CCTV Intelligence for Retail

Turn every camera into a business decision.

Drasi reads the footfall, dwell and queues your cameras already see — and turns them into staffing, layout and pricing decisions that grow revenue per square foot. No new hardware.

16
decision playbooks
6
analytics lenses
0
new cameras needed
STORE A · LIVE FLOOR
14:07
FOOTFALL · HR
418 ▲12%
QUEUE · TILL
7 wait 9m
ACTION
Open 2nd counter
Works with existing CCTV / RTSP & ONVIF cameras / Edge or cloud / POS-integrated / DPDP-ready
The platform

Three things your cameras start doing on day one.

Drasi layers computer vision over the feeds you already record. Every frame becomes a count, a dwell time, a queue length — and every metric maps to a decision a store manager can act on.

Count & convert

Footfall by hour, by door, by store — combined with POS bills to expose true conversion. Staff to actual traffic, not guesswork.

Staff rostering Conversion rate Location ROI

Map & merchandise

Zone-level dwell heatmaps show where attention goes — and where it dies. Place product, plan layout and test displays on evidence.

Hot & cold zones Layout flow VM A/B tests

Queue & retain

Live queue length and wait time trigger counter-opening rules — and quantify the revenue you lose every time someone abandons the line.

Queue alerts Counter SOPs Lost-sales recovery
The console

One dashboard for every store, every metric.

app.drasi.fynd.com/insights

Footfall, dwell and queue analytics across the estate — one screen.

Solution index

What the platform helps teams decide.

A quick map of the sections below.

01
Footfall analytics
Staffing, conversion, location
02
Campaign evaluation
Mannequins, signage, offers
03
Zone dwell
Hot zones, dead zones, layout
04
Queue analytics
Counters, wait time, lost sales
05
Exit patterns
Why visitors leave
06
Staff productivity
Coverage, alerts, training
01 — Footfall analytics

Staff to the traffic that actually walks in.

Most rosters are built on gut feel. Drasi maps hour-by-hour footfall against who's on the floor, so you add people where customers are waiting and pull them where the aisles are empty.

Decision made

"From next month, Store A gets 2 extra salespeople from 4–8 PM on Fri–Sun." Lower manpower cost in quiet hours, better service at peak.

Footfall vs staffing — Store A, Friday
Numbers above bars = Drasi-recommended staff
Footfall Rec. staff
{{ bar.staff }}
{{ bar.label }}
PEAK WINDOW
4–7 PM
QUIET WINDOW
11–1 PM
SHIFT
+2 staff to peak, −2 in lull
Conversion diagnosis

One conversion diagnosis meeting.

Footfall, dwell, staff coverage and POS expose whether a store has a traffic problem or a selling problem.

High footfall, low billsFix staff engagement, price clarity or size availability
High dwell, low billingReview trial-room, product pitch and bundle offers
High conversion storeCopy staff script, layout and campaign model
Store location ROI

Evaluate rent, expansion and exit decisions.

Store
Footfall
Rent / visitor
Decision
Mall A
30k
₹26.6
Renegotiate / exit
High-Street B
24k
₹20.8
Benchmark / expand

Mall A sells ₹40L on ₹8L rent; High-Street B sells ₹38L on ₹5L rent. Efficiency decides the location plan.

02 — Campaign evaluation

Know which mannequins, signage and offers actually move customers.

Campaign evaluation is a separate analytics layer in Drasi. It measures how shoppers interact with visual merchandising assets before you connect the impact to traffic, conversion and sales.

Decision made

Keep the window message that increases zone visits. Replace mannequin styling or signage that gets seen but does not create dwell, trials or bills.

CAMPAIGN BOARD · WEEK 32
A/B LIVE
MANNEQUIN + SIGNAGE TRACKING
WINDOW MANNEQUIN
42% stop-rate+11%
OFFER SIGNAGE
18s dwelllow trial
ACTION
Keep visual route, change product styling and price callout.
Campaign impact table

Separate attention from revenue.

Asset
Attention
Conversion
Decision
Mannequin A
High
11%
Scale styling
Sale signage
High
Low
Rewrite offer
Back poster
Low
Medium
Move forward
Problem → solution
New mannequin outfit does not lift dwellChange styling and retest before rollout
Signage is seen but trial stays lowRewrite the offer or put entry products nearby
Campaign lifts visits but conversion dropsChange targeting, creative or entrance display
03 — Zone & dwell analytics

Find the zones that hold attention — and the ones that kill it.

STORE A · DWELL HEATMAP
cold hot
New arrivals FRONT
3.5min
600 visitors · 30% of sales
Premium section LEAK
4.2min
500 visitors · only 8% of sales
Discount section
2.1min
300 visitors · 35% of sales
Accessories COLD
0.7min
100 visitors · 5% of sales
STORE A · FLOOR CAM
70%

of visitors never leave the first 40% of the store. Only 18% reach the back wall — so bestsellers move deep to pull customers through.

The premium leak

Customers spend the longest in premium denim but barely buy. That's not a traffic problem — it's pricing, clarity or staffing.

→ Add price signage, a bundle offer, and a trained associate to the zone.

Heatmaps also rank product placement (sneakers front-left, watches at billing as impulse) and let you A/B test displays store-by-store — merchandising by evidence, not opinion.

Problem → solution
Premium zone gets attention but not sales

Add price signage, bundle offers and a trained associate before discounting the product.

Problem → solution
70% of visitors stay in the front 40%

Move bestsellers or new arrivals deeper and add visibility cues to pull customers through.

Problem → solution
Kidswear or accessories become dead zones

Move the category near family/high-footfall routes or add directional signage.

04 — Queue analytics

Every abandoned queue is revenue walking out the door.

Drasi watches the till line in real time, opens counters before customers give up, and puts a rupee figure on the walkouts you never used to see.

Queue length & wait by hour
RULE · >5 for 3min → open counter
{{ q.people }} · {{ q.wait }}
{{ q.time }}
{{ q.action }}
Lost-sales recovery

~20 customers abandon the queue each day at ₹1,500 average bill. Drasi turns that invisible leak into a number you can act on.

ESTIMATED LOSS · {{ lostSalesPeriodLabel }}
{{ lostSalesValue }}
DECISION
One extra cashier pays for itself many times over.
05 — Exit patterns

Why customers leave without buying.

Different exit signatures need different fixes — so you stop blanket-discounting healthy products.

PatternLikely issueAction
Enters, exits in 2 minPoor first impressionFix entrance display
Visits zone, no trialUnattractive / unclear priceImprove signage
Trial room, then exitsFit / size / productReview inventory
Waits in queue, exitsBilling delayAdd counter / mobile POS
Stands in zone, no staffService gapStaff alert / SOP
06 — Staff productivity

Train the weak stores, reward the right ones.

When two stores see the same traffic and dwell but one converts far worse, the gap is people — not footfall.

Store ALow conv.
FootfallHigh
DwellHigh
ConversionLow
Store BHealthy
FootfallHigh
DwellHigh
ConversionHigh
DECISION

Send the regional trainer to Store A. Copy Store B's sales script and staff-allocation model. Auto-alert when a customer dwells >90s in a premium zone with no associate present.

Six lenses. Sixteen plays. One platform.

Every Drasi metric is wired to a documented decision a store team can run this week.

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{{ l.title }}

{{ l.desc }}

{{ l.plays }}
"We used to roster on instinct and discount whatever wasn't selling. Drasi showed us the premium aisle was a conversion problem, not a traffic problem — we fixed signage and staffing and lifted that zone's sales 31%."
R
Retail Ops Lead
National fashion chain · 40+ stores · illustrative

Start with one store. Scale to the whole estate.

Every edition runs on the cameras you already have.

Starter

Single store, one lens to prove value fast.

Footfall & conversion
Hourly staffing report
POS integration
Zone heatmaps
Multi-site dashboards
Talk to us
POPULAR
Growth

Full analytics for a cluster of stores.

Everything in Starter
Campaign/display analytics
Zone dwell & heatmaps
Queue alerts & SOPs
Exit-pattern analytics
Store-vs-store benchmarks
Book a demo
Enterprise

Estate-wide intelligence with custom SOPs.

Everything in Growth
Staff-productivity analytics
Custom alert rules & API
Rent / location modelling
Dedicated success team
Talk to sales

Frequently asked questions

Do we need to buy new cameras?+
No. Drasi works with the RTSP/ONVIF CCTV you already run. We tap the existing feeds, so there's no rip-and-replace and no new hardware on the wall.
How does Drasi measure conversion?+
We count unique visitors at the door from video and divide bills (from your POS) by that footfall. That separates a traffic problem from a conversion problem — store by store, hour by hour.
Is customer privacy protected?+
Drasi works on anonymised counts and movement — no facial identity is stored to produce footfall, dwell or queue analytics. Processing can run on-prem at the edge, and the platform is built to align with India's DPDP requirements.
How fast can one store go live?+
A single-store Starter pilot typically goes live within days of camera access — fast enough to validate footfall and conversion before you roll out across the estate.

See Drasi read your store.

Book a one-to-one demo customised to your stores. We'll turn one of your camera feeds into footfall, dwell and queue insights — live.

Book a demo → Download one-pager