Find the sales your stores are missing.

Lenstat Retail reads the cameras you already have and shows each store where it loses sales, when, and what to do about it.

Talk to us Watch the floor
5money levers, counted daily
3alerts a day that matter
30days to prove each action
Retail store and street Street, 84 passing an hourEntrance, 40 in this hourEntrance, 41 in this hourFootwear wall, busiest nowHigh. 3 waiting at the fitting roomsSend an attendant

Five levers. Priced with your numbers.

Weekly counts from the cameras you already have, turned into sales with your own ticket.

  1. 1
    Second till at the peakWeekend shoppers who never reach the till
    0
  2. 2
    A seller on the busiest wallStops at the hottest wall, unassisted
    0
  3. 3
    Fitting-room attendantWaits at the door, closest to buying
    0
  4. 4
    Same-day queue alertLong waits nobody was told about
    0
  5. 5
    Window and greeterPassers-by who never turn in
    0
4,000
50
Every four weeks, for one store16k to 42k

ModelledLow and high rules of thumb per lever, at your inputs. The first thirty days replace them with your own numbers.

Watch the floor sell, hour by hour.

A real sales floor through one trading day. The heat is where shoppers stop.

Store clock17:00Busiest hour of the week
Busiest areas now, stops an hour
    What the store does

    The kids shoe wall pulls hardest. Put a seller there from 15:00 to 19:00.

    Every store has its own clock.

    Visits by hour and day, against the store's own busiest hour. Rosters start from the hot cells.

    Sun 17:00busiest hour
    2×weekend day against a weekday
    45%of visits after 16:00

    Sample data, approximate

    Five moments where stores lose sales.

    Each with the fix and the number that proves it in thirty days. Every fix moves hours you already have.

    1

    The till has a ceiling

    Sample data: on a weekend afternoon visits keep rising while customers who reach the till stay flat at the pace of one till025507510012510111213141516171819VisitsAt the tillOne tillFlat while the door climbs
    Fix
    A second till, weekends 12:00 to 19:00
    30 days
    Weekend till share up, long waits halved
    2

    A queue nobody saw

    Sample data: waits over a minute at the till, day by day for six weeks; a run of days far above the alert rule that an alert would have caught on its first day01020W1W2W3W4W5W6Waits over a minuteRuleDays above the rule, and nobody toldAlert on day one
    Fix
    A same-day alert at the wait rule
    30 days
    No run of days above the rule
    3

    The last hour keeps selling

    Sample data: customers who reach the till by hour, highest in the last hour, while arrivals fall in the evening0102010111213141516171819Reached the tillArrivalsThe last hour sells mostwhile arrivals fall
    Fix
    A full till to close, no early cash-up
    30 days
    Last-hour sales held
    4

    Fitting rooms break at the weekend

    Sample data: fitting-room use by day of the week, far higher at the weekend, and waits per hundred fittings rising far faster than use04080120MonTueWedThuFriSatSunFittingsWaits per 100At the weekend, waits outrun use
    Fix
    An attendant and staged sizes at the peak
    30 days
    Weekend waits per fitting halved
    5

    The street walks past

    Sample data: people passing the storefront and people turning in, by hour; the share who turn in is lowest at the hour the most people pass0500100015001011121314151617181920PassingTurned inShareMost passers-by, fewest turn in
    Fix
    A two-week window and greeter test
    30 days
    More passers-by turn in at the test hours

    Every number says what it is.

    • MeasuredVisits, waits, fittings, stops, passers-by
    • ProxyReached the till, until joined to your sales
    • ModelledMoney, at your inputs, never annualised

    Anonymous events. No faces or names kept.

    Answers before the doors open. Alerts before the queue forms.

    Sample data: one Saturday of visits with the morning brief, the second till, the fitting-room attendant, a queue alert and the closing scorecard marked at their times08:0009:0010:0011:0012:0013:0014:0015:0016:0017:0018:0019:0020:0021:0008:30 morning brief11:45 second till ready15:00 fitting-room attendant16:12 queue alert20:30 day closed, scorecardVisits through one Saturday, and the moments the routine reaches the manager
    LenstatStore 4, 08:30 brief

    Yesterday, Saturday: 1,120 visits, twice a weekday. Busiest hour 16:00.

    Till: 3 waits over three minutes, all between 16:00 and 17:00. Busiest wall: kids shoes.

    Today: about 1,000 visits. Prepare: second till from 12:00, a seller on the kids shoe wall from 15:00.

    How was the queue at 16:00?

    Up to 4 waited at the till, 3 over three minutes. Clip attached.

    Three alerts that matter

    Queue at the till

    Three or more waiting for three minutes.

    Waiting at the fitting rooms

    Two or more waiting over a minute.

    Entrance ahead of forecast

    The peak is coming early today.

    Each alert links to its clip. Rules agreed per store, reviewed monthly. Monday brings the scorecard; LensChat answers the rest.

    Every store on one page.

    One definition per measure. Each store leads at something, and the others can copy it.

    Sample data. Colour runs from the weakest store in a row to the strongest; rank in brackets.
    MeasureStore A, mallStore B, streetStore C, mallStore D, outlet
    Visits a week3,900(3)5,600(2)6,300(1)2,800(4)
    Reached the till44%(1)18%(3)16%(4)29%(2)
    Queue episodes per 100 visits4.8(3)1.9(1)6.6(4)3.1(2)
    Fitting rooms per 100 visits16(1)not measured9(3)12(2)
    Passers-by who turn in46%(2)84%(1)not measured38%(3)
    Busiest hourSun 16:00Sat 18:00Sat 16:00Sat 13:00
    1. Week oneCameras you have, a gateway per storeGate: every camera healthy
    2. Thirty daysThree stores, live actions, named ownersGate: the numbers move
    3. ThenThe network, store against storeGate: expand, adjust or stop

    See Lenstat Retail in your own stores.

    Tell us about your stores. We will show you what your cameras already see.

    hello@lenstat.com QA+974 6650 7955 AU+61 480 009 095 US+1 234 529 3634

    We reply within one business day.

    Privacy Policy

    Last updated June 2026

    Our approach

    Lenstat is built privacy-first. Our edge platform analyses video where it is captured, on NPU-powered gateways inside your own network. Raw footage stays on your site and is not transmitted to or stored by Lenstat. This policy explains the limited information we do handle and how we protect it.

    Information we handle

    Through this website we receive only what you choose to send us, such as your name, organisation, email, phone number and the details of your enquiry. We also collect basic, aggregated usage statistics to keep the site running well. We do not use the website to collect video or biometric data.

    Video and on-site processing

    Within the product, video is processed locally on your gateways. Lenstat analyses frames on the device and keeps only the anonymised findings and metadata that you configure, such as counts, dwell times and events. You stay in control of what is retained on your premises, and for how long.

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    Questions about this policy can be sent to hello@lenstat.com.

    Terms of Service

    Last updated June 2026

    Agreement

    These terms govern your use of the Lenstat website and, where applicable, the Lenstat edge analytics platform. By using the site or the service you agree to these terms. If you are accepting on behalf of an organisation, you confirm that you are authorised to do so.

    The service

    Lenstat provides edge AI video analytics software that runs on gateways within your environment, together with this informational website. Features, specifications and the example figures shown on this site are provided for illustration and may change as the product evolves.

    Acceptable use

    You agree to use the site and service lawfully, and not to misuse them, including no attempts to disrupt, reverse-engineer, scrape or gain unauthorised access. When you deploy the platform, you are responsible for operating your cameras lawfully and for providing any notices, signage or consents that local law requires.

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    Disclaimers

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    Changes

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    Questions about these terms can be sent to hello@lenstat.com.

    Security

    Last updated June 2026

    Security by design

    Security and privacy are built into Lenstat from the ground up. The most effective protection for video is not to move it, so our platform analyses footage on site and keeps raw video within your own network.

    Edge processing

    Analysis runs on NPU-powered gateways inside your environment. Only the anonymised findings and metadata you configure are retained, and raw video is not transmitted to or stored by Lenstat.

    Encryption

    Findings and metadata are encrypted in transit using current TLS standards, and at rest where they are stored. Administrative access to our own systems is encrypted end to end.

    Access control

    We apply least-privilege and role-based access, with multi-factor authentication on administrative accounts and audit logging of sensitive actions. Customers manage their own user roles within the platform.

    Deployment options

    Lenstat supports on-premises and fully air-gapped deployments for sensitive and sovereign environments, with network segmentation between gateways, management and any optional cloud services.

    Secure development

    We follow a secure development lifecycle that includes code review, dependency monitoring and testing before release, so security is considered at every stage.

    Monitoring and response

    We maintain logging and monitoring across our own infrastructure and follow a defined incident-response process to investigate and contain issues quickly.

    If you believe you have found a security issue, please contact us at hello@lenstat.com and we will respond promptly.