ATHENIAN PLUG-IN SYSTEM
Athenian Taste Intelligence Platform turns shopper preference signals into smarter product discovery and recommendations.
Model product taste attributes, capture customer signals, interpret preference patterns, and power more relevant discovery, recommendations, merchandising, and decision intelligence across WooCommerce.
Preference signals
Taste attributes
Recommendations
Merchandising insight
Preference intelligence layer
Show product taste attributes, shopper preference profile, signal capture, recommendation cards, similarity scoring, and merchandising insight dashboard.
PRODUCT SNAPSHOT
Taste and preference data connected to commerce decisions.
Position this as a discovery intelligence layer for Catmilk-style content, product matching, recommendations, and personalized storefronts.
Best-fit workflow
Stores where subjective preferences, styles, flavors, aesthetics, finishes, moods, or use cases shape product discovery and buying decisions.
Operational friction
Flat categories, manual recommendations, generic product filters, and merchandising decisions without preference data.
Systems connected
WooCommerce products, attributes, customer profiles, searches, product views, recommendations, AI chat, Site Search, Data Intelligence, and merchandising tools.
Business result
Product discovery can respond to what customers like, not just what category a product belongs to.
FROM FRICTION TO FLOW
Show how the plug-in changes day-to-day work.
The before/after framing makes the value obvious before visitors read feature details.
CURRENT WORKFLOW
Before this plug-in
-> Products are filtered by basic taxonomy.
-> Recommendations are manual or generic.
-> Preference signals are not modeled.
-> Merchandising lacks taste-level insight.
CONNECTED WORKFLOW
After this plug-in
-> Products carry taste attributes.
-> Customer signals build preference context.
-> Recommendations can use similarity and fit.
-> Merchandising sees patterns across preferences.
FEATURE MODULES
Six capabilities for taste and preference intelligence.
The page should explain how subjective preference becomes structured platform data.
Taste attributes
Model style, flavor, finish, mood, category nuance, use case, or subjective product traits.
Signal capture
Collect views, likes, quiz answers, searches, saves, purchases, and feedback.
Preference profiles
Summarize customer or segment preference patterns.
Recommendation logic
Match products by similarity, fit, attribute weights, or behavioral signals.
Discovery surfaces
Power search, filters, AI chat, product cards, and guided selection.
Merchandising insight
Reveal what tastes, traits, or combinations drive engagement and conversion.
WORKFLOW
Explain the product as a sequence from setup to outcome.
The workflow section helps buyers understand how the plug-in fits into real operations.
01
Model
Define product taste attributes and scoring cues.
02
Capture
Collect shopper preference signals.
03
Match
Generate recommendation or discovery signals.
04
Learn
Use analytics to refine merchandising and content.
VISUAL DIRECTION
Use real product visuals, then add compact callouts.
Keep screenshots specific to the product and use the shared compact card system for consistency.
Preference profile
Show taste signals and traits.
Recommendation grid
Show products matched by fit and similarity.
Insight dashboard
Show popular traits and conversion patterns.
ECOSYSTEM
Platforms and systems this plug-in touches.
Use official marks where licensing allows; otherwise keep these as Material-style text/logo slots.
WordPress
WooCommerce
Taste Intelligence
Recommendations
Site Search
AI Chat
Data Intelligence
Catmilk
Products
Athenian Platform
OUTCOMES
Close with the operational change the buyer should expect.
These outcomes should stay practical and tied to the operational friction the plug-in removes.
Improve discovery
Customers find products based on preference fit.
Support personalization
Profiles and signals can tune recommendations.
Guide merchandising
Taste-level data reveals what customers respond to.
Ready to make shopper preferences part of product discovery?
This plugin-linked page is based on WooCommerce product 90487, local folder athenian-taste-intelligence-platform, and available plugin documentation/code signals. Use the product page for licensing and purchase details.