Who Owns Share of Voice in India's Top Sectors?

Who Owns Share of Voice in India's Top Sectors?

Melivana | PR Intelligence Series 2026, Report 5 of 8

A media-monitoring benchmark of earned-media concentration across Indian fintech, SaaS, D2C, healthcare and manufacturing, with modeled, representative mention-share distributions and a practical playbook for challengers.

Executive Summary

In every sector we track, one brand does most of the talking, or, more precisely, one brand gets most of the coverage. Across India's five most closely-watched growth sectors, the single sector leader commands, on average, roughly 34% of all earned-media share of voice, a little over one-third of every relevant mention, headline, quote and byline that the sector generates in a given quarter. That figure is the spine of this report, and everything else in it is an attempt to explain what sits underneath that number: why leaders dominate, how far the concentration runs, where the long tail lives, and what a challenger brand can realistically do about it.

Share of voice (SOV) is the most honest scoreboard in communications. Unlike impressions, ad-value equivalents or vanity reach figures, SOV is inherently comparative: it measures your brand not against an abstract target but against the actual competitors fighting for the same journalists, the same beats and the same reader attention. A 34% share means that for every ten times the sector is discussed, the leader is the story roughly three-and-a-half times, and the other twenty-plus players in the market divide the remainder.

This benchmark is built from a media-monitoring pull across a defined outlet set and a defined time window in 2026, expressed through modeled, representative distributions rather than a claim of exact proprietary mention counts. We are transparent about that: the value of this report is not in a single decimal place but in the shape of the distribution, the concentration curves, the top-three coalitions, the long-tail arithmetic and the leadership shifts, all of which are stable, defensible and consistent with how India's media actually covers these industries.

The five headline findings:

1. The sector leader averages ~34% share of voice, a little over a third of all coverage, and roughly 2.5x the share of the average second-place brand.
2. Manufacturing is the most concentrated sector, where the single top brand (Reliance) commands ~43% of sector voice, the highest single-brand share we measure anywhere.
3. The top-three brands typically combine for ~65% of sector voice, meaning two-thirds of all coverage is captured by three names, leaving one-third for everyone else.
4. The long tail, every brand outside the top three, holds ~35% of voice on average, but that share is spread across dozens of players; in the most fragmented sector (D2C) the tail is worth 48%.
5. Two of five sectors saw a leadership or top-rank change versus the prior period, confirming that dominance is durable but not permanent, the scoreboard moves.

The strategic message is simple. Share of voice in India is a power law, not a bell curve. Leadership is real, it is defensible, and it compounds. But the long tail is larger than most challenger brands assume, the concentration is thinnest exactly where the market is youngest, and the two leadership changes we recorded prove that incumbency is rented, not owned. This report is the map. The playbook at the end is how you use it.

Part 1, What Share of Voice Is, and Why It Is the Metric That Matters

1.1 A working definition

Share of voice is the proportion of total media conversation about a category that is captured by a single brand. In its simplest form:

Brand SOV (%) = (Brand mentions ÷ Total category mentions) × 100

If the Indian fintech category generated 10,000 qualifying media mentions in a quarter and PhonePe accounted for 3,400 of them, PhonePe's share of voice is 34%. The elegance of the metric is that it is closed: every share must come from somewhere, so one brand's gain is always another's loss. This is what makes SOV a genuine competitive metric rather than an activity metric. You can double your press releases and still lose share of voice if your rivals tripled theirs.

There are several flavours of SOV, and it is worth being precise about which one this report measures:

• Media / PR SOV, earned coverage in news outlets, trade press, wires and journalist-authored content. This is our primary lens.
• Social SOV, brand mentions across social platforms and communities.
• Search / SEO SOV, visibility share for category keywords in organic search.
• Paid / PPC SOV, impression share in paid media auctions.
• AI-answer SOV, the emerging frontier: how often a brand is named in the answers of generative AI systems and AI-powered search. We treat this as a forward-looking extension of media SOV, and return to it in Part 6.

This report is anchored in earned media SOV, because earned coverage is the hardest to buy, the closest proxy for genuine narrative authority, and the input that increasingly feeds the AI systems now mediating discovery.

1.2 Why SOV matters more in 2026 than it did in 2020

Three shifts have promoted SOV from a nice-to-have PR dashboard tile to a board-level metric.

First, the correlation with market share is now well-established. Decades of marketing science, from the Les Binet and Peter Field body of work onwards, hold that when a brand's share of voice exceeds its share of market, the brand tends to grow, and when SOV sits below market share, the brand tends to shrink. The gap between the two, often called "excess share of voice," is one of the more reliable leading indicators of future market movement that communications teams have. SOV is not a lagging report card; it is an early-warning system.

Second, media supply has been financialised and consolidated. India's business and technology press has more titles than ever but a narrower pool of high-authority mastheads that genuinely move narrative. When the number of truly consequential outlets shrinks relative to the number of brands chasing them, coverage concentrates, and the brands that already own relationships, spokespeople and story pipelines pull further ahead. SOV measures exactly this dynamic.

Third, and most important for 2026, AI systems now read the same coverage you do. Generative answer engines are trained and grounded on the corpus of published media. A brand that owns share of voice in the earned-media layer is disproportionately likely to be the brand an AI names when a prospect asks "who are the top fintech companies in India?" SOV has quietly become the upstream input to AI visibility. Winning the newsroom is now the same project as winning the model.

1.3 The difference between loud and dominant

A crucial nuance: high share of voice is not automatically good. A brand embroiled in a data breach, a regulatory action or a founder controversy can spike to the top of the SOV chart while its quality of voice collapses. This is why serious SOV work always pairs the quantity metric with two quality overlays, sentiment (is the coverage positive, neutral or negative?) and message pull-through (are the brand's intended messages actually surfacing in the coverage, or is the brand merely being named?). We treat these overlays as first-class citizens, not footnotes, and Part 5 is devoted to them.

Part 2, Methodology: How This Benchmark Was Built

We are deliberately transparent about method, because a benchmark is only as trustworthy as the rules that produced it. This report is a modeled, representative view of earned-media share of voice, calibrated against public market-structure data and Melivana's ongoing media-monitoring practice. It is designed to be directionally accurate and structurally honest; it is not a claim of exact, audited mention counts.

2.1 The defined outlet set

SOV is meaningless without a fixed universe of sources. Change the outlet set and you change the answer. For this benchmark we model coverage across a representative Indian earned-media set spanning four tiers:

1. National business and financial dailies and their digital editions, the mastheads that set the agenda for corporate India.
2. Technology, startup and sector trade media, the specialist titles that cover fintech, SaaS, D2C, healthtech and industrials in depth.
3. Wire services and syndicated feeds, which multiply a single story across dozens of downstream carriers.
4. High-authority digital-native and creator business media, newsletters, explainer platforms and video-first business channels that increasingly shape founder and investor opinion.

We deliberately exclude pure press-release distribution wires from the "earned" count, and we treat syndicated republications with a de-duplication rule (see 2.3) so that one wire pickup does not inflate a brand's share fifty-fold.

2.2 The time window

All figures represent a rolling quarter within 2026, a long enough window to smooth out single-event spikes (a funding round, a product launch, a quarterly result) but short enough to remain a current picture rather than a historical average. Where we refer to "the prior period," we mean the immediately preceding comparable quarter. Quarterly framing matters: a monthly window is too noisy for stable SOV, and an annual window hides the leadership shifts that make the metric interesting.

2.3 Mention counting and de-duplication

A "mention" is a distinct, qualifying reference to a brand within a piece of category-relevant coverage. Our counting rules:

• Relevance gating. A mention counts only if it appears in coverage genuinely about the sector or the brand's role in it. A passing reference to "Tata" in an unrelated cricket sponsorship story does not count toward manufacturing SOV.
• De-duplication. Verbatim syndicated copies of a single wire story are collapsed toward a single weighted mention, so wire-heavy brands are not artificially inflated.
• Entity disambiguation. Brands with common-word names or multiple business lines (Tata, Reliance, Apollo) are disambiguated to the relevant operating entity where the coverage context allows.

2.4 Weighting: not all mentions are equal

A raw mention count treats a one-line aggregator blurb the same as a 2,000-word profile in a national daily. That is analytically lazy. Our model applies three weighting overlays to move from raw counts to weighted share of voice:

• Prominence weight. Headline and first-paragraph mentions, and pieces where the brand is the primary subject, carry more weight than incidental name-drops deep in a listicle.
• Reach weight. A mention in a top-tier national masthead carries more weight than the same mention in a low-authority republisher, scaled by the outlet's audited or estimated reach and authority.
• Sentiment weight. Each mention is scored positive, neutral or negative, and the sentiment layer is reported alongside raw share so that "loud but negative" brands are visible as such rather than flattered by a high headline number.

The headline SOV figures in this report are prominence- and reach-weighted; sentiment is reported as a separate quality overlay rather than folded silently into the share number, because collapsing them hides more than it reveals.

2.5 Honest limitations

We state the boundaries plainly, and Part 8 expands on them. These are modeled distributions, not a proprietary census. The outlet set is representative, not exhaustive. Sentiment scoring at scale carries a known error band, particularly around sarcasm, vernacular and mixed coverage. And SOV measures presence in media, which is a powerful proxy for, but not identical to, market power, brand preference or commercial outcome. Read the shape, not the decimal.

Part 3, The Five Key Findings

Finding 1, The sector leader averages ~34% share of voice

Across the five sectors, the average share of voice held by the single leading brand is approximately 34%, a little over one-third of all category coverage, captured by one name.

The sector-by-sector leader shares are: fintech ~34% (PhonePe), SaaS ~30% (Zoho), D2C ~27% (boAt), healthcare ~38% (Apollo Group), and manufacturing ~43% (Reliance). The simple average of these five is 34.4%, which we round to ~34% as the report headline.

Why is 34% the right number, and why not higher or lower? Two structural forces set the floor and the ceiling. The floor is set by the fact that in every one of these sectors there is a genuine incumbent with a spokesperson bench, a standing relationship with the beat reporters, a steady cadence of newsworthy events (results, funding, launches, policy engagement) and a brand name that journalists reach for as shorthand for the whole category. That reliably pushes the leader above a quarter of all voice. The ceiling is set by the reality that India's growth sectors are competitive and well-funded; no leader operates in a vacuum, and even the most dominant brand cedes meaningful voice to at least two credible challengers. That reliably keeps the leader below half.

Thirty-four percent is therefore not a soft consensus midpoint, it is the natural resting point of a competitive-but-concentrated media market. It also carries a memorable strategic implication: the leader is roughly 2.5 times louder than the average second-place brand, which typically lands in the 13 to 16% range. That multiple, not the absolute share, is what makes leadership so hard to dislodge.

Finding 2, The most concentrated sector is manufacturing, where the top brand holds ~43%

Not all sectors concentrate equally. The most concentrated is manufacturing, where the single leading brand, Reliance Industries, commands approximately 43% of sector share of voice, the highest single-brand share we measure anywhere in this report.

The reason is structural. India's large-cap industrial and conglomerate landscape is dominated by a very small number of house names, Reliance, the Tata Group and, increasingly, Adani, whose scale, market capitalisation and cross-sector footprint make them a near-permanent presence in business news. When Reliance reports results, launches an energy or telecom initiative, or engages on policy, it is national front-page news by default. The company is also a hub: it appears in coverage of its suppliers, partners, competitors and the broader economy, not just its own announcements. That hub effect compounds raw event volume into dominant share.

Manufacturing therefore behaves less like a competitive market for attention and more like a gravitational system with one or two very heavy bodies. For a mid-tier industrial brand, this is sobering: the two heaviest names alone can absorb well over half of all sector voice before the challenger has said a word. It also means that in manufacturing, the realistic challenger goal is not to beat the leader on total volume, that is close to impossible, but to own a specific, defensible sub-narrative (defence, green energy, precision engineering) where the giants are less concentrated.

Finding 3, The top three brands typically combine for ~65% of voice

Across the five sectors, the top three brands together capture, on average, approximately 65% of all category share of voice. Two-thirds of every conversation in these industries is owned by three names.

The sector figures for top-three combined share are: manufacturing ~78%, healthcare ~70%, fintech ~66%, SaaS ~60% and D2C ~52%. The pattern is clear and intuitive: the older, more capital-intensive and more consolidated the sector, the tighter the top-three grip; the younger and more fundable the sector, the looser it becomes.

The "top-three ~65%" rule is the single most useful planning number in this report for a challenger brand, because it defines the addressable voice pool. If three brands own 65%, then the entire remaining market, often twenty, thirty or more named players, is fighting over the other 35%. That reframes the challenge productively. A challenger's realistic near-term ambition is rarely to crack the top three; it is to become the clear leader of the contested 35%, the loudest voice among the non-incumbents, which is both achievable and, as Part 4 shows, commercially valuable in its own right.

Finding 4, The long tail holds ~35% of voice, but it is spread thin

The mirror image of Finding 3 is the long tail: every brand outside the top three combines for, on average, approximately 35% of sector share of voice. But that 35% is not a prize held by one runner-up, it is divided among dozens of players, which means the typical individual long-tail brand holds low-single-digit share.

The long tail is largest in D2C, where it is worth 48%, nearly half the sector's voice sits outside the top three brands. This is the fingerprint of a genuinely fragmented, entrepreneurial market: hundreds of direct-to-consumer brands across beauty, personal care, food, apparel, electronics and home, each generating founder-led coverage, funding-round stories and product-launch buzz, none yet large enough to dominate. The long tail is smallest in manufacturing (22%) and healthcare (30%), where consolidation squeezes it.

The strategic reading of the long tail is a story of both opportunity and risk. The opportunity is that a fragmented tail is a contestable tail: no single challenger has locked it down, so a disciplined, well-resourced brand can consolidate a meaningful slice of it faster than in a concentrated sector. The risk is that thin, undifferentiated share is fragile, a long-tail brand that wins coverage only through funding announcements and founder profiles has borrowed voice, not built it, and that voice evaporates the moment the funding cycle turns. The winning long-tail strategy is to convert scattered, event-driven mentions into a durable ownable narrative before the capital narrative fades.

Finding 5, Two of five sectors changed leadership or top rank versus the prior period

Dominance is durable but not permanent. Of the five sectors we track, two saw a change in the leadership or top-rank order versus the prior comparable period.

The clearest example is fintech, where the media-share leadership reflects PhonePe's consolidation of narrative dominance on the back of its UPI leadership and IPO trajectory, moving ahead of a Paytm that had historically owned more of the category conversation. The category's centre of gravity shifted, and the SOV chart shifted with it. The second is in healthcare, where the rapid, aggressively-covered offline-plus-online expansion of Tata-backed omnichannel players reshuffled the ranks beneath the Apollo Group's leadership, changing who holds the second and third chairs even as the top name held.

Three of five sectors, by contrast, showed stable leadership, SaaS (Zoho's bootstrapped, profitable, globally-covered story remains the reference point), D2C (boAt's audio-and-lifestyle dominance held at the top even as the tail churned) and manufacturing (Reliance's incumbency is close to structural). The lesson is balanced and important: leadership in Indian earned media is sticky but not sealed. Roughly 40% of sectors saw meaningful movement in a single year. For incumbents, that is a warning against complacency. For challengers, it is proof that the scoreboard can be moved, usually by a genuine business inflection (an IPO, a category-defining product, an aggressive expansion) amplified by disciplined communications, rather than by communications alone.

Part 4, The Benchmark Table

The table below is the quantitative core of the report. All figures are prominence- and reach-weighted earned-media share of voice, modeled as representative distributions for a rolling quarter in 2026. "Long-tail share" is defined as total sector voice minus the top-three combined share, i.e., everyone outside the top three.

Read across the rows and a clean gradient appears. Manufacturing sits at one pole, a 43% leader, a 78% top-three, a 22% tail: the signature of a consolidated, incumbent-dominated attention market. D2C sits at the other, a 27% leader, a 52% top-three, a 48% tail: the signature of a young, fragmented, contestable one. Fintech, SaaS and healthcare arrange themselves along the spectrum in between, with fintech and healthcare leaning concentrated and SaaS leaning fragmented.

The single most decision-relevant column is the last one. It tells a challenger, at a glance, how much voice is actually available to be won without displacing an entrenched top-three brand, 48 points of it in D2C, but only 22 in manufacturing.

Part 5, Sector Deep Dives: Who Dominates, and Why

5.1 Fintech, PhonePe leads a concentrated, high-velocity sector

India's fintech sector is one of the largest and most closely-covered technology stories in the country, anchored by a payments layer that touches hundreds of millions of users daily. In our model PhonePe leads with ~34% of sector voice, with Paytm and Razorpay completing a top three worth ~66%; the long tail (Pine Labs, PayU, Cred, Groww, Zerodha's payments adjacencies, neobanking and lending players and dozens more) shares the remaining 34%.

PhonePe's dominance is not an accident of PR spend. It is downstream of genuine category leadership in UPI, where it holds the largest share of transaction volume, amplified by a steady drumbeat of newsworthy events: an IPO trajectory reportedly targeting a multi-billion-dollar valuation, product expansion beyond payments, and a role as the default reference point whenever journalists explain how UPI works. When a brand is the shorthand for a category, it accrues voice on every category story, not just its own. Paytm retains enormous voice through its listed-company status, its scale and a coverage-heavy history; Razorpay leads the online-payments and business-facing narrative. The concentration here reflects a market where three names have each earned a durable narrative franchise. This is also the sector where we recorded a leadership shift, PhonePe's consolidation of the top narrative slot over a historically louder Paytm, a reminder that even in a concentrated sector, the order can change on a genuine business inflection.

5.2 SaaS, Zoho leads the most credibility-driven sector

Indian SaaS is a global success story told in the domestic press with unusual pride, and its SOV structure reflects that. Zoho leads with ~30%, with Freshworks and a rotating third name (Postman, Zerodha's technology story, Chargebee, BrowserStack and other unicorns compete for the slot) forming a top three worth ~60%. The 40% long tail is one of the deepest and most credentialed in this report, populated by more than a dozen genuine unicorns and a long bench of fast-growing challengers.

Zoho's leadership is instructive because it is built almost entirely on narrative authority rather than announcement volume. The company's bootstrapped, profitable, revenue-past-a-billion-dollars, no-outside-capital story is a journalist's dream: it is contrarian, it is Indian-founded and globally scaled, and it comes with a founder willing to articulate a distinctive worldview on technology, rural India and independence from venture capital. That gives Zoho a quality of voice, high message pull-through, overwhelmingly positive sentiment, that pure mention-count leaders in other sectors cannot match. Freshworks, as the first India-born SaaS company to list on NASDAQ, owns the "Indian SaaS goes public" narrative outright. SaaS is the sector where the gap between loud and respected is smallest, because coverage tends to be substantive rather than event-driven.

5.3 D2C, boAt leads India's most fragmented attention market

Direct-to-consumer is the most fragmented sector we measure, and its numbers show it: a 27% leader, a 52% top three, and a 48% long tail. boAt (Imagine Marketing) leads on the strength of its audio-and-lifestyle brand dominance and its status as one of the most-covered consumer-brand IPO and growth stories; Mamaearth (Honasa Consumer) and Nykaa round out a top three, with the exact ordering sensitive to the quarter's news flow.

The fragmentation is the whole point. D2C in India spans beauty and personal care, food and beverage, apparel, electronics, home, wellness and more, with hundreds of venture-backed brands each generating founder-led coverage, funding stories and launch buzz. No single brand can dominate a market this broad, so voice disperses. boAt leads because it combines genuine consumer scale with a marketing-and-media culture that treats earned coverage as a core competency, and because personal electronics generate more mainstream-media surface area than a niche skincare line. Mamaearth and Nykaa bring listed-company scrutiny and a steady stream of financial and strategic coverage. But beneath the top three, the 48% tail is a genuine contest, which is exactly why D2C is the sector where a disciplined challenger can move its SOV fastest. The flip side is durability: much of the tail's voice is funding- and founder-driven, and therefore fragile.

5.4 Healthcare, the Apollo Group leads a consolidating sector

Healthcare and healthtech present a concentrated top with a rapidly reshuffling middle: the Apollo Group leads with ~38%, and a top three worth ~70% includes the large hospital-and-pharmacy incumbents alongside the leading digital-health platforms. The 30% tail spans e-pharmacy, telemedicine, diagnostics, AI-diagnostics and healthtech.

Apollo's leadership rests on a combination that is hard to replicate: a trusted, decades-old hospital brand; a large physical footprint that generates local and national coverage; and a digital arm (Apollo 24/7, Apollo HealthCo) that lets it participate in the healthtech narrative rather than being disrupted by it. Trust is the currency of healthcare coverage, and incumbency in trust translates directly into voice. Beneath Apollo, the ranks are moving fast: aggressively-covered omnichannel expansion by Tata-backed players and the pure-play e-pharmacy and telemedicine brands (PharmEasy, Practo, Tata 1mg, MediBuddy) are reshuffling the second and third positions, which is why we flagged healthcare as a sector with rank change even though the top name held. Healthcare is where the quality overlay matters most: coverage here can turn on regulatory, safety and pricing stories, so a high raw SOV must always be read against sentiment before it is celebrated.

5.5 Manufacturing, Reliance leads the most concentrated sector in India

Manufacturing and industrials is the most concentrated attention market we measure, and it is dominated by house names. Reliance leads with ~43%, the Tata Group and L&T (with Adani a rising presence) complete a top three worth ~78%, and the entire rest of the vast Indian industrial landscape shares just 22%.

The concentration is structural and self-reinforcing. Reliance is India's most valuable company, a perennial front-page presence, and a hub that appears in coverage of energy, telecom, retail, chemicals and the macroeconomy, not just its own manufacturing operations. Tata is the country's most valuable business house by aggregate value, with a coverage footprint spanning steel, autos, chemicals, IT and consumer. L&T owns the engineering-and-construction narrative and increasingly the defence-and-infrastructure story. These names are so large that their gravitational pull absorbs the majority of sector voice before any mid-cap industrial gets a word in. For challengers, manufacturing is the clearest illustration of the report's central asymmetry: you will not out-shout the giants on total volume, so the only viable SOV strategy is to own a narrow, defensible sub-category narrative where the giants are diffuse.

Part 6, The Big Dynamics: Concentration, the Long Tail, Quality, and AI

6.1 Concentration versus fragmentation

Lay the five sectors on a single axis and the report's deepest pattern emerges: SOV concentration tracks sector maturity and capital intensity. The older, more consolidated, more capital-heavy the industry (manufacturing, healthcare), the more voice concentrates in a tiny handful of incumbents. The younger, more fundable, more entrepreneurial the industry (D2C, SaaS), the more voice fragments across a deep bench of challengers.

This is not merely descriptive; it is prescriptive. Concentration tells you what kind of game you are playing. In a concentrated sector, the incumbents own the general-category narrative, so a challenger must play a niche-ownership game, winning a specific, defensible sub-story rather than competing for the whole. In a fragmented sector, no one owns the general narrative yet, so a challenger can play a consolidation game, moving to become the clear voice of the category before it consolidates around someone else. Reading your sector's concentration curve correctly is the first strategic act of any SOV programme.

6.2 The long-tail challenger opportunity

The long tail is where most brands reading this report actually live, and it is more valuable than its thin per-brand share suggests. Three truths govern it.

First, the tail is contestable in exact proportion to its size. A 48% tail (D2C) is a large, unclaimed pool that rewards aggression; a 22% tail (manufacturing) is a scrap that rewards patience and niche focus. Match your ambition to your tail.

Second, winning the tail is a relative game.* A long-tail brand does not need to beat the leader; it needs to become the loudest of the non-incumbents. Being the clear number four or five in a sector, the brand journalists call when they want a challenger perspective, is a real, ownable and commercially useful position, and it is the natural staging ground for a later run at the top three.

Third, tail voice must be converted from borrowed to built. Much long-tail coverage is event-driven, funding rounds, founder profiles, launch buzz, and event-driven voice is rented from the news cycle. The brands that graduate out of the tail are the ones that convert that attention into a durable, ownable narrative (a category they define, a data franchise they own, a point of view they are quoted on) before the events dry up.

6.3 Quality versus quantity of voice

Raw share of voice is a volume metric, and volume alone can mislead. Two brands with identical 20% shares can be in completely different competitive positions once you apply the quality overlays.

• Sentiment separates positive dominance from crisis-driven noise. A brand that spikes to high SOV during a data breach or regulatory action is loud, not winning. We report sentiment alongside share precisely so that "loud and negative" is never mistaken for strength.
• Message pull-through measures whether the brand's intended messages actually appear in coverage, or whether the brand is merely named while the story is about something else. High share with low pull-through means the brand is a bystander in its own coverage.

The sector deep dives show why this matters. Zoho's ~30% in SaaS is worth more than a numerically larger share elsewhere because it comes with overwhelmingly positive sentiment and high message pull-through, the coverage says what Zoho wants said. A raw-count leader in a sentiment-volatile sector like healthcare or fintech must always discount its headline number by the quality of the coverage underneath it. Weighted, sentiment-aware SOV is the only version of the metric a board should act on.

6.4 From SOV to market share, and to AI-search visibility

Two connections turn SOV from an interesting chart into a strategic instrument.

SOV and market share. The empirical relationship, that excess share of voice (SOV above market share) predicts future market-share growth, and deficit SOV predicts decline, makes SOV a leading indicator. The practical technique is to plot every brand's SOV against its market share: brands above the diagonal are "over-indexing" and tend to be gaining ground; brands below it are "under-indexing" and are vulnerable. For a challenger, deliberately running SOV ahead of current market share is one of the few reliable ways to manufacture future growth.

SOV and AI-search visibility. This is the 2026 frontier and the reason SOV has been promoted to a board metric. Generative answer engines and AI-powered search are grounded on the published media corpus. The brands that own earned-media share of voice are disproportionately the brands these systems name when a user asks an open question, "best fintech app in India," "top D2C beauty brands," "leading Indian SaaS companies." Media SOV is, in effect, the training and grounding signal for AI-answer share. This creates a compounding advantage: today's earned-media leaders are becoming tomorrow's default AI answers, which drives discovery, which drives more coverage. Winning share of voice in the newsroom and winning it in the model are now the same project, a theme the later reports in this series (on AEO, citation and AI-answer share) take up directly.

Part 7, The Playbook: How Brands Grow Share of Voice

SOV is winnable, but only with a programme, not a campaign. The following playbook is sequenced from diagnosis to compounding.

1. Fix your outlet set and measure honestly. You cannot manage what you define loosely. Lock a defined outlet set and time window, measure your weighted SOV against named competitors, and refuse to move the goalposts quarter to quarter. Vanity reach numbers are not SOV; comparative, competitor-anchored share is.

2. Read your concentration curve before you set targets. Know whether you are in a concentrated sector (play niche-ownership) or a fragmented one (play consolidation). Set the right game before you spend a rupee.

3. Target the contested pool, not the leader. In most sectors the top three own ~65% and are near-immovable in the short term. Aim to become the clear leader of the remaining ~35%, the loudest non-incumbent, which is achievable and commercially real.

4. Own a narrative, not just announcements. Event-driven voice (funding, launches) is rented. Build a durable, ownable story: define a category, own a data franchise, take a distinctive point of view. Zoho's independence narrative and Freshworks' listing narrative are worth more than any single press release because they are franchises, not events.

5. Build a spokesperson bench and a proprietary-data habit. The brands that lead SOV are the ones journalists can always reach and always quote. Invest in media-ready spokespeople and in publishing original data the press wants to cite, proprietary data is the single most reliable earned-media multiplier available to a challenger.

6. Manage quality as hard as quantity. Track sentiment and message pull-through beside raw share. Chasing volume through controversy or undifferentiated name-drops inflates the number while eroding the position.

7. Run SOV ahead of market share, deliberately. If you are a challenger, target an excess share of voice, voice above your current market share, and hold it long enough for the market-share growth it predicts to arrive.

8. Instrument for AI visibility now. Treat earned-media SOV as the upstream input to AI-answer share. The coverage you win in 2026 is the answer an AI gives in 2027. Prioritise the high-authority, frequently-cited outlets that AI systems lean on.

9. Defend, if you are the incumbent. Two of five sectors changed rank in a year. Incumbency is rented. Sustain the cadence, protect sentiment, and watch the challenger consolidating your long tail, that is who takes your chair.

Part 8, How to Use This Benchmark, and Its Limitations

8.1 How to use this benchmark

This report is a reference frame, not a scoreboard for any one brand. Use it in four ways.

• Calibrate your own SOV. Measure your weighted share in your sector and compare it to the structure here. If you are a fintech brand at 8% share, this report tells you the leader is at ~34%, the top three at ~66%, and the contested tail at 34%, so your realistic near-term target is to lead that tail, not to dethrone PhonePe.
• Set defensible board targets. "Grow SOV from 8% to 12%" is a credible, benchmarked goal when it is set against a known concentration curve. This report gives you that curve.
• Choose your game. Use the concentration reading in Part 6 to decide between niche-ownership and consolidation strategies before committing budget.
• Brief the C-suite on the AI stakes. Use Part 6.4 to make the case that earned-media SOV is now the upstream input to AI-answer visibility, which is what turns a PR budget into a discovery investment.

8.2 Limitations

We restate the boundaries honestly, because a benchmark that oversells itself is worse than useless.

• Modeled, not censused. These are representative, modeled distributions calibrated against public market-structure data and monitoring practice, not a claim of exact, audited proprietary mention counts. Read the shape, not the decimal.
• Outlet-set dependent. Change the defined outlet set and the numbers move. Our set is representative of high-authority Indian earned media; a different set (heavily regional, heavily social, or heavily trade) would yield a different, though structurally similar, picture.
• Window-dependent. These are rolling-quarter figures. A single large event (a mega-IPO, a crisis) can distort a shorter window; a longer window would smooth out the very leadership shifts that make the metric interesting.
• Sentiment error band. Automated sentiment and message-pull-through scoring carry known error, especially around vernacular, sarcasm and mixed coverage. The quality overlays are directional, not exact.
• Proxy, not outcome. SOV measures presence in media. It is a strong leading indicator of market movement and AI visibility, but it is not itself market share, brand preference or revenue. Treat it as the early-warning system it is, not the destination.

Used within those boundaries, the benchmark is robust where it matters: the concentration curves, the top-three coalitions, the long-tail arithmetic and the leadership dynamics are stable, defensible and consistent with how India's media actually covers these sectors.

Appendix, Glossary and Notes

Share of Voice (SOV). The proportion of total category media conversation captured by a single brand, expressed as a percentage. Inherently comparative and closed, all shares sum to 100%.

Weighted SOV. SOV after applying prominence, reach and (separately reported) sentiment overlays, so that a headline national feature counts for more than an incidental aggregator mention.

Prominence weight. The premium given to mentions in headlines, opening paragraphs, and pieces where the brand is the primary subject.

Reach weight. The premium given to mentions in higher-authority, higher-reach outlets.

Sentiment overlay. The positive/neutral/negative scoring reported alongside raw share so that loud-but-negative coverage is visible as such.

Message pull-through. The extent to which a brand's intended messages actually appear in the coverage it earns, versus the brand being merely named.

Top-three combined share. The summed SOV of the three leading brands in a sector, the report's measure of concentration.

Long-tail share. Total sector voice minus the top-three combined share, i.e., the pool held by every brand outside the top three.

Excess share of voice (ESOV). The gap between a brand's SOV and its market share; positive ESOV is empirically associated with future market-share growth.

Concentration curve. The distribution of SOV across brands in a sector, from the leader through the long tail; steeper curves (manufacturing) indicate incumbent dominance, flatter curves (D2C) indicate fragmentation.

AI-answer SOV. The emerging measure of how often a brand is named in the outputs of generative AI and AI-powered search, increasingly grounded in, and predicted by, earned-media SOV.

Defined outlet set. The fixed universe of media sources against which SOV is measured; changing it changes the result, which is why it is fixed in advance.

Time window. The fixed period over which mentions are counted; this report uses a rolling quarter within 2026.

Note on brand names. Brands named in this report (PhonePe, Paytm, Razorpay, Zoho, Freshworks, boAt, Mamaearth, Nykaa, Apollo, PharmEasy, Practo, Tata 1mg, Reliance, Tata Group, L&T and others) are real, sector-leading Indian companies used to illustrate plausible, representative share-of-voice structures. The specific share percentages are modeled representative distributions for illustrative benchmarking, not audited proprietary counts.

Melivana | PR Intelligence Series 2026, Report 5 of 8. Prepared by the PR Intelligence unit. This report is intended as a strategic benchmark for communications planning and should be read alongside the companion reports in the series on AEO, media citation and AI-answer share.