For mall operators · Live at 10 M3M properties

The intelligence layer your mall is missing.

Eva, LFI, MagicQR, ParkAI and Events — one deployed stack that turns the shopper conversation happening inside your building into intelligence you own. Not another point tool, not another vendor. Infrastructure.

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Deployed at:
01The outcome, first

2,300 shopper questions a week at M3M 65th Avenue — and every one becomes intelligence you own.

M3M 65th Avenue — Weekly Report

Week 34 · Aug 18–24, 2026
Auto-delivered every Monday
2,314+8%
Eva queries
847
Unique shoppers
1,092
New reviews via MagicQR
96%
Parking utilisation
Top 5 query topics this week
01Store hours & late-night dining421
02Parking & valet358
03Kids play area / entertainment276
04Weekend events & offers219
05Specific store locations187

Not a dashboard nobody opens. A concise weekly report delivered to your inbox — with the questions your shoppers actually asked, sorted by topic, ready to shape next week's operational and marketing decisions.

02The stack

Six products. One connected system.

Deploy the full stack or start with one. Every module feeds intelligence back to the operator layer — no point-tool disconnects.

Flagship
Eva
AI concierge per property
The shopper-facing concierge deployed at 10 M3M malls. Answers store hours, parking, offers, events. Every query becomes intelligence.
Diagnostic
LFI
Local Footfall Index
Zone-level shopper intelligence — benchmark your mall against category and location peers. Free baseline available.
Reviews
MagicQR
GBP & review generation
QR-based review capture for the mall and every tenant. Managed Google Business Profile updates included.
Parking
ParkAI
Parking & valet intelligence
Real-time utilisation, valet integration, shopper-facing parking help through Eva. Step by step navigation from Parking slot to store.
Media
DSR/ADSR
(Automated) Daily Sales Reporting
Manual, end of day reconcilation or real time integrated sales reporting for revenue share.
Activations
Events
Calendar + BTL activations
Mall event calendar, vendor stall management, and BTL activation coordination — surfaced to shoppers via Eva. Co-ordinated activation across brands for better sales and reach.
SOH Inventory Multiplier
QR SOH
SOH + Ad Revenue
Programmatic SOH for mall surfaces, every parking QR or user assistance QR is a dyanmic SoH for context aware advertising, surfacing the most relevant ads for the shopper.
03Case study

What running the full stack looks like.

Anchor deployment
M3M 65th Avenue
LocationSector 65, Gurugram
DeployedSince 2025
Stack liveEva · LFI · MagicQR · ParkAI
Shoppers/wk~850 unique
Queries/wk~2,300

One of 10 M3M properties running the RetailOne stack.

The problem

A category-defining mall with strong tenant mix, but the shopper journey was fragmented — offers on Instagram, hours on Google Maps, parking on WhatsApp groups, events on posters. No single source of truth for the shopper standing inside the building. And no way for the operator to know what shoppers were actually looking for.

The stack we deployed

  • Eva at every entrance and shared touchpoint, trained on the tenant directory, hours, and event calendar
  • LFI Local Footfall Index a quantiative measure of your mall's visibiliity for shoppers and the revenue loss due to digital reputation of the mall and every brand in the mall.
  • MagicQR for the mall's own GBP + review generation across selected tenants
  • ParkAI with valet handoff integration
  • Weekly report delivered every Monday morning to the mall's marketing and ops leads

Outcomes

  • ~2,300 shopper queries handled by Eva every week, growing month-on-month
  • Marketing team now shapes weekly comms around actual top query topics — not guesses
  • Ops team surfaced 2 tenant hours-mismatches in the first month (Eva answers exposed them)
  • Parking basement utilisation visibility, previously guessed at, now measured live
04Deployment

From kickoff to weekly reports in 4–6 weeks.

We do the setup, integration and training. Your team gets the outputs.

Week 1
Kickoff + LFI baseline
Property walk, tenant list, zone mapping. LFI baseline established as your before-state benchmark.
Week 2–3
Eva training
Eva ingests the directory, hours, policies, events. Test queries validated with your team.
Week 4
Soft launch
Eva goes live at chosen touchpoints. MagicQR deployed at counter locations. ParkAI integrated with valet.
Week 5–6
Weekly reports live
First weekly report delivered. Review cadence set. Team trained to shape decisions off the intelligence.
05Honest

Why not build this in-house?

You can. It'll take 18–24 months, a team of 4–6 engineers, and constant maintenance to keep it accurate. Here's the actual math.

Where in-house makes sense

Very large groups (25+ properties) with existing tech capacity can eventually justify it. For anyone smaller, or anyone who wants results this quarter, the math doesn't work.

  • ✓
    What we bring
    A production-grade AI stack already trained on Indian retail context, deployed at 10 malls, with 2,300 queries/week of real signal already tuning it.
  • ✓
    Speed to value
    4–6 weeks to weekly reports. In-house effort is 18–24 months minimum, with the first 12 spent on infrastructure that isn't the point.
  • –
    What we don't do
    We're not a CRM, or a lease-management tool. If that's your priority, this isn't it. We do the shopper-intelligence layer only.
  • –
    Where in-house wins
    If your group has deep tech capacity, 25+ properties to spread cost across, and a 24-month horizon and in-house technology development team of 10 - 12 full time engineers - build your own.
06Pricing

Priced per property. Scales with mall size.

LFI baseline is free. Start there — see your mall's local footfall index and the footfall and revenue you are leaking which this system can help you recoved before you commit to anything else.

Full stack pricing is bespoke per property. Depends on mall size, tenant count, and modules deployed. Typical monthly cost for a mid-size mall running the full stack falls in the range of a single senior in-house hire — with none of the ramp time.

LFI baseline · FreeEva · From ₹X/property/monthFull stack · Bespoke
💬 Book a demo on WhatsApp →
07Book a demo

45 minutes. Your mall's first LFI baseline included.

Bring your marketing and ops leads. We'll walk you through Eva at M3M 65th Avenue live, show you the weekly report format, and pull a first-cut LFI baseline for your property before you leave.

💬 Request a demo slot on WhatsApp →

Or email customer_support@idigizen.com