Category: Perspectives

We think about brands and their impact on business…all day, every day. About the issues, the trends, the opportunities. About how the world is changing and what it takes for clients to succeed.

  • Culture of Innovation

    In business, Innovation is a concept that constantly re-invents itself.

    Whether invigorating established business segments with fresh ideas or inventing entirely new business categories, innovation has become a foundational value for today’s successful corporations.

    But to be more than a buzzword, innovation must be supported and promoted by management and employees throughout a corporation’s culture. This consistent Culture of Innovation (COI) can be seen in the ways a company puts a priority on advancing new ideas that will create value across all operations.

    In theory, a Culture of Innovation would seem to be a worthwhile pursuit for any company to nurture. However, measuring and valuing the financial impact of a Culture of Innovation has eluded many corporations. Typically, organizations define innovation as a focus on R&D, or by the number of patents granted and new products developed.

    While these are all significant quantitative components of innovation, a cultural definition for innovation must encompass the entire company, and the quantifiable results should be reflected in the financial performance as a whole.

    These thoughts opened my doctoral dissertation that I defended last August at the Muma School of Business, University of South Florida. I was curious to find out how an engaged audience of impartial observers viewed the importance of a Culture of Innovation.

    Culture of innovation and its impact on the cash flow multiple

    Flow multiple and it's impact on cash

    Utilizing the quantitative research database of the CoreBrand Index™ (CBI) my dissertation studied, for the first time, the impact of the Culture of Innovation attribute associated with 160 large public companies. The findings were then analyzed with the cash flow multiple (CFM), which is a firm-wide financial variable that explains the premium investors are willing to pay over the cash flow of the corporation.

    The CFM is calculated by dividing the stock price per share by the cash flow per share, which provides a calculation that reflects the premium value of market capitalization. Since estimates of future cash flow are a component of quarterly reports, the CFM has the advantage of being able to project expected returns into the future; this helps a company to evaluate the potential return on investment (ROI) for capital spending required for improving—and innovating—intangible assets.

    The analysis evaluated whether COI is more or less predictive of the CFM than historical attributes collected in the long running, and highly reliable CoreBrand Index. The dissertation verified CoreBrand’s past research and reconfirmed that each of the individual attributes in the CoreBrand Index contributes a positive effect to the firm’s market value.

    The study supported the conceptual framework that adding the additional attributes to the intangible assets of a company could explain even more of the unexplained variable associated with stock market value, which is paramount to the development of the emerging theory of intangible capital.

    By adding Culture of Innovation attribute to the historical attributes measured by CoreBrand, the predictability of the cash flow multiple improved from 64% to 77%. This is not only statistically significant, but also an important breakthrough on the ability to forecast the potential return for investments made in intangibles such as brands.

    The Theory of Intangible Capital

    Flow multiple and it's impact on cash

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  • A message from our CEO

    WELCOME TO TENET’S 2019 TOP 100 MOST POWERFUL BRANDS REPORT.

    This is a tumultuous time for corporate brands and leaders navigating the ever-growing complexities of global markets.

    The past five years have seen the most significant expansion of brand value for U.S corporate brands in the history of the CoreBrand Corporate Brand Index. Yet, at the same time, some of the most iconic brands in history have fallen precipitously.

    Without question, Digital Transformation and new business models are setting the standard. The dramatic rise of “platform” based companies, such as Facebook, Amazon, Apple, Netflix and Google, is forcing others to follow their lead. Affectionally called “FAANG” stocks after their initials, these notable examples account for 40% of the rise in the market and are even larger in Brand Value. In this current report, FAANG stocks represent a staggering $300 Billion of brand value.

    A common thread that makes these companies unique is their unrelenting embrace of data to drive their platforms. For many of the companies that are lagging behind, closing the data gap is daunting as Big Tech is accelerating the digital economy at a blinding pace with levels of capital investments that are hard to match. So much so, regulators around the world are increasingly concerned about the power these corporates wield.

    Brand Power is also playing an outsized role in the success of these leaders. Brand is not only a result of a well-spent investment in communications; it’s also a tool that focuses and delivers a competitive advantage. The network effect of the brand experience is well-played by these platform companies, and they are taking advantage of the opportunity.

    WITH GREAT BRANDS COME GREAT RESPONSIBILITY

    Technology companies have become the darlings of today’s businesses. They are employers of choice, enjoy strong reputations for management, and are loved by investors. This multiple dynamic becomes a powerful source of capital that enables these firms to scale in ways that most experts thought was not possible.

    But there’s also a downside to so much brand power. New players are quickly learning that there is also a greater risk in being a big brand. Facebook, one of our fastest risers over the years in the Top 100, has declined for the first time in our research. Their misstep on consumer privacy and a blind eye to ethics has put Facebook’s management and reputation on the defensive. We expect similar stories to unfold in the years ahead as the world grapples with the profusion of intelligent systems, including artificial intelligence, machine learning and advanced analytics. These new technologies can deliver experiences that touch consumer emotions, and more darkly, even manipulate the masses. It’s a power of branding that is not yet well understood by these companies. Ultimately, how companies build stronger governance of their systems and how they align with consumers will be key.

    TRADING IN BRAND VALUE

    2019 is our third year as the data engine for the only brand-based index, BVAL, and the publicly traded ETF under the same stock symbol. The Brand Value Index seeks to find unrealized value in strong brands such as some American icons like GE, Amazon and Microsoft. That may not be a great sign for these companies, but a good one for investors. Our research shows that Brandpower tend to fall at a slower rate and are very hard to destroy rapidly. Even then, brands can show tremendous resiliency. As under-performing brands like GE struggle with the shift, we believe that the best of them—especially those companies with management teams who can embrace transformation—have an opportunity to create new value. Of course, a few will flame out, but that’s the exception, not the rule.

    BRAND SCHOLARSHIP EXPLORES INNOVATION

    Our work in exploring how perceptions of innovation may relate to a company’s ability to survive is telling. Dr. James Gregory, our Chairman Emeritus, recently completed a compelling paper that explores the relationship of innovation to a company’s valuation. He discovered that perception of innovation is a predictor of a company’s revenue multiple. Stop for a moment and think about it—a perception of any kind that predicts a financial component should be a wake-up call for all CEO’s and CFOs. Dr. Gregory’s work is a remarkable breakthrough that also illustrates the percentage of a company’s stock price is attributable to its corporate brand investments, as well. The work by our CoreBrand team to help leaders understand the value in these intangible assets is a source of great pride at Tenet, and an important tool for corporate leaders.

    As you study the Top 100 brands and their movement in this report, it’s a look into the performance of leading companies, how they manage their brand asset, for better or worse. Our aim is to help leaders across the C‑suite and boards who must make difficult decisions have greater understanding of the role their incredible brand asset plays in driving corporate value, performance and resiliency.

    Hampton Bridwell
    CEO, Tenet Partners

  • Frequently Asked Questions

  • A Brand New Look at the Election

    A Brand New Look at the Election

    There was much to keep our attention during this election season. As a result, I found my professional role as a brand strategist inserting itself into my personal role as a voter. My natural tendency was to glean where I saw brand concepts playing a key role – in our perceptions of the candidates, their platforms and the multitude of consumer businesses that chose to get involved.

    Personality drove brand perceptions

    A strong brand positioning integrates both positioning attributes and personality attributes. Shorthanded, positioning integrates both what you say as well as how you say it or the tone of voice. This construct was evident by both candidates’ positioning, whether by intention or by perception. In addition to their differing policy viewpoints, which in large part, define what they say or what they stand for, President Trump and President-elect Biden have distinctly different personalities. While some of that personality is an extension of their party’s platform, much of it is inherent to who they are or who they chose to appear as to the electorate.

    This difference in personality became highly relevant as the election became about identity over policy. Their identities (or personalities) defined the brand of each candidate.

    Trump’s core supporters see him as aggressive, a bold outsider to the system, and fighting the good fight. His detractors see him as self-serving, dishonest and reckless. Biden’s voters see him as “not Trump.” His active supporters also define him as authentic, experienced, a stalwart (having gracefully persevered through a lifetime of tragedies) and sincere. His detractors see him as an entrenched insider, outdated and weak. The narrative for this election was essentially cast as a good versus evil storyline. Which candidate was good and which was evil was defined by how you perceived their personality, and thus, their brand.

    Platforms defined campaign slogans

    For each candidate, multiple slogans were used at varying points over the campaign. Trump brought forward his ubiquitous 2016 campaign theme, “Make America Great Again,” as well as others such as “Law and Order” and “Promises Made, Promises Kept.”

    Biden launched with a “Battle for the Soul of the Nation,” later introduced “Build Back Better” at the Democratic National Convention and complemented with other ideas, including “Unite for a Better America” and “Our Best Days Still Lie Ahead.”

    For me “Make America Great Again” rose to the top as the core reflection of what Trump’s campaign stood for in the eyes of its supporters. Biden’s slogans were less sticky and no one slogan seemed to identify the campaign.

    Reflecting back to what defines a brand positioning, these slogans are a distillation of “what you say.” In essence, they serve the same role as a tagline.

    A tagline is an external expression of an internal brand positioning. It can serve as a rallying cry for employees or in this instance, for supporters. It offers a compelling shorthand for the positioning, and if done well, is concise, memorable, relevant and differentiating.

    Whether or not you agree with the position that underlies these slogans (taglines), most are objectively successful from a brand standpoint. “Make America Great Again” is deeply embedded in the Trump ethos. It emotionally ties the campaign to its supporters. It’s memorable. And it certainly became a rallying cry. That said, I do question the use of the same tagline after four years in office. It seemed like an evolution to “Keep America Great” was attempted, but didn’t stick. This in itself reinforces the strength of the original tagline.

    For Biden, “Battle for the Soul of the Nation” was his best effort at creating a powerful emotional connection. “Build Back Better” never attracted quite the same level of emotion, but structurally, its memorability is enhanced by the alliteration. And tactically, it was tied to every Biden proposal from jobs and economic recovery to racial equity and pandemic policy. Its strength was in its consistency at all levels of campaign messaging, exactly how a positioning statement and its shorthand tagline should be implemented.

    Corporate voices demanded to be heard

    From large consumer companies to financial institutions, many brands attempted to turn votes into marketing. Boosting voter turnout, encouraging voter registration, aligning with specific candidates – many companies attempted to accomplish at least one of these objectives, often times while simultaneously selling product. Like no other election I recall in my lifetime, the number of companies and corporations demanding to have a voice in the election was near immeasurable. According to a recent article in Fortune, “over 2,200 companies stepped up their civic responsibility efforts, embracing their power to drive increased voter participation.”

    And yet, such action risks alienating a large percentage of buyers and users. Seemingly, it was a risk many companies were willing to take this election. In our article entitled, “Five ideas to help brands make an impact” we spoke about the importance of speaking out and leading society forward in a way that is authentic and true to their brand platforms. I’d argue that many companies took that advice when considering their election-related outreach.

    For Gen Xers (like me) the first corporate election initiative that comes to mind is likely MTV’s long-standing “Rock the vote” partnership. For 30 years, MTV has been partnering and funding this high-level initiative to encourage voter registration. It is impossible to separate MTV from the program, as it’s become an authentic part of what the company stands for.

    This year sports leagues, most especially the NBA and its players, complemented MTV’s work with initiatives to encourage voter registration and enable voting in their stadiums. A natural outcome of players’ outspokenness and powerful actions in support of Black Lives Matter and in direct response to the shooting of Jacob Blake in Kenosha, these get-out-the-vote initiatives seemed natural and authentic. And more than any other sport, the NBA players’ voices combined and elevated to the league level.

    Other companies got involved by giving employees time off to vote. JPMorgan Chase, Coca Cola and Twitter, among others, ensured that at least one of the boundaries that prevents people from voting was removed. It’s an action that demonstrated leadership, I believe, in hopes that others – and perhaps the federal government – will follow.

    And in yet another effort that one might cynically describe as less generous and more aimed at selling product, many fashion companies united behind the “I am a voter” campaign by offering for purchase a mix of approachable and high-end products featuring the slogan. The outreach is defined as a “public awareness campaign that aims to create a cultural shift around voting and civic engagement by unifying around a central truth: that our democracy works best when we all participate.” Bringing together fashion and social media with designs from the likes of Stuart Weitzman, Jennifer Meyer, Tory Burch and Grayson, ensured the importance of voting was emblazoned on celebrities, influencers and everyday folk across the country. If nothing else, awareness was raised.

    Perhaps this election was unlike any other. And it looks like it may continue to be. As you tire from the rhetoric, distract yourself like I do, by finding where brand is playing a role.

  • Elevating brand ROI to a science

    Elevating brand ROI to a science

    “Data science” is a term unfamiliar to most marketers. I believe it should—and will—be given more attention because in my view it can be a true game-changer. This highly evolved form of analytics can, if employed properly, open the door to new actions that optimize the return on brand investment.

    To improve ROI look forward, not back

    When CMOs think of ways to optimize ROI they generally turn to tried-and-true metrics. What was the response rate on a campaign? What net promoter scores are we achieving? How many clicks is the website getting? Measurements such as these are valid, but they all have one thing in common: they’re retrospective.

    Marketers look at dashboards and reports, and use that historical data to decide what to do next. That’s the way it’s always been done, but it’s as much art as science. It’s future planning based on hindsight.

    What intrigues me about applied data science is its potential to proactively solve targeted business problems. Adding machine learning, AI, unstructured data and models that leverage these new elements to structured operational data opens up completely new areas of exploration, making it possible to predict the future more confidently and forecast more accurately. It’s a shift from understanding what happened to understanding why it happened: going beyond correlation to reveal causation.

    This predictive foresight is a fundamental driver of improved ROI on brand investments. Using evidence-based prescriptive intelligence to drive action brings the solution closer to the challenge. That boosts effectiveness from the outset, meaning less money spent for more benefit.

    Let’s take a look at a specific example: customer churn. What specific actions does a business have to take to boost retention? An analysis of customer attributes and the actions they’ve taken reveals something about the those who leave compared to those who stay, but that macro-level insight is very broad. Digging in to both the structured and unstructured data, however, can help marketers connect the dots and change outcomes. Spotting an unhappy customer early makes it possible to take preventive steps before that customer leaves…and may even prompt that customer to become a brand advocate, simply because the company came through in a pinch.

    Getting ahead of problems can have effects that extend across the business. It’s about more than driving sales or improving retention. It might be a manufacturer tracking problem reports to predict warranty claims, or a bank being able to spot anomalies and abnormal behavior to combat fraud. All of this ultimately comes back to the brand because how a business responds to challenges has a real impact on reputation: the brand benefits from the halo effect of a better-run business.

    To better meet your customers’ needs, listen to them

    There’s a treasure trove of useful information in the voice of the customer, contained in everything from market research and survey responses to emails, chats, reviews and customer service transcripts.

    What data science allows CMOs to do is marry those open-ended comments with operational data to generate insights not typically available from structured data. The voice of the customer adds vitally important context.

    There’s a lot of promise in the natural language processing space. By using machine learning and AI, it’s possible to uncover trends and patterns in speech and how people are talking about you. What’s the buzz on social media about your brand? What’s the reaction to your latest product announcement? Are people singing your praises or taking shots at you? Taking these learnings from the realm of random anecdote to rigorous analytic insight and linking actions to outcomes can be an incredibly powerful strategic planning tool.

    You can start from anywhere

    The sophisticated capabilities described here may seem inaccessible, but that’s far from the case. Data science is inherently scalable because it’s a methodology, not a rigidly defined solution. Whatever data is available can serve as the core of an emerging data science capability. For example, customer reviews are available across ecommerce platforms but the scale and complexity would be hard to resolve insights. Using AI and Machine learning is both time and cost efficient, and in this case, get marketers closer to the voice of the consumer. Traditional research methods just can’t achieve this level of efficiency.

    Data science extracts relationships between variables in a way that simply is not possible using reporting and planning tools such as spreadsheets. It’s about taking available data and mining it in a new way to get at what’s driving the outcomes that traditional methods are already reporting. Making more data available and adjusting the models accordingly extends the potential.

    Unanswered business challenges are the true starting point. Experience has shown us that businesses are sitting on a wealth of information, but that the value of that data often goes unrecognized. They have questions that seem impossible to answer, while in reality everything needed to find the answers already exists—it just needs to be looked at in the right way.

    There’s more to explore

    Tenet Partners has a Data Science practice for marketers, rooted in advanced analytics and driven by analytic expertise. To find out more, visit our Data Science offering page.

  • A message from our CEO

    WELCOME TO TENET’S 2020 TOP 100 MOST POWERFUL BRANDS REPORT.

    Few moments in our lives, careers and even mankind’s past are truly remarkable. The 2020 pandemic is our moment. Disease and uncertainty have halted life in every corner of society, reshaping and reorganizing economies and ecosystems over one of the shortest periods in history. Each shift profoundly impacts us all. This report, while looking back into 2019 and early 2020, aims to help leaders consider the changes that will impact their companies, specifically the corporate brands.

    For over 25 years, Tenet has tracked corporate brands through the longest longitudinal study of its kind. This body of work drives the only exchange traded fund that seeks unrealized value in corporate brands, guides CMOs, CEOs and boards, and helps brand managers understand how communication investments impact company value.

    This year’s report, and the supplemental report coming later this year, have special importance to our team. For 2019 and Q1 of 2020 leading into the pandemic, corporate brands were at their highest BrandPower and brand valuations in our research’s history. Apple, Microsoft, Amazon and others achieved enterprise valuations that seemed impossible a decade ago, lifting many boats with them. With few exceptions, brands have enjoyed a robust time of growth.

    Today, we see vast swaths of winners and losers in the pandemic. What is interesting, and unique in modern history, is witnessing many industries face dramatic headwinds while others rise to newfound dominance. It may take years to close the divides between the haves and have nots, if it’s even possible.

    Pre-pandemic, consumers had settled into strong B2C and B2B brand relationships. And, in a heartbeat, those relationships shifted. What was essential, was no longer. What is essential now, is redefining our take on companies and their existence. Many consumers are choosing new brands as essential to their lives in this moment. And, craving ones that they have been forced to put aside. Lastly, they’ve deemed new brands as essential to them going forward. The essential brand is the essence of this year’s report. We hope that no matter where you are on the continuum of being essential, that these strategies can help all companies create sustainable competitive advantage and resiliency.

    This report is a pre-pandemic snapshot — our follow-up later this year will look toward the other side of the recovery. Both reports will provide CMOs and brand leaders sound guidance to re-center and move forward.

    Hampton Bridwell
    CEO, Tenet Partners

  • The AI Capability Index: Top 10 AI Branding Firms

    Republished from bestbrandconsultants.com

    Every consultancy now claims AI capability. Far fewer can support the claim through real capabilities that impact client performance. This index assesses the ten branding firms with the most substantive, verifiable artificial intelligence capabilities: proprietary platforms, longitudinal data assets, agentic systems, and formal AI partnerships, framed by leading market analysis on the transformation of professional services.

    • 10 firms assessed
    • 4 capability dimensions
    • 5 documented market shifts

    0.0 Abstract: Findings in brief

    1. Tenet Partners holds the strongest combined platform, agentic, and data-asset assessment among the ten firms in this index, based on CorebrandAI‘s patent-pending architecture, real-time signals, and the 35-year Corporate Branding Index® training data, all owned outright.
    2. Prophet operates the category’s most fully realized application of agentic AI to marketing through MAIA, its multi-agent platform with multi-LLM access and a vetted marketing-AI partner network.
    3. Accenture Song deploys AI for brand and marketing at the greatest scale of any firm assessed, though its capability runs substantially through Amazon, Google, and venture-stake partnerships rather than owned IP.
    4. The index’s governing principle: owned, proprietary, and independently validated AI capability rates above partner-accessed infrastructure, because owned capability persists when partnerships change and cannot be procured by a competitor.
    5. The market context is structural, not cyclical: leading market analysis predicts 60% of brands will use agentic AI for one-to-one interactions by 2028, and 90% of B2B buying will be intermediated by AI agents in the same period.

    1.0 Market context

    In January 2026, a leading market analysis firm published research describing what it calls a crucible moment for the services industry. Artificial intelligence is dismantling the consulting business model built on labor leverage, time-based pricing, and tool implementation, compressing project timelines, shifting purchasing power from IT to business leadership, and forcing a pivot from selling resources to delivering measurable outcomes.

    For brand consultancies, the implications are direct. Research from the same leading market analysis firm finds that 82% of business leaders expect their company’s identity to change significantly to keep pace with AI, and that companies with a strong brand strategy are twice as likely to exceed growth goals. At the same time, the buyers of brand work are under pressure of their own: a 2026 survey of marketing spending found marketing leaders allocating 15.3% of budgets to AI while only 30% report the organizational readiness to scale it. The gap between AI ambition and AI capability, on both sides of the client relationship, is now the defining commercial dynamic of the category.

    The firms in this index are responding in structurally different ways: some by building proprietary platforms, some by scaling decades of longitudinal data through machine learning, some by leveraging the AI infrastructure of a parent network, and some by assembling open ecosystems of best-in-class AI partners. Each approach solves distinctive challenges for clients seeking growth, reinvention, sustainable futures, or a deep management system for brand value and equity.

    60%
    of brands will use agentic AI to deliver streamlined one-to-one customer interactions by 2028, according to 2026 marketing predictions research from a leading market analysis firm.
    90%
    of B2B buying will be intermediated by AI agents by 2028, a structural change in who, or what, sits between a brand and its buyer.
    40%
    of enterprise applications will feature task-specific AI agents by the end of 2026, up from less than 5% in 2025.
    2x
    Companies with a strong brand strategy are twice as likely to exceed growth goals; the importance is rising as AI-generated content raises the premium on distinctive, trustworthy positioning (2026 brand and business strategy survey, leading market analysis firm).
    2029
    AI-services revenue is forecast to more than double by 2029 at a 16.2% compound annual growth rate, even as large traditional providers see growth slow to mid-single digits.

    “Intelligence at scale is required beyond individual consultant expertise.”

    One of five market shifts identified in January 2026 research from a leading market analysis firm

    2.0 The index: Ten firms, assessed on evidence

    Entries are assessed on four dimensions (proprietary platform, agentic capability, data assets, and ecosystem) using the tint system defined in Section 5.0. Ratings reflect publicly documented evidence, not marketing claims.

    2.01

    Agentic marketing

    San Francisco · Founded 1992 · 500+ across 15 global offices · Independent

    Prophet has moved further and faster than most of its peers in converting AI ambition into operating infrastructure, and it has aimed that infrastructure squarely at the marketing organization. In early 2026 the firm launched MAIA (Multi-Agent Intelligent Assistant), an agentic AI platform providing access to multiple frontier models (Anthropic, Google, OpenAI) and a portfolio of pre-built, customizable agents spanning marketing research, insights, innovation, validation, and campaign activation. Early deployments include a custom market-sizing agent that reduced weeks of analysis to hours for a consumer brand, and a bespoke multi-agent system for a large software company.

    MAIA sits within a broader architecture: the AI Accelerator Network assembles vetted partners including Jasper (agentic marketing), Quilt.AI (cultural intelligence), and consumr.ai (AI customer twins), while a partnership with Lyzr adds applied AI engineering capability. The firm’s annual AI-Powered Consumer Study, which tracked consumer GenAI adoption rising from 45% to 73% between 2024 and 2026, gives its strategy work a proprietary evidence base. For clients of CVS Health, Salesforce, T-Mobile, and Marriott caliber, Prophet is the clearest example in this index of agentic AI applied to marketing. Its center of gravity is the CMO’s marketing agenda (insight, content, campaigns, and growth programs), with brand as one lever among several rather than the organizing system.

    Capability assessment

    • Platform Established
    • Agentic Established
    • Data assets Developing
    • Ecosystem Established

    Documented evidence: MAIA agentic platform (launched Feb 2026; available internally, with client co-creation phased in later in the year) · AI Accelerator Network with Jasper, Quilt.AI, consumr.ai · Lyzr strategic partnership · Annual AI-Powered Consumer Study, second edition

    2.02

    Brand value system

    New York · Boston · Columbus · Los Angeles · 50 years · A Brandlogic Corp company · “Bridging brands to futures”

    Tenet’s 2026 repositioning, Bridging brands to futures, states plainly what the rest of this index measures indirectly: the work of a brand consultancy is no longer to codify what a company has been, but to help it recognize future possibilities and assertively lay claim to them. It is the positioning most directly aligned with the market condition leading market analysis documents: 82% of business leaders expect their company’s identity to change significantly to keep pace with AI. Tenet delivers it through a stated triad of insight, foresight, and brand innovation, a full brand-building practice spanning strategy, identity, and deployment, with foresighting a named service rather than a slide. The credentials behind the claim span 50 years: a client record running from GE, IBM, and Dow to PepsiCo, Merck, John Deere, UBS, and the Smithsonian, and a top-three brand strategy agency ranking from Clutch in December 2025.

    What separates the positioning from rhetoric is that foresight, at Tenet, rests on the category’s deepest measurement foundation. The Corporate Branding Index®, developed by Dr. James Gregory beginning in the 1980s, is the longest-running continuous study of corporate brand equity in the world, an unbroken 35-year record measuring the familiarity, favorability, and reputation of the largest publicly traded U.S. companies. Its market-based valuation model was independently validated by Fischer and Hornig (2014) as the only one of nine leading brand valuation methods to demonstrate reliability, convergent validity, and predictive validity in stock returns across a 22-year, 4,879-brand dataset, and it remains the only brand valuation research method audited by the Marketing Accountability Standards Board. A firm cannot see forward credibly without a validated record of what has driven value looking back. Tenet has the longest one there is. And the applied work predates the platform: Tenet began its AI journey in 2018, deploying custom machine learning, natural language processing, and advanced forecasting led by data scientist Kellan Williams, a co-founder of CorebrandAI and Senior Partner at Tenet.

    CorebrandAI, co-founded by Tenet CEO Hampton Bridwell, is the operational engine of the futures positioning, with two patents pending on the architecture. Five integrated modules span deterministic brand valuation implementing four methods within the ISO 10668 framework (Capital Premium, Royalty Relief, Earnings Attribution, and Demand Driver, triangulated into a range built to withstand CFO scrutiny), AI-powered growth driver identification, seven-dimension reputation intelligence, probability-weighted Strategic Foresight (structural force mapping, scenario generation, early-warning signals, and response playbooks), and a C-Suite Briefing Room producing role-specific briefs for CEO, CFO, CMO, and CTO. The modules operate as one multi-step decision workflow: the system ingests live SEC EDGAR data, generates triangulated valuations, sizes growth drivers, produces phased roadmaps with KPIs and executive ownership, runs the scenarios, and synthesizes it all into executive action: the patent-pending synthesis of an agentic decision system reasoning over validated proprietary data, not a general-purpose model with a brand prompt. Where Prophet points agentic AI at the marketing agenda, Tenet points it at the brand itself: brand building and brand value run as a continuous management system: measured as an asset, governed at the C-suite, and tied to enterprise value between rebrand moments, not only during them. The toolset is extending along the same axis: Tenet is also advancing tools for brand governance of AI and for brand asset management that renders assets machine-readable, so brand expression stays governed, and assets are found, interpreted, and applied properly by human teams and AI systems alike. For leadership teams that need brand treated as a measurable economic asset with a forward view (a platform record spanning Dow, Fifth Third, Safelite, and CME Group), the combination has no peer in this index.

    Capability assessment

    • Platform Established
    • Agentic Established
    • Data assets Established
    • Ecosystem Developing

    Documented evidence: 2026 repositioning “Bridging brands to futures” with foresighting as a named service · In-house AI practice since 2018: custom machine learning, natural language processing, and advanced forecasting · CorebrandAI five-module platform: ISO 10668 four-method valuation, brand intelligence, reputation intelligence, Strategic Foresight, C-Suite Briefing Room (two patents pending on the synthesis architecture) · Corporate Branding Index®: 35-year continuous record, 500+ brand library · Fischer & Hornig (2014) independent validation across 4,879 brands · MASB-audited methodology · Live SEC EDGAR integration · CoreBrand data powering the Brand Value ETF (NYSE: BVAL) · Clutch top-three brand strategy agency, December 2025

    2.03

    Enterprise scale

    Global · Accenture (NYSE: ACN) · Formed 2009 as Accenture Interactive, rebranded 2022

    No firm in this index deploys AI for brand and marketing at greater scale. In 2026 alone, Accenture Song launched the Accenture Marketing Investment Navigator, an AI-native unified measurement platform built on Amazon Ads’ authenticated graph reaching over 90% of U.S. households, with initial deployments improving business outcomes by 17% or more at twice the speed of prior approaches. With Google Cloud, it added a Generative Content OS that rebuilds marketing content operations around Gemini Enterprise.

    Song’s agentic commerce position is equally deliberate. Accenture Ventures investments in DaVinci Commerce (branded, governed conversational storefronts inside large language models) and Netomi (agentic customer experience) reflect the firm’s own research finding that over 90% of frequent AI users would switch brands based on an agent’s recommendation. For Fortune 500 organizations undertaking AI transformation where brand, technology, and operations must move together, Song’s combination of strategy, creative, and engineering at 25,000-plus scale remains unmatched, with the tradeoff of enterprise-level engagement economics.

    Capability assessment

    • Platform Established
    • Agentic Established
    • Data assets Established
    • Ecosystem Established

    Documented evidence: Marketing Investment Navigator (AI-native measurement, 2026, powered by Amazon Ads’ graph) · Generative Content OS built on Google Cloud Gemini · Accenture Ventures investments in DaVinci Commerce and Netomi · Google Cloud Global Services Partner of the Year, four consecutive years

    2.04

    Owned AI IP

    New York · Founded 1977 · Independent (exited IPG 2024) · Studios across Americas, EMEA, APAC

    R/GA was building AI-enabled brand platforms before AI was a category (Nike+ remains the textbook case of a connected brand ecosystem), and its return to independence after 23 years inside IPG has visibly accelerated its AI agenda. The firm now positions itself as “an independent creative innovation company for the intelligence age,” designing what it calls intelligent brand systems.

    The structural commitments are concrete: a dedicated global AI Products team with a track record of more than 100 AI products delivered, formed explicitly to build reusable, R/GA-owned IP that clients adapt rather than commission from scratch; the acquisition of AI system design studio Addition in 2025; and capabilities spanning AI strategy, AI product development, agentic applications, and brand AI tools. Marking its 50th anniversary in 2026, the firm partnered with Runway on Forever Founder, a conversational AI trained on its archives, a signal of how thoroughly it treats AI as both medium and product. Best suited to large brands that need brand and technology work genuinely joined up.

    Capability assessment

    • Platform Established
    • Agentic Developing
    • Data assets Developing
    • Ecosystem Developing

    Documented evidence: Global AI Products team with 100+ AI products delivered · Acquisition of AI design studio Addition (2025) · Runway collaboration (Forever Founder) · Nike+ connected-platform heritage

    2.05

    Generative design

    Global · Part of Capgemini Invent · 35+ design and innovation studios · Founded 1969

    frog approaches AI from the discipline where it has always led: the design of systems. Its published work on AI-powered design systems, including a working Figma-native prototype that translates text and imagery into brand design directions in real time, points toward brand-specific generative models acting as engines for design language systems, a structurally different proposition from using off-the-shelf image generation. Its Futurescape: Artificial Realities research program, presented at Milan Design Week 2026, and its work on physical AI and robotics extend that thinking beyond the screen.

    Membership in Capgemini Invent matters commercially. frog’s design and brand capability sits on top of Capgemini’s 270,000-person engineering, data, and AI organization, including Cambridge Consultants’ deep-tech capability, giving clients a path from brand and experience strategy through to production-grade AI implementation. Recent work with Unilever on intelligent marketing systems illustrates the model. The consideration for buyers: frog’s AI strength is delivered through the group rather than as a standalone named platform.

    Capability assessment

    • Platform Developing
    • Agentic Developing
    • Data assets Developing
    • Ecosystem Established

    Documented evidence: Generative design-language-system prototyping in Figma · Futurescape: Artificial Realities research (2026) · Physical AI and robotics design work · Capgemini Invent data & AI backbone

    2.06

    Frontier agency

    Global · Founded 1994 · 2,400+ across 30 countries · WPP Creative (announced Feb 2026)

    AKQA’s AI position rests on two pillars: a creative pedigree few can match: Cannes Lions Grand Prix wins for Digital Craft (2023), Design and Glass (2024), and Innovation (2025); and full leverage of WPP Open, the holding company’s AI-powered marketing operating system. The 2025 appointment of Baiju Shah, formerly Chief Strategy Officer of Accenture Song, as Global CEO signaled the mandate directly: Shah describes AKQA as a “frontier agency” helping clients find new growth, experiences, and brands that combine imagination with advanced AI.

    Client work already reflects the shift: from Lexus’s AI-crafted “Built for Every Kind of Wonder” holiday film to Montblanc Digital Paper, the maison’s first luxury e-writing device. Buyers should note the structural context: in February 2026, WPP announced AKQA would be consolidated with Ogilvy, VML, and Burson under a new WPP Creative division as part of a £500 million restructuring, with agency brands retained but operations unified. That consolidation deepens AKQA’s access to WPP’s AI infrastructure while introducing organizational transition risk worth probing in any selection process.

    Capability assessment

    • Platform Developing
    • Agentic Developing
    • Data assets Developing
    • Ecosystem Established

    Documented evidence: WPP Open AI operating system · Cannes Lions Innovation Grand Prix 2025 · AI-led client work for Lexus and Montblanc · Global restructure for the AI era under CEO Baiju Shah

    2.07

    Human-centered AI

    San Francisco · Founded 1991 · Global studios · Independent

    IDEO’s AI contribution is methodological rather than infrastructural, and for a specific class of problem, that is exactly what is required. The firm that popularized design thinking now operates a dedicated AI Lab within its Emerging Technology practice, helping organizations decide what to build with AI, how it should behave, and why it matters, with people rather than models at the center. Its AI Ethics Cards, four design principles and ten team activities for data-driven product development, remain among the most widely used responsible-AI design tools in the field, and IDEO U has built substantial AI curriculum teaching designers to integrate generative AI across the design-thinking process.

    IDEO’s 2026 IQ research, surveying leaders at 100 of the world’s largest companies, makes the firm’s argument empirically: in a period of rapid technological change, the human behaviors associated with design and creativity are what set the conditions for lasting growth. Clients including Sephora, H&M, Ford, and Moderna engage IDEO when the AI question is as much cultural and organizational as technical. Teams that need production AI engineering on a fixed clock typically pair IDEO’s strategic reframing with a specialist build partner.

    Capability assessment

    • Platform Emerging
    • Agentic Emerging
    • Data assets Developing
    • Ecosystem Developing

    Documented evidence: AI Lab within the Emerging Technology practice · AI Ethics Cards design toolkit · IDEO U generative AI curriculum · 2026 IDEO IQ research across 100 major enterprises

    2.08

    Open orchestration

    Amsterdam · Founded 2015 · 4,000+ across 30+ locations · Independent

    Dept has staked out the contrarian position in the category’s central architecture debate. Where WPP built Open, Publicis built CoreAI, Omnicom built Omni, and Dentsu built Dentsu.Connect, proprietary systems designed to bring clients into a holding company’s ecosystem, Dept launched an open AI orchestration layer that follows users across projects and platforms without vendor lock-in. The firm’s argument, made explicitly against the holdco stacks, is that closed AI operating systems ultimately limit clients as the underlying model landscape shifts.

    The position is credible because Dept committed early: it was among the first major agencies to establish AI transformation as a dedicated offering, with a practice spanning AI strategy, data infrastructure, customer experience, and AI-powered marketing for clients including eBay, Google, and Samsung. For pioneering, digitally mature organizations that want AI capability without inheriting a holding company’s technology roadmap, Dept is the strongest independent alternative at scale.

    Capability assessment

    • Platform Established
    • Agentic Developing
    • Data assets Developing
    • Ecosystem Established

    Documented evidence: Open, model-agnostic AI orchestration layer (2026) · Dedicated AI transformation practice, established early · AI-driven product and content systems for eBay, Google, Samsung

    2.09

    Systems thinking

    New York · Founded by Erich Joachimsthaler · Global offices · Independent

    Vivaldi’s thesis is stated plainly on its own masthead: AI won’t create value as a tool; it creates value as a system. The firm operates Fifth Season, its AI platform for building interconnected decision systems where high-value choices connect, learn, and compound, and backs the thesis with research: its AI Report exposed the limits of superficial AI adoption and introduced the “Superpower of Duality” framework for rethinking customer value propositions in an AI economy.

    Two 2025–26 moves extend the firm’s reach. A strategic partnership with Silverside AI, the innovation lab founded by Pereira O’Dell and Serviceplan Group, pairs Vivaldi’s brand and business reinvention consulting with hands-on AI implementation for Fortune 500 marketing organizations, and a partnership with Andersen Consulting adds global delivery scale. Founder Erich Joachimsthaler’s platform-and-ecosystem thinking (The Interaction Field) gives the firm unusual intellectual depth on precisely the question leading market analysis says now defines the market: how brands create value in interconnected, AI-mediated systems rather than linear channels.

    Capability assessment

    • Platform Developing
    • Agentic Developing
    • Data assets Developing
    • Ecosystem Established

    Documented evidence: Fifth Season AI platform · Silverside AI strategic partnership (2026) · Andersen Consulting partnership (2025) · AI Report and “Superpower of Duality” framework

    2.10

    Predictive demand

    Founded 1941 by Walter Landor · Part of WPP · Global studio network · Landor companies: amp, BDG, Deep Local, ManvsMachine

    Landor’s analytical instinct is the oldest in this index: Walter Landor was among the first to apply consumer research to design when he founded the firm in 1941, and the firm’s archive now sits in the Smithsonian. The modern expression of that instinct is the BrandAsset® Valuator (BAV), described by WPP as the world’s largest brand database: continuous consumer perception research, run on a uniform methodology across roughly fifty markets for more than three decades, scoring tens of thousands of brands on four measured pillars (Differentiation, Relevance, Esteem, and Knowledge). BAV operates as a diagnostic of how brands grow and decline, a prescriptive engine for strategy, and an accountability benchmark over time; it has fed Landor’s Breakaway Brands analysis, cited in Fortune and Forbes, since 2004, and a dedicated Brand Performance practice connects the data to financial modeling, giving working substance to the firm’s promise to make brands “more valuable and less vulnerable.”

    What earns Landor its place in an AI index is where BAV is now pointed. Operated with WPP sibling BAV Group, whose stated mandate is making brand demand “understandable, predictable, and shapable,” the database underwrites published research on how brands surface inside AI platforms, including work on the AI brand metrics that determine machine-side visibility (The Algorithmic Persona Imperative) and the finding that 60% of shoppers expect to use AI to help them buy within the next year. On the delivery side, Landor operates on WPP Open, the group’s agentic marketing platform, with creative technologists Deep Local inside the Landor group. The buyer’s consideration follows this index’s weighting principle directly: BAV is decades-deep, continuously validated, and effectively impossible to replicate, and it is a WPP asset, accessed through the network rather than owned at the firm level. It is the strongest partner-accessed data position in this index: the structural mirror image of Tenet’s owned Corporate Branding Index®.

    Capability assessment

    • Platform Developing
    • Agentic Developing
    • Data assets Established
    • Ecosystem Established

    Documented evidence: BrandAsset® Valuator: described by WPP as the world’s largest brand database; four-pillar methodology across ~50 markets and 30+ years · Breakaway Brands analysis based on BAV data, published since 2004 · BAV Group AI brand-metrics research (“The Algorithmic Persona Imperative”) · WPP Open agentic marketing platform · Landor companies including creative technologists Deep Local

    Summary table: The ten firms at a glance

    No.FirmNamed AI platform or IPCapability routeDistinguishing strength
    2.01ProphetMAIA multi-agent platform; AI Accelerator NetworkOwned platform + partner networkAgentic AI for marketing
    2.02Tenet PartnersCorebrandAI: five modules, two patents pending; Corporate Branding Index® (35 years)Owned outright: platform, data, workflowBrand value as a management system; strongest combined Platform · Agentic · Data
    2.03Accenture SongMarketing Investment Navigator; Generative Content OSPartner-built (Amazon, Google) at enterprise scaleScale
    2.04R/GAGlobal AI Products team; Addition acquisition; 100+ AI productsOwned IP, independentIntelligent brand systems
    2.05frogGenerative design-language-system prototypingVia Capgemini Invent group capabilityAI-native design systems
    2.06AKQAWPP Open operating systemHolding-company platformCreative excellence at network scale
    2.07IDEOAI Lab; AI Ethics Cards; IDEO U curriculumMethod-ledHuman-centered AI adoption
    2.08DeptOpen, model-agnostic AI orchestration layerOwned architecture, vendor-neutralArchitectural freedom
    2.09VivaldiFifth Season platform; Silverside AI partnershipOwned platform + implementation alliancesAI systems strategy
    2.10LandorBrandAsset® Valuator (BAV); Breakaway Brands analysisVia WPP / BAV Group networkPredictive demand data at scale

    The differentiating question is no longer whether a firm uses AI. It is what the AI generates from.

    Editorial thesis of this index

    3.0 The quadrant: Ownership against maturity

    The quadrant plots the Section 2.0 assessments on the two variables this index argues matter most. The vertical axis is AI capability maturity: a composite of each firm’s Platform, Agentic, and Data assets ratings. The horizontal axis is capability ownership, the weighting principle defined in Section 5.0: whether a firm’s AI capability is owned outright (its own platform architecture, its own data) or accessed through technology partners, data partners, and holding-company operating systems.

    Read together, the axes separate four structural positions. Firms in the upper left deliver established AI capability at scale through alliance: powerful, but contingent on partnerships that can change. Firms in the upper right own what they operate. Tenet Partners holds the furthest position on both axes together: the only firm in the index combining established capability across platform, agentic workflow, and data with outright ownership of all three.

    ALLIED · ESTABLISHED OWNED · ESTABLISHED ALLIED · EMERGING OWNED · EMERGING PARTNER-ACCESSED OWNED / PROPRIETARY CAPABILITY OWNERSHIP → EMERGING ESTABLISHED AI CAPABILITY MATURITY → 2.01 Prophet 2.02 Tenet Partners 2.03 Accenture Song 2.04 R/GA 2.05 frog 2.06 AKQA 2.07 IDEO 2.08 Dept 2.09 Vivaldi 2.10 Landor
    Positions are editorial judgments derived from the Section 2.0 capability assessments and the ownership weighting defined in Section 5.0. Distances are directional, not measured. The tinted zone marks the owned-and-established quadrant.

    4.0 Five shifts reshaping the services market

    January 2026 research from a leading market analysis firm identifies five fundamental shifts. Each is a test that buyers can apply directly to any firm in this index, and each explains a design choice visible in the entries above.

    1. 4.1 Business buyers replace IT as decision-makers

      Economic buyers in the business (CMOs, CEOs, chief growth officers) are now the primary decision-makers for AI investment. Firms in this index sell brand and growth outcomes to that buyer, not technology to IT.

    2. 4.2 Answers and results replace tools as the deliverable

      Clients no longer buy discrete tools and applications; they buy resolved questions and measured outcomes. Accenture Song’s Marketing Investment Navigator and Tenet’s Foresight platform are structured around this shift: delivering decisions, not dashboards.

    3. 4.3 Value-based pricing replaces labor cost-plus

      When AI compresses a six-week analysis to hours, as Prophet’s market-sizing agent demonstrably does, pricing tied to hours collapses. Firms with owned platforms and IP can price against value created; firms selling only staffed time cannot.

    4. 4.4 Enterprise-specific solutions beat generic platforms

      The research finds preference moving toward solutions built for a specific enterprise rather than one-size-fits-all market platforms. R/GA’s reusable-but-tailored IP model and Dept’s open orchestration layer are direct responses; Tenet’s client-specific application of thirty years of category data is another.

    5. 4.5 Intelligence at scale beyond individual expertise

      The consultant’s individual expertise is no longer the ceiling of a firm’s intelligence. The firms in this index have institutionalized intelligence (in platforms, longitudinal datasets, agent portfolios, and partner networks) that compounds beyond any single engagement team.

    5.0 Method: How capability was assessed

    Each firm is assessed on four dimensions using publicly documented evidence: company announcements, analyst coverage, trade press, and published research. Ratings are editorial judgments of documented capability; they are not scores supplied by the firms and should be read as directional, not precise.

    Platform: a named, in-market AI platform or owned AI IP. Agentic: documented agentic systems (autonomous multi-step agents in research, delivery, or client products). Data assets: proprietary data the firm’s AI reasons over, weighted for longitudinality and financial linkage. Ecosystem: formal AI partnerships, acquisitions, or parent-network infrastructure.

    One weighting principle governs all four dimensions: owned, proprietary, and independently validated capability rates above partner-accessed capability. A platform built on a firm’s own patented architecture and its own longitudinal data outrates a platform assembled on a technology partner’s models and a data partner’s graph, because owned capability persists when partnerships change, prices against value rather than pass-through cost, and cannot be procured by a competitor. This is the same logic leading market analysis applies to the market at large: enterprise-specific solutions gaining preference over generic platforms, and intelligence at scale that belongs to the firm rather than to its vendors. It is why Tenet Partners, with patent-pending architecture, a 35-year validated data asset, and an integrated agentic decision workflow (all owned outright), carries the strongest combined Platform, Agentic, and Data assessment in this index, ahead of larger firms whose capability runs through Amazon, Google, or a holding company’s operating system.

    Established
    Documented proprietary capability in market: a named platform, owned IP, or a validated longitudinal data asset.
    Developing
    Capability delivered through formal partnerships, parent-network infrastructure, or announced systems with limited public deployment evidence.
    Emerging
    Experimentation, method, and education rather than infrastructure. Valuable for the right problem; not a production capability claim.

    6.0 Questions buyers ask

    Which branding firm has the deepest proprietary brand data for AI?

    Tenet Partners. Its Corporate Branding Index® is the longest-running continuous study of corporate brand equity in the world: an unbroken 35-year record with independent academic validation (Fischer & Hornig, 2014) and MASB auditing behind it. CorebrandAI converts that record into a five-module intelligence platform spanning ISO 10668-aligned valuation, reputation intelligence, and strategic foresight, with two patents pending. The asset cannot be replicated quickly at any price, because the value is in the years.

    Which firm has the strongest combined platform, agentic, and data capability?

    Under this index’s methodology, which weights owned, proprietary, and independently validated capability above partner-accessed infrastructure, Tenet Partners carries the strongest combined assessment across Platform, Agentic, and Data assets. CorebrandAI is a patent-pending, in-market platform whose five modules operate as one integrated agentic decision workflow, reasoning over a 35-year validated proprietary dataset the firm owns outright. Larger firms deploy AI at greater scale, but their capability runs substantially through Amazon, Google, or a holding company’s operating system: capability that changes when the partnership does.

    Which firm should a Fortune 500 company choose for full AI transformation?

    Accenture Song is built for exactly that engagement: eight-figure budgets, multi-year timelines, and programs where brand, technology, operations, and organizational change must move together. Prophet offers comparable agentic sophistication with a more focused, marketing-centered delivery model. Tenet with CorebrandAI enables organizations to build a management system of record for the C-suite to drive brand value.

    What is the difference between a firm using AI and a firm with AI capability?

    A firm using AI has adopted general-purpose tools its clients could adopt themselves. A firm with AI capability has something the model alone cannot supply: proprietary data, owned platforms, documented agentic systems, or formal AI partnerships. Every entry in this index lists documented evidence precisely so buyers can make that distinction firm by firm.

    How does AI change what a brand consultancy is for?

    As leading market analysis shows, AI agents will increasingly intermediate discovery and buying: 90% of B2B purchasing by 2028. Brands must now be legible to machines as well as memorable to people. The consultancy’s job expands from positioning and identity to designing brand systems that AI platforms can retrieve, interpret, and recommend, and to proving, with data, that brand investment drives business outcomes.

    Are independent firms or network firms better positioned for AI?

    The evidence cuts both ways. Networks contribute infrastructure at scale: WPP Open behind AKQA and Landor, the BAV database behind Landor, Capgemini’s engineering behind frog. Independents contribute speed and structural freedom: R/GA formed its AI Products team only after exiting IPG, Dept built its open orchestration layer explicitly against the holdco stacks, and Tenet’s employee ownership let it invest in AI five years before the category moved. The right answer depends on whether a client values scale of infrastructure or freedom of architecture.

    The AI Capability Index is a Tenet Partners perspective on the state of artificial intelligence capability among the world’s leading branding firms. Research compiled July 2026 from company announcements, published analyst research, trade press, and firm publications. Capability assessments are editorial judgments based on publicly documented evidence.

  • CPG brands remain prominent in Tenet Partner’s 2019 Top 100 Most Powerful Brands study, but slipping

    Losing relevance vs. more digitally-oriented brands

    The traditional CPG powerhouses are facing unprecedented challenges due to shifting consumer usage and purchase preferences, as well as technology advances impacting global commerce. Our recently released report, 2019 Top 100 Most Powerful Brands shows CPG brands remain prominent in the rankings but are slipping. The data used in the report is derived from our CoreBrand Index which calculates a company’s brand strength, or, as we like to call it, “BrandPower.”

    BrandPower is a weighted composite of Familiarity and Favorability metrics, delivering a single benchmark for brand strength and its ability to impact business results. This metric, expressed as an index, has been validated by the Marketing Accountability Standards Board (MASB) and tracked for over 25 years.

    Among this year’s Top 100 are 17 consumer packaged goods (CPG) brands, including both food & beverage as well as personal care & household products brands, 7 of which fall within the Top 20 (with 3 in the Top 10). Among these 17 brands, Clorox (+32 spots) and P&G (+18 spots) have seen the most improvement since 2014 while KraftHeinz (-49 spots) and Tyson Foods (-33 spots) have experienced the steepest drops in ranking over that same time period.

    Coca-Cola retains the top spot overall!
    First among the CPG brands – and first among all brands in the Top 100 – is Coca-Cola, which retains its #1 spot for the 18th consecutive year. This perennially iconic brand continues to excel through consistent brand investment, excellent execution, and strategic communications to deliver stability to its brand and its investors. That said, #2 ranked Apple is nipping at its heels, having closed the BrandPower gap between the two from 2.1 to 1.3 points.

    PepsiCo and Hershey round out Top 10
    Rounding out the Top 10 are PepsiCo at #6 and Hershey at #9. PepsiCo has moved up a spot vs. last year due to strengthening of Familiarity and Reputation metrics, while Hershey has slipped several spots from #5 in 2018 and #2 back in 2014, driven by declining Investment Potential. Both have been overtaken by the rise of tech giants Apple, Microsoft, and Alphabet (Google), with Facebook and Amazon not far behind.

    Kellogg’s, General Mills, Colgate-Palmolive and Campbell’s also in Top 20
    Also remaining in the Top 20 this year are Kellogg’s (#15), General Mills (#16), Colgate-Palmolive (#17) and Campbell’s (#19), all of whose rankings have eroded a bit vs. last year, with the exception of Colgate-Palmolive, which has remained steady. Both Kellogg’s (-6 spots) & Campbell’s (-5 spots) have fallen significantly vs. 2014, with Campbell’s experiencing a meaningful drop on our Culture of Innovation metric. This metric has been proven to improve the cash flow multiple predictability in our model from 64% to 77%.

    Nestle, Revlon, Estee Lauder, Clorox, L’Oréal, Keurig Dr. Pepper and P&G within the Top 50
    Another 7 CPG brands fall within the ranks of 34-50, with Nestle (#34), Revlon (#35), Estee Lauder (#36) and Clorox (#39) within the Top 40 and L’Oréal (#43), Keurig Dr. Pepper (#46) and P&G (#48) squeezing into the Top 50. Among this set, Clorox (+32 spots), P&G (+18 spots) and L’Oréal (+10 spots) have experienced the largest 5-year advances, while Revlon and Estee Lauder have both dropped down 11 spots over the same period. Both of these cosmetics and fragrance brands have suffered 5-year declines in Overall Reputation, Perception of Management and Investment Potential. Clorox appears to have been bolstered by growing Familiarity, while P&G shows strong long-term improvement across all tracked metrics.

    JM Smucker shows momentum, while Tyson Foods and KraftHeinz continue their steep declines
    Among the remaining CPG companies in the 2019 Top 100 Most Powerful Brands list, only JM Smucker (#54) ranks in the 50s through 80s in 2019, up 10 points vs. last year due to across-the-board improvements on captured metrics, notably Familiarity and Overall Reputation. Tyson Foods (#97) and KraftHeinz (#99) complete the CPG entries in the Top 100 for 2019. Both Tyson Foods (-33 spots vs. 2014) and KraftHeinz (-49 spots vs. 2014) continue their long-term slides and are now perilously close to dropping out of the Top 100 in 2020. Tyson Foods’ decline appears linked to having the lowest Culture of Innovation scores among those in the Top 100, with a gap of over 20 percentage points vs. the next lowest brand. KraftHeinz’s rankings drop since 2014, just prior to its formation by 3G, is the steepest of any corporate brand tracked in this study over that time period. Declines in both Perception of Management and Investment Potential are likely contributing factors.

    Company Name2019 Rank2018 Rank
    Coca-Cola11
    PepsiCo67
    Hershey95
    Kellogg1512
    General Mills1614
    Colgate-Palmolive1717
    Campbell Soup1918
    Nestlé3431
    Revlon3534
    Estée Lauder3636
    Clorox3938
    L’Oréal4340
    Keurig Dr Pepper4642
    P&G4852
    J.M. Smucker5464
    Tyson Foods9790
    Kraft Heinz9993

    ‘So what’ for CPG companies?
    The big CPG players are facing unprecedented challenges due to shifting consumer preferences and technology advances impacting global commerce. Today’s consumers seek offerings that not only address their category needs, but also align with their lifestyles. They still want consistent quality, but they also want it delivered conveniently, sustainably, and authentically – all at a fair price. Amazon has changed the game forever, lowering barriers of entry for smaller players to reach the masses, while also serving up its set of private label offerings at lower prices across an increasing number of categories. The broader democratization of digital commerce has only served to level the playing field between large and small CPG players even further. The net result is declining relevance and share for the larger, typically more established brands.

    The digital revolution is causing seismic shifts across the global economy, with the new tech giants Facebook, Apple, Amazon, Netflix and Google (collectively FAANG for short) accountable for 40% of the recent rise in the stock market and now commanding over $400 billion of brand value. Along with Microsoft, which is #5 in our BrandPower rankings, these brands are creating powerful ecosystems that not only drive the digital economy, but also siphon off professional talent and investment dollars from more mature industries like CPG.

    To stem the tide and regain their growth momentum, the CPG powerhouses will need to accelerate innovation efforts, creating new products, augmented services, and usage/purchase experiences that 1) align with and support their respective brands, 2) leverage emerging technologies and 3) better deliver on consumer needs and desires. Only then will they see meaningful improvement in terms of Brand Power, which in turn will help them remain attractive to both high-talent employees and financial investors.

    About the author
    Sean Folan is a Senior Partner of Brand & Innovation Strategy at Tenet Partners. He co-leads the firm’s innovation practice, which works with clients and their end-users to generate consumer-inspired product, service and experience innovation concepts through an iterative, human-centered approach called Co-Magination.

  • How to Revive Innovation in 2018

    We’ve been involved in product innovation, design and development for decades. Both on the client side and as consultants. We’ve seen first hand many of the victories enjoyed and the struggles endured by companies engaged in innovation regardless of size, industry and culture. It’s clear to us that the risk inherent in launching new products hasn’t gone away. Or even been greatly diminished. What has changed is the source of that risk and the way companies have chosen to contend with it over time.

    In several studies conducted by the Product Development and Management Association over the years, the failure rate of new products has remained remarkably constant from decade to decade.

    1980s: 42% failure rate
    1990’s: 40% failure rate
    2000’s: 46% failure rate

    A failed product is defined as one that doesn’t meet the objectives management established for it over a specified period and is withdrawn from the market. As you can see, not a promising trend. In fact, these are incredible statistics given all the strides we think we’ve made as an innovation community. Of course, different industries show different failure rates. Unfortunately for most readers here, consumer products and services show higher failure rates than commercial products. An interesting distinction that perhaps has something to do with the challenge of properly reading evolving consumer wants and expectations. As well as quick shifting tastes and trends that require rapid response—a difficult task for many organizations. The good news is that the often cited “80% failure rate” statistic appears to be a myth perpetuated by those who may stand to benefit from such a claim.

    Why, after all our advancement in methodology and process, do so many new products continue to fail? It’s reasonable to say that the standardization we impose on other business functions just doesn’t work for innovation. That which is mission-critical for Accounting and Production may not play well in the art-and-science realm of innovation. That may be part of the answer, but far from the entire story. Let’s take a look back at innovation practices through the (recent) ages and see what we can conclude about why we seem to have hit a wall.

    The 1980’s: Companies didn’t really know what innovation was, though many were doing it instinctively. 3M, GE and others were starting to measure the business impact of new products and considering “new product development” a survival tactic. It was popular to say that “X% of our revenue comes from products less than Y years old” as if that was, by definition, a good thing. Yet there was no clear, standardized approach to innovation. Companies were learning as they were doing. In this pre-methodology era, those few dedicated product development staffers were likely deported from mainstream, revenue generating business roles. And not always as a reward for strong performance.

    Back then, new products were more likely to come out of R&D and then passed along to Marketing for packaging and communications. Companies would discover a new utility and then look for ways to exploit it in the marketplace. If there were people dedicated to product development, they were likely close to the technical side, challenged to find a customer for some new skunkworks invention. There wasn’t much in the way of discipline. But there was a bunch of ad-hoc creativity. And lots of dabbling.

    It’s interesting that despite the risk inherent in this rather informal technology-driven innovation, the success rate was not abysmal. It could be theorized that risk in this environment almost took care of itself, as many of the skunkworks innovations didn’t prove out in the lab and never made it to market. And those that did were exposed to such a rigorous vetting process (and were so novel) that they likely stood a better than even chance of success. Perhaps the “hammer looking for a nail” approach is unfairly maligned!

    Even so, it became clear that the practice of new product development needed some structure. Companies were fond of systematizing work for efficiency and to eliminate error across functions. Imposing methodology was thought to be the answer. And “innovation” as a discipline was born.

    The 1990’s: Process discipline was all the rage. Standardized practices. Stage Gate methodologies and Six Sigma. Companies looked to import and install commoditized innovation methods in an attempt to minimize risk—considered the enemy of product development at the time. Organizations can’t survive without structure and process. So we asked the obvious question: Why can’t we automate innovation down to a zero error rate?

    Well, we learned a few things in the 90’s: First, innovation is a blend of art, judgement and science. While we talked ourselves into believing that these ingredients are ripe for systemization, our efforts to do so underestimated the resistance natural creativity has toward any attempt to instill order. And while imposing rigorous process on innovation made everyone feel safer, it didn’t do much to ameliorate risk or improve success rates, as we know. But we did get a lot better at stopping things that appeared unpromising. But it’s not clear we were necessarily green-lighting the right initiatives.

    Second, we learned that a year’s worth of standardization was in fact putting a choke hold on innovation. Production assets were designed decades earlier to do one thing really well: Fill this specific bottle with that specific goop. So now we have this early focus on innovation, people to staff it, methodology to guide it but not enough latitude to deliver on it. Frustrating.

    Process, in conjunction with a lack of asset flexibility (ironic since process inherently limits flexibility as well) resulted in a desolate landscape for innovation. Great ideas were contorted to run on existing lines. And their salience suffered, victims of what we might call “Adaptation Risk”. Success rates stagnated. Methodology got the blame, but it was no one’s fault. The machines chunking out soap and cheese were paid off long ago. And no one wanted to pay to replace them. The tension was building.

    The 2000’s: Design consultants save the day. Sort of. Companies decided they need outside help in cracking the innovation code. Design firms proliferated to address the mounting frustration internal methodology has left behind with copious amounts of creative energy. Some firms forwarded their own methodologies for those clients late to the discipline table and in need of that security blanket. Others promised raging creativity that internal staffers presumably couldn’t muster. And yet others dug deep into client production facilities looking for ways to squeeze a drop of flexibility out of those machines built to do one thing really well, really fast.

    This was, in an odd way, the golden age for innovation. Many companies recognized that process discipline wasn’t the solution it promised to be. And we learned that risk could be a good thing. The power of creativity was winning favor on both the marketing and manufacturing sides. Those in innovation roles began to earn respect and were chosen for a set of personal and professional attributes that seemed to align with the welcomed uncertainty of innovation.

    Management started—we say started—to become comfortable with risk and the notion that not all new products succeed. And that failures provided learning to feed later success. In fact, there was a certain misplaced pride in failure until management realized there was only so much failure an organization could enjoy without an occasional knock-out success to pay for it.

    This, we believe, was the start of “Design Thinking” as we know it today. When companies can recognize failure as part of an iterative prototyping effort and can value the kind of user empathy that internal market research wasn’t providing at the time, we knew we were making real progress. Now, if companies could only learn to iterate and fail before launch…

    The 2010’s: The smart money knows it’s not about “product” anymore. It’s about the story. The experience. The BRAND. Gone are the days of utmost concern about the new functional benefits consumers demand from products. It’s not enough to leapfrog competition with features we think we know consumers want. Consumer wants have been replaced by Need States: The emotional underpinnings that drive choice. People out there are too busy to discern why one product may be better than another without taking the time to experience it. So benefit-driven messaging no longer wins hearts and minds. And in most categories, those hearts and minds don’t care enough.

    What they do care about is affiliation. Experience. Values. The absence of frustration. What does that mean for innovation? Tons. Now, innovation is about making a promise to consumers that resonates. That reflects who they think they are and what they want to say about themselves. And doing a job they care to get done with confidence and style. So, it’s the holistic offering that will win the day. Not just a new package. Not a new flavor. But the integration of everything we used to think of independently. Together. It’s about The Story.

    As a consumer product, how does aesthetics, formulation and utility come together in integrated fashion to deliver a coherent brand promise? As a service, how must all the brand touch points behave to achieve performance and satisfaction? Key questions: What’s the difference between product and service in this new order? Answer: Not much.

    How does a brand set parameters, provide latitude and profess values to guide new product and service development? Or better yet, become product development. It’s not about the “thing” anymore. It’s the experience. Sure, technology plays a facilitating and exciting new role. IoT for instance enables change and utility like nothing we’ve seen before, with the potential to upgrade convenience and lifestyle. But it’s a “how”, not a “what”. The “what” remains that need state fulfillment grounded in a satisfying experience, however delivered.

    Why is this tectonic shift in the definition of “new product” so important to acknowledge? While this turn of events tamps down certain kinds of risk in innovation, it elevates others. And for companies, innovation has always been about risk. Now, there are more kinds. Where today’s innovation can ride on the strength of a brand and diversify across multiple touch points, its chances of success can be greater. And its costs can be lower. But—and this is a big one—in this day and age, a brand innovation story is subject to incredible scrutiny (and brand abuse). Much more so than a new feature set or package form.

    Think about Dove’s recent stab at bringing the brand to life in an array of body-shaped bottles. In hindsight, it was easy to see how this would go wrong. A brand’s values are just that—values. They cannot be literally translated into a package form or any other physical manifestation. They tell a story—they don’t dictate product. Why dwell on poor Dove? Because in an attempt to define a brand message in the merging of new and old innovation paradigms (story meets design), they achieved nothing. That, coupled with a few thousand haters with the hand-held technology to make their feelings known can upend innovation like nothing has before it.

    However, in an age where Tweets, stories, and pins are exchanged with lightning fast speed, companies can find a logical application for social media in the ideation and crowdsourcing phase of product innovation. There’s a definite draw for brands to use social media to replace some kinds of market research. However, brands struggle to find the right strategy.

    Oftentimes, data from samples on social media can lead brands astray. There’s just too much of it and a lot of noise that comes with it. So, they’re relegated to “testing the waters” rather than to dive in completely. Why? Social media is an intrinsically consumer-focused and controlled channel. It gives consumers the freedom to express their feelings instantaneously, creating an emotionally charged environment where users are quick to react to experiences that either exceed or fall short of their expectations.

    And, there lies the problem. Sharing and posting on social media is driven by emotional extremes whether negative or positive, which can make social data a bit unreliable. And it’s often the unqualified negatives that can torpedo a new product on emotional grounds before it gains momentum. One could call this “Hater Risk”. It’s important for companies to track not only the quality of the social data, but also the qualifications of the participants who provide that data. Identifying subject matter experts leads to the best expertise and increases the quality of insight for innovation. It’s all about listening to the right kind of data from the right kind of users while tuning out distractions, which is easier said than done.

    While the risk to innovating has changed, it hasn’t diminished. As we pointed out, the proportion of successful new product launches has remained roughly constant since the early days. Why is that? We think it’s because:

    1. We still face rigid actionability parameters in many companies. So we focus attention on the near-term little wins at the expense of category transformation. And the best ideas are often truncated to fit the parameters allowed by existing assets. One would think those little wins have a better chance to succeed. But we’d guess that incremental change does more to mess with a winning formula than it does to improve it.
    2. Brand extension mania seems like a risk averse strategy for innovation. We would allege that such efforts can dilute a brand’s core attributes, perhaps weakening it’s pull for consumers. So not only might brand extensions fail of their own accord, they could bring the brand down a peg with them.
    3. Cross-functional teams are great because they get things done. But they also water down great ideas. Let’s face it: If you’re representing R&D on a project team you may still be incented to push back against anything that could throw a wrench into a finely tuned production machine. And who could blame you with new product success rates as they are.
    4. As a corollary to the above, organizational complexity has created project complexity. Core teams are huge and sell-in audiences are vast. We firmly believe that minds that work alone or in very small groups have the best chance of surfacing the truly transformational. That’s because mandating consensus is the surest way to dumb down a fabulous idea.
    5. As suggested, consumer tastes and trends are moving so fast. Reading consumers properly and translating that insight into winning product on the store shelf has become more difficult. The science of consumer research and product development has had a difficult time keeping up.
    6. Innovation as the melding of art, judgment and science continues to—and will always—defy standardization. Period.

    We would like to think that process discipline, creative energy and risk is achieving a new, healthier balance. And that may finally reduce those intractable failure rate numbers. Perhaps the failure rate isn’t even that meaningful a measure. If you have one wild blow-away success in ten, you can absorb a lot of failure. Hollywood as learned that lesson, as they make bigger bets on fewer potential blockbusters. But there’s much to unpack in that change-of-paradigm for corporate America. In the meantime, here are a few tips for how to think about managing risk in your innovation projects, day-to-day:

    1. Leverage consumers better. Don’t “order take”. Put them in contexts that allow them to do what they do best. And use what you see and hear as inspiration—not direction—for concept development and refinement. Talk to us about our Co-Magination approach. It’s a collaborative tool set that’s fast and flexible enough to avoid the rigid process trap and the pitfalls of taste-and-trend whimsy.
    2. Don’t let process discipline choke off creativity. Reverse course. Deviate. Meander. Just don’t get lost. Remember: You manage the process—not vice-versa.
    3. Use the brilliance of the single creative mind to your advantage. And then incubate it in close quarters until it has matured before letting it loose on the organization.
    4. Don’t skip the design strategy phase where you assimilate defensible consumer insights (not evident observations) and chart specific innovation platforms. Use tools that focus creative energy, build team consensus when necessary and crisply communicate a path forward.
    5. Be careful when concept screening. Many breakthrough ideas fall to the ground in the earliest stages because as initially presented, they don’t appear actionable or have too many moving parts and confuse consumers. In other words, rethink the “concept board”.
    6. Iteration is your friend. Test and refine, test and refine, then test and refine. See #1 above.

    So how can companies change the consistent flatlining of product success that’s plagued innovation for decades? There are two ways to go. Option one: Winners have to be bigger. Which means risks taken must be greater. Therefore, companies must be open to the heightened internal and external scrutiny that comes with misjudgment—fair or not. Doesn’t sound great.

    Option two: Decades of circumstantial evidence points to an inability to read consumers as the largest thorn in the side of innovation. Sure, new product development has got to get faster. From ideation to production, there’s no time to waste. But that’s not enough. Tastes and trends come and go. But our new need state order remains fundamentally the same.

    So focus on surfacing those underlying emotional triggers that may evolve slowly but don’t dramatically shift. Then, craft a story that’s much bigger than the singular dimension of new product success. And bring that story to life in redefined brand-relevant experiences that provide meaningful context (and content) for products and services rather than letting them hang out there all alone.

    Can we break trend and revive innovation success starting in 2018? Certainly. We think the best way to do that is to rethink the role of consumers in your projects and the tools you use to engage with them. If we’ve learned anything over the past 30 years it’s that traditional research and creativity methods can reduce a project to a hit-or-miss proposition. This year, why not better your odds.

  • Powerhouse: The Secrets of Corporate Branding

    Powerhouse: The Secrets of Corporate Branding

    by James R. Gregory

    From entrepreneurs starting a new venture to Chief Marketing Officers (CMO) at Fortune 500 companies — this is a book for business managers who care about the reputation of their company and understand that by managing it they can create greater enterprise value.

    This is the essence of “Corporate Branding“ and I am a pioneer in the field –– these are my own personal observations of the best practices that have worked for our clients.

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