News & Updates

Run a smarter venue with better data

Written by Aanchal Midha | Aug 4, 2026

If you've ever closed up on a Saturday night not quite sure whether it was a good week or just a busy one, you're not alone. Most venue owners are making decisions on gut feel, not because they don't care about the numbers, but because getting to those numbers takes time nobody has. Here's what you can understand better about your venue and customers with Oolio Insights and reporting.

Know who's coming back and who isn't

You probably already know your regulars by name. But what about the ones who used to come in every week and haven't been back in a month? Customer Intelligence in your Oolio reporting shows you exactly who's who, automatically grouping your loyalty members by how often they visit and how much they spend, so you know where to focus your energy.

All your customers can probably fit into four categories:

Oolio One automatically puts every loyalty member into one of these groups, so you always know where to focus.

You can dig into the data through visual charts, filtered by location, service period, and day of week. Every member has a last visit date and at-risk status, so you always know exactly who needs attention.

Make changes to your floor in real time

Imagine being able to make changes to your floor in real time, instead of realising the night before you were overstaffed after the fact. If you're connected to Deputy or Tanda, Oolio One shows you your labour cost as a percentage of revenue while service is happening. Set a target, set a buffer, and you'll know the moment you're running over, while you can still do something about it.

Know what's coming before it arrives

Most venue owners set a budget at the start of the year and check back in at the end of the month to see how far off they were. By then it's too late to change anything. The difference with Oolio One is that the forecast builds itself, using your actual trading history, so it's not a number you estimated in a spreadsheet six months ago. For some Oolio customers, system projections have been within approximately 2% variance.

Every time you open your reporting you can see what you're on track to make versus what's actually coming in. Spot a slow week early and you can do something about it, run a last minute special, tweak your roster, or pull back on ordering. Small adjustments in the moment add up to a much healthier end of month.

Menu engineering: Make every item on your menu earn its place

Your menu is one of the biggest levers you have on profitability. This gives you a reason to pull it.

Menu optimisation: faster service, cleaner system, better revenue

Modifiers are the add-ons, swaps, and extras on your menu, things like 'add bacon', 'swap to oat milk', or 'make it a large'. They seem small but they have a big impact on how fast your staff can take an order and how much a customer ends up spending.

Oolio reporting shows you which modifiers your customers actually choose, which ones get ignored, and how they're affecting average order value. Maybe oat milk is your most popular swap and you should be charging more for it. Maybe half your menu has an 'add a side' option that nobody ever clicks. Cleaning that up means a faster ordering experience for your customers and less noise for your staff.

Factor in the weather

A quiet Tuesday after a long weekend feels different from a quiet Tuesday in the middle of winter. Weather has a real impact on how your venue trades, and Oolio layers that context directly into your reporting.

You can see weather data overlaid across your key reports, like hourly sales, sales summary, product performance, and more, so when you're reviewing a slow Friday, you can see how the weather has imacted your revenue and foot traffic. That context changes how you read the data and how you plan for the next one.

It also flows through into your forecasting. When you're setting your weekly budget, Oolio shows you the projected weather for each day alongside your sales projection, so you can adjust your forecast before the week starts rather than explaining the variance after.