As a pub landlord, you make dozens of decisions every day. What specials should go on the board? Is the new craft ale selling? Do we need an extra person on the bar this Friday? Most of the time, these decisions are based on gut feel, experience, and the last conversation you had with a regular. This intuition is invaluable, but in today’s competitive market, it’s no longer enough.
Your customers and your operations are generating a huge amount of data every single day. Hidden in your till receipts, online reviews, and casual conversations is the key to unlocking your pub’s true potential. Learning how to conduct effective pub customer feedback analysis is about moving from guesswork to a data-driven strategy.
This isn’t about becoming a statistician or getting lost in complex spreadsheets. It’s about using a simple, structured approach to listen to what your customers are really telling you, and turning those insights into smarter, more profitable business decisions.
The Problem: Flying Blind in a Competitive Market
Without a system for collecting and analysing feedback, you are essentially flying blind. You might think you know your business inside and out, but gut feel can be misleading and can lead to costly mistakes:
- Wasted Marketing Spend: You might be spending money on promotions that target the wrong people at the wrong time. A simple analysis of your booking data could reveal that your most profitable customers are not who you think they are.
- Inefficient Staffing: You could be overstaffed during unexpectedly quiet periods and understaffed during a surprise rush, leading to high labour costs and poor customer service.
- Missing a Recurring Problem: A single complaint about a slow kitchen might seem like a one-off. But without tracking feedback, you might miss a pattern of slow service that is quietly driving customers away.
- Stagnation: You miss opportunities for growth because you aren’t seeing the new trends or demands emerging from your customer base.
In short, by not systematically listening to feedback, you are leaving money on the table and giving your competitors an edge.
The Solution: A Simple Four-Step Process for Data-Driven Decisions
You don’t need a data science degree to make this work. All you need is a clear process. The key is to start with a question or an idea (a hypothesis) and then use the data to see if you’re right.
1. Ask the Right Question (Form a Hypothesis): Start with a specific issue you want to know more about. What are you trying to find out from the data? For example: “I would like to know more about what times of day our pub is busiest so I can plan staff rotas better”. Your hypothesis is your educated guess: “I think our busiest period is Friday between 6 pm and 9 pm.”
2. Gather Your Evidence (Data Collection): Next, you need to collate the relevant data to test your idea. This involves identifying the right sources and types of information.
3. Connect the Dots (Analysis):
Now you look for patterns in the data to see if they prove or disprove your hypothesis. You examine the information you’ve gathered to see what it’s actually telling you.
4. Take Action (Conclusion & Implementation): Finally, you draw a conclusion from your findings and turn it into an actionable business decision.
Deep Dive: Your Pub’s Data Goldmine
Before you can analyse, you need to collect. Your pub is a rich source of valuable data, which can be split into different types.
Quantitative vs. Qualitative Data
You need both numbers and words to get the full picture.
- Quantitative data is anything that can be written in numbers. It tells you what is happening. Examples include:
- The number of customer complaints
- The number of positive reviews on platforms like TripAdvisor or Google
- Mystery shopper or guest visit scores
- Sales figures from your EPOS system
- Qualitative data is information that can only be written in words. It tells you why something is happening. Examples include:
- Comments written in customer feedback or surveys
- Verbal feedback from customers and staff
- Comments on TripAdvisor
Quantitative data might tell you that your Sunday roast sales are down 15%, but qualitative data from reviews will tell you it’s because customers think the potatoes are undercooked.
Primary vs. Secondary Data
- Primary data is information you have collated yourself, for your specific purpose. For example, asking your own customers to fill in a feedback questionnaire.
- Secondary data is data that has been researched or published by someone else. For example, reading a report from your brewery about national drinking trends.
For most day-to-day decisions, you will be focusing on primary data collected directly from your own business.
Deep Dive: Turning Numbers and Natter into Profit
Once you have your data, you can start the analysis. Let’s return to our hypothesis: “I think our busiest period is Friday between 6 pm and 9 pm.”
- Analysis: You look at your quantitative EPOS data for the last three months. The figures confirm that Friday evenings are indeed very busy. However, the data also reveals something you hadn’t realised: whenever there is a major midweek football match on TV, your revenue per hour between 7 pm and 9 pm is actually 20% higher than on an average Friday. You then look at your qualitative feedback from Google reviews and see several comments praising the pub’s great atmosphere on match days.
- Conclusion: Your initial hypothesis was only partially correct. While Fridays are consistently busy, major match days are your most profitable, high-density trading periods.
- Action: This data-driven insight leads to several smart business decisions. You adjust the staff rota to ensure you have an extra person on the floor during big matches. You create a specific “Match Day Burger & Pint” deal to further increase the average spend. You update your marketing to heavily promote the fact you show live sports.
This is the power of analysis. You have moved from a general “gut feel” to a specific, evidence-backed strategy that directly drives business performance.
Case Study: The Teal Farm Pub’s Mid-Week Makeover
Let’s look at a real-world example of this process in action.
- The Question: The manager of the Teal Farm Pub wants to increase trade during the quiet mid-week period. His initial hypothesis is that customers are price-sensitive, and a simple food discount will be enough to bring more people in.
- Data Collection:
- Quantitative: He looks at his sales reports and confirms that Wednesday evenings are his quietest period.
- Qualitative: He reads through his pub’s TripAdvisor and Google reviews. While some mention price, he notices a recurring theme: several positive reviews specifically praise the pub’s “cosy and inviting atmosphere” and “friendly, welcoming staff”. One review even says, “This would be a great place for a quiz night.”
- Analysis: The manager realises his initial hypothesis was too simplistic. The feedback suggests that while value is important, his customers are also looking for a community feel and an enjoyable experience. A generic discount might not be enough to stand out. He decides his original hypothesis is likely incorrect.
- Action: Instead of just launching a discount, he decides to address the customer desire for a great atmosphere. He launches a new Wednesday Quiz Night. He uses his EPOS system to track food and drink sales on Wednesdays and uses the Marstons reputation app to specifically monitor feedback about the quiz night.
- The Result: The data quickly shows a significant uplift in Wednesday sales, far exceeding what a simple discount would have achieved. The online reviews are overwhelmingly positive, with customers praising the fun atmosphere. The manager used a combination of quantitative and qualitative data to make a smarter decision that delivered better results.
Conclusion: Your Best Business Advisor is Your Customer
As a manager, you have a responsibility to own and protect your business’s brand. A huge part of this is listening to your customers and handling their feedback professionally to protect your reputation. Customer feedback isn’t something to be feared; it is the most honest and valuable business intelligence you will ever receive. All feedback, positive or negative, is useful.
By adopting a simple, structured approach to pub customer feedback analysis, you can take the guesswork out of your decision-making. You can create better marketing, smarter rotas, and a customer experience that is constantly improving. Listening to your data is, in effect, listening to your entire customer base at once. It’s the most powerful way to build a stronger, more resilient, and more profitable pub.
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