When it comes to buying hotel tech, there is no such thing as a one size fits all solution. Every hotel has different needs based on location, size and property type.
To help hoteliers more easily determine best fit solutions, HTR created a segmentation schema for hotel types based on unique characteristics and purchase drivers that impact:
(a) The types of tech a given property type is typically interested in
(b) The products that have functionality and price points that fit their properties' unique and distinct needs
Below are the key personas/segments that tend to have similar priorities and preferences when making tech purchasing decisions for their properties as well as what defines their unique attributes.
These segments will continue to be more ingrained throughout the user experience of the site to help hoteliers find best-fit tooling for their properties beginning with the sub-category page update.
1. Hotel Type Segments, Definitions and Purchase Drivers
Segment | Unique Tech Purchase Drivers |
Luxury Hotels |
|
Resorts |
|
Bed & Breakfasts & Inns |
|
Branded Hotels |
|
Vacation Rentals & Villas |
|
Hostels |
|
Motels |
|
Extended Stay & Serviced Apartments |
|
Boutiques |
|
Casinos |
|
Limited Service & Budget Hotels |
|
Airport/Conference Hotels |
|
City Center Hotels |
|
More Details About Each Segment
More Details About Each Segment
Luxury Hotels: Luxury hotels typically have higher expectation guests, higher ADRs and more budget to invest in premium tech solutions.
Resorts: Resorts typically have multiple outlets and venues which tend to require more tools to operate and also have more revenue streams and guest interactions to keep track of.
Bed & Breakfasts & Inns: B&Bs and inns tend to be smaller properties with more limited budgets. At the same time they also tend to have smaller teams and (proportionately) higher fixed costs meaning that investing in technology that automates processes can have a substantial impact on bottom line performance.
Branded Hotels: Branded hotels typically have corporate offices that purchasing decisions must be routed through and/or approved by. Depending on the brand and purchase characteristics such as budget size, budget source (ex. capex vs opex) and product type--tools tend to fall into three buckets (1) brand mandated requirement (2) must be approved and/or certified by the corporate office to meet brand standards or (3) able to be purchased at the property level up to the owners discretion.
Vacation Rentals & Villas: While most lodging establishments have one location with multiple dwellings/rooms, vacation rentals & villas are unique in that they can have multiple locations each with a single unit. This unique structure tends to lead to unique requirements that influence purchasing decisions ranging from portfolio management to budget.
Hostels: Hostels have the unique characteristic of being able to have multiple beds in a single unit that are rented to different customers at the same time. They also tend to have a more self service model with limited staffing which tends to draw them to products that offer self service capabilities.
Motels: Motels are unique in that they tend to have extremely low ADRs, limited service offerings, limited staffing and lower expectation guests which tends to make them extremely price sensitive and pricing is typically the primary purchasing decision factor.
Extended Stay & Serviced Apartments: Extended stay & serviced apartments are unique in that the average length of stay is substantially longer than typical hotels. As a result, they often have unique requirements that are a subset of what is needed for a high turnover hotel. They also tend to offer units with additional amenities like in room kitchens as well as services like dry cleaning that enable them to create a more home like experience.
Boutiques: Similar to luxury hotels, boutiques tend to have high expectation guests, more budget to invest in tech but yet they tend to not have enough budget to invest in enterprise solutions. They are typically independently owned or run by management company and design & experience are high priorities when it comes to purchase decisions. Additionally, boutique hotels tend to place high emphasis on F&B outlets as a way to create a unique and engaging environment for guests.
Casinos: Casino hotels typically have gaming operations as well as increased needs to track guests for both security and customer loyalty. They tend to be highly profitable businesses that can invest more in tech and also typically require more enterprise grade solutions with deeper functionality and a focus on data driven decision making. They also tend to have more outlets and amenities for guests increasing their need for hardware solutions (eg. digital signage) as well as tech tools to upsell and cross sell guests. Also unique to casino tech purchases, rooms revenue tends not to be the highest priority as rooms are often comp'd and/or discounted with the goal of offsetting the revenue with higher margin gaming and/or outlet revenue.
Limited Service & Budget Hotels: Limited service & budget hotels tend to have lower ADRs, are often branded properties and tend to experience a higher ratio of walk-ins. Guests are highly price sensitive as are operators of these properties who typically look to pricing as the most critical decision factor in tech purchases. Additionally, they have lower expectation guests and therefore tend to invest less in tools catered to guest experience.
Airport/Conference Hotels: Airport/Conference hotels typically have a larger footprint with large meeting space and as a result tend to be located in business districts that are proximate to conference centers and airports catering to a higher mix of business travelers. This segmentation and group oriented focus tends to influence the types of tech products they are interested in including a heightened focus on sales, catering and meetings & events tech.
City Center Hotels: Hotels that classify themselves as city center hotels tend to be larger properties that are in prime city centers typically indicating higher ADRs and occupancy (due to prime location), shorter length of stays (due to high price point) and have higher velocity of guest turnover. These factors typically lead to large volumes of high expectation guests which tend to influence their purchasing decisions and priorities from a tech perspective placing emphasis on automating routine tasks, streamlining operational efficiencies and improving the guest experience (both to reduce frequent requests and avoid reputational impact that can negatively impact occupancy levels).
2. Methodology: How HotelTechReport's Proprietary Hotel Segmentation Framework Helps Hoteliers Find the Right Tech Faster
When it comes to buying hotel software, one thing is certain: "one size fits all" doesn’t work in hospitality.
Hotel operations vary massively—from a 12-room countryside B&B run by a retired couple to a 500-room resort with multiple restaurants, spas, and a full-time IT department. Yet despite these differences, most hotel tech comparison sites still treat these properties like they have the same needs.
That’s where our segmentation framework comes in. At HTR, we’ve built a simplified but highly effective model that groups the majority of global hotel properties into four core operational segments. It’s the foundation behind our comparison tools, rankings, and product-fit recommendations—and it helps hoteliers find the best-fit solutions based on how their hotel actually runs.
🧩 Why Segmenting Matters in Hotel Tech
We’ve seen firsthand how tech evaluations go wrong: hoteliers get drawn in by feature checklists or flashy demos, only to realize later that the platform doesn’t fit their workflows, staff capabilities, or guest expectations.
Segmenting the market based on real-world operational characteristics helps prevent that. It ensures you're not comparing a boutique hotel’s needs with those of a budget motel—or assuming a large resort can run on tools built for a solo operator.
We’ve built on research and frameworks from HotelTechReport’s in-depth segmentation studies and simplified the market into a structure that’s both practically useful and broadly accurate for the majority of hotels worldwide.
🔍 The Four Core Segments in Our Framework
Below are the four segments we use to organize the market and guide vendor recommendations. Each one represents a distinct set of operational realities, tech needs, and purchasing behaviors.
i. Large Hotels & Resorts
Typical Profile:
150+ rooms
$$$–$$$$ ADR
Multi-outlet operations (spa, golf, F&B, events)
Structured departments (IT, revenue, marketing, etc.)
Buyer Persona:
Corporate IT, revenue team, or experienced GM with procurement process.
Key Characteristics:
Require enterprise-grade software with deep integrations
Emphasis on centralized oversight, scalability, and reliability
Need cross-departmental visibility and automation at scale
Guests expect consistent, high-touch service across all outlets
ii. Boutique & Independent Hotels
Typical Profile:
20–100 rooms
Independently owned or small collection
Brand- and design-forward
Buyer Persona:
Owner-operator or GM wearing multiple hats.
Key Characteristics:
Prioritize aesthetics, guest experience, and brand consistency
Value tools that are intuitive, customizable, and easy to implement
Strong focus on direct bookings and guest engagement
Lean teams, but ambitious service expectations
iii. Small Hotels & B&Bs
Typical Profile:
<20 rooms
Often owner-run, family-operated
Hyper-local, personal service
Buyer Persona:
Solo operator or owner with little to no tech background.
Key Characteristics:
Needs simplicity, reliability, and affordability
Avoids complexity and long onboarding processes
High reliance on repeat guests and word-of-mouth
Prefers plug-and-play solutions with low ongoing costs
iv. Budget Hotels, Motels & Hostels
Typical Profile:
20–100 rooms or beds
$–$$ ADR
High guest turnover, OTA-reliant
Lean operations with minimal staff
Buyer Persona:
General manager or owner focused on efficiency and cost control.
Key Characteristics:
Operational automation is key (check-in, housekeeping, OTA sync)
Guests are price-sensitive with low service expectations
Low tolerance for complexity or expensive add-ons
Prefers fast setup, low cost, and minimal ongoing support needs
Why This Simplified Segmentation Works (Even If It’s Not Perfect)
No framework is perfect. There are always edge cases—luxury hostels, hybrid conference hotels, or serviced apartments with long stays and short-stay guests. But here’s the thing: this framework captures the core operational truths of the vast majority of hotels.
It’s intentionally designed to help hoteliers:
Orient quickly and identify their closest match
Cut through the noise of one-size-fits-all vendor lists
Make confident, context-aware tech decisions
Think of it less like a rigid label and more like a compass—it won’t tell you exactly which path to take, but it ensures you’re headed in the right direction.
How This Powers Smarter Comparisons Across Hotel Software Categories
Whether you’re shopping for an HMS, PMS, CRM, booking engine, housekeeping app, or revenue management system, your segment profile shapes:
Which features matter most
Which pricing models make sense
How easily your team can implement and use the tool
Which vendors have a proven track record in similar hotels
That’s why our rankings, guides, and recommendations are built around segment-aware logic. We don’t just show you what’s popular—we show you what’s relevant.
The Bottom Line
Choosing hotel tech is hard enough. Our segmentation framework makes it easier by aligning your search with the operational reality of your property—not a generic industry label. It’s not about oversimplifying the market—it’s about simplifying the decision for you.
Explore our rankings, filter by your segment, and find the best-fit tools without second-guessing whether you're comparing apples to oranges.
3. Why Grouping Segments Makes Our Recommendations Smarter
Beyond making it easier for hoteliers to identify their fit, our simplified segmentation framework unlocks another critical advantage: better data.
By consolidating similar hotel types into broader operational segments, we’re able to aggregate data across a larger sample size—giving us a richer, more reliable foundation to power rankings, insights, and vendor recommendations.
Here’s why that matters:
1. Bigger Sample = Better Signal
Many niche hotel types don’t generate enough reviews or usage data individually to confidently assess product-market fit. But by grouping similar properties (e.g., inns, B&Bs, and small hotels) into one segment, we get a critical mass of data that reveals what tools actually perform best across that shared operational context.
2. Less Noise, More Clarity
Without segment grouping, individual property quirks can skew results. One luxury hostel might love a certain tool—but that doesn’t mean it’s right for most budget hotels. Aggregated segment-level data helps filter out anomalies and surface trends that are statistically significant—not just anecdotal.
3. More Accurate Fit Scoring
When a vendor performs consistently well across dozens (or hundreds) of properties in the same segment, we can say with confidence: this tool fits the way you operate. That means fewer false positives in recommendations and more high-fit matches.
In short, grouping segments isn’t just about simplifying the experience for hoteliers—it’s about creating a stronger data engine that drives more relevant, evidence-based tech recommendations. It’s how we go beyond star ratings and surface the tools that actually work for hotels like yours.
4. A Letter from Our Founders: Pairing HotelTechReport's Proprietary Hotel Tech Buying Framework
When we built this framework, we couldn't have just repurposed how STR or Tripadvisor segment the market and it would have been a lot easier but we didn't. Their segmentation is great for benchmarking and guest reviews—but we’re not trying to help people choose where to stay. We’re helping them choose the right tech to run their business.
So we started from first principles and asked: What actually drives technology buying decisions inside a hotel?
Not brand tier. Not star rating. Not price point.
But actual operational variables:
How complex is the hotel’s operation?
What kind of staff and tech capabilities do they have?
What do guests expect from the experience?
Who owns the budget and makes the decisions?
How tolerant is the team of complexity, training, or change?
This approach gave us a much stronger foundation for tech selection—because it’s built around how hotels operate, not how they look to travelers.
Now, does this framework capture every single nuance of every hotel type out there?
No—and that’s not the point.
There are always edge cases: hybrid models, luxury hostels, casinos with comped rooms, serviced apartments that act more like hotels.
But operationally, most hotels behave like one of our four core segments when it comes to how they evaluate, implement, and use software. And by grouping them this way, we can:
Eliminate irrelevant comparisons
Focus on real priorities
Speed up the decision process without compromising fit
The goal isn’t perfection. It’s getting hoteliers 80–90% of the way to a high-confidence decision, fast.
Of course, a good framework only works if you feed it the right data.
That’s where HTR has a unique advantage. This segmentation engine isn’t just theoretical—it’s powered by:
80,000+ verified hotel tech reviews
Verified integrations and partner certifications
Segment-specific case studies
Hands-on testing and expert analysis
And a constant flow of fresh data coming into the system every single day
That depth lets us see patterns that individual hoteliers can’t:
Which vendors actually work in practice for your segment
Where tools fall apart after onboarding
Which integrations are truly plug-and-play
How satisfaction and ROI evolve over time
The framework gives us structure. The data gives us truth. That’s what turns our recommendations from subjective lists into decision tools that work.
This whole system exists to make tech buying easier, more personalized, and grounded in how hotels actually operate.
Not how they’re marketed. Not how they rank on a review site. Not how they looked in a sales demo.
When you pair a first-principles framework with one of the most comprehensive datasets in hotel tech?
That’s when things start to click.
Yours in Hospitality,