Visitor analytics for retail

See what happens in your stores. And how they differ. .

Connect visitor data with transactions and sales to see when store traffic changes, how locations develop and where it is worth looking more closely.

Store traffic See how many people visit your stores — and when.

Comparison Compare stores, periods and changes over time.

Commercial context See visits, transactions and sales in context.

Talk to CountMatters See how it works

30+ years of visitor data

Visits today 1,284 ▲ +12% vs. last Saturday

Change by store

Brompton +18%

Westfield +6%

King's Road -4%

Conversion Rate 6.8% ▲ +0.9 pp

People in store now 42

LOOK BEYOND SALES

Sales show the result. Visitor data shows what sits behind it.

Two stores can deliver similar sales with very different traffic and conversion figures. Looking at traffic, Conversion Rate and sales together makes those differences visible.

TRAFFIC How many visits did the store have?

CONVERSION RATE What share resulted in a transaction?

SALES What was the sales result?

Similar sales can hide very different patterns in traffic and Conversion Rate.

SIMILAR SALES. DIFFERENT PATTERNS.

STORE A Higher traffic

VISITS 12,400

CONVERSION RATE 4.8%

SALES €72k

More visits, but a lower Conversion Rate.

STORE B Lower traffic

VISITS 9,100

CONVERSION RATE 6.2%

SALES €69k

Fewer visits, but a higher Conversion Rate.

↗

THE POINT Similar sales. Two very different traffic and conversion profiles.

Illustrative example. Available data depends on setup and integrations.

FROM DATA TO DECISIONS

Turn store traffic into questions you can answer.

Visitor data becomes useful when it shows what is changing, where differences appear and what is worth investigating further.

Industries - Retail - section 2 - Traffic_image

+24% Store traffic

↗

Is store traffic growing?

Track store traffic across hours, days, weeks and seasons to see how visit volumes change over time.

TRENDS PERIOD COMPARISON

Industries - Retail - section 2 - Store comparison image

+32% -18%

⌖

Which stores are developing differently?

Compare locations on the same data foundation and see which stores are developing differently from the rest of the portfolio.

STORE COMPARISON DIFFERENCES

Industries - Retail - section 2 - Campaign image

+28% Store traffic

◖

Did store traffic change during the campaign?

Compare store traffic before, during and after the campaign to see whether visit patterns changed over the same period.

CAMPAIGNS BEFORE / DURING / AFTER

Industries - Retail - section 2 - Peak periods image

Busiest times

08 12 16 20

◷

When are stores busiest?

Identify peak periods and use actual visit patterns to support staffing and operational planning.

PEAK PERIODS STAFFING

FROM ONE STORE TO THE WHOLE PORTFOLIO

See every store in context.

A single store shows what is happening there. Consistent visitor data across the portfolio shows how stores are developing in relation to each other — and where differences are worth investigating further.

Compare on the same basis

Use the same definitions and periods across locations.

See where development differs

Identify stores developing differently from the rest of the portfolio.

Know where to look closer

Give central and regional teams a clearer starting point for further analysis.

PORTFOLIO OVERVIEW

Store traffic

SELECTED PERIOD Last 30 days

LOCATIONS 31

PORTFOLIO TREND +4.8%

DIFFERENT DEVELOPMENT 6

STORE TRAFFIC CHANGE PORTFOLIO

Oslo City NO · 01

42,810 ↑ 8.4%

Above portfolio trend

Stockholm Central SE · 02

38,240 ↑ 2.1%

Near portfolio trend

Copenhagen DK · 03

31,670 ↓ 6.8%

Below portfolio trend

Hamburg Mitte DE · 04

29,420 ↑ 11.2%

Above portfolio trend

Illustrative view. Figures are examples and do not represent actual customer data.

The goal is not to rank stores. It is to see how they develop differently — and where to investigate further.

01 MEASURE

02 UNDERSTAND CHANGE

03 ADD CONTEXT

Industries - Retail - Section 3 - People Counting image

IN 124 ↑

OUT 118 ↓

PEOPLE COUNTING

Measure store traffic.

Know how many people enter and leave your stores with a consistent, reliable data foundation.

ENTRY / EXIT RELIABLE FOUNDATION

EXPLORE PEOPLE COUNTING

Industries - Retail - Section 4 - Fotfall Analytics image

FOOTFALL ANALYTICS

See how store traffic changes.

Compare locations and periods, and see peaks, trends and changes in store traffic over time.

TRENDS COMPARISON

EXPLORE FOOTFALL ANALYTICS

VISITOR INTELLIGENCE

Add more context to the visit.

Add context such as passerby traffic, Capture Rate, dwell time and commercial data where relevant and available.

CAPTURE RATE CONTEXT

EXPLORE VISITOR INTELLIGENCE

One data foundation. More context when you need it.

SHARED DATA FOUNDATION

Same data. Different questions.

CONSISTENT

↗ VISITOR TREND

+4.8%

◷ PEAK PERIOD

14:00–17:00 Highest traffic

◉ LOCATIONS

31 Same definitions

▥ DIFFERENCES

6 Locations developing differently

RETAIL OPERATIONS

Plan around when customers actually arrive.

Use actual visitor patterns to support staffing, opening hours and day-to-day operations.

01 When do stores need the most resources?

02 How does traffic vary through the week?

03 When do the largest traffic peaks occur?

Industries - Retail - Section 5 - operations image

Different roles. One consistent view of visitor data.

START WITH WHAT YOU NEED TO UNDERSTAND

What do you need to understand about your stores?

Tell us what you measure today, how many locations you have and which questions you want better answers to. Then we can look at how CountMatters could fit.

Understand store traffic

See how visit volumes, peaks and patterns change over time.

Compare stores

See which locations are developing differently from the rest of the portfolio.

Add more context

Combine visitor data with relevant signals to see what is worth investigating further.

TALK TO US

Let’s look at your stores.

Tell us briefly about your current setup and what you want to understand. We’ll get in touch for a practical conversation about your requirements.

A short conversation. No obligation.