Voyado Product Discovery functional specification

The following specification outlines the core functionality of Voyado Product Discovery. It provides an overview of available features, data structures, and integrations designed to optimize product discovery, personalization, and merchandising. Product Discovery enables retailers to deliver relevant search, recommendations, and content to shoppers, while giving administrators full control through a dedicated application.

Search intelligence

  • Query analysis: Product Discovery interprets user queries using semantic analysis to understand intent.
  • Query matching: Queries are matched against enriched product data to deliver accurate results.
  • Search assistant (Autocomplete)
    • Phrase suggestions
    • Recent searches (by user)
    • Suggested searches (popular searches)
    • Product suggestions
    • Content suggestions
    • Recently viewed (products)
  • Search result page
    • Ranked product listing
    • Autocorrect
    • Facets (filters)
    • Sort order
    • Content listings

Product recommendations

Product Discovery analyzes shopper behavior such as searches, clicks, and purchases. Its recommendation engine uses algorithms to identify patterns and suggest products tailored to each user.

Available recommendation types:

  • Top products
  • Personal
  • Recently viewed
  • Recently bought
  • Alternatives
  • Upsell
  • Style with
  • More from series
  • Add-to-cart recommendations
  • Cart
  • Favorites
  • Newest products

Landing page listings

Landing pages can serve as start pages, category pages, brand pages, or collection pages.

Product Discovery's Landing Page API includes:

  • Ranked product listing
  • Recommendation product listings
  • Autocorrect
  • Facets (filters)
  • Sort order
  • Content listings
  • Navigation tree

Product detail pages (PDP)

Product pages present detailed product information and can include recommendation lists.

Product Discovery's Product Page API includes:

  • Detailed product information for rendering the PDP
  • Selection of recommendation product listings

Data

Product data

Product Discovery uses a three-level product data model:

  1. Product group
  2. Product
  3. Variant

Product data import & export

Product data can be imported and exported through the Admin API endpoints.

Content data

Content items allow visitors to search for site content such as guides or contact details.

Key attributes: Title, Description, URL.

Translation

Translation tables can be imported to map stable keys across multiple languages.

Data templates

Define which data fields are returned in product lists.

Add and remove visitor data

APIs exist to add and remove available data in Product Discovery related to a visitor.

Product Discovery application

The Product Discovery application provides a comprehensive set of features for managing and optimizing Product Discovery 4:

  • Dashboard
  • Exposure strategies
  • Boost (including Audience promotion when Customer Engagement is implemented)
  • Bury
  • Search reports
  • Synonyms
  • Product sets
  • Page merchandising
    • Pinning
    • Slices
    • Facets
    • Keywords
    • Tweak recommendations
  • Navigation tree management
  • User management
  • Email recommendations (Add-on feature)

Additional core functionalities

  • Ranked product listings: Based on query relevance, sales performance, lifecycle analysis, and merchandising rules (boost, bury, pin).
  • Data enrichment: Identifies relevant product types and attributes.
  • Relevance through behavioral data: Notifications triggered by actions such as Payment, Add to Cart, or Click.
  • Built-in language and terminology database
  • Multilingual market support
    • A market typically refers to a specific geographical region where the collective user behavior is relevant(1) and the retailer offers a similar assortment of products or services.
  • Customer Engagement integration (requires both Voyado Customer Engagement and Product Discovery)
    • Cross-product identification
    • Target boosts and buries based on Customer Engagement audiences
    • Build audiences in Customer Engagement using Product Discovery events and product intelligence

(1) Relevant visitor behavior is shared within a market, regardless of locales

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