PolicyBazaar · Media Intelligence Command Center

Media Campaign Overview

Driving reach to policy sale

Plan: ₹150 Cr · TV ₹100 Cr / Digital ₹50 Cr
Data refreshed 14 Jun 2026, 09:12 IST

Net Reach · TG

◎

134M

▲ 64% of 210M TG universe

1+ reachTarget 60%

Incremental Reach /TV

＋

+38%

▲ 36.4M cord-cutters added

OTT + YouTube de-dupvs TV-only

GRP / SOV

▦

1,240GRP

▲ 31% category SOV

TV target-GRPsP1 markets

Traffic & Leads

⤓

33.0M

▲ 8.6M leads · +27% YoY

sessions → enquiriesGoal +30%

Conversions (Attributed)

⟿

0.61M

▲ 34% brand-attributed

policies issuedMMM + view-through

The Media Waterfall

FY 26–27 YTD · all channels de-duplicated

0.025%Impression → policy

3.6%Reach → enquiry

7.1%Lead → policy

₹2,459Blended cost / policy

Read left→right: paid impressions compress into reach, into site/app sessions, into raw enquiries, into agent-qualified leads, into issued policies. Stage conversion % shown at right.

Budget Distribution

Annual

₹150 Cr · FY 26–27

Spend pacing vs flight plan

₹ Cr / month

₹150 CrPlanned

₹71 CrSpent YTD

98%On pace

Brand lift study — pre vs post

Δ points

Health signals

vs target

Lead growth → +30% goal91%

Net reach → 60% goal107%

High-income reach → 55%87%

Video VTR → 65%109%

!

Pacing flag: Term lead growth (+19%) trails Health (+34%). Re-weight ₹4–6 Cr of Q3 OTT toward Term-intent cohorts.

Illustrative dataset modelled on the PolicyBazaar brand media brief (May 2026) for pitch demonstration. Figures are simulated to show the measurement architecture, not actuals.

Brand Health · Upper Funnel

Brand Metrics

Currency: Net Reach (000s) · TG M 26–48 Urban
Source: BARC + OTT log-level + panel fusion

1+ Net Reach

64%

▲ vs 58% TV-only

134M of TG

Avg Frequency

4.3x

● optimal band 3–5

3+ reach: 71% of reached

Video VTR

71%

▲ +6pts vs benchmark

completed views / starts

High-Income Reach

48%

▲ NCCS A / ₹15L+ HHI

fixed-impression buys

Reach & frequency build curve

TV + Digital · gap vs TV = incremental

Cumulative 1+ net reach as GRPs / impressions accumulate across the flight. Switch the media source in the top bar; the gap between TV+Digital and TV-only is the incremental reach digital unlocks — the brief's primary KPI.

Frequency distribution

% of reached TG

◎

22% of reached audience sits at 1–2 exposures — a re-targetable shoulder for OTT/YouTube top-ups without inflating TV.

Incremental reach by channel

over TV baseline

High-income reach delivery

NCCS A · ₹15L+ HHI

48%of target

28.4MHigh-income TG reached

₹248Cost per high-income reach point

1.7×Index vs all-audience CPRP

Brand trust & consideration tracker

wave-on-wave

34 → 46Consideration · +12 pts

41 → 49Trust · +8 pts

Channel scorecard — brand layer

fixed-impression / non-biddable inventory

TV delivery is shown in GRPs (not impressions) with the on-air ACD mix; digital in impressions. CPRP = cost per rating point equiv. (digital normalised to TV target-GRP). VTR = video through rate. ¹ For linear TV there is no VTR — the figure shown is spot-completion as a proxy. Incremental reach is measured via cross-media de-duplication against the TV panel.

Television · GRP & Reach Deep-Dive

TV delivery — GRP, SOV, reach & CPRP

Currency: BARC · TG M 26–48 Urban
Daypart: predominantly Prime Time

Total GRPs

1,240

▲ vs 1,150 planned

target-GRPs · TG

Category SOV (GRP)

31%

▲ leads category

share of category GRPs

Reach 1+ / 3+

64% / 42%

▲ 3+ above 40% threshold

net of TV panel

CPRP · actual

₹172

▼ vs ₹185 planned

cost / rating point

CPRP — planned vs actual

₹ per rating point · by market

GRP split by genre

GEC · News · Sports · Movies · Regional

Market-wise GRP & reach delivery

Urban · BARC · Target'000 / GRP / Cov'000 / OTS / 1+ / 3+ / 5+

Target'000 = TG universe in thousands · GRP = gross rating points delivered · Cov'000 = covered (reached) audience in thousands · OTS = opportunities to see (avg frequency) · 1+/3+/5+ = % of TG reached at that frequency. Mirrors the BARC market-delivery export.

GRP by genre & channel — HSM

channel-level delivery

Genre contribution

HSM · share of GRP

GEC carries the bulk of HSM weight; News adds frequency at low CPRP; HD genres extend high-income reach.

Performance · Lower Funnel

From Impression to Conversion

Tracking the entire funnel beyond GRP & CPL.

Window: FY 26–27 YTD
Lead = high-intent enquiry · Policy = issued

Clicks

41.2M

▲ 16% YoY

Sessions

33.0M

▲ 80% click→session

CTL · Click→Lead

20.9%

▲ +1.4pp

Lead → Conversion

7.1%

▲ +0.6pp

Channel efficiency matrix

bubble = lead volume

X = cost per lead, Y = lead→policy conversion. Top-left is the sweet spot: cheap leads that convert. Bubble size = lead share.

Performance funnel

all paid digital

Leads by category

Health · Term · Motor · Investments

Spends by category

₹ Cr · paid digital

Cost-per-lead trend

₹ · rolling monthly

Channel performance scorecard

click → verified-lead economics

CTL = click→lead rate · CPL = cost per raw lead · CVR = lead→conversion · Verified Leads = leads validated by the call-centre (contactable + genuine intent) · CP Verified Lead = cost per verified lead. Only lead-driving channels shown; OTT & CTV sit in the Brand Health view as upper-funnel reach media.

Lead Lifecycle · Non-Converted

Where leads sit & drop off — the full pipeline

Not every lead converts the same day. This is the complete post-lead funnel: how many are in pipeline, where they drop off, how many await a call-centre callback, and how many are stuck at payment — split by product.

Snapshot: 8.6M leads YTD
0.61M converted · 8.0M in lifecycle

In Pipeline (open)

2.94M

● 34% of leads active

Awaiting Callback

1.12M

● agent queue

Payment Pending

0.38M

▲ recoverable revenue

Dropped / Lost

4.55M

▼ 53% leakage

Post-lead stage funnel

where the 8.6M leads are now

Each step shows how many leads remain; the % at right is the share retained from the previous stage. The gaps are the drop-off points to attack — biggest leakage is contact→quote.

Drop-off by stage

% of leads lost at each step

Pipeline by product

leads · stage split · per category

Stage definitions — Contacted: call-centre reached the lead · Quote shared: a comparison/quote was delivered · Callback: lead asked to be re-contacted (in agent queue) · Payment pending: chose a plan, payment not completed · Converted: policy issued · Dropped: unreachable / not interested / lapsed.

Markets & Category

Market Performance

P1/P2 state delivery with Tamil Nadu broken out — the brief's regional-affinity priority, anchored by a TN-specific celebrity and a ₹2–5 Cr flight. Reach, leads and efficiency, market by market.

Priority: P1 HSM·AP+TL·Kar·TN·Ker·WB·Mah · P2 Odisha·Pun·Guj

State delivery scorecard

urban · TG net reach & leads

Reach %low → high

Leads per market

urban · YTD

Where the leads are actually coming from across priority markets — the demand counterpart to the reach scorecard on the left.

3.1MHSM — top market

78%P1 share of leads

₹262Lowest CPL (HSM)

Lead share by priority tier

P1 vs P2

Category mix by region

North vs South

Language-creative VTR

10 TVC languages

Intelligence · Signature View

Attribution of brand on performance

The hardest question in the brief, answered: how much of the lead & policy outcome is caused by upper-funnel brand. A marketing-mix model plus view-through and branded-search uplift, in one flow.

Model: Bayesian MMM + multi-touch
Confidence 86% · 18-mo training window

The halo, traced

contribution-weighted flow · brand → outcome

Upper funnel · brand

Mid funnel · demand signal

Outcome · 0.61M policies

34%Brand-driven policies

+41%Branded-search uplift in flight

0.18MView-through conversions

2.9×Brand-assisted ROI multiple

MMM contribution decomposition

of total policies

Branded search lift during flights

indexed search demand

Diminishing returns by channel

marginal CPL response

Attribution model comparison

How credit shifts by model. Last-touch starves brand; MMM & data-driven recover its true contribution — the argument for funding the upper funnel.

Brand → lead lag & carryover

adstock decay

Brand exposure keeps producing leads after the spend stops. ~3.2 week half-life means TV/OTT bursts should lead category-buy moments.

⟿

Planning rule: front-load brand 2–3 weeks before performance pushes; ~38% of a burst's lead impact lands in the following fortnight.

Competitive Intelligence

Share of voice & spend tracking

The brief's strategic question: how to track competitive digital spend in chosen markets. Estimated SOV against insurers and aggregators, with a spend index and SOV-vs-SOM gap.

Source: est. via impression scraping + ad-library + panel
Refreshed weekly

Share of voice — category

est. paid impressions, all media

SOV vs SOM gap

excess share of voice

Brands above the line are "investing to grow" (SOV > market share). PolicyBazaar's positive eSOV supports share gains.

Spend index trend

indexed to Jan = 100

SOV by priority market

PolicyBazaar share %

Competitive spend tracker

est. monthly · digital + TV

eSOV = SOV minus market share. Estimates blend ad-library scraping, impression-share modelling and TV monitoring; treat as directional, not audited spend.