Complete Market Research Guide for Hotels

Few businesses are described in as much detail by their customers as hotels. A guest review often reads like a short diary of the stay: how easy the booking was, whether the room was ready on arrival, how the check-in went, what the room and the bed were like, whether the breakfast was worth getting up for and how the check-out felt. Every step of the stay leaves a trace, and guests write about each one.

That makes hotel reviews one of the richest sources of evidence in any industry, and one of the least used. Most hotels read their latest reviews, reply to the critical ones and track the average rating. Far fewer read their reviews, and their competitors' reviews, as a body of research that shows which step of the stay is costing them guests and which kind of guest they serve best.

This guide shows how an independent hotel, a boutique hotel, a guesthouse or a small hotel group can turn that feedback into real market research about its own property, its competitors and the market it operates in.

Key Research Questions

Before collecting anything, it helps to know what the research is for. For a hotel, the questions fall into three groups: questions about your own property, questions about the hotels guests compare you with, and questions about how demand in your area is changing.

Your Hotel

The first questions follow the stay. Where in the guest's journey does the experience go well, and where does it break: the booking, the arrival, the check-in, the room, the breakfast, the check-out? Which parts of the stay do guests mention when they explain a five-star review, and which when they explain a two-star one?

The second set is about who your guests are. Do business travelers, couples, families and groups describe the same stay differently? Which of them are the most satisfied, and which are you serving by accident rather than by design?

Your Competitors

A hotel's competitors are the properties guests consider for the same trip: hotels in the same area and price range, and increasingly short-term rentals. What do their guests praise that yours never mention? What do they complain about that you already do well? Reviews of competing properties are as public as your own, and they show what guests in your market have come to expect.

The Hotel Market

The third group concerns demand. Why do guests come to your area, and does that change between seasons? Which types of travelers are growing, and what do they expect from a stay? How do guests weigh hotels against apartments and other alternatives? Reviews answer these questions with the guest's own reasons, which booking data alone cannot provide.

Sources of Evidence

Evidence about a hotel comes from four places: what your own guests tell you directly, what guests of every hotel in your area write in public, what you can learn by asking and observing, and what you can compare yourself. Each answers the questions above from a different angle, and the strongest research combines them.

Guest Surveys and Front Desk Records

The open-ended answers in post-stay surveys and the complaints logged by the front desk are the most specific feedback a hotel has. They often describe a problem at the moment it happened: a room that was not ready, a noisy neighbor, a missing item at breakfast. Collected in one spreadsheet, with columns for the date, the room type, the length of stay and the source, they become the beginning of a customer feedback analysis practice.

Public Reviews

Tripadvisor and Google Business are the main public sources, and they cover your property and every competitor in the same detail. Guests on the two platforms are not always the same people and do not always write the same way, so comparing them is itself informative. Booking.com and Airbnb add reviews from guests who booked through those channels, and Airbnb shows how guests judge the apartments and homes that compete with hotels for the same trips.

Interviews and Observation

Traditional methods still have a role. A short conversation at check-out, or a call with a regular corporate client, shows how guests decide where to stay and what would bring them back. Staff are another source: the front desk, housekeeping and breakfast teams hear comments that never reach a review. Notes from these conversations are qualitative research data, and they need the same structured analysis as reviews to become more than a collection of opinions.

Location and Pricing

Two practical checks sit slightly outside feedback research. A location check looks at what brings travelers to the area: offices, attractions, transport links, events and the seasons they follow. A pricing check compares your rates with those of the properties you compete with, by room type, season and channel. Reviews then add what a rate comparison cannot: whether guests felt the stay was worth what they paid.

Researching Hotels with Kimola

Kimola is an AI platform that turns customer feedback into enterprise-grade market research. For a hotel, that means taking reviews of your property and of the hotels you compete with, together with your own survey answers and complaint records, and turning them into a structured study of where the stay succeeds, where it fails and for which guests. The steps below follow the order a researcher would work in, and you can start with a free account, without a credit card.

Building the Dataset

After signing up, go to the Create your report area on the Home screen and paste the link to your hotel's page on Tripadvisor or its Google Business listing. With the Add Multiple option you can paste several links, one per line, and Kimola collects the reviews from all of them into a single dataset. A practical first report includes your own property on both platforms and three or four hotels that guests consider for the same trip. The support article on creating a report by adding links walks through each screen.

For Booking.com or Airbnb, Kimola's browser extension, Airset Generator, collects the reviews from a page and sends them to your account as an Airset, which you can turn into a report. Your own data, such as survey answers or front desk complaint logs, can be uploaded as an .xls, .xlsx, .csv or .tsv file. If the file contains columns like room type, stay date, length of stay or booking channel, Kimola reads them, and you can filter and compare the results by those values.

By default, Kimola finds the themes in the data itself. If you prefer a classifier built for hospitality feedback, the Advanced option lets you choose the HoReCa Feedback Classifier, one of Kimola's pretrained models.

Choosing Dimensions

Dimensions are the research questions Kimola asks of every piece of feedback. You choose them when you create the report or add them later, and the guide to Dimensions explains each one. For a hotel, five are especially useful, and one of them belongs at the center of the research.

Experience Stages places each comment at a moment in the stay: the booking, the arrival, the check-in, the room and the stay itself, the breakfast and the check-out. Because hotel guests describe their stay step by step, this Dimension turns a pile of reviews into a map of the guest journey, showing which step produces the most praise and which the most complaints. It is the best starting point for almost every hotel.

Personas groups guests by who they are and why they travel: business travelers, couples, families and groups. The same breakfast can delight a family and disappoint a business traveler who needed to leave at seven. Social Context adds who the guest was with, which separates a solo work trip from a family holiday even when the guest does not say so directly.

Motivations asks why guests chose the hotel, which separates location from price, a particular facility or a recommendation. Pain Points asks what goes wrong, which in hotel reviews usually covers noise, cleanliness, room temperature, waiting times, Wi-Fi and unexpected charges.

Reading the Report

The Overview shows the main themes in the feedback and how sentiment is distributed. Kimola finds those themes in the data itself instead of sorting comments into a fixed list of categories, so a review about the room can be tagged with something as specific as street noise in rooms facing the main road or blackout curtains that let in light.

Each review can mention several themes, and each theme gets its own sentiment. A guest who loved the location and the staff but found the room too small contributes positive mentions of the location and the staff and a negative mention of the room size, which a single star rating would hide.

The Performance screen ranks themes with a Satisfaction Score and a Dissatisfaction Score. These scores account for how many reviews mention a theme as well as the percentage, so a theme backed by five reviews does not outrank one backed by fifty. For a small property with a modest number of reviews, this protects against the most common mistake in small-scale research, which is drawing confident conclusions from a handful of comments.

Signals

Signals are findings that have passed a statistical test. Kimola crosses every theme and Dimension with the columns in your dataset, such as hotel, platform, star rating or date, and checks whether a topic is discussed more often or more negatively in one group than in the others (Differences) or more often recently than before (Trends). Only significant results become Signals, and they are ranked so the most important ones come first. The explanation of how Signals are tested covers the method in more detail.

For a hotel, two columns are especially revealing. The platform column can show that a topic, such as value for money or breakfast, is discussed more negatively on Tripadvisor than on Google Business, which often points to different guests or different expectations. The date column shows seasonal patterns, such as complaints about air conditioning in summer or about noise during a busy event season. Signals need enough feedback and at least some selected Dimensions. When the data does not contain a pattern strong enough to report, the report shows none, which is an honest result.

Compare

Compare puts segments of a report side by side: different hotels, different platforms, or one-star and five-star reviews. Up to five can be compared at once, without using extra queries. For a hotel, the most valuable use is placing your property next to the hotels guests consider for the same trip and seeing the volume of feedback, the sentiment, the themes they share and the themes that appear for only one of them. If a competitor's guests keep praising its breakfast or its quiet rooms and yours never mention either, that is a decision waiting to be made.

Action Plans

Action Plans turn the findings into steps. You start by choosing or creating a Profile that describes your hotel, its location and the guests it serves, then select a perspective: Our own offering, A rival or Our market. These match the three groups of questions at the beginning of this guide. A sensible first plan uses Our own offering with the Customer Experience goal. Once you have a report that includes competing hotels, a second plan with the Competitive Strategy goal focuses on how to position your property against them.

Kimola builds hypotheses from the report, tests each one against the feedback and drops the actions the evidence does not support. Each remaining action comes with a confidence level and explains why it matters, who it is for, when and where to act, the risk involved and how to see that it worked, along with the evidence behind it. A plan contains up to 12 actions. Plans work best when the report already has Signals, as the support article on how actions are built explains.

From Findings to Decisions

Research is only useful if it changes a decision. For a hotel the decisions are concrete, and each one connects to a specific part of the report.

Rooms and Facilities

Room investments are expensive, so they should follow the evidence. When Pain Points shows that complaints about the room concentrate on one issue, such as noise, beds or bathrooms, and Signals show that issue concentrated in certain room types, the investment can be targeted. Compare shows whether competitors' guests praise something your rooms lack, and whether it matters to the guests you most want to attract.

Breakfast and Dining

Breakfast is one of the most discussed parts of a hotel stay and one of the easiest to change. Experience Stages shows how breakfast compares with the rest of the stay, and Personas shows whose expectations it meets. If business travelers mention the opening time and families mention variety, a small change for each group may matter more than a larger overhaul.

Staff and Service

Guests often name the staff, and these comments are among the most useful for training. When Experience Stages shows that service complaints concentrate at check-in or check-out, the issue may be process or staffing at peak times rather than attitude. Positive mentions are just as useful, because they show what guests value and what to keep doing.

Pricing and Channels

Value for money is judged against the whole stay. Compare shows how guests describe value at your property and at competitors in the same price range, and the platform column shows whether guests from different channels judge it differently. If guests from one channel consistently report lower value, the rate, the room they are given or the expectations set by that channel may need attention.

Guest Segments

Personas and Social Context together show which kinds of guests are most satisfied with your property. A hotel that delights couples and disappoints families has two options, and both start from evidence: invest in what families need, or focus its marketing and its offer on couples. Motivations shows what each segment came for, which tells you what to emphasize.

Repeat Stays

Guests who return describe what brought them back, and their reviews are a direct record of loyalty. Look for themes that appear in reviews from returning guests and in reviews from guests who say they would not return. When the same Pain Point appears in both your own feedback and public reviews from disappointed guests, it is a strong candidate for a real reason guests do not come back.

Ongoing Research

A single report gives you a snapshot, and a hotel's year moves through seasons, events and changing guest mixes. Repeating the research at regular intervals, for example at the end of each season or after a renovation, shows whether the changes you made actually moved the themes they were meant to move.

On paid plans, Feeds keep the research running continuously. A Feed collects public mentions from social media, news sites, blogs, forums, YouTube and review sites, based on the keywords and links you define. Alerts email your team when something important happens, and Mailings send a regular summary. Over time, Trends Signals show which topics are rising and which are fading.

Hotel Groups and Multi-Property Operators

Hotel groups and operators with several properties face the same questions at a larger scale, with one more added: why does the same brand perform differently from one hotel to another? On the Enterprise plan, each hotel can become a Space, a continuously growing source of feedback classified with the same Funnel, which is a shared set of custom models and Dimensions. Because every property is analyzed the same way, results stay comparable over time and between hotels, so a breakfast problem in one property and a check-in problem in another can be seen side by side. Spaces also calculate an NPS from what customers write, on a scale from -100 to 100. It is derived from the positive and negative share of written feedback, so it is not the same as a Net Promoter Score from a 0 to 10 survey, and NPS targets can be set for each hotel.

When a finding needs action, Tasks assign it to a member of the operations team at the relevant property, with the underlying feedback attached as evidence, and Tasks can be sent to Jira. After a Task is closed, Kimola measures feedback on the same topic again two and four weeks later, so a change at the front desk or in housekeeping can be checked against what guests say afterwards. Executive summary screens give leadership a single view of what guests are saying across the group. Enterprise accounts are set up together with a dedicated Account Manager, and you can request a demo to discuss your setup.

Frequently Asked Questions

A few practical questions come up when a hotel starts researching with customer feedback for the first time.

Should reviews from different platforms be analyzed together?

Usually yes. Putting Tripadvisor and Google Business reviews in one report gives you a larger dataset, and the platform column lets Signals and Compare show whether guests on each platform describe the stay differently.

Which competitors should a first report include?

The hotels guests actually consider for the same trip, which are usually nearby properties in a similar price range. Your own reviews sometimes name them, and Substitutions can surface them if you add that Dimension later.

How many reviews do I need before the findings mean anything?

There is no fixed threshold, and the ranking on the Performance screen is designed to protect you from small samples by weighing how many reviews support each theme. Adding a few competing hotels to the same report is the easiest way to reach a dataset large enough for Signals.

Getting Started

Your guests, and the guests of every hotel nearby, have already described much of what your property needs to know, step by step through the stay. Create a free Kimola account, add your hotel and a few competitors to a single report, and see which step of the stay guests talk about most. If you work with travel partners or run a restaurant alongside your rooms, the market research guides for travel agencies and restaurant owners apply the same approach, and the market research guide for small businesses covers the method for any industry.