Compare Sales Across Different Opening Hours

Why weekly sales totals can tell the wrong story

A weekly sales total answers an important question: how much was sold during that period using the definition in your report. What it does not tell you is how much opportunity each venue had to generate those sales.

Hypothetical example: Venue A opens five days and trades for 40 hours during the week. Venue B opens six days and trades for 60 hours. Venue B would normally have more trading time in which customers can spend money.

If Venue B reports higher weekly sales, that may be useful, but the total alone does not tell you whether it was busier while open. Equally, a venue with fewer opening hours should not automatically be considered more efficient simply because its hourly figure is higher.

The useful comparison starts by keeping the total and adding context rather than replacing one simplistic number with another.

Do not ask one number to explain the whole venue. Use it to decide what to investigate next.

Add sales per opening hour

A straightforward way to account for different opening hours is to divide sales for the period by the number of hours the venue was actually open.

Sales per opening hour = sales for the period ÷ actual opening hours

Use actual trading hours rather than the standard timetable if a venue opened late, closed early or did not trade on one of its usual days.

These figures are illustrative. They show why the £6,000 total and the £100 hourly figure answer different questions. Neither figure tells you profit, and neither is enough to decide which venue is performing “better”.

Make sure you are comparing the same thing

Before calculating anything, check that the numbers on both sides have been prepared on the same basis. Otherwise, a difference in reporting can look like a difference in trading.

Use the same date range for every venue. Then confirm how the sales figure treats VAT, refunds and discounts, and apply the same definition throughout the comparison.

Next, record actual opening hours for that period. If Venue A closed two hours early on Tuesday, use the hours it actually traded rather than copying its usual timetable.

Build one comparison record for each venue

For every site, record:

• the exact start and end dates;
• the sales figure using the same agreed definition;
• actual opening hours during that period;
• any full or partial closures;
• promotions or events likely to make the period unusual; and
• any known reporting difference that prevents a like-for-like comparison.

If you cannot make two figures genuinely comparable, label the limitation rather than presenting a precise-looking result that suggests more certainty than you have.

Add customer numbers and spend to understand what changed

Sales per hour can show trading intensity, but it cannot tell you whether a difference came from more transactions, larger purchases or a different type of visit.

Hypothetical example: Venue A records £4,800 from 200 transactions, giving an average of £24 per transaction. Venue B records £6,000 from 300 transactions, averaging £20 per transaction.

That immediately creates better questions. Venue B handled more transactions. Venue A recorded more sales per transaction. You can now investigate whether the difference reflects the venues’ offers, customer mix, trading periods or something else relevant to the business.

Be careful with the word “customer”. A transaction is not necessarily one person. One parent might pay for a whole family, while one visitor could make separate purchases during the same visit. If you want to calculate spend per visitor, use an appropriate attendance measure rather than automatically treating receipt count as visitor count.

Likewise, do not assume a higher average transaction value is automatically preferable. The two venues may sell different things or serve customers in different ways.

Look inside the week, not just at the average

An average can hide the exact trading period you need to understand.

Suppose a venue averages £100 in sales per opening hour. That does not mean every hour produces £100. Saturday lunchtime could be extremely busy while the final hour on several weekdays is quiet.

If you are investigating opening hours, break the data into useful periods that match how the venue operates. Compare the same weekday and time across several suitable weeks rather than comparing Tuesday afternoon with Saturday morning.

Hypothetical example: the quiet final hour

A venue manager notices that till sales between 5pm and 6pm appear low and wonders whether the venue should close at 5pm.

Before changing the timetable, look at several comparable weeks. Check whether customers who arrived or booked earlier remain in the venue during that hour. Look at whether purchases happen earlier in the visit even though the customer still needs the venue to remain open. Note whether school holidays, events or seasonal patterns affect the comparison.

The absence of many transactions during the final hour does not automatically mean the hour has no value to the customer experience.

Mark unusual weeks before drawing conclusions

One week can be real without being representative.

A private event, temporary closure, local event, promotion or unusual trading day can change the figures substantially. Do not automatically delete unusual periods; record what happened so you understand why the number moved.

Hypothetical example: Venue A appears to have an exceptional Saturday compared with Venue B. The manager checks the diary and discovers Venue A hosted an event that is not part of its ordinary Saturday pattern.

That sale still happened and belongs in the business records. But if your question is “How do our normal Saturdays compare?”, it should be identified when interpreting the result.

Start with an ordinary comparable period where possible, then look at several periods to see whether the same pattern returns. Avoid changing opening hours, staffing expectations or targets because of a single unexplained week.

Use venue sales comparisons to ask better questions

A comparison is most useful when it leads to a specific investigation rather than a league table.

If one venue has lower sales per hour, ask where the difference occurs. Is it consistently quieter on particular weekdays? Does it trade for longer at the edges of the day? Does it serve a different customer mix? Is its capacity different?

If one site has higher total sales but lower sales per hour, ask whether those additional opening hours still contribute enough value to the business when considered alongside relevant costs and customer needs. Sales reporting alone cannot answer the profitability question.

If the analysis will influence significant decisions about staffing, opening hours, pricing or financial performance, combine the operational information with the relevant cost and financial information and seek appropriate professional advice where needed.

If you use EPOS Reporting Software, decide the business question first and then identify the reports and definitions needed to answer it. A large collection of figures is less useful than a smaller set that everyone understands consistently.

Checklist: how to compare venue sales fairly

Use this sequence when comparing sites with different opening hours:

1. Choose one date range. Use exactly the same period for every venue.
2. Define sales consistently. Confirm how VAT, refunds and discounts are being treated.
3. Record actual opening hours. Include early closures or other changes to the normal timetable.
4. Calculate sales per opening hour. Divide the agreed sales figure by actual trading hours.
5. Keep total sales beside it. The hourly figure adds context; it does not replace the total.
6. Add transaction or attendance context where appropriate. Be clear about what each count actually measures.
7. Look at comparable time periods. Investigate weekdays or hours rather than relying only on a weekly average.
8. Mark unusual events. Note closures, promotions and events that could explain a difference.
9. Repeat the comparison. Check whether the pattern appears across several suitable periods.
10. Ask what information is still missing. Costs, capacity and customer behaviour may matter before making a business decision.