How do I choose bar analytics software?
By Better Bartender · Published
Start with a decision your team needs to make, then ask the supplier to demonstrate it using a clearly identified source, period and calculation. A polished dashboard is useful only when the underlying information can be trusted.
What problem am I trying to solve?
Write down one recurring question. You might want to compare drinks sold across shifts, understand discounts or combine sales with recipe costs. These require different inputs. Sales reporting is not automatically inventory management, and an AI assistant is not automatically a forecasting system. Define what a successful answer would let you do.
Will it work with my actual POS account?
Ask about your provider, product edition, country, locations and account permissions. A familiar logo does not prove that every edition exposes the same reports. Establish whether data comes through an API, a scheduled report or a manual file. Ask who completes sign-in and security challenges, and how a failed connection is reported.
Can I trace a number back to its source?
Request a demonstration showing the original reporting period, item identifiers, quantities, discounts and refunds. Check the timezone and how an overnight shift is assigned. Ask what happens when a report is late, duplicated or corrected. Missing information should be visible; it should never silently become zero sales.
Our bar sales reporting checklist explains the distinction between sales and payments and shows why revenue and quantities need separate comparisons.
Does “profit” include the costs I care about?
Ingredient contribution needs recipe costs as well as sales revenue. Operating profit needs a wider picture, including labour and overheads. Ask whether figures use actual realised revenue or a menu price, and whether tax treatment is consistent. A system without your current costs should not present an exact profit figure as fact. Work through our pour-cost example before comparing margin claims.
What is the AI doing, and what checks its answer?
Ask the supplier to separate AI-assisted setup, calculations, generated explanations and predictions. For each, request an example of an uncertain or unsuccessful result. The useful question is how uncertainty is shown and corrected. An explanation that sounds confident is not evidence that a calculation is right.
Who controls access and what happens if we leave?
Confirm who can see venue data, what permissions are requested and which information reaches an AI model. Ask how to stop collection, remove provider access and request an export or deletion. Keep a record of what the supplier confirms and of any provider settings your own team must change.
How should we evaluate a pilot?
Agree a short, specific test: one venue, a defined reporting period and a named question. Record time spent checking reports, completeness and any corrections. Compare the outcome with your existing method. Do not count an attractive demo or a saved schedule as proof that recurring data delivery works.
Better Bartender brings an AI-native approach to bar analytics. Read our pilot scope, our approach to hospitality AI and request early access. This checklist is published by Better Bartender; it is not an independent ranking of suppliers.