R&D: The Marketing Nobody Measures

February 14, 2026

R&D Is the Marketing Nobody Measures: How Corporate Research Builds Brands, Attracts Talent, and Moves Markets

Why the most powerful brand-building mechanism in technology has no framework, no budget line, and no place in the marketing curriculum.

In 2016, a machine learning system called AlphaGo defeated the world champion of Go in a five-game match broadcast to over 200 million viewers worldwide. The event generated front-page coverage in virtually every major global newspaper, triggered South Korea’s announcement of an $860 million national AI investment fund, spawned an award-winning documentary that reached Netflix audiences globally, and ultimately contributed to a Nobel Prize in Chemistry in 2024.

That same year, Warner Bros. spent an estimated $150–160 million on marketing for Batman v Superman: Dawn of Justice — a film that grossed $873 million but was considered underperforming and has largely faded from cultural memory.

DeepMind’s total operating costs in 2016–2017 were comparable to that marketing budget. The difference is that Batman v Superman’s marketing impact decayed within weeks. AlphaGo’s brand impact compounded over a decade. And yet, in every textbook, in every marketing course, and in every corporate budget, one of these is classified as “marketing” and the other as “R&D.”

This distinction is not merely semantic. It represents a fundamental blind spot in how businesses understand, measure, and allocate resources toward brand building. A growing body of academic evidence — spanning marketing, finance, strategy, and organisational behaviour — suggests that corporate R&D functions as one of the most powerful implicit marketing mechanisms available, yet no unified theoretical framework treats it as such.

1. The Theory: Why R&D Is a Near-Perfect Brand Signal

The theoretical foundations for understanding R&D as an implicit marketing channel are well-established, even if they have never been formally integrated into marketing theory.

Signaling theory, originally developed by Michael Spence in his 1973 work on job-market signaling (for which he received the Nobel Prize in 2001), explains how agents communicate unobservable quality through costly, observable actions. A signal is credible precisely because it is expensive and difficult to fake. R&D investment satisfies these conditions almost perfectly: it is capital-intensive, its outcomes are publicly verifiable through patents, publications, and product launches, and its quality is assessed by expert communities (peer reviewers, industry analysts, patent examiners) rather than self-reported.

Contrast this with traditional advertising, which is also costly but whose claims are self-generated and lack independent verification. When Apple runs a television advertisement claiming its products are innovative, the audience must decide whether to believe the claim. When Apple publishes a paper at a top machine learning conference, the claim has been independently verified through peer review. The signaling mechanism is fundamentally different.

Natalie Mizik and Robert Jacobson established the foundational measurement framework in their influential 2003 paper in the Journal of Marketing, “Trading off between Value Creation and Value Appropriation.” They operationalized R&D spending as “value creation” and advertising/SGA spending as “value appropriation,” demonstrating that stock markets respond positively to both. Their framework has been adopted across dozens of subsequent studies — but, as we shall see, it contains an assumption that inadvertently renders R&D’s marketing effects invisible.

David Aaker and Robert Jacobson (1994, 2001) demonstrated in the Journal of Marketing Research that perceived quality — partly driven by innovation — contains financial information valued by investors. Their work showed that brand attitudes have particular value relevance in high-technology markets, precisely because innovation signals are harder for non-expert investors to evaluate directly.

Perhaps the most striking finding comes from Höflinger, Nagel, and Sandner (2018), published in the Journal of Innovation & Knowledge. Studying the relationship between actual innovative activity and reputation for technological innovation, they found that while patent citation intensity positively builds innovation reputation, marketing intensity actually negatively influences innovation reputation. Their conclusion is worth paraphrasing carefully: authentic technological advancement attracts attention that cannot be replicated through increased marketing spend. This is a direct empirical demonstration that R&D and advertising do not merely build brand through different channels — they can actively work at cross-purposes. A firm that substitutes advertising for genuine research may be destroying the very brand equity it seeks to create.

Henard and Dacin (2010) in the Journal of Product Innovation Management examined the consumer-facing effects directly, finding that a reputation for product innovation increases consumer enthusiasm, engagement, and willingness to try new products. Crucially, these effects operate independently of the specific products being offered — the reputation itself functions as a brand asset. Rubera and Kirca’s (2012) meta-analysis in the Journal of Marketing, synthesizing dozens of studies, confirmed that firm innovativeness has a direct positive effect on firm value beyond its mediated effects through market and financial performance. This direct effect is perhaps the clearest evidence that innovation carries reputational value independent of the revenue generated by the products it creates.

Taken together, these findings describe a mechanism that marketing theorists would immediately recognise if it appeared in any other context: R&D activities generate positive brand associations, increase consumer willingness to engage, build prestige, and create measurable firm value through reputational channels. This is, by any reasonable definition, marketing.

2. The Evidence: DeepMind, Tesla, and the Economics of Research as Publicity

The theoretical case is supported by some remarkable natural experiments in the technology sector.

DeepMind: Nobel-Prize-Level Brand Building at Movie-Marketing Prices

According to UK Companies House filings reported by Quartz and CNBC, DeepMind’s losses to Alphabet escalated from approximately £123.5 million ($162 million) in 2017 to £477 million ($649 million) in 2019, with Alphabet waiving a £1.1 billion ($1.5 billion) debt in 2020. Cumulative costs have been estimated at $5 billion or more since Google’s 2014 acquisition.

These are substantial figures — but they are not out of line with major corporate marketing campaigns. The global advertising market spends hundreds of billions annually, and individual campaigns for major films, product launches, or brand repositioning exercises routinely reach the hundreds of millions. The relevant comparison is not whether DeepMind was expensive in absolute terms, but what Alphabet received per dollar relative to conventional marketing alternatives.

The AlphaGo match against Lee Sedol drew over 200 million online viewers. The AlphaGo documentary premiered at the Tribeca Film Festival, scored 100% on Rotten Tomatoes, and reached global Netflix audiences. South Korea’s $860 million national AI investment response — the so-called “AlphaGo shock” — represented a geopolitical event triggered by a research demonstration. No advertising campaign in history has ever prompted a sovereign government to announce a near-billion-dollar industrial policy response.

More importantly, unlike a film marketing campaign with a defined theatrical window, AlphaGo’s brand impact compounded. The 2016 match led to a 2017 documentary. AlphaFold’s protein structure prediction breakthrough followed in 2020, generating another wave of global coverage. By 2024, DeepMind co-founder Demis Hassabis and researcher John Jumper had received the Nobel Prize in Chemistry. AlphaFold has been cited in over 40,000 academic papers and used by 3.3 million researchers worldwide.

Huberman and Regev (2001) documented a relevant mechanism: when the New York Times reported on a cancer therapy breakthrough that had already been published in Nature, the associated company’s stock price surged dramatically. The scientific result had been publicly available, but the media coverage created an independent market impact. This suggests that the media amplification of R&D achievements generates brand value beyond the informational content of the research itself.

James and Shaver (2016), published in Academy of Management Discoveries, found that firms strategically issue R&D press releases before observable outcomes, using R&D communication proactively. This implies that at least some firms recognise the marketing value of R&D announcements, even if marketing theory does not.

Tesla: A Trillion-Dollar Brand Built on Zero Advertising

Tesla provides perhaps the purest case study of R&D substituting entirely for traditional marketing. For most of its history through to recent years, Tesla spent $0 on traditional advertising, instead investing heavily in R&D — approximately $2,984 per vehicle, which exceeded the combined R&D and advertising spend per vehicle of Ford, Toyota, and Chrysler. The company built a market capitalisation that exceeded $1 trillion on the strength of product innovation, engineering milestones, and the earned media these generated.

Tesla’s product launches, software updates, and engineering demonstrations (such as the Cybertruck unveiling or Full Self-Driving beta releases) generate extensive media coverage without the need for explicitly paid promotion. Each acts as a brand-building event. The mechanism is identical to what signaling theory predicts: costly, verifiable demonstrations of capability that audiences interpret as quality signals.

SpaceX illustrates the same principle in an adjacent domain. Each rocket launch — a live, high-stakes engineering demonstration — generates millions of viewers and global headlines. SpaceX has become one of the most recognised technology brands in the world, reportedly valued at $350 billion as of late 2025, without a marketing department in any traditional sense. The R&D is the marketing.

IBM Watson: The Cautionary Tale

Not all R&D-as-marketing stories end well. IBM’s Watson victory on Jeopardy! in 2011 generated enormous publicity and positioned IBM as a leader in artificial intelligence. However, IBM subsequently leveraged the research publicity with marketing claims that outpaced the technology’s actual capabilities. Watson Health, promoted as a revolutionary healthcare AI, was eventually divested in 2022 after failing to deliver on its marketed promises.

The Watson case illustrates an important boundary condition: R&D-as-marketing works precisely because research signals are costly and authentic. When traditional marketing hype is layered on top of R&D achievements and begins to exceed what the technology can deliver, the signal collapses. The authenticity that makes R&D an effective brand signal is destroyed by the very marketing practices it was supposed to complement.

3. The Talent Pipeline: R&D Reputation as the Ultimate Recruiting Tool

The third channel through which R&D generates marketing value — and arguably the most economically significant in knowledge-intensive industries — is employer branding and talent acquisition.

The academic literature on employer branding provides robust evidence for this mechanism. Lievens and Highhouse (2003) distinguished between “instrumental” employer brand attributes (tangible benefits like salary and location) and “symbolic” attributes (intangible qualities like innovativeness and prestige). They found that symbolic attributes, including innovativeness, are key drivers of organisational attractiveness and, critically, are harder for competitors to imitate. A company can match a competitor’s salary offer overnight; it cannot replicate a decade of published research and engineering breakthroughs.

Berthon, Ewing, and Hah (2005) identified five employer brand dimensions, with “interest value” — relating to innovative and stimulating work environments — emerging as a significant factor in attracting talent. A systematic literature review by Frontiers in Psychology (2022), covering employer attractiveness from the employee perspective, consistently identified innovation orientation as a top-tier attractor.

The financial implications are substantial. LinkedIn’s employer branding data indicates that companies with strong employer brands experience a 43% decrease in cost-per-hire and receive more than double the applicants per posting. Research published by Harvard Business Review (Burgess, 2016) found that companies with poor employer reputations must offer a minimum 10% salary premium — approximately $4,723 more per hire — to attract candidates. For a company of 10,000 employees, this translates to up to $7.6 million annually in additional wage costs. Glassdoor’s research finds a 50% decrease in cost-per-hire and a 28% reduction in turnover from strong employer brand investment.

In AI specifically, where talent scarcity defines competitive dynamics, these effects are dramatically amplified. The White House Council of Economic Advisers reported in January 2025 that AI labs spend 29–49% of total costs on labour, with salaries increasing 10–13% annually. In this environment, the ability to attract talent through research reputation rather than pure compensation is not a marginal advantage — it is a core economic driver.

Corporate AI labs function as explicit recruitment infrastructure, whether or not they are formally categorised as such. Meta’s Fundamental AI Research (FAIR) lab was established in 2013 in significant part as a talent pipeline. Yann LeCun built FAIR into a world-class research organisation that published prolifically, creating an academic-like environment that attracted top researchers. Google DeepMind positions itself as offering the best environment for advancing AI research, using landmark achievements as recruitment signals. A systematic review of 164 studies on corporate scientific publishing in Research Policy (2022) confirmed that attracting and retaining researchers is one of five primary strategic incentives for why firms publish research at all.

What do top researchers actually want? Surveys consistently find that elite AI talent prioritises freedom to publish at conferences, access to significant compute resources, academic-like autonomy, and the opportunity to work alongside world-class peers. Mark Zuckerberg reportedly captured this as researchers wanting minimal management overhead and maximum computational resources. R&D reputation directly satisfies these preferences in ways that traditional employer marketing campaigns — career fairs, branded recruitment videos, sponsored job posts — fundamentally cannot.

The mechanism is again one of signaling: a company’s published research portfolio, conference presence, and engineering demonstrations serve as credible signals of the working environment a prospective employee can expect. These signals are verified by the expert community (through peer review, citations, and industry recognition) rather than generated by a marketing department. Their credibility is what makes them effective.

4. The Financial Markets: How R&D Builds Intangible Value That Analysts Struggle to Price

A fourth body of evidence comes from the marketing-finance interface, where researchers have examined how R&D investment affects firm valuation, risk, and brand equity.

McAlister, Srinivasan, and Kim (2007) in the Journal of Marketing found that both R&D intensity and advertising intensity lower a firm’s systematic risk (beta). This means R&D creates intangible assets — brand equity, customer loyalty, innovation pipeline expectations — that insulate firms from market-wide volatility. In financial terms, R&D functions as a form of reputational insurance. This is a marketing effect, even though it appears in finance metrics.

Peterson and Jeong (2010) in the Journal of the Academy of Marketing Science analysed 125 firms over 16 years, finding that both R&D and advertising expenditures are significantly related to brand value as measured by Interbrand’s widely-used methodology. Notably, the R&D effect on brand value was not merely indirect (through better products leading to stronger brands) but appeared to operate through direct reputational channels.

Chan, Lakonishok, and Sougiannis (2001) in the Journal of Finance discovered that R&D-intensive firms earn large excess returns, suggesting that financial markets systematically fail to fully price the value R&D creates. If part of that unpriced value is the brand equity and reputational capital generated by R&D activities, then markets are not merely underpricing innovation — they are underpricing marketing that happens to be categorised as R&D.

Sorescu and Spanjol (2008) in the Journal of Marketing found that each breakthrough innovation is associated with an average $4.2 million increase in firm value, with the effect working through multiple channels including the signaling of innovative capability. Srinivasan, Pauwels, Silva-Risso, and Hanssens (2009) showed that innovation effects on stock returns are enhanced by advertising support — their model combining marketing and finance variables explained twice as much variance in stock returns as a finance-only model. Yet Ho, Keh, and Ong (2005) found the interaction between R&D and advertising intensities was “generally insignificant,” suggesting they may operate through different mechanisms rather than simply amplifying each other.

A study in the Schmalenbach Journal of Business Research (2023) adds another dimension: corporate reputation amplifies the impact of media coverage on market value. Higher-reputation firms benefit disproportionately from positive press. This creates a compounding cycle for R&D-intensive companies: R&D builds reputation, reputation amplifies media impact, and media coverage further reinforces reputation. The flywheel effect is precisely what explains why AlphaGo’s brand impact compounded over a decade rather than decaying like a conventional advertising campaign.

The financial evidence also reveals a measurement problem that echoes the theoretical blind spot. Chauvin and Hirschey (1993) in Financial Management found that both R&D and advertising have “large, positive and consistent influences on market value.” But because R&D and advertising are measured as separate inputs with separate assumed outputs, the brand-building component of R&D is either attributed to “advertising-like” effects (and thus assigned to the wrong input) or left unexplained in the residual. The standard econometric models are not designed to detect R&D’s marketing function — and what models are not designed to detect, they will not find.

The most significant finding from surveying this literature is not any single study but a structural absence. Five specific gaps emerge from the intersection of marketing, strategy, finance, and innovation management research.

First, there is no unified theory of R&D as a marketing channel. Peter Drucker wrote in 1973 that “the business enterprise has two — and only two — basic functions: marketing and innovation.” Regis McKenna argued in the Harvard Business Review in 1991 that “marketing is everything.” Yet no formal academic framework has taken these claims seriously enough to model R&D as an implicit marketing activity. The literature fragments into disconnected streams: R&D–marketing interface studies (focused on new product development coordination, not brand building), R&D–advertising complementarity studies (treating them as parallel investments rather than recognising R&D’s direct brand effects), and innovation reputation studies (a small literature lacking integration with mainstream marketing theory).

Second, the dominant measurement framework excludes R&D’s marketing effects by construction. Mizik and Jacobson’s (2003) widely-adopted distinction between “value creation” (R&D) and “value appropriation” (advertising/marketing) has been enormously influential — it appears in dozens of subsequent studies across the marketing-finance interface. But the framework assumes by definition that R&D does not appropriate value. Every study built on this dichotomy inherits the assumption that R&D cannot function as marketing. The brand-building effects of R&D are not merely unmeasured; they are excluded from the measurement model before data is collected.

Third, marketing education treats R&D exclusively as an input to “Product.” The standard marketing curriculum, built on frameworks like the 4Ps (Product, Price, Place, Promotion) and the 7Ps, positions R&D as an upstream function that feeds the “Product” element of the marketing mix. R&D’s role in generating earned media, building brand prestige, signaling quality to consumers, and creating employer brand equity receives no systematic treatment. A student completing a marketing degree — as this author did — can graduate without ever encountering the idea that research activities constitute a form of promotion.

Fourth, earned media from R&D is essentially unstudied. Growing literatures examine user-generated content, influencer marketing, word-of-mouth dynamics, and social media marketing as forms of earned media. But no research stream specifically examines the earned media generated by R&D activities — scientific publications, patent announcements, conference presentations, public demonstrations like AlphaGo — as a marketing output with measurable return on investment. The marketing field has developed sophisticated tools for measuring the brand impact of a viral tweet but has no methodology for measuring the brand impact of a Nature paper.

Fifth, the Höflinger paradox remains largely unexplored. The finding that marketing spending can reduce innovation reputation challenges fundamental assumptions about brand building in innovation-intensive industries. If substituting advertising for authentic R&D signals actively destroys brand equity, then the standard recommendation to “support innovation with marketing” may be counterproductive in precisely the industries where innovation matters most. This finding deserves far deeper investigation than it has received.

Griffin and Hauser’s (1996) definitive review of the R&D–marketing interface in the Journal of Product Innovation Management is symptomatic of the problem: it exhaustively examines how R&D and marketing functions cooperate to develop new products, but never considers that R&D activities themselves constitute marketing. Krasnikov and Jayachandran’s (2008) meta-analysis in the Journal of Marketing found that marketing capability has a stronger impact on firm performance than R&D capability — but if R&D’s brand-building effects are silently attributed to “marketing capability” rather than “R&D capability,” then R&D’s total contribution is being systematically underestimated while marketing’s is being inflated.

Implications: What Changes if We Take This Seriously

If R&D is recognised as an implicit marketing channel, several practical consequences follow.

Corporate budgeting needs to account for R&D’s brand-building returns. When a CFO evaluates a research programme, the standard analysis considers direct commercial applications (products, patents, licensing revenue) and possibly knowledge spillovers. It does not typically include the earned media value of research publicity, the reduction in recruitment costs from enhanced employer brand, or the brand equity effects on consumer willingness to pay. Adding these to the ROI calculation would, in many cases, substantially change the apparent return on research investment — and might justify research programmes that appear unprofitable when only direct commercial returns are considered.

Marketing strategy in innovation-intensive industries should be reconceived. The Höflinger finding — that traditional marketing can diminish innovation reputation — suggests that the standard playbook of “develop the technology, then market it” may be backwards for firms competing on innovation. Tesla’s approach of investing in R&D and allowing the products to generate their own publicity may not be eccentric frugality; it may be optimal marketing strategy for technology companies.

Recruitment budgets and research budgets should be considered jointly. In industries where talent costs represent 29–49% of total expenditure and salaries are growing at 10–13% annually, the recruitment efficiency gained from R&D reputation is not a minor benefit — it is potentially worth hundreds of millions of dollars. A corporate AI lab that publishes at top conferences may generate more recruitment value than the entirety of a company’s employer branding budget.

Marketing theory needs a new framework. The tools exist — signaling theory, brand equity models, earned media measurement, employer branding research — but they have never been assembled into a coherent framework for analysing R&D as a marketing activity. The field needs models that can account for the fact that a Nature paper and a Super Bowl advertisement both build brand equity, but through fundamentally different mechanisms with different credibility profiles, different decay rates, and different audience effects.

Conclusion: The Most Expensive Marketing Campaign That Nobody Calls Marketing

The evidence presented here supports a clear thesis: R&D investment generates substantial, measurable brand-building returns through signaling to consumers (innovation reputation), investors (firm value and risk reduction), and potential employees (employer brand and recruitment efficiency).

DeepMind’s trajectory — from a $162 million annual cost centre to a Nobel Prize prestige asset — illustrates how R&D publicity can compound over years in ways that conventional marketing cannot. Tesla’s trillion-dollar brand built on zero advertising demonstrates the thesis at its most extreme. The financial markets consistently show that R&D creates intangible value beyond direct innovation outputs, and the employer branding literature quantifies the recruitment advantages that research reputation provides.

The novel claim is not that R&D builds brands — practitioners at Google, Tesla, SpaceX, and many other firms clearly understand this intuitively. The claim is that academic marketing theory has no framework for analysing, measuring, or optimising this effect. The Mizik-Jacobson measurement paradigm, the 4Ps curriculum, the R&D–marketing interface literature, and the advertising-effectiveness research tradition all systematically exclude R&D’s marketing function from their models. The result is that one of the most powerful brand-building mechanisms available to modern firms remains unmeasured, unoptimised, and absent from the education of every marketing professional.

In an era where the most valuable companies in the world are technology firms whose brands were built primarily through innovation rather than advertising, this is no longer an academic curiosity. It is a gap with billion-dollar consequences.

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