+8% Booking Conversions on India's Top Travel Platform

8%

Uplift in property bookings

98%

Accuracy of listing details

12%

Improvement in content quality score

About the Client

One of India's leading online travel platforms managing multi-modal property data across hotels, homestays, vacation rentals, and alternative accommodations. The platform serves as a critical distribution channel for property owners while helping millions of travelers discover and book accommodations daily.

Challenge

The platform was struggling with a fundamental trust problem: travelers couldn't rely on listing information to make confident booking decisions. This was manifesting across multiple dimensions:

Outdated and Inconsistent Visuals: Property photos ranged from professional HDR shots to blurry smartphone images taken years ago. Some listings showed amenities that no longer existed; others had seasonal photos that misrepresented current conditions.

Incomplete Hotel Data: Critical information gaps plagued the catalogue. Room dimensions, bed configurations, accessibility features, and view descriptions were inconsistently populated.

Poor Content Quality Affecting Conversions: Descriptions were often copy-pasted from property management systems, filled with jargon, or machine-translated with grammatical errors.

Rating and Review Inconsistencies: The platform aggregated reviews from multiple sources, leading to conflicting ratings.

Cross-Platform Mapping Failures: The same property listed on multiple OTAs often had different names, addresses, and identifiers.

No Persona-Based Discovery: A couple seeking a romantic getaway and a family looking for kid-friendly activities were seeing the same generic search results.

Our Approach

BergLabs deployed a comprehensive multimodal annotation system-combining text, image, and video analysis at the entity level to build reliable property data pipelines.

Text & Review Annotation

Comprehensive review analysis and content enhancement to improve property descriptions and ratings.

Standardized Rating Reconciliation: Reviewed 500,000+ ratings across source platforms, establishing ground-truth scores through weighted averaging and recency adjustments.
Sentiment Analysis on Reviews: Analyzed 2M+ review texts to extract sentiment signals on specific attributes: cleanliness, location, service quality, food, and value.
Description Enhancement: Annotators rewrote 150,000+ property descriptions, transforming generic copy into compelling, accurate narratives validated against photos and reviews.

Entity Mapping Annotation

Cross-platform property identification and attribute standardization.

Cross-Platform Property Matching: Using name matching, address verification, and photo comparison, we identified and merged 80,000+ duplicate listings.
Attribute Standardization: Created consistent taxonomies for amenities, room types, and property features across all listings.
Location Verification: Every property's coordinates were validated against satellite imagery and street-view data. Properties claiming "beachfront" locations were verified; 12% were reclassified to more accurate descriptors.

Visual Annotation

Image and video quality assessment and content curation.

Photo Quality Scoring: AI-assisted scoring identified low-quality images (blurry, poorly lit, outdated). Properties with updated photos saw 23% higher click-through rates.
Photo-to-Amenity Validation: Annotators cross-referenced photos against claimed amenities, catching 15,000+ misleading listings.
Video Content Curation: For properties with video tours, we tagged timestamps for specific features (lobby, rooms, restaurant, pool), enabling relevant video snippets in search results.

Contextual Annotation

Persona-based classification and occasion tagging for personalized discovery.

Persona-Based Classification: Every property was labeled for suitability across traveler personas-Family (kid-friendly amenities, connecting rooms), Couples (romantic ambiance, privacy, spa), Solo (safety ratings, social spaces), Business (work desks, meeting facilities, connectivity).
Occasion Tagging: Properties were tagged for specific occasions: honeymoon, anniversary, workation, staycation, pilgrimage-enabling contextually relevant options during seasonal campaigns.

                    ┌─────────────────────────────────────────┐
                    │       Property Data Sources             │
                    │  (Feeds, APIs, Manual Submissions)      │
                    └─────────────────┬───────────────────────┘
                                      │
                                      ▼
┌─────────────────────────────────────────────────────────────────┐
│                    BergFlow Annotation Layer                    │
├───────────────┬───────────────┬───────────────┬─────────────────┤
│  Text & Review│ Entity Mapping│    Visual     │   Contextual    │
│   Annotation  │   Annotation  │  Annotation   │   Annotation    │
├───────────────┴───────────────┴───────────────┴─────────────────┤
│                AI Pre-Processing (90% confidence)               │
│                Human Validation (Edge Cases)                    │
└─────────────────────────────────┬───────────────────────────────┘
                                  │
                                  ▼
                    ┌─────────────────────────────────┐
                    │       QA & Validation           │
                    │   (Statistical Sampling)        │
                    └─────────────────┬───────────────┘
                                      │
                                      ▼
                    ┌─────────────────────────────────┐
                    │    Enriched Property Data       │
                    │   (Push to Client Systems)      │
                    └─────────────────────────────────┘

Impact

The comprehensive multimodal approach delivered measurable improvements across all key metrics:

Metric	Before	After	Improvement
Booking Conversion Rate	Baseline	+8%	8% uplift
Property Detail Accuracy	82%	98%	16% improvement
Content Quality Score	Baseline	+12%	12% improvement
Customer Complaints (Data Accuracy)	100%	35%	65% reduction

Revenue Impact: $6M+ annual revenue lift from improved conversion, with additional gains from reduced refund/cancellation rates due to expectation mismatches.

Traveler Trust: Post-stay satisfaction scores improved by 15%, with "accurate description" ratings increasing from 3.8 to 4.4 out of 5.

Property Partner Satisfaction: Properties with enhanced content saw 18% more bookings, improving platform retention and enabling premium placement negotiations.

Testimonial

“Our conversion rates had plateaued despite increasing traffic. BergLabs helped us understand that travelers weren't abandoning because of price-they were abandoning because they didn't trust what they were seeing. The multimodal annotation approach was exactly what we needed: comprehensive, accurate, and fast enough to cover our entire catalogue.”

VP of Product & Experience

Leading Travel Platform

Engagement Model

Type

Managed Operations

Duration

12 weeks initial + ongoing content maintenance

Team

80+ annotators (hospitality-trained), 2 ML engineers, 1 domain expert

Platforms

BergFlow (multimodal annotation), BergForge (quality automation)