detail, and negative – ‘stuffing’) Title accuracy and relevance (e.g. brand, technical specifications, etc.) Date of market entry Concise answers, for example as regards products or services offered, or in response to FAQs Paid ranking (including by online intermediation services on online search engines) — bid — quality of ad, context — reliability of advertiser Size of offer (e.g. breadth of product or service offer, or in-app purchases featured separately in app stores ranking) Editorial processes and specific selection criteria (e.g. platform-reviewed apps or art projects) Adjustment algorithms (concerning, for example, spam, freshness, quality) Mobile app uninstall rates Bounce rates A/B testing (impact can be influenced by certain elements such as timing – peak demand, duration and sample size) Randomisation Personalisation — the extent of personalisation (number and types of features that come into play), whether and how it may be dependent on users’ privacy settings, etc. — geographic location, timing of search — user search history, acquisition history — undoing default settings — impact of filters (and remaining parameters) Multi-platform presence (e.g. negative impact of lower pricing on competing platform on ranking, social media ‘scoring’, referencing/linkage rate of the site, frequency of referencing, reputation of referencing sites or blogs) ‘Brand appeal’ of new entrant business users being measured using factors external to the online intermediation services concerned (e.g. surveys among a specialised community) Strength of the offer, e.g.: — comparable competitiveness (e.g. ratings, consumer reviews) — relevance — availability — rejection tracker — cancellations — double bookings (sector specific) Conversion rates Geographic proximity Level of commission paid Non-participation in certain programme (causing degradation in a ranking) or participation in a certain program/purchase of additional services (leading to improved ranking) Business user’s stock depth Seasonality and temporary deviations (e.g. a one-day-long sales event) National approach (Cross-border cultural differences) Particular methodology of weighing user reviews (e.g. usage of trusted reviewers) Experimentation (e.g. platforms pro-actively pushing new entrant business users) ‘Mobile-friendliness’ of a website Editorial interventions (editor’s ‘top picks’, ‘deals of the day’, corrections made to search results that are specific to an individual business user or corporate website user, regardless of whether these are ‘manual/human’ or ‘algorithmic’, etc.) Housekeeping practices (e.g. deletion of old apps) Click-through rates Access rules Fraud prevention mechanisms Bundled services of business or corporate website users (e.g. free shipping, easy returns policy, etc.) Quality of the description of the offer (written description, usage of pictures, etc.) Use of options for premium visibility/temporary visibility boosting (e.g. the use of such mechanism to generate additional income and/or to facilitate product/service launches or market entry) possibly combined with, or in the form of, mechanisms or actions that reduce the importance for relative prominence of ‘otherwise applicable’ parameters Importance of reputation/trust based on e.g. user reviews or ratings Quality of content including regular update of content Use of clear and brief titles The speed and all-device user–friendliness Number of listings matching the buyer's query Domain age Uniqueness of content Input provided by the user (words typed or spoken, gender, age, culture, language, address, previous interactions, etc.) ‘Objective’ platform-external data (date, time, weather, etc.) Personal data related to other users (likes, most searched words, products most sold, etc.) Number of ‘shares’/ number of views / number of ‘saves’, ‘favourites’ Technological means/medium (i.e. how the ranking is being accessed by the consumer) Multi-links Remuneration Business relationship with the business user (length of historical relationship, privileged business relationship, any investment related to the platform, etc.) Quality of the customer service Ratio of cancellations Market-related features (general demand, competitive prices, competitive availability, etc.) Negative criteria such as incidence scores for consumer complaints or assumptions that certain features are disliked by consumers Scores for resolutions of consumer issues Parity (e.g. comparison of intermediary rates with rates in other channels of distribution) Store conversion Application Not-Responding (ANR) Retention Installs and back-links to external websites Stock availability Quality and characteristics of the product Relevance of the product to the assortment Filters applied by consumers to narrow down their search Search-related inputs (listing content, listing attributes, keywords/tags/labels) Relevance based on the match of end user and business user inputs Popularity of offers End user demonstration of ranking order preference (most recent, most relevant, highest reviewed, etc.) Legal requirements (including fraud/anti-counterfeiting issues) Newly listed Preference towards business users opting for the possibility to use MFN clauses, e.g. if these are not generally imposed Offers ending soon Nearest first Auction vs buy it now Brand Item condition (new vs used) Example of specific parameters that may be used in the accommodation sector: Minimum availability indicated by the accommodation The volume realised by the accommodation Services and amenities (e.g. dining, parking, fitness facilities, front desk and concierge services, WiFi and business centres, proximity to transportation and local attractions) The number of bookings related to the number of visits to the relevant accommodation page on the platform (conversion rates) Quality of the hotel compared to the quality advertised Confirmation of the reservation of the hotel or restaurant Distance of the restaurant to the customer or previous user patterns Policies (regarding e.g. early check-in, late departure, and cancellation privileges) Property-related (number and quality of consumer reviews, commission level, punctuality of invoice payments, promotions, participation in preferred programmes, etc.) Purpose of travel (business/leisure)

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Source: EUR-Lex (Cellar) · retrieved 2026-09-07