Product Strategy

Pre-Dispatch Serviceability:
Solving Wiom's Trust Gap

Customers are told we can install, but technicians arrive to find locations unserviceable — wasting capacity and breaking trust.

Data window: Feb 25 – Mar 27, 2026 | Source: Snowflake prod_db | 2,766 paid bookings analyzed

37%
Booking-to-install rate
Only 1 in 3 bookings converts to install
594
Location-related declines
In 30-day window
776
"Can't understand address" events
Proxy for infra gap
27%
Declined then installed by another
Wrong partner, not wrong address
Current State

The 10-Step Booking Flow

Problems are baked into the sequence. Money is collected before address validation, and partners cannot verify coverage before assignment.

The Core Problem

The current flow collects payment at step 4 but doesn't validate the actual address and partner coverage until step 10. By then, we've made a promise we may not be able to keep. The customer has paid, expects installation, and the partner discovers the location is outside their network.

Analysis

Root Cause Analysis

Four root causes identified from data

1

Critical Reframe: The Problem is Bigger Than Wasted Visits

The original problem: "technicians arrive to find locations unserviceable." Data shows that's only 15% of the story.

524
pre-assignment declines
(85% of location failures)

Partner reads address, rejects on paper before anyone dispatched. Shows up as "delay in installation" to customer.

89
post-assignment declines
(15% of location failures)

Rohit dispatched then declined. Wasted tech visit. Of these, 57 (22%) later installed by another partner.

Key Finding

The matching logic itself needs overhaul, not just a pre-dispatch gate. 85% of failures are caught before dispatch — but only because partners reject bookings Genie shouldn't have sent them.

2

Multiple Location Sources Drive Booking Leakage

GPS disagreement predicts overall cancel rates (39% → 72%) but does NOT predict address-specific declines — those are flat at ~16% regardless.

Source Disagreement vs Install Rate

Source Disagreement vs Address Decline

Source disagreementCancel Rate
Exact match2.8% cancel
<50m41.0% cancel
50-200m44.7% cancel
200m-3km55.0% cancel

Worst case: GPS #1 shows Delhi, GPS #2 shows Bihar (864km), chat address says "Block D, New Ashok Nagar, Delhi" — three sources, three different stories, no reconciliation

3

Partners Have Little Buy-In to the Matching Process

Even with address and lat/long, partners rely on phone calls to confirm location. They haven't understood the effort Wiom takes to match — and have no stake in making it work.

29.6%
of partner-customer calls discuss location
594
unique bookings declined for location reasons

Call Transcript Evidence

CABLE DOESN'T REACH

"Sorry sir, us side hamari line nahi hai"

— Cable doesn't go there

INFRA GAP

"वहां तो भाई लग नहीं पाएगा हमारा"

— Understood address perfectly, infra gap

GATED SOCIETY

"society में permission नहीं होती है"

— Gated society restriction

Key Finding

Address quality is IDENTICAL for declined vs installed. Avg length 51 chars vs 50 chars. Partners use "can't understand address" as proxy for "my cable doesn't reach."

4

Genie Routing

Genie finds the right AREA — but sends to the wrong PARTNER.

Distance from Nearest Base Point vs Install Rate

Genie Doesn't Learn From Mistakes

Partner A declined → Partner B installedTimes in 30 days
Bharat Broadband → Bhatia Cable TV3 times
M R NETWORKS → Bottam Cable TV3 times
TECHFIBER → Umang Cable TV3 times

22 partner-cell combos had the same partner decline 2+ bookings in the same ~100m area. 136 total reroutes where A declined and B installed — none fed back into routing.

84% of bookings are within 25m of a known base point — Genie finds the right AREA. But 8.8% still get partner decline because it sends to the wrong PARTNER. Dense multi-partner areas have the highest decline rate (9.3%).

Design Principles

Design Objectives

🤝

Commitment Integrity

Once we accept a booking, we MUST install. No false promises — payment only after partner confirms serviceability.

🗺️

Visual Proof

Partner sees their own customers on a map around the booking. Data they can't ignore — not just a text address.

🔄

Learning Loops

Every install expands green zones. Every decline sharpens boundaries. Every reroute fixes partner routing. The system gets smarter with each booking.

👥

Partner as Co-Owner

Partners are stakeholders in zone accuracy — bigger green zone = more guaranteed leads. Decline in committed zone = financial recovery. Good behavior rewarded, bad behavior self-corrects.

Solution

Green / Amber / Red Zone Framework

Don't take money until serviceability is confirmed by the partner. Three zones, built from data, confirmed by partners, honest to customers.

Green Zone

70% of bookings

5+ customers in ~100m cell from ANY partner combination. Area is proven serviceable. Best-performing partner gets priority with fair rotation.

Customer pays immediately — area is proven

Routed to best scorer, rotation for fairness

No monopoly — partners compete on performance

Amber Zone

21% of bookings

1-4 customers in cell — some evidence but not proven. Broadcast to partners. Partner confirms → then payment taken.

Payment ONLY after partner confirms

2-hour SLA for partner response

No confirm = "Not available yet"

Red Zone

10% of bookings

No customer data in area. Customer told honestly. No false promise, no payment.

No payment taken, no false promise

Customer notified when area expands

Never routed until partner expands

⚡ Built-in Incentive Alignment

The zone system naturally rewards good partners and sidelines bad ones — no manual intervention needed.

Good Partner

Installs consistently → green zone grows → more auto-confirmed leads, guaranteed revenue

Inconsistent Partner

Frequent declines → green zone stays small → only amber broadcasts, must compete for each lead

Bad Actor

Declines in committed zone → zone shrinks + financial recovery → fewer leads, trust score drops

Validation

Green Zone Validation — Using Real Data

We tested different green zone definitions against actual booking outcomes.

Green Zone Definition Coverage Install Rate Addr Decline
GREEN: 5+ customers (area-level) 70% 44.1% install 22.2% decline
— Single-partner cells within green 14% 35.3% install 7.4% decline
— Multi-partner cells within green 55% 46.3% install 25.9% decline

Key Finding

Area-level green (5+ customers) gives 70% coverage with 44.1% install rate. Within green, multi-partner cells install MORE (46.3%) but waste 3.5x the effort on address declines (25.9% vs 7.4%) — proving the problem is routing, not area coverage. Layer 2 (performance-based routing) eliminates this wasted effort without creating monopolies.

1
Customer App

Honest Serviceability Before Payment

Customer gives location, we check with real partner data, and tell the truth. Payment only when a partner is committed.

9:41📶 🔋
🏠

Internet kahan chahiye?

Apna address search karein...

Map View

Apna ghar ka address search karein

9:41📶 🔋
📍

B-42, Sector 15, Noida, UP 201301

3rd floor, Flat 302
Red gate ke paas

🏠 Sahi location dena zaroori hai — hum isi location pe partner check karenge

9:41📶 🔋

Aapke area mein available hai! 🎉

🤝

Partner: Sharma Cable Network

Install within 2 days

Payment sirf confirmed booking ke liye

AMBER result

Hum local partner se confirm kar rahe hain...

Aapko 2 ghante mein pata chalega

Koi payment abhi nahi lagega

Agar partner confirm kare → hum aapko notify karenge

RED result

Abhi aapke area mein available nahi hai

Jaise hi expand karein, aapko notify karenge

Notify me

Koi payment nahi liya gaya

9:41📶 🔋

Hum local partner se confirm kar rahe hain...

Aapko 2 ghante mein pata chalega

Partner ko check karne mein thoda waqt lagega

Koi payment abhi nahi lagega

🔔

Agar partner confirm kare → hum aapko notify karenge aur tab payment hoga

Agar koi partner confirm nahi karta → hum aapko bata denge "abhi available nahi hai"

2
Partner App

Data-Built Zones, Partner Confirmed

Green zones auto-created from install history. Amber bookings broadcast for confirmation. No partner drawing polygons — just confirming what data already shows.

9:41📶 🔋
Partner App
Aapka service area
Suggested zone
Aapke customers

Wiom ne aapke install data se yeh area suggest kiya hai

⚠️

Is zone mein aap decline nahi kar sakte. Booking aate hi install karna hoga.

47

installs

0

declines

9:41📶 🔋
Partner App
New booking request
🟡 CONFIRM REQUIRED
Customer
Aapke customer

Priya Singh

H-12, Block C, Mayur Vihar

Aapka 1 customer 200m mein hai

Kya reason hai?

🛑Last DP se aage hai
🔄Doosre partner ka area
🏢Gated / restricted area
⚠️Infra nahi hai

Customer ko abhi payment nahi liya gaya hai. Aapke confirm karne ke baad hi booking hogi.

9:41📶 🔋
Partner App
New booking — auto-assigned
🟢 YOUR CORE ZONE
Core zone
Naya customer
Aapke customers

100m mein aapke 8 customer hain

Rajesh Kumar

3rd Floor, B-42, Sector 15, Noida

🔒

Yeh aapke core zone mein hai. Decline available nahi hai.

3
Self-Learning

Every Interaction Trains the Map

Green zones grow organically from partner behavior, not declarations. Every install and every decline reshapes the coverage map.

Install → Green zone grows

Every install adds a confirmed point. Amber cells near it graduate to green.

Partner passes in amber → Boundary learned

Decline + structured reason = that cell is marked for THIS partner. Other partners still get it.

🔄

Declined by A, installed by B → Auto-reroute

Next time a booking hits this cell, Partner B gets priority. Partner A doesn't see it.

🚫

3 partners decline same cell → Red zone

No partner can service here. Customer told "not available" upfront. No wasted time.

Projected Outcomes

Expected Impact

Conservative targets based on root cause analysis. These numbers compound as the self-learning model matures.

Metric Today After
False promise (paid but can't install)~46% of bookings0% by design
Booking → Install rate37%70%+ (confirmed only)
Wasted tech visits (post-assign decline)89 in 30 days< 10
Booking cycling (pre-assign decline)524 in 30 daysEliminated
Time to first installDays of cyclingGreen: instant. Amber: 2hr max.
Partner trust score accuracyNoneAuto-built from 262K installs + 136 reroute signals
W
Wiom

Pre-Dispatch Serviceability — Product Strategy Document

March 2026

Alternate Solution

"Ghar ka Internet" — Let Physics Do the Matching

What if we could eliminate partner matching entirely and turn every Wiom router into both a serviceability proof AND a zero-cost acquisition channel?

?

The Question That Changes Everything

Today we ask: "Which partner should we send this booking to?" — and the partner says no 26% of the time.

The right question is: "How do we KNOW — with certainty — that Partner X's cable reaches Building Y, without asking Partner X?"

Every solution that still involves asking the partner is just a fancier way of asking. What if you never need to ask?

📡

Part 1: WiFi Signal = Cable Reach Proof

262K routers are already proving serviceability 24/7

Every Wiom netbox broadcasts a "Wiom Net" SSID. That's 262K routers constantly proving where cable infrastructure exists. Each router belongs to a specific partner. If a new customer's phone detects the signal — the cable is physically there.

Step 1

Customer opens app at home. App scans WiFi in background.

Step 2

Detects "Wiom_Net_XXXX" nearby. That router = Partner A, installed 30m away.

Step 3

Cable physically exists. Auto-assign Partner A. No GPS, no address, no partner call needed.

Why it kills every RCA

RCA1: No decline possible — cable proven. RCA2: GPS/address irrelevant. RCA3: Partner doesn't need to confirm. RCA4: No Genie routing — physics routes.

Self-learning built in

Every new install = new broadcasting router = bigger signal footprint. Coverage grows automatically. Partner's own hardware defines their territory.

🏠

Part 2: "Ghar ka Internet" — Same Signal, Free Acquisition Channel

Turn every router into a zero-cost billboard that only targets serviceable addresses

What if the WiFi signal doesn't just verify serviceability — it generates demand? Rename the public SSID to "Ghar ka Internet". Every non-Wiom person in range sees it on their phone. They tap to connect. Captive portal opens.

📱

Person sees WiFi

"Ghar ka Internet" appears on their phone at home

👆

Taps to connect

Captive portal: "Unlimited home WiFi from Rs500/month"

📝

Drops their info

Name, phone, flat number. Gets 15 min free WiFi as reward.

Pre-qualified lead

Within signal range = 100% serviceable. Partner already known.

Zero CAC

No ads, no pamphlets, no door-knocking. 262K routers already broadcasting 24/7. Every router is a billboard that costs nothing extra.

100% Serviceable Leads

If they can see the signal, cable reaches them. No serviceability check. No partner confirmation. No decline. Book and install.

Self-Reinforcing Loop

Every new customer adds a new "Ghar ka Internet" signal. More installs = more signals = more leads = more installs. Compounding growth.

The math: 262K routers x ~20 neighbors in signal range = 5M+ impressions/day at Rs0 CAC

Even a 0.1% conversion = 5,000 pre-qualified leads/day. Each one guaranteed serviceable, partner pre-matched, zero matching friction.

Why This Is Fundamentally Different

Zone Framework (Primary Solution)

Classifies areas, gates payment, routes to best partner. Still relies on historical data + partner confirmation for amber zones. Incremental improvement on existing flow.

"Ghar ka Internet" (Alternate)

Eliminates matching entirely. Physics proves serviceability. Same signal generates demand. No GPS, no address, no Genie, no partner call. The infrastructure IS the product AND the marketing.

Exploration

More Ideas Worth Exploring

Additional approaches that use community, economics, and visual proof to solve matching from different angles.

🏘️

Padosi Guarantee

Ask the nearest existing Wiom customer: "Aapke padosi ko Wiom chahiye. Kya aapke partner ki cable unke building tak pahunchti hai?" Neighbor gets Rs50 credit on install.

Ground truth 2 min response Referral flywheel
💰

Partner Commitment Auction

Broadcast booking to nearby partners: "Deposit Rs200 to claim. Install in 48h or lose it." Only confident partners bid. Market reveals truth. Repeat decliners self-eliminate.

Skin in the game Self-selecting Incentive flip
📹

2-Minute Video Recce

Customer sends 30-sec video of their building/gali. Partner watches, recognizes the area, confirms or declines — BEFORE payment, BEFORE dispatch. Kills 776 "can't understand address" events.

Visual proof Zero dispatch waste WhatsApp-simple
🗺️

Cable Trace Mapping

Rohit walks his cable route with GPS on. 2 hours per partner, one-time. Creates true cable-path graph. Match by "can cable reach this building?" not "is this building CLOSE to a point?"

One-time effort Permanent fix Physical truth
🔄

Reverse the Flow

Partner publishes capacity: "I can add 5 customers on Gali X this week." Customer sees "instant install available." Like Swiggy Instamart — supply before demand. Zero declines.

Pre-committed Zero matching Real-time
🏃

Customer Scout Network

Pay nearby customer Rs100 to walk to new customer's building and check cable visibility. Costs Rs8,900 vs Rs26,700 in wasted Rohit visits. 262K scouts on every gali.

3x cheaper 10 min check Community-powered
Common thread: stop asking the partner. Use physics, neighbors, economics, and video to KNOW before committing.