Research
January 8, 2026/Industry Report

The Link Between Vacation Rental Management Software and OTA Dependency

How does property management software choice relate to OTA dependency? We analyzed data from over 300+ vacation rental companies across 11 PMS platforms to uncover patterns.

We analyzed over 300 vacation rental companies across 11 property management software platforms to see if PMS choice correlates with OTA (Online Travel Agency) dependency levels.

For this analysis, we exclusively used Airbnb as the OTA channel to measure OTA dependency.

Our analysis found that older, enterprise-focused PMS platforms serve users with significantly lower OTA dependency than newer, growth-oriented platforms.

We observed a 37-point gap between VRM (avg OTA score: 33.3) and Guesty (avg OTA score: 70.1). Platforms like Barefoot and VRM have 0% of users with "High" OTA dependency, while Guesty, OwnerRez, Hostfully, and LiveRez have 0% of users with "Low" dependency.

What the data can't answer is causation. The data reveals patterns between vacation rental management software choice and OTA dependency levels, but does not prove that using a particular property management software actually causes higher or lower OTA dependency.

We make no implications that switching property management software platforms will change your OTA dependency, nor do we suggest any PMS is "better" or "worse" based on this data. Channel strategy is a business decision influenced by numerous factors beyond software choice.

Key Findings

58% of OwnerRez users have "High" OTA dependency — the highest rate among all PMS platforms

4 PMS platforms have 0% of users in the "Low" OTA dependency tier: Guesty, OwnerRez, Hostfully, and LiveRez

Only 5% of Track users fall into the "High" dependency category — the lowest rate among PMS with 60+ companies

VRM has the lowest average OTA score (33.3) with 64% of users in the "Low" dependency category

Barefoot and VRM both have 0% "High" OTA dependency — no users heavily reliant on OTAs

Streamline is the most widely used PMS in the dataset with 96 companies (30% of total)

All 3 pre-2005 platforms (Barefoot, Escapia, VRM) have average OTA scores below 50

A 37-point gap exists between VRM (est. 2000, score 33.3) and Guesty (est. 2013, score 70.1)

Platforms with 140+ avg. properties (Track, VRM, Streamline, Barefoot) all have OTA scores under 50

Methodology: How We Measure "OTA Dependency"

For our analysis, we used Nearsight's OTA Dependency Score, which is a proprietary model that we use to estimate how much a vacation rental company relies on third-party booking platforms (Airbnb) versus getting guests directly through their own direct channel.

How is the Nearsight OTA Dependency Score calculated?

Since we can't see a company's actual booking data, we look at publicly available "signals" that hint at where their bookings are likely coming from. Some of the signals included in our model are:

  • Website traffic — We look at the estimated monthly organic traffic to their known primary direct booking website
  • Social Media presence — A larger social following indicates they're investing in building their own audience rather than just relying on 3rd party platforms
  • Airbnb reviews — A proxy for OTA-specific booking volume, high review counts on Airbnb suggests a lot of their business could flow through that platform
  • Portfolio size — Often, but not always, vacation rental companies with larger portfolios are less reliant on OTAs for bookings

Based on these signals (which are aggregated and normalized), we assign a score between 0 and 100, with 0 being the lowest dependency and 100 being the highest dependency.

We then categorize the score into one of three tiers:

  • Low (0-33) — Appears to be more direct booking focused
  • Medium (34-66) — Appears to have a balanced distribution of bookings across direct and OTA channels
  • High (67-100) — Appears to rely more heavily on OTA platforms for bookings

Distribution of OTA Dependency Levels Across Property Management Software Platforms

When we grouped vacation rental companies by their PMS provider, a clear pattern emerged: certain platforms have user bases that skew heavily toward OTA reliance, while others are dominated by users with a strong direct-booking focus.

The visualization below shows each PMS as a stacked bar representing the distribution of its users across the three dependency levels. Green indicates "Low" dependency (direct-booking focused), yellow indicates "Medium" (balanced), and red indicates "High" (OTA-reliant). Platforms are sorted by highest percentage of "High" dependency users at the top.

For example, we can see that 54% of Guesty users have been categorized as having a "High" (red) OTA dependency, while 46% have been categorized as having a "Medium" (yellow) OTA dependency.

OwnerRez logo

OwnerRez

19 companies

42%
58%
Guesty logo

Guesty

24 companies

46%
54%
Hostaway logo

Hostaway

10 companies

10%
40%
50%
Hostfully logo

Hostfully

4 companies

75%
25%
LMPM logo

LMPM

9 companies

11%
67%
22%
Streamline logo

Streamline

96 companies

20%
58%
22%
LiveRez logo

LiveRez

6 companies

83%
17%
Escapia logo

Escapia

61 companies

25%
59%
16%
Track logo

Track

61 companies

36%
59%
5%
Barefoot logo

Barefoot

12 companies

42%
58%
Virtual Resort Manager (VRM) logo

Virtual Resort Manager (VRM)

14 companies

64%
36%
Low Dependency (0-33)
Medium (34-66)
High (67-100)

Observations

  • Four platforms show zero "Low" dependency users: Guesty, OwnerRez, Hostfully, and LiveRez all have 0% of users in the low OTA dependency tier. Among these, Guesty (54%) and OwnerRez (58%) have the highest rates of "High" dependency users.
  • VRM and Barefoot have zero "High" dependency users: On the opposite end, these legacy platforms show no users with high OTA reliance—64% of VRM users and 42% of Barefoot users are in the "Low" dependency tier.
  • The middle tier dominates most platforms: LiveRez (83%), Hostfully (75%), and LMPM (67%) have the majority of their users in the "Medium" dependency category, suggesting a balanced channel strategy.
  • Track stands out among high-volume platforms: With 61 companies in our sample, Track has only 5% in the "High" category—the lowest rate among platforms with 60+ companies.

Platform Archetypes

Based on the distribution patterns, we can identify two distinct platform archetypes:

  • Enterprise/Legacy platforms (VRM, Barefoot, Track): These platforms serve larger portfolios (avg. 140-228 units) and their users demonstrate strong direct booking capabilities. The data suggests these operators have invested in brand-building and guest retention systems over time.
  • Growth-oriented platforms (Guesty, OwnerRez, Hostaway): These newer platforms attract operators who may be prioritizing rapid growth through OTA channels. Their strong channel management features make it easy to scale quickly via third-party platforms.

Does Software Age Matter? PMS Founding Year vs. OTA Dependency

One pattern emerged when we cross-referenced each PMS platform's founding year with its users' average OTA dependency score: older software platforms tend to serve users with lower OTA dependency.

The visualization below plots each PMS by its founding year (x-axis) against the average OTA dependency score of its users (y-axis). Bubble size represents the number of companies in our study using each platform, and color indicates the dependency level classification.

Low Dependency (0-33)
Medium (34-66)
High (67-100)
Small
Large = More Users

Simplified Table View

Property Management SoftwareYear Founded# of UsersAvg. OTA Dependency Score
Barefoot19981235.7
Escapia20006147.0
Virtual Resort Manager (VRM)20001433.3
Streamline20059649.3
LiveRez2008653.0
Track20126140.0
Guesty20132470.1
OwnerRez20131967.2
Hostaway20151064.4
Hostfully2015462.0
LMPM2015953.7

Observations

  • Pre-2005 platforms cluster at low dependency: Barefoot (1998), VRM (2000), and Escapia (2000) all serve users with average OTA scores below 50, with VRM showing the lowest at 33.3.
  • 2013-2015 platforms show mixed results: Guesty (2013, score 70.1), OwnerRez (2013, score 67.2), Hostaway (2015, score 64.4), and Hostfully (2015, score 62) all average above 60. However, Track (2012, score 40) and LMPM (2015, score 53.7) buck the trend with lower scores.
  • Streamline is an outlier: Founded in 2005 with the largest user base (96 companies), Streamline sits in the middle at 49.3—suggesting that scale and maturity can support a balanced channel mix.

Average Portfolio Size by Property Management Software

Beyond OTA dependency patterns, our dataset reveals significant differences in the average portfolio sizes served by each PMS platform. This metric provides insight into which platforms attract enterprise-scale operators versus smaller property managers.

The visualization below ranks each PMS by the average number of properties managed by its users, from highest to lowest.

Track logo

Track

61 companies

228
Virtual Resort Manager (VRM) logo

Virtual Resort Manager (VRM)

14 companies

206
Streamline logo

Streamline

96 companies

169
Barefoot logo

Barefoot

12 companies

141
LMPM logo

LMPM

9 companies

120
Escapia logo

Escapia

61 companies

120
Guesty logo

Guesty

24 companies

101
OwnerRez logo

OwnerRez

19 companies

99
Hostfully logo

Hostfully

4 companies

82
LiveRez logo

LiveRez

6 companies

60
Hostaway logo

Hostaway

10 companies

51
Average number of properties managed per company

Observations

  • Track leads with the largest portfolios: Track users average 228 properties—nearly 4.5x the average of Hostaway users (51 properties), the smallest in our study.
  • Clear tier separation: Enterprise-focused platforms (Track, VRM, Streamline) serve users with 169-228 average properties, while growth-stage platforms (Hostaway, LiveRez, Hostfully) serve users averaging 51-82 properties.
  • Mid-market clustering: Five platforms (Barefoot, LMPM, Escapia, Guesty, OwnerRez) cluster in the 99-141 property range, representing the mid-market segment.
  • Portfolio size correlates with OTA dependency: Notably, the top 4 platforms by portfolio size (Track, VRM, Streamline, Barefoot) all have average OTA scores below 50, while platforms with sub-100 average properties tend to score higher.

Data Sourcing & Limitations

Data Sourcing

All data was collected from publicly available sources including company websites, social media profiles, OTA profiles (Airbnb) and search engine results (Google).

Property management software attribution was determined through website technology analysis and public company disclosures.

Property management software data was collected during April through December 2025.

All other data was collected during December 2025.

Limitations

  • Sample size varies significantly — Some PMS platforms have 90+ companies while others have fewer than 10. Findings from smaller samples are less statistically reliable.
  • US-focused sample — Results may not generalize to international markets.
  • Selection bias — Our dataset does not represent all users of each property management software, only ones that are in Nearsight's database.
  • Proxy metrics — OTA dependency is inferred from indirect indicators, not actual booking data.

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