What retail analytics covers
Retail analytics brings together what happens at the door, on the shop floor and at the till. For a fashion, electronics, perfume, gift or home store, that means knowing how many people came in, how many bought, what they spent, and whether your team was there to help them.
In Saudi Arabia, retail patterns follow paydays, seasons, Ramadan and Eid, back to school and big sale periods. Analytics helps you prepare for each one rather than react to it.
The four numbers that run a shop
Revenue is simply footfall times conversion times average basket. When revenue moves, one of these moved, and knowing which one tells you whether the fix is in marketing, on the floor, or in your range and pricing.
- Footfall: people entering, by hour, from a footfall counter.
- Conversion rate: transactions divided by footfall.
- Average basket: revenue divided by transactions.
- Footfall per staff member: whether customers can get help when they need it.
ExampleA perfume shop sees 900 visitors in a week, 135 transactions and an average basket of 240 SAR, so 32,400 SAR in sales. Lifting transactions to 150 with the same traffic would add about 3,600 SAR.
Where retail shops lose sales
Each of these shows up in the data as the same thing: decent footfall with weak conversion at specific hours. Finding those hours is the first step to fixing them.
- No one free to help at busy times, especially in categories where customers need advice.
- Sizes or bestsellers out of stock on the busiest days.
- Long queues at the till during peak hours.
- Window displays or campaigns that bring browsers, not buyers.
- Changing the layout without checking what it did to conversion.
Common retail analytics mistakes
- Tracking sales only, so a busy day with poor conversion looks like a normal day.
- Comparing stores by revenue instead of by conversion and basket size.
- Judging a sale season by revenue alone without counting the discount cost.
- Getting reports too late to change anything that month.
- Moving staff between stores without checking which store's footfall really needed them.
How Tapsiera works for retail
Our team installs and connects a people-counter sensor at your entrance. Tapsiera links it with your POS sales data and your staffing, then shows you the decision in riyals: you need one more person on the floor on Friday evening, conversion dropped after the new layout, or the sale brought traffic but not buyers.
You also get forecasts, alerts, targets per store, a weekly WhatsApp report and an AI assistant you can ask in Arabic. See conversion rate and campaign analysis for the details. The sensor counts people and does not identify anyone; your data is encrypted and under your control.
ExampleTapsiera finds that weekend evening footfall at your store is high but conversion is the lowest of the week, with only one person on the floor. Adding a second could bring back around 1,000 SAR a week.
Who it is for
Independent shops, retail brands with several stores, salons and beauty shops, and store managers who need clear weekly targets. No POS? Tapsiera asks for daily sales on WhatsApp each night, or you can upload Excel. You can try the demo with sample data at app.tapsiera.com.
Frequently asked questions
Is retail analytics only for big chains?
No. A single shop with steady traffic benefits as much, because the decisions are simple: staff, stock and opening hours.
Can it tell me if my sale season worked?
Yes. Compare footfall, conversion and basket during the sale with normal weeks, and see what came back after the discount.
Does the sensor identify customers?
No. It only counts people coming in and going out. It does not identify anyone.
How much does Tapsiera cost?
199 SAR per branch per month, VAT included. The door sensor is 1,599 SAR one time per sensor with installation included, and you can reserve now for 99 SAR, which is deducted from your first payment.