Smart Suggestions: Personalization & Chained Event Recommendations

Delivering the right events at the right time takes more than a simple list—it requires intelligent ranking, personalized filtering, and context-aware sequencing. In this article, we break down how our app transforms raw event data into curated, dynamic suggestions.

Ranking & Filtering Basics

Popularity Signals
Events with high community upvotes or attendance history get a visibility boost.
Recency & Relevance
Freshly added or upcoming events are prioritized, ensuring you don’t miss out.
Category & Mood Matching
Filters narrow suggestions to match your selected mood spectrum (e.g., Relax, Explore, Focus, Energize).

Location-Aware Recommendations

Proximity Weighting
Nearby events surface first, with distance factored into the ranking score.
Geographic Clustering
Suggest event “clusters” (e.g., a trio of activities downtown) to minimize travel time and increase convenience.

Behavior-Driven Personalization

Swipe Data & History
Every swipe, tap, and save refines your profile, tuning future suggestions to your tastes.
Temporal Patterns
The system learns your preferred time windows (e.g., Fri 6–9 pm) and prioritizes events that fit.

Chaining Logic: Building Seamless Itineraries

Seed Event Selection
User selects a primary event (e.g., evening concert).
Related Activity Suggestions
Immediately recommend pre- or post-event options—dinner spots, after-parties, or scenic walks.
Adaptive Chains
If the user adds a chaining suggestion, the system extends the sequence (e.g., coffee + art exhibit + live show).

Example Flow: A Friday Night Out

Initial Swipe: Concert at 8 pm in the Old Town.
Pre-Event Suggestion: “Tapas bar 10 min away” → user adds it.
Post-Event Suggestion: “Late-night jazz at 11 pm” → user dismisses.
Alternate Post-Event: “Moonlit harbor walk” → user adds.

The result is a ready-made itinerary: tapas, concert, and a scenic walk—all laid out on your calendar with one tap each.

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