How to calculate store conversion rate

Store conversion rate, often called retail conversion rate, shows what percentage of the visitors who enter your store make a purchase. The formula: conversion rate = number of sales receipts ÷ number of people entering × 100. For example, if 100 people came in during an hour and 21 receipts were issued, the conversion rate is 21%. The arithmetic is simple; the real work is measuring entries reliably and matching them to sales data over the same time window.

The retail conversion rate formula, with a worked example

You need two numbers: the number of sales receipts in a given time window and the number of entries in the same window. The figures below are illustrative:

• On Tuesday between 2 and 3 p.m., 100 people enter the store (from the people counter at the door).
• In the same hour, 21 receipts are issued at the till (from the POS).
• Conversion rate = 21 ÷ 100 = 0.21, i.e. 21%.
• If the same hour next week brings 120 entries and again 21 receipts, the rate drops to 17.5%.

That last line sums up why conversion rate matters: looking at receipts alone, the two hours would look identical. In fact, more people came in during the second week, but those extra visitors did not turn into sales.

Why you need entry data

Sales reports tell you how many people bought, not how many did not. The way to see visitors who came in and left empty-handed is to count entries, which is why the denominator of conversion rate is the entry count measured at the door. The Sayiyo PEOPLE people counter counts only the people entering, anonymously, with an AI camera above the door; images are processed on the device and not recorded. Entry counts reach the dashboard about every 10 minutes, which is enough to follow conversion rate hour by hour.

Using an estimate instead of an entry count can look tempting: staff observation, say, or the queue at the till. But estimates are least reliable exactly when you need them most, at peak hours. Without measured entries, when you compare two branches or two weeks you cannot tell whether a difference comes from traffic or from in-store performance.

Connecting sales data: integration

To calculate conversion rate, sales (receipt) data has to reach Sayiyo. This is done through integration with your POS or ERP system: sales data is sent to Sayiyo via REST API, and the dashboard matches entries and receipts by store and hour and calculates conversion rate automatically. Without integration, Sayiyo does not calculate conversion rate, though you always see entry data in the dashboard. If you wish, you can also pull entry and conversion data into your own BI or reporting system via API or webhook.

Visit rate vs conversion rate

The two rates are often confused, but they answer different questions. Visit rate = entries ÷ passers-by; it shows whether your window and location draw people in, and it is measured together with the Sayiyo PASS storefront counter. Conversion rate = receipts ÷ entries; it shows whether the in-store experience, product and staff turn visitors into buyers. Read together they form a full funnel: passing by → coming in → buying. We cover visit rate in detail in what is visit rate.

Common mistakes

• Mismatched time windows: dividing daily receipts by hourly entries is misleading; both numbers must cover the same interval.
• Missing doors: if a side or second entrance is not counted, entries come out low and conversion rate looks higher than it is.
• Forgetting staff traffic: at doors with heavy staff or supplier traffic, factor this in when you interpret the numbers; if there is a separate staff entrance, leave it out of visitor counting.
• Ignoring groups: three members of one family are three entries but often a single receipt. Read the rate against your own history rather than as an absolute target.
• Leaving “receipt” undefined: decide up front whether returns and exchanges count.
• Deciding on a single day: weather, campaigns and holidays move the rate; look at a trend of at least a few weeks.

Which time window should you track?

Conversion rate says more when you read it across different time windows rather than as a single number. The hourly rate serves staff and till planning, the daily rate shows the rhythm of the week, and weekly and monthly rates track the trend. Comparing with the same period last year is the easiest way to separate seasonal swings from real change. Whatever window you choose, the rule is the same: numerator and denominator must cover the same interval.

Where to start improving conversion rate

When the rate drops, the first job is to find out in which hours and which stores it dropped. Then teams usually look at the following in the store:

• Attention: is there enough staff to help visitors at peak hours?
• Waiting: are queues forming at the till or the fitting rooms?
• Availability: are the sizes, colours and models people ask for on the shelf?
• Layout: does the area just inside the entrance draw visitors further in?

After each change, compare the periods before and after over the same hours; that way you measure which intervention worked instead of guessing.

What to do with the number

The rate is a starting point; its value comes from the decisions you make with it.

• Put hourly conversion next to the staff plan: hours with high entries and low conversion are often hours when there aren’t enough people to help. There is an example in planning shifts around footfall.
• Rank stores not only by revenue but also by conversion rate; the store comparison and ranking in the Sayiyo visitor analytics dashboard are built for this.
• Compare the periods before and after a campaign, layout or window change.
• Compare with the same period last year to separate out seasonality.

A widely used retail equation shows where conversion rate sits: revenue = entries × conversion rate × average transaction value. Tracking the three components separately shows whether a change in revenue came from traffic, conversion or basket. Entries and conversion rate are in the Sayiyo dashboard; average transaction value is in your POS data.

Frequently asked questions

What is a good conversion rate?

It varies widely by sector, store format and basket profile; no single number applies to everyone. The most meaningful comparison is with the same store’s past periods and with similar branches of your own.

Does Sayiyo calculate conversion rate itself?

Yes. Once sales data comes in through POS/ERP integration, the dashboard calculates conversion rate per store automatically. Without integration, only entry data is shown.

Can I see conversion rate hour by hour?

Yes. Once sales data is integrated, entries and receipts are matched by hour; you can see hourly conversion rate in the dashboard and pull it into your own systems via API or webhook.

Can I export the data?

Yes. You can download data from the dashboard as Excel/CSV or pull it into your own systems via API and webhook.