Real Sales Conversion
The only conversion metric that reflects what actually happens in your store
Conventional counters divide your tickets by raw traffic. KSI filters staff, identifies repeat visits, and detects purchase groups to give you a clean, fair, and actionable conversion metric.
Request my demo→Your conversion rate is contaminated
Every conventional sensor counts raw traffic: employees going in and out, visitors returning several times during the day, families of four counted as four conversion opportunities but generating only one purchase.
The result is that the reported conversion rate is artificially low. What is reported as 4% might be 15% in reality. Decisions made on that gap are consistently wrong.
Raw traffic ≠ real visits
KSI filters unique visitors and separates staff so real conversion is measured with people who actually represent demand.
Three filters that transform the data
Staff Filter
KSI identifies and excludes employees anonymously, without uniforms or badges. The resulting traffic count includes only real customers.
Anonymous Re-identification
If a person enters, leaves, and comes back, KSI counts them only once as a unique visit. Without storing personal data. GDPR compliant.
Group & Family Detection
A family of four generates one purchase decision, not four. KSI identifies groups that move together and treats them as a single conversion unit.
Conversion by segment
Once you have clean data, the next step is understanding which segments convert most. Do families convert more? Adult groups? At what time of day?
Families
Average ticket and conversion rate for family groups
Couples
Behavior and conversion rate for visitors in pairs
Solo visitors
Individual conversion by gender and time slot
Gender & Age
Conversion comparison across different demographic profiles
The same number. Very different meanings.
| Concept | Conventional sensors | KSI Vision |
|---|---|---|
| Staff | Included in traffic count | Automatically excluded |
| Repeat visits | Counted multiple times | Unified as one visit |
| Groups & families | Each person = one opportunity | The group = one purchase unit |
| Segment conversion | Not available | Family, couple, solo, gender, age |
| Result | Artificially low conversion | Real and actionable conversion |
Not every zone converts the same
Store-wide conversion is just an average. Zone-level conversion is where the decisions live. KSI reconstructs each visit's path and measures how many people reach each area.
1. Identification at the entrance
Every visitor gets a unique, anonymous ID at entry. The journey starts there.
2. Path reconstruction
KSI links the visitor's internal trajectories across cameras into a single end-to-end path.
3. Conversion per zone
Computes what share of incoming traffic reached each zone. Pinpoints exactly where the funnel drops.
What it unlocks
Funnel: window → fitting room → checkout
See where customers drop out on the path to purchase.
Category optimization
Detect which sections actually get traffic and which are ignored.
Cross-shop between categories
Measure which zones get visited together to improve layout and promos.
Blind spots and shortcuts
Discover paths you didn't expect - and the ones no customer ever takes.
98% accuracy validated with multi-camera setups. No personal data stored.
Decisions you will be able to make
Real commercial targets
Set conversion goals based on a number that reflects reality, not one inflated by staff noise and repeat visits.
Identify which hours and zones convert most
With clean data, you will finally be able to see whether the problem is traffic, time of day, store zone, or visitor profile.
Real-time conversion alerts
KSI will send an alert when real conversion drops below a threshold, before the day ends badly.
Fair benchmarking across locations
Compare real conversion between stores without staff or operational flow distorting the comparison.
Privacy by design
No personal data. No exceptions.
KSI's anonymous re-identification works through morphological recognition: it identifies visual patterns without storing images or personal data. Your store does not become a surveillance system - it becomes an intelligence system.