How does CountMatters support sales analytics?

CountMatters links foot traffic with conversion data to help businesses understand what drives sales, identify bottlenecks, and optimize performance.

Is sales and visitor tracking GDPR-compliant?

Yes. Our solution is fully GDPR-compliant. All data is anonymized on-device with no personal identifiers or facial recognition involved.

What types of data can I track for sales analytics?

Track real-time footfall, conversion rates, dwell time, sales by zone, and product engagement using our AI-powered sensors and analytics dashboard.

Standardized Performance Across Every Location

PORTFOLIO BENCHMARKING.MULTI-SITE PERFORMANCE, COMPARED.

Compare occupancy, traffic, and conversion across your portfolio. Identify top and underperforming locations with consistent, verified data.

Request a Portfolio Review

DEFINITION

Portfolio Benchmarking

Portfolio benchmarking means comparing locations across the same portfolio on a shared, audit-ready data foundation—so prioritization is fast and consistent.

What it is

Standardized measurement and comparison of visits and movement flow across multiple locations over the same period.

What it requires

Shared definitions, stable operations, and traceability—so numbers hold up in internal controls, vendor changes, and audits.

What you get

Decision-grade comparability: ranking, segmentation, and clear variance per location.

AUTHORITY

Why it’s difficult

Portfolio benchmarking fails for one reason: small differences in method become big differences in results. Without control of definitions and operations, the “best site” is often just the “best measured”.

Different definitions

“Visit” does not mean the same thing if count points, zones, or rules vary between sites.

Entry/exit handled differently
Filtering and double-counting differ

Operational noise

When sensors move, get blocked, or go down, the benchmark looks “real” but is actually operations.

Breaks in series and gaps
Without quality signals, variance becomes political

Normalization that holds

Comparing sites without accounting for opening hours, seasonality, and profile leads to wrong conclusions.

“Similar” sites are rarely similar
Requires documented rules, not assumptions

That’s why benchmarking is a method problem before it’s an analytics problem.

OUTCOME LAYER

What it enables

When the portfolio is measured consistently, you can manage across sites: prioritize actions, track impact, and explain variance without method debates.

Audit-ready prioritization

Rank sites on the same definitions and data quality—so capex and actions follow facts.

Clear “why” behind top/bottom
Comparable periods and segments

Impact measurement by site

See before/after changes without results getting distorted by seasonality, opening hours, or measurement noise.

Stable baseline for tests
Better decisions on what to scale

Portfolio operating model

Make the portfolio manageable with fixed KPIs, clear tolerances, and traceable variance—from site to exec.

One language across ops and commercial
Less “Excel politics” in QBRs

When comparisons are correct, you can move from numbers to actions.

TRUST

What makes the numbers credible

Benchmarking is used for decisions. Numbers must be traceable, stable, and explainable—especially when something deviates.

Traceability by site

Numbers can be explained back to count point, zone, and rule set—without manual “in-between” work.

Documented definitions
Change tracking over time

Data quality as a signal

Quality is made explicit so variance is interpreted correctly—not turned into a “who’s right” debate.

Coverage, status, and variance per sensor
Breaks in series are flagged and explained

Stable operations

Benchmarking over time requires operations that don’t drift—same method, same standards, same follow-up.

Defined routines for control and maintenance
Changes handled as part of the method

Trust is not a design choice. It’s an operating choice.

FAQ

Frequently asked questions

Short, concrete, decision-oriented. For deeper detail, we handle it in a technical review.

What’s the minimum to compare sites?

A shared visit definition, the same entry/exit counting approach, and a common filtering rule. Otherwise you’re comparing methods, not performance.

How do you handle opening hours and seasonality?

We normalize to defined opening hours and compare like-for-like periods. Holidays and exceptions are handled as explicit rules—not assumptions.

What happens when a sensor moves or goes down?

It shows up as a quality signal / break in series, so you can tell whether variance is operational or real. That keeps the benchmark interpretable.

Can we benchmark different site types in the same portfolio?

Yes—but not as if they’re the same. Segment by site type and compare within segments before comparing across them.

30+ YEARS OF ACTIONABLE INSIGHTS

BENCHMARKING ONLY WORKS IF THE NUMBERS ARE COMPARABLE.

Request a Portfolio Benchmarking Readiness Review.

WHAT YOU RECEIVE

Assessment of whether your portfolio can be benchmarked like-for-like (today)
Standard definition for counting rules, site structures, and reporting periods
Identification of bias drivers: coverage gaps, mixed technologies, local exceptions
A clear path to scalable, audit-ready benchmarking across sites and regions

✓ No obligation
✓ Tailored to your portfolio structure