Skip to content

Platform

How TravelSpy works Traveller intelligence AI traveller profiles Data sources Journey orchestration Integrations Live demo

Solutions

Tour operators Airlines Online travel agencies Hotels & resorts Cruise lines Travel advisors Pricing

Resources

Insights library Case studies Documentation & API Trust & security

Company

About us Careers Contact Book a demo Log in

Home/ Platform/ Traveller intelligence

Platform

Traveller intelligence

Know what someone wants to book before they tell you. TravelSpy reads intent, affluence and timing from behaviour rather than guesswork.

92%

Destination affinity precision at top decile

11 days

Median lead time on a predicted booking window

7

Spend bands modelled per traveller

What you get

Intent signals

Scroll depth on a destination page, repeat visits to a date picker, abandoned fare searches, map interactions and returning search refinements all carry different weight. TravelSpy learns that weighting per brand instead of applying a generic rule.

Source intelligence

Where a visitor came from is one of the strongest predictors of what they will buy. TravelSpy classifies referral sources across news, editorial, social, community forums, comparison sites, creator content and paid placements, and learns the commercial value of each.

Network and location context

IP intelligence adds country, region, connection type, carrier, VPN detection and business-versus-residential signals. This sharpens currency, seasonality and departure-airport predictions without touching sensitive personal data.

Revenue modelling

Spend capacity is inferred from device class, geography, browsing basket, previous quote values and the tier of content a visitor engages with. The output is a band and a confidence, never a fabricated income figure.

Timing models

Booking-window models predict the day range in which a traveller is most likely to transact, so discounting and outreach land at the moment they change the outcome rather than a moment too early.

Explainability

Every score opens into an evidence panel: the signals that drove it, their contribution, and how the score has moved over time. Your team can challenge the model, and the model answers.

Questions teams ask

No. TravelSpy is built for a post-cookie world using first-party behaviour, server-side ingestion, consented identifiers and contextual signals.

Banding is probabilistic and always surfaced with confidence. Teams use it to prioritise and to price ranges, not to make individual financial claims.

See what your traffic is actually worth

Book a 30-minute session. We will run your own traffic through the model and show you the segments, the predicted spend bands and the packages you are not selling yet.