Complete Market Research Guide for Coffee Shops & Roasters

Coffee businesses make a surprising number of decisions on instinct. A café adds a seasonal drink because the team liked it, extends opening hours because the street seems busier, or raises prices because a nearby shop did. A roaster launches a new single origin because it cupped well, changes its bag design because the old one felt dated, or starts a subscription because other roasters offer one. Some of these decisions work. Few of them are tested against what customers actually say.

Customers say a lot. Café guests write about the wait at 8 a.m., the Wi-Fi, the seating and whether the flat white was worth the price. People who buy roasted beans write about freshness, grind, roast level, packaging and how a coffee tasted compared with the description on the bag. Most of this is public, and much of it is written about your competitors as well as about you.

This guide shows how a café owner and an independent roaster can turn that feedback into real market research. It covers both businesses, because they sit in the same category but answer to different evidence.

Key Research Questions

A café sells an experience in a specific place, and its guests judge the drink together with the queue, the staff, the room and whether it is a good place to work or meet. A roaster sells a product that is brewed somewhere else, often weeks after roasting, and its customers judge flavor, freshness, packaging, delivery and value. For both, the questions fall into three groups: questions about your own business, questions about your competitors, and questions about where the coffee market is moving.

Your Café or Roastery

For a café, the key questions are why people choose it and where the visit goes wrong. Some guests come for the coffee, others for the location, the pastries, a place to work or the atmosphere. Problems tend to cluster around the morning rush, inconsistent drinks, seating, noise, cleanliness and price.

For a roaster, the questions are which coffees customers return to, how they describe the flavor compared with your tasting notes, and what goes wrong with freshness, grind, packaging or delivery. If you run a subscription, the most important question is why subscribers cancel.

Many businesses are both: a café that roasts its own beans, or a roaster with a tasting room. In that case, ask both sets of questions and keep the answers apart, because the decisions they lead to are different.

Your Competitors

A café's direct competitors are the other coffee shops guests could walk to instead. Indirect competitors include bakeries, tea shops, convenience stores with a coffee machine and fast-food chains that sell coffee. What do their guests value that yours never mention? What do they complain about that you could solve?

A roaster competes with other specialty roasters, with supermarket coffee and with capsules. Competitors' product reviews often reveal expectations about roast dates, resealable bags or grind options that your own customers have not yet mentioned, because they describe experiences with products you have never sold.

The Coffee Market

The third group concerns the category. For a café, it starts with local demand: who lives and works nearby, when they need coffee and how they use a café. A café near offices serves a different morning from one near a university or a park. For a roaster, the questions are which kinds of coffee people are asking for more often, what they buy instead of specialty beans and why, and how expectations around subscriptions, sustainability and packaging are changing.

Sources of Evidence

Evidence about a coffee business comes from four places: what your own customers already tell you, what customers of every café and roaster in your category write in public, what you can ask people directly, and what you can observe and compare yourself. None of these has to come first. Each answers the questions above from a different angle, and the strongest research combines them.

Café Reviews and Sales Data

For a café, Google Business is usually the richest public source. Every café has its own listing, including your competitors, and reviews tend to describe specific visits. Tripadvisor matters for cafés in tourist areas, and Yelp is an important source in many US cities.

Your point-of-sale data shows what sells, when and in what combinations. It tells you which hours are busiest and which items carry the morning, though it cannot tell you why a guest left the queue. Comment cards, social media messages and notes from staff fill in some of the why. Collected in one spreadsheet, with a column for the date and the location, they become the beginning of a customer feedback analysis practice.

Product and Store Reviews

For a roaster that sells on Amazon, product reviews of your own beans and of competing beans are the most direct evidence about flavor, freshness and packaging. Trustpilot collects reviews about online stores as a whole, which is where delivery, customer service and subscription management are discussed. Etsy matters for smaller roasters, and Reddit hosts long discussions about specific roasters, brewing methods and where to buy beans.

Subscription cancellation reasons are some of the most valuable feedback a roaster has. They often name the exact moment a customer decided the service was not worth it: a late delivery, too much coffee, a roast they did not enjoy.

Surveys, Interviews and Tastings

Traditional methods still have a role. A short survey, at the counter or after an online order, can combine a rating with one open question about what the customer would change. Rating questions give you numbers to track over time; open questions give you the reasons behind them.

For roasters, a tasting with regular customers is a natural form of interview: you learn how people describe flavor in their own words, which is often different from the language on the bag. For cafés, a few conversations with regulars and with people who stopped coming are worth more than a long questionnaire. The limitation of these methods is scale. Survey answers and interview notes are also qualitative research data, and they need the same structured analysis as reviews to become more than a collection of opinions.

Location and Pricing

For a café, a location check looks at foot traffic at different times of day, visibility from the street, access by public transport and parking, the number of cafés nearby and the rent the location can support. A cluster of nearby cafés is also a sign that an area has demand for coffee. Walking the area in the morning, at lunch and in the afternoon, and watching where people go, remains the most reliable part of this check.

A pricing check compares your menu or your bean prices with those of your direct competitors. For roasters, price per bag only makes sense alongside the size, the origin and the roast date. Reviews then add what a price list cannot: whether customers feel the price is justified.

Researching Coffee Shops with Kimola

Kimola is an AI platform that turns customer feedback into enterprise-grade market research. For a coffee business, that means taking reviews of your café or your beans, and of your competitors, together with your own feedback, and turning them into a structured study of what customers value, where expectations are missed and what to change. 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. A café pastes its Google Business or Tripadvisor link; a roaster pastes an Amazon product page or its Trustpilot page. With the Add Multiple option you can paste several links, one per line, and Kimola collects all the reviews into a single dataset. For a café, a good first report includes your own listing and the three or four cafés your guests could walk to instead. For a roaster, it includes a few of your products and comparable products from competing roasters. A business that does both should build two reports, because café reviews describe visits and bean reviews describe a product used at home. The support article on creating a report by adding links walks through each screen.

For Yelp, Etsy or Reddit, Kimola's browser extension, Airset Generator, collects the comments from a page and sends them to your account as an Airset, which you can turn into a report. Your own data, such as comment cards, survey answers or subscription cancellation reasons, can be uploaded as an .xls, .xlsx, .csv or .tsv file. If the file contains columns like location, product or month, Kimola reads them, and you can filter and compare the results by those values.

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. The useful set differs between a café and a roaster.

For a café, Experience Context asks what situation the visit was for: a quick coffee before work, a morning of remote work, a weekend brunch. Social Context asks who the guest was with or what kind of meeting it was: alone with a laptop, catching up with a friend, a business meeting. Together they show whether your space serves the visits your guests actually make, and whether people who come to work and people who come to talk get in each other's way.

Motivations asks why guests choose a place, which separates coffee quality from convenience, atmosphere or food. Pain Points asks what goes wrong, which is where waiting times, seating, noise and inconsistent drinks appear.

For a roaster, Unmet Needs asks what customers want and cannot find, such as a decaf that tastes like the regular blend, a smaller bag size or a clearer roast date. Personas groups customers by who they are and how they brew, such as espresso enthusiasts, filter drinkers and people buying a gift. Substitutions asks what customers compare your coffee with or switch to, including supermarket brands, capsules and other specialty roasters.

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 service can be tagged with something as specific as a slow mobile order pickup or baristas who remember regular orders.

Each review can mention several themes, and each theme gets its own sentiment. A guest who loves the coffee but finds the café too loud for work contributes a positive mention of the coffee and a negative mention of the noise, 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 with five enthusiastic reviews does not outrank one supported by fifty. For a small café or roaster with a modest number of reviews, this is a safeguard 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 the café or product a review is about, its rating or its 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.

A Signal might show that complaints about waiting time are concentrated in the reviews of one competitor, or that mentions of freshness have increased for one of your products in recent months. 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, up to five at a time, without using extra queries. A café can compare itself with nearby competitors; a roaster can compare its products with competing products, or its one-star reviews with its five-star reviews. The comparison shows the volume of feedback, the sentiment, the themes everyone shares and the themes that appear for only one segment. Those unshared themes are often where a positioning idea or a fix comes from.

Action Plans

Action Plans turn the findings into steps. You start by choosing or creating a Profile that describes your café or roastery, 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. For a café, a first plan with Our own offering and the Customer Experience goal focuses on the visit. For a roaster, the Product Development goal fits a report about your own beans, and Competitive Strategy fits one that includes competing roasters.

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. The first three decisions below belong mostly to cafés, the next two to roasters, and the last one to both.

Menu and Pricing

If Motivations shows that guests come mainly for the coffee, simplifying the food offer may cost little; if they come for brunch, the kitchen deserves as much attention as the espresso machine. Unmet Needs often surfaces requests for plant-based milks, decaf options or lighter food that are easy to test. On price, Compare helps: if guests at nearby cafés describe similar prices as fair and yours describe them as expensive, the themes around the cup usually show where the difference lies.

Speed and Service

The morning rush is a common source of complaints. If Pain Points and Experience Context show that waiting time is the main complaint among commuters, mobile ordering, a separate pickup point or one more barista at peak hours are options to test, and your point-of-sale data shows exactly which hours to staff. When service themes are positive but drink consistency is not, the issue is more likely training or equipment than staffing.

Space and Atmosphere

Seating and atmosphere decisions follow from Social Context. If remote workers dominate the reviews and mention outlets and Wi-Fi while social visitors mention difficulty finding a table, the space may need clearer zones or time limits at peak hours.

Bean Selection

Bean profiles and the range follow from Unmet Needs and Substitutions. If customers repeatedly ask for a lower-acidity blend, a stronger decaf or a particular origin, those are candidates for your next release. If they compare you with capsules or supermarket coffee, the comparison tells you what convenience or price point you are up against. When reviews say a coffee tasted different from its description, the tasting notes and brewing guidance on the product page may need work as much as the roast.

Packaging and Subscriptions

Packaging is a frequent and concrete theme: resealable bags, valves, roast dates, bag size and recyclability. Pain Points across your products and your competitors' products show which of these customers actually notice. For subscriptions, cancellation reasons combined with Trustpilot reviews show whether customers leave because of delivery timing, quantity, flexibility or flavor, and each of those has a different fix.

Customer Loyalty

For a café, loyalty shows in reviews from regulars: what they mention about being recognized, about consistency and about changes they noticed. For a roaster, it shows in repeat purchases and in reviews from long-term customers. In both cases, when the same Pain Point appears in your own feedback and in public reviews from former customers, it is a strong candidate for a real reason people stop coming back.

Ongoing Research

A single report gives you a snapshot. Cafés change with the seasons and with new competitors on the street; roasters change with every new crop and release. Repeating the research every quarter, or after each significant change, shows whether the changes actually moved what customers say.

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.

Coffee Chains and Multi-Location Roasters

Coffee chains and larger roasters face the same questions across many locations, products and channels, with one more added: why does the same brand perform differently from one location or channel to another? On the Enterprise plan, each café, sales channel or survey program 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 location is analyzed the same way, results stay comparable over time and between branches. 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 location.

When a finding needs action, Tasks assign it to a team member 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 you can see whether customers noticed the change. Executive summary screens give leadership a single view of what customers are saying across the organization. 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 café or roaster starts researching with customer feedback for the first time.

Should a café that also roasts run one report or two?

Two is usually clearer. Café reviews describe visits, and bean reviews describe a product used at home, so mixing them blurs both. Keeping them separate lets you choose the right Dimensions for each and compare each with the right competitors.

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 competitors' listings or products to the same report is the easiest way to build a dataset large enough for Signals.

Can I research a café or roaster I have never visited?

Yes. Their Google Business, Tripadvisor, Trustpilot or Amazon pages can be added to a report just like your own. A visit or a tasting will still tell you things reviews cannot, so the two methods work best together.

Getting Started

Your guests and your customers, and those of your competitors, have already described much of what your coffee business needs to know. Create a free Kimola account, add your café or your beans and a few competitors to a single report, and read what they have been saying. If you also run a kitchen or sell on marketplaces, the market research guides for restaurant owners and Amazon sellers apply the same approach, and the market research guide for small businesses covers the method for any industry.