Methodology

Technical details

Collection is geo-targeted on the analyzed city to reflect what a traveler would see when searching from or for that destination.

Typical sample: 21-30 visible offers, depending on Google result availability at the time of analysis.

The index measures structural visibility, not total market inventory.

Pure editorial sites (media, blogs without transaction) are excluded from the sample. Only actors participating in the transaction chain are measured.

Signal attribution rule

Platforms are systematically classified as "Platform only" (intermediated).

Remote resellers are classified according to their observable booking mode (platform_only, contact_only, none).

Only local operators (strictly local or regionally extended) can receive Direct or Contact classifications.

Distribution vs technology provider

The TPDI measures dependence on distribution intermediaries (OTAs, resellers), not dependence on technology providers.

An operator using FareHarbor (commission ~6%) retains control of their client relationship and pricing. This is not the same structural dependence as presence on Viator (commission ~25%, client captured by the platform).

TravelClick, iHotelier and SynXis are grouped under the travelclick identifier — these three products belong to Amadeus Hospitality and share the same technical infrastructure.

Formula

TPDI = (N_intermediated / N_total) × 100

Rounded to the nearest integer.

Where:

• N_intermediated = Number of visible offers whose observable reservation checkout occurs via an intermediary platform infrastructure.
• N_total = Total number of offers in the sample, all categories combined

Offer categories and coefficients

Each visible offer is classified according to its booking model:

Important note

Only local operators (strictly local or regionally extended) can be classified as Direct or Contact. Platforms are systematically classified as "Platform only". Remote resellers are counted as intermediated only when their observable signal is platform_only; those classified contact_only or none are not included in N_intermediated.

Platform and Reseller Classification

In the TPDI calculation, N_intermediated includes:

Technological platforms: OTA (Online Travel Agency) — Booking.com, Expedia, Hotels.com, Agoda — primarily accommodation, with extension to activities. Experience platforms — Viator, GetYourGuide, Klook, Airbnb Experiences — primarily guided activities and tours. Always classified platform_only.

Remote resellers: Counted as intermediated only when their observable signal is platform_only (OTA redirect). Remote resellers classified contact_only or none are not included in N_intermediated.

Distinction maintained for analysis: These actors are distinguished in visibility charts to enable a fine-grained understanding of the competitive structure.

In many cases, remote resellers redirect to OTA platforms. The TPDI measures the first visible point of intermediation in search results, without attempting to reconstruct the entire transactional chain.

Weighting logic

Platform only (1.0): The offer can only be booked via an intermediary. Total dependence. The operator has no visible alternative to capture direct bookings.

Direct (0.0): Booking via the operator's website (proprietary or third-party infrastructure such as FareHarbor, Bokun, etc.). Complete autonomy in observable digital distribution. The TPDI measures structural visibility: a local operator appearing in the sample with a direct booking system is classified as Direct, regardless of their potential presence on platforms outside the sample.

Contact only (0.0): No online booking system. The operator manages bookings through direct contact (email/phone). Although this limits scalability, there is no dependence on an intermediary infrastructure.

Not detected (0.0): No booking signal could be identified during analysis. Treated as autonomous by default.

Observable intermediation structure

The TPDI fits into an analysis of the "intermediation structure" of tourism markets.

Each visible offer can belong to different layers: Local operator; Remote reseller; OTA platform.

In some cases, several layers coexist (e.g. affiliate blog redirecting to Booking.com). The TPDI measures the layer visible in Google results at the time of analysis.

It does not reconstruct internal contractual flows or actual commissions.

Detailed calculation example

Market analyzed: Cancún · Guided experience · Family-friendly

Sample: 28 visible offers

Observed distribution: Platform only 22 offers (including 12 via OTA such as Booking.com + 10 via experience platforms such as Viator); Direct 5 offers; Contact only 1 offer; Total 28 offers.

Calculation: TPDI = (22 / 28) × 100 = 78.57… → TPDI = 79 (rounded).

Interpretation: In this market, 79% of visible offers rely on intermediary platforms to complete bookings.

Acknowledged methodological limit

The TPDI measures observable structure (who is visible, how booking is completed), not real booking volumes by channel. An operator classified as Direct may generate a significant share of bookings through non-visible channels (B2B, word-of-mouth, etc.). Any methodology modification will be documented and dated (e.g. "TPDI v2.0").

Technical note

The final score is rounded to the nearest integer according to standard mathematical rules.

• 78.57 → 79
• 82.67 → 83
• 82.50 → 83 (rounded up in case of tie)

What the TPDI does not measure

The TPDI is a structural visibility index, not an exhaustive census of the tourism market.

It does not measure:

• Total market share: only visibility in the first 3 Google pages, not all bookings made
• Offline sales: phone, direct email, walk-in bookings, private B2B contracts
• Real booking volumes: we observe visibility, not transactions
• Customer satisfaction: no service quality assessment
• Profitability: we do not measure margins or operator financial performance
• Exact commission flows or the full depth of intermediation chains (e.g. reseller redirecting to OTA).

What it measures

The TPDI captures:

• Observable digital structure: who is visible, how, through which channels
• Comparative visibility: what proportion of offers goes through intermediaries
• Dominant distribution models: direct, platform, reseller

Margin of error and variability

Like any observation-based index, the TPDI has structural margins of error:

1. Sampling (Google variability): Analysis covers the first 3 Google pages (21-30 results depending on availability). Results may vary by location, search history, query timing. Impact: an analysis repeated 48 hours apart may show ±2-5 TPDI point variations.

2. Manual classification (human error): Each offer is manually verified to determine its booking model. This verification has an estimated error possibility of ~2-5%. Complex cases: multi-language sites, unidentified booking engines, ambiguous booking flows.

3. Temporality (instant snapshot): Each analysis is a snapshot at a specific date. Market structures evolve. Impact: the TPDI reflects the observed state at a point in time, not a permanent truth.

Reliability and appropriate use

Despite these limitations, the TPDI captures observable structure with sufficient accuracy for:

• Inter-city comparisons: "Tulum has a higher TPDI than Bacalar"
• Sector trend detection: "Private tours are less dependent than group tours"
• Strategic analysis: "This market is dominated by 2 platforms"
• Competitive benchmark: "My positioning vs market average"

The TPDI is not suitable for

• Legal disputes requiring 100% accuracy
• Investment decisions based solely on a score
• Individual operator performance evaluation

Continuous improvement

For uses requiring absolute accuracy or custom scope, we recommend a tailored audit rather than relying solely on public TPDI analyses.

We constantly work to reduce these margins of error: enriching the platform database, refining classification rules, documenting edge cases, corrections following user reports.

Any error observation can be reported to: contact@tpdi.io

Public data (free)

Each published analysis includes:

• TPDI score (0-100)
• Distribution by actor category
• Main actors by visibility
• Analyzed sample size
• Observation date

Detailed data (Pro Dashboard)

The complete dataset includes:

• Exact URLs of all visible offers
• Detailed ranking (positions 1-30)
• Booking metadata (booking method, platform)
• Temporal evolution (multi-month history)
• Unlimited custom comparisons
• CSV/Excel export
• API access

This approach ensures

• Sufficient transparency for general analytical use
• Project funding through professional subscriptions
• Continuous geographic scope expansion

Project genesis

The TPDI was born from field experience. In 2021, we founded Adorable Sailing, a sailing excursion company on the Bacalar lagoon (Quintana Roo, Mexico).

From the start, we made a choice: operate without intermediary booking platforms. No Booking.com. No Viator. No GetYourGuide. We wanted to preserve our margins and our direct relationship with customers.

To achieve this, we developed holaOlas: a direct booking system, no commission, no intermediary. A simple tool that allowed us to manage our bookings autonomously.

From tool to measure

Then a question emerged: how many tourism operators are structurally dependent on platforms with no viable alternative?

This question had no answer. No index measured this dependence in a standardized, comparable way.

We built the TPDI to fill this gap. Not as a promotional tool, but as a neutral, reproducible measurement instrument.

Our positioning

We believe tourism operators should have the choice of their distribution model. The TPDI prescribes no strategy. It measures what exists.

What the TPDI does NOT say: that OTAs are "bad" or harmful; that direct booking is always superior; that an operator must change strategy; that high dependence is a failure.

What the TPDI measures: observable dependence structure on a given market; variations between cities, countries and sectors; dominant distribution models at a point in time.

Transparency on potential bias

We acknowledge that our experience as independent operators influences our interest in this topic. An operator who chose autonomy necessarily observes the market from that angle.

That is precisely why we built the TPDI with strict methodological rigor: public methodology (reproducible by anyone), standardized analysis framework, verifiable data, total transparency.

Any TPDI analysis can be audited, challenged or reproduced independently. That is what guarantees its integrity.

Funding and independence

The TPDI project is funded by: Pro Dashboard subscriptions (tourism professionals accessing complete data); internal development (no external funding, no obligation to investors).

We do not sell data to booking platforms or OTAs. We receive no commission or remuneration from sector actors.

This financial independence ensures the TPDI remains a measurement tool, not a commercial instrument.

Who we are

The TPDI is developed by the holaOlas team, based in Bacalar, Mexico. We are tourism operators, developers, and digital tourism observers.

For any questions about methodology, data or project independence: contact@tpdi.io