Industries · LUMEN

The till counts what sold. Nobody counts who came in.

Your existing cameras plug into your till: who walked in, how many bought, how many left empty-handed.

Eleven trades · shop floors, service floors and front desks

  • Your existing IP cameras
  • Alongside the till and 1C
  • Server in your building
  • Free 3-day pilot
10
modules on one core
8
retail trades
3
days to go live
One on-premise corePick a module03/10
03Customer Journey

Every shopper's path becomes a conversion funnel you can act on.

Primary inRetail & SupermarketsPharmacies & DrugstoresShopping Malls & CentresAuto & DealershipsTransport & AirportsHealthcare & Clinics+$4.4K/mo from one layout changeModel

All ten on one core, one panel, one contract.

Monday meeting

Every one of these is a guess.

When takings fall, these are the sentences said on the floor. Not one of them has been checked — because nobody counted the door.

  • 01«There were fewer people this week.»Guess
  • 02«The campaign did not work.»Guess
  • 03«It was the weather.»Guess
  • 04«A new shop opened nearby and took our customers.»Guess
  • 05«The cashiers were slow.»Guess
  • 06«Our prices looked high.»Guess

Until somebody counts the door, all of them weigh the same. After it is counted, one of them is left.

One revenue, two truths

A busy day is not a good day.

Both branches bank the same money. The till calls both of them normal. With the cameras the difference shows: in one of them every third guest walked out with nothing.

Revenue for the month$372Kidentical in both branches
  • Branch A26 04015 96042 00038%empty-handed
  • Branch B26 0404 96031 00016%empty-handed
  • Buyers
  • Left without buying
  • Both rows on one scale

ModelThe figures are modelled — with your own numbers the arithmetic changes. The point is not the figure: the same revenue can hide two different floors.

The result

How much the conversion moves.

The model promises no uniform lift. The leading branch stays where it is — the gain comes from pulling the weaker branches up to it. So the network average rises, not the record.

Before LUMENAfter three months
  • Chilonzorthe leader — unchanged73%73%0 pp
  • Yunusobod70%72%+2 pp
  • Sergeli68%71%+3 pp
Network average70.3% 72.0%
  • Month 170.8%
  • Month 271.4%
  • Month 372.0%

ModelThe branch figures come from the same table the LUMEN product page uses. The gain is spread over three months: 30% in the first, 65% in the second, in full by the third.

Where the money stays

Four places the till cannot see.

All four are one day of real data — the console draws these four panels every day.

Your busiest hour is your worst hour.

The evening peak brings the most people in and sells to the fewest. The roster was not written for that hour.

910111213141516171819202122
  • Visits
  • Conversion
  • 19:00 — peak · 54.0%

ModelThe panels are built on one day of the demo store. On your own floor each of them fills with what your cameras counted.

The network

Every branch on one line.

Ranked not by takings but by how many people leave empty-handed each day. The worst percentage and the biggest loss of customers are two different branches.

BranchVisitsConversionEmpty-handed — people/day
01Chilonzor1,28467%42433%
02Sergeli83661%32639%
03Yunusobod1,10271%32029%
04Mirzo Ulugbek94869%29431%
05Olmazor74066%25234%

ModelThe branch with the most visitors loses the most customers. On the monthly report it is the one in first place.

Your trade

Eight trades — each loses money differently.

LUMEN runs on a floor a shopper walks. Pick your trade: which modules are primary, where the money goes and what gets measured.

Retail & Supermarkets10/10 modules
  • Customer Recognitionprimary
  • Store Heatmapprimary
  • Customer Journeyprimary
  • Employee KPIprimary
  • AI Predictionprimary
  • Smart Checkoutprimary
  • Demographicsprimary
  • Customer Segmentsprimary
  • Service & CXprimary
  • Loyalty & LTVprimary
Where the money goesWhat closes itWhat gets measured
01The visitor never becomes a buyer — and which aisle broke it is unknown.Customer JourneyStore HeatmapDoor-to-till conversion, by zone
02A queue at the evening peak — baskets get abandoned.Smart CheckoutAI PredictionWait time and abandoned baskets
03A regular leaves quietly — you find out a month later.Loyalty & LTVCustomer SegmentsReturn rate and churn risk

8 trades — one core, one panel, one contract.

Your own numbers

One point of conversion, in money.

Not a promise — a unit: what one point of conversion is worth on your own figures. The arithmetic stays on screen, so you can check it.

The arithmetic
  • Visitors a month126,000
  • +1 point = extra buyers1,260 people
  • Extra revenue$18K
  • Profit — at a 22% margin$4K
Extra profit a month$4K a monthPlatform cost−$1.8KNet result+$2.2K

One point covers what the platform costs.

ModelThe margin and the platform cost are the same ones the model on the LUMEN page uses. The result is not a promise — it is arithmetic over what you typed.

Implementation Plan

Live in three days. One workshop of yours.

Every day in two lines: what that day takes from you, and what you hold by the end of it.

  • 3 daysfrom audit to live
  • 1manager workshop — your time
  • 0new cameras — yours are used
  1. Day 1

    Audit and install

    From you
    Access to cameras and network
    You have
    A camera-coverage map and your GPU server in place
  2. Day 2

    Integrate and tune

    From you
    Nothing
    You have
    Existing cameras connected, POS / 1C in sync, models tuned to your store
  3. Day 3

    Train and go live

    From you
    A manager workshop
    You have
    Dashboards per role and pilot sign-off. From that day, in production.
After go-live
  • 24/7 monitoring from Tashkent
  • A weekly success manager
  • A report every morning at 09:00

Check it against your own count.

One branch, three days, your own cameras. If it does not hold, the pilot is off.

  • 1location — for the pilot
  • 3days — audit to live
  • 0new cameras — yours will do
  • The report stays with you — whether to continue is your call.