The Brand Beneath the Platform

Jess Wen does not separate brand from growth. After eight years and more than 150 venture-backed companies, she has stopped treating them as competing priorities.

“Brand is what people say about you when you’re not in the room,” she says. “It’s the sum total of all touch points.”

That definition sounds simple. The execution is not. For Jess, brand is not a logo refresh or a tagline. It is every product decision, every certification pursued, every member story told, and every moment a company chooses to act in accordance with what it says it believes. When a company does that consistently, over time, something measurable happens. Retention improves. Referrals increase. Word of mouth compounds.

That is the financial case for brand. And it is the operating thesis behind her work at SoLo Funds.

Meet Jess

Ask Jess about her ideal environment and she does not hesitate. A cozy room, a stack of books, a cup of hot tea, and what she calls her “fat lazy dog.” She is currently reading “The Anxious Generation” by Jonathan Haidt. She gamifies her personal life the way she structures her professional one: with deliberate quests. Last year, during a sabbatical in San Francisco, she set a goal of 100 new experiences in the city. She completed it.

When she returned to full-time work, she found herself slipping back into routine. So she set a new side quest: introduce deliberate newness into daily life and keep wandering down the small alleyways of a city she already knows well. “Continue to discover, continue to be curious,” she says. For Jess, that restlessness is not a personality quirk. It is a professional discipline.

She also teaches. Jess runs a creative entrepreneurship course for undergraduate design students, a 15-week class that, in her words, makes her a better operator. “Teaching actually makes me better at my day job,” she says. “I see the parallel of people leaning into the skills they have and immediately wanting to flex that skill set.” Watching students default to building before defining the problem taught her something she now applies every day at work.

From Client Service to In-House: Two Very Different Maps

Jess spent the majority of her career on the client service side, working as an outside consultant across a broad range of venture-backed companies spanning sectors and stages. She describes the work as pattern recognition at scale. “I’ve probably seen a version of every possible problem within venture-backed companies,” she says.

That breadth trained her well. The transition to an in-house leadership role, however, required a different kind of map.

In client service, brand strategy begins with a bird’s-eye view of the customer journey. The team identifies key touch points across awareness, consideration, and engagement, scopes the work, executes with precision, and exits. The time horizon is short. The brief defines the boundaries.

In-house, the exercise runs in the other direction. Jess starts with the annual business roadmap and reverse engineers into the touch points worth prioritizing. “What is reasonable, given resources and dependencies? What are the A, B, C we should focus on to improve brand and experience for Q1?” The horizon is longer. The constraints are internal. And unlike a client engagement, there is no clean exit.

“I want to run with B and C initiatives, but the dependency results in a lot of reality checks and rescoping,” she says. “Picking the battles, when wearing an in-house leadership hat, is about having my immediate function’s priorities and goals but also handling curveballs with grace and a collaborative spirit.”

The Patterns That Keep Repeating

After working with more than 150 venture-backed companies, Jess has catalogued a short list of brand failures that repeat across stages. Two stand out.

The first is what she calls the founder-as-brand trap. In the earliest days of a company, this is not a trap at all. It is necessary. Founders typically carry the charisma, the conviction, and the credibility. The brand and the person are inseparable by design. “Any entrepreneur who goes into a startup scenario usually has a certain charisma to really believe in what they’re building,” she says.

The problem arrives at the growth stage, when the company begins to scale and the founder cannot duplicate themselves five times over. If all of the brand equity has accumulated in a single person, the company has not built a brand. It has built a personal platform.

Jess uses an education metaphor to describe the transition. Early-stage companies are the grade schoolers. There are very few rules. The founder leads. But moving into the growth stage requires separating individual personal brand from company brand.

“The company brand needs to be strong enough and firm enough to stand on its own, without over-relying on the individual charisma.”

Her diagnostic question for founders who want to self-assess: when you walk into a conference and introduce yourself, do people think of your company name first, or do they think of you?

The second pattern is the “if we build it, they will come” assumption, most common among technical founders. Jess sees this clearly in the current AI funding environment, where some companies are getting away with skipping the story because capital is flowing fast. But she does not believe that lasts. “Those companies will not be the most stable ones going forward,” she says. The mirror image of that failure is the founder who sells aggressively before the product exists and then scrambles to build it after. Both profiles skip the same foundational question: what problem are we solving, and who actually cares?

She points to consumer brand companies as a model for tech founders to study. Omsom, a direct-to-consumer sauce brand co-founded by two Asian American sisters, earns her admiration not because of its size but because of its clarity. The company solved a specific problem: busy professionals who want to cook flavorful, internationally inspired meals without stocking dozens of bottles and knowing what to do with them. “They found their story early on,” she says. “They are solving a very clear problem that people care about.”

SoLo Funds: Humanity Inside a Financial Product

Jess first encountered SoLo Funds in 2020 as an outside consultant, brought in to lay the initial brand foundation for a peer-to-peer lending and borrowing platform still finding its language. She joined full time as Vice President of Brand and Growth in December 2025.

SoLo Funds operates as a community banking platform. Roughly 50 percent of American households live paycheck to paycheck, a figure the company tracks each year through its Cash Poor Report, produced in partnership with academic research institutions. When an unexpected expense hits, which it does, frequently, the traditional options are either a big bank or a predatory lender. SoLo offers a third path. The platform connects members who want to lend with members who need to borrow. Nearly three million members strong, the platform recorded close to 600,000 individual peer-to-peer transactions in 2025 alone. SoLo also holds the distinction of being the first and only B Corp certified lending company in the United States.

The brand work Jess began in 2020 had a clear brief: bring humanity into fintech. “Every messaging, visual, and brand touch point needed to really honor that,” she says. The founders, both Black, built the company from direct experience. They had been the person who needed to call a cousin or an aunt for help getting by. That sincerity, in Jess’s view, is not a marketing angle. It is the actual brand. “Over time, it’s not just a founder story,” she says. “It’s about actual member stories, people who are benefiting from our platform.”

The B Corp certification is a concrete example of how that belief system translates into a business decision. Going through the certification process requires significant resources and a rigorous accounting of social impact practices. The company chose to do it anyway. “The willingness to commit the resource to go through it backs the belief system,” Jess says. That commitment is brand. The certification is the proof.

Why Brand Matters More Now Than It Did Before

Jess makes a specific argument for why brand has become more important in the current environment, not less. Product parity is accelerating. With AI tools now available to most teams, shipping a clean, functional product is becoming closer to a baseline expectation.

“Consumer expects the product to work. Beyond that, whether or not it can speak to people, relate to people, connect to people, all of that is the importance of brand.”

She frames it bluntly. “Everything looks the same.” Consumers are fatigued. Attention spans have shortened. The volume of content, advertising, and product noise flooding any given channel has never been higher. In that environment, the companies that earn trust are the ones that stand for something clearly and demonstrate it repeatedly. Not through campaign flags. Through consistent behavior over time.

The analogy she draws is a useful one. Nike does not put a consumer’s name on an ad to earn business. Nike earns business by consistently aligning with aspiration through the athletes it chooses, the stories it tells, and the standard it sets for what the brand represents. That distinction, between brand audience and acquisition audience, matters.

“Brand should always feel a little more aspirational versus the acquisition audience who will actually use the product.”

AI, Personalization, and the Limits of Automation

SoLo Funds recently built and launched SoLo IQ, a proprietary AI-powered personal finance tool available to members within the platform. The motivation was observational. The team noticed members uploading personal bank statements into open-source AI tools to get budgeting advice. Recognizing a significant data risk, Solo developed a GLBA-compliant, secure, and encrypted alternative inside its own ecosystem.

The response was immediate and overwhelming. Between September 2024 and now, the platform recorded 74,428 unique IQ users against 68,290 unique borrowers—an adoption rate of 109%. This figure exceeds 100% because the tool’s value extends beyond active borrowers to members simply browsing the app or exploring features. It isn’t just a novelty, either: SoLo IQ maintains 94.65% uptime, averaging 23 conversations per hour, with 93.34% of those interactions delivering measurable value to the user. The product did not begin as a growth initiative; it began as a response to a real and specific human need.

The retention data tells an equally compelling story—and reinforces that brand is built across every touchpoint a member encounters, not just marketing campaigns. SoLo IQ users retained at 69.4%, compared to 60.6% for non-users, a lift of 8.8 percentage points. The more striking figure is on the lender side: IQ-enabled lenders retained at a rate 13.5 points higher than their non-IQ counterparts. Because lenders represent the supply side of the marketplace, that number carries outsized weight.

On the question of AI within her own team, Jess is measured. She references a Harvard Business Review article that found people are working more, not less, after introducing AI into their workflows. She sees that pattern in her own department. Every Thursday, her team holds a learning session dedicated entirely to sharing new AI workflows with each other, a structured attempt to raise collective literacy rather than assume everyone will figure it out independently.

Her framework for how AI changes the role of the marketer: AI is excellent at repeatable tasks and detailed research. Humans remain responsible for weaving those outputs into a coherent point of view. “I need the human intelligence to tell me the so what,” she says. Her goal is to move team members from straight-line execution toward a higher altitude, where the job is connecting dots and understanding the strategic reasoning behind the work.

"I need to elevate my team from a straight-line execution perspective to an airplane view. A higher altitude where you see a wider picture, connect the dots, and understand the strategic thinking behind why we are running all of these tasks in the first place."

She gave a talk to roughly 200 creatives in San Francisco two weeks before our conversation. Her call to action: continue to imagine, continue to grow in creativity, and continue to elevate your taste. Not just from good AI output to acceptable AI output, but from acceptable to genuinely great. “It’s not prompt it and forget it,” she says. “How do we continue pushing apart and moving forward?”

Looking Ahead

Jess is thinking about what comes after SoLo IQ. The next chapter, she describes as a “bit of a spoiler,” involves using AI analytics to tell a larger data story about everyday American spending habits and financial behavior. SoLo sits on a rich and growing proprietary data set from millions of members across diverse economic circumstances. The team is working toward surfacing that data in ways that reveal something true and specific about how ordinary households manage money, not to sell a product but to anchor a public narrative.

For a brand built on the premise that the financial system has underserved a significant portion of the population, that kind of data storytelling is not adjacent to the mission. It is the mission made visible.

“I think there is a lot of very rich story there. AI for real human needs that realistically benefit not just the top one percent, but a much wider population.”

As AI tools spread further into daily consumer behavior, Jess believes the most durable brands will be the ones doing exactly what SoLo has always done: starting with what is real, telling it clearly, and earning trust one touch point at a time.

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Isla Dickerson has a framework she uses before she touches a campaign brief. She does not start with key performance indicators. She does not open a channel dashboard. She starts with a question most marketing teams have set aside: what does this person actually feel right now?

As Head of Marketing at Happy Money, a consumer finance company that has helped more than 350,000 customers achieve their goals with a personal loan that provides a path out of credit card debt, Isla centers her operating philosophy around the gap between behavioral data and experiential truth. In her view, that gap is where most modern marketing falls short — and where the next generation of great brands will be built.

Meet Isla

Ask Isla about her ideal life and she does not hesitate. In the summer, she would run a bed and breakfast on an island off the coast of Maine, cooking lobster stew and strawberry rhubarb pie for interesting strangers, listening to their stories, and photographing the food for a cookbook she would write during winters in Hilo, on the quiet side of Hawaii’s Big Island. Every detail has a purpose. Every element earns its place. That instinct, to find what is true and what resonates, runs through everything she does at work.

From Community Banking to Fintech: What the Jump Actually Taught Her

Isla’s career began at a large independent credit card issuer, where volume was the currency and acquisition was the objective. After years at that scale, she founded an award-winning marketing and communications agency that never advertised, then returned home where she spent eight years leading marketing, community relations, and public relations at Bangor Savings Bank. Out of the blue, a former colleague called to say he had co-founded a startup and needed help. She left the structure of community banking for the disorientation of fintech.

What she found on the other side reframed how she thinks about the entire discipline. In a startup, product and marketing are not separate functions. They are often the same person making the same decisions.

“You are building a product while you are designing a marketing campaign and oftentimes you are doing that before the product is even fully built.”

She had to create marketing for an unfinished product while simultaneously marketing the organization, its people, structure, and potential, to multiple audiences. No historical data. No established playbooks. The friction was the education.

That experience sharpened a belief she now holds firmly: the best marketing thinking happens before the metrics arrive.

“Performance Ready” vs. Performance Marketing: A Framework for Building Backwards

Isla draws a distinction that sounds subtle but carries real consequences for how a team operates. She calls it the difference between performance marketing and being performance ready.

Performance marketing, as it has been practiced for the past two decades, starts from the back end. You define your target cost per acquisition. You set your click rate benchmarks. You design creative to pass an A/B test window. You optimize. The numbers tighten. And then, slowly, something else happens: the campaign converts in the moment but does not stick. The customer clicks and then leaves. The brand registers and then disappears.

“You’re optimizing yourself into this corner where everything converts in the moment, but it doesn’t resonate and it doesn’t stick.”

Performance ready is the opposing motion. You start with a human truth. What does this person fear? What are they hoping for? What would make them feel seen rather than targeted? You build from that place. You honor that truth in the creative before you touch the measurement framework.

“It’s not anti-data. It’s not dismissing the need for measurement. This is actually the more data-driven, rigorous approach.” Being performance ready multiplies what you measure and how you build. It expands the system beyond conversion to include sentiment shift, brand recall, referral, and long-term value, because you are no longer optimizing for the moment. You are designing for what makes performance sustainable. That requires deeper analysis, stronger synthesis, and tighter integration between data and human understanding. You are not just measuring what happens. You are designing for why it happens.

The campaign still gets measured. It just gets built differently.

Emotional Precision: The Operational Problem She Is Solving Right Now

Isla uses the phrase “emotional precision” to describe where she believes marketing is heading and where Happy Money is actively working towards.

She is not talking about putting a first name in a subject line. That, she says, is a playbook that was already aging before email existed. “We transferred the way that we wrote direct mail pieces into the email journey. Same content, different medium, no evolution.” What she is describing is harder to engineer: understanding not just what a customer did on your website, but why they did it, and what emotional state they were in when they arrived.

For Happy Money, this is not theoretical. Two visitors can land on the same debt consolidation page through the same search. One is on their lunch break, casually comparing rates. The other is at 2 a.m., having avoided their credit card statement for three weeks and living with constant financial anxiety. The action that got them to the site is identical. What they need from you at that moment is not.

One needs a nudge. The other needs reassurance. A single campaign version serves neither of them well.

Operationalizing this requires segmentation not just by behavior or demographic profile, but also by stage of readiness. Isla frames it as a binary: is this person in problem-awareness mode, or are they in immediate-action mode? That distinction shapes message, tone, creative direction, and offer structure.

The data needed to make these distinctions exists. The constraint has been speed: the inability to extract and act on contextual signals fast enough for them to be meaningful. That is the opening for AI.

Machines for Intelligence, Not Wisdom

AI handles the mechanical layer: A/B testing, bid optimization, content variations, reporting. It gets the middle steps done faster. What it cannot do is understand why a customer who just consolidated $30,000 in credit card debt might feel simultaneously relieved and ashamed. “It can’t feel the difference between a headline that’s clever and one that’s really true.”

“It’s machines for intelligence. It’s not machines for wisdom.”

The practical implication for her team is that AI accelerates the pipeline to insight. It surfaces patterns in data that used to take weeks to extract and makes them available in hours. That speed frees up human judgment to do the harder work: identifying the emotional truth, building the creative that honors it, and making the call on where to press and where to pull back. The skill that appreciates in value is not execution speed. It is human interpretation.

On agentic commerce, where AI agents locate and evaluate financial products on a customer’s behalf, she is measured rather than alarmed. “We are already heading down that path,” she says, drawing a direct parallel to the early days of Google search and the emergence of SEO. The search tools change. The underlying imperative: to be findable, credible, and emotionally resonant when the moment arrives, stays constant.

Credit Risk, Product, and Marketing

At Happy Money, Isla does not run marketing as a standalone function. Her closest operational partners are the credit risk team and the product team. She describes the three as pillars: none of them move without at least informing the others, and most significant decisions surface through all three before any action is taken.

The credit risk partnership is particularly concrete. Happy Money receives leads through affiliates, email, prior customer lists, and pre-screened direct mail channels. Every campaign Isla runs is shaped in dialogue with the credit risk team’s modeling. They inform her segmentation. They help build out personas. They review creative, not for compliance alone, but to ensure that the people being targeted with a given message are the people the model has identified as the right audience for that offer.

“Designing creative that blends and serves the segmentation that credit risk models out is an art.”

The result is a pre-screened direct mail process that operates as a precision instrument: response rates, approval rates, and risk-reward weighed together. Marketing and credit risk are not running separate plays. They are co-designing the same one.

Loyalty as Forgiveness: The Long Arc of Retention

The definition of loyalty Isla operates from now is less about repeat purchase and more about forgiveness.

“Repeat purchases are the baseline. Loyalty is resilient trust—the kind that holds when something goes wrong and the relationship endures. And it’s that trust, not behavior, that ultimately defines customer long-term value. If we’re not measuring it, we’re missing the signal that matters most.”

Her example is L.L. Bean, a brand she grew up with in Maine. When the company changed its longstanding return policy, one she had relied on personally, they explained the decision in a way that made sense to her. The relationship held. She still buys from them. She still recommends them. The brand had built enough trust that a broken promise did not break the relationship.

That is the standard she is building toward at Happy Money. Campaigns that convert are an imperative. Relationships that survive a mistake are the goal.

Looking Ahead: The Marketer as Psychologist

The marketing team of the future, as Isla envisions it, still operates as a performance engine, but one increasingly powered by AI and machine learning. Automation takes on execution and optimization, making the system faster, more precise, and more efficient.

Alongside it, a human data lab emerges. Fewer specialists focused on channel mechanics. More psychologists, storytellers, and community builders. More people with experience beyond marketing: those who have run businesses, worked in customer service, or developed a deeper understanding of human behavior, capable of directing machine output with judgment and applied wisdom.

“You can never outsource humans. We’re selling things to humans. We need human wisdom to do that effectively.”

The technical layer scales through automation. The human insight layer directs it and becomes the competitive advantage. The role of the CMO expands accordingly: still building and managing a demand generation engine, and now requiring an honest read of what customers feel and experience with the ability to translate that truth into inputs that guide the system, so what gets optimized is not just efficient, but meaningful.

Start with insight. Build for stickiness.

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Lauren Dresnick does not romanticize the markets she operates in. She diagnoses them.

Her career has moved through developer trade publications, enterprise B2B creative agencies, and the frontier of crypto and blockchain. The through-line is consistent: find the real audience hiding beneath the noise, build a clear message for them, and engineer the distribution to reach them. Hype is everywhere. Clarity is the edge.

That orientation has been tested inside two demanding marketing environments. First at Ripple, the payments network affiliated with the digital asset XRP, during the first crypto bull market of 2017. Now at Nexus, an early-stage infrastructure startup building verifiable computation for an emerging world of AI-driven transactions. In both cases, Lauren walked into environments overflowing with speculation and retail enthusiasm, and in both cases, her job was to locate the audience that actually mattered to the business and build a coherent program around them.

Meet Lauren

Lauren’s version of a reset involves oil paint, a canvas, and a playlist that moves freely from Fleetwood Mac to Lizzo, with some Taylor Swift folded in since her kids arrived. She has mostly created figurative work throughout her career, but lately she has been painting landscapes and more abstract urban scenes. “Since the pandemic, it’s hard to get in a room with other painters,” she says. “But I get into that flow state where I’m really just looking at the textures and the colors and what’s in front of me. That’s how I unwind.”

Two Audiences, One Company

When Lauren joined Ripple in early 2018, the company was sitting inside one of the most unusual marketing situations in recent memory. XRP, the digital asset affiliated with the payments network, was trading third globally behind Bitcoin and Ethereum. The retail community had built enormous organic momentum around it, and internally, that attention was creating the impression that the marketing function was delivering meaningful results.

When you unpacked it, the picture was more complicated.

Ripple’s actual product was a B2B payments network designed to move money across borders faster, cheaper, and more reliably than Swift, the international payments messaging network that had long served as the de facto standard for cross-border transactions. The banks, payment service providers, and remittance corridor operators who needed to evaluate that network were not the people speculating on XRP. They were IT leaders, innovation officers, and remittance specialists at mid-market financial institutions.

Lauren’s first operational problem was that these were not the same audience, and they could not be reached the same way.

“We wanted to reach people who were working at banks and at payment service providers,” she says, “and telling them about this technology and how this network was going to be better than Swift.”

The retail audience could not be ignored. XRP needed liquidity and trading activity to function as the intermediary asset in cross-border exchanges. But the organic retail enthusiasm was also generating confusion. Community sentiment was volatile. The XRP army, as it became known, was loud, engaged, and ultimately not the buyer. And the attention it commanded internally was, at times, pulling focus away from the harder work of building counterparties on either end of the payment corridors.

The solution required running two fundamentally different programs at the same time.

Localization as a Marketing Tactic

For the retail audience, the work was geographic and deeply granular. In the Chinese market, the character for Ripple and the character for XRP were identical. Lauren’s team researched and rolled out a distinct character to establish that these were separate entities. In Korea, broad awareness of XRP and its utility was critical even though no specific remittance use case was targeted there. In the United States, the goal was to build trust around blockchain-enabled rails so that consumers would specifically seek out Ripple-powered infrastructure when sending money internationally.

Each market required a localized interpretation of the same underlying message: XRP had real utility, and that utility would support its long-term stability.

On the B2B side, the precision requirement was different. Once the team identified that mid-market banks and payment service providers were the right entry point, not the large global banks and not the smallest upstarts, they built account-based marketing and lifecycle programs around specific payment corridors. Thailand emerged as an early-penetration endpoint. “We spent a lot of time marketing just to senders into Thai corridors,” Lauren says. “Those became very localized demand generation and ABM programs, and very localized lifecycle marketing programs to get those senders to actually start transacting so that we could get volume numbers up.”

The event strategy mirrored the funnel. Webinar series anchored by proprietary data and industry findings served as early-stage demand generation. Small, white-glove in-person gatherings brought corridor counterparties together around specific business opportunities. Ripple’s Swell event series, which brought regulatory leaders and prominent industry voices onto a shared stage, created category-level awareness while simultaneously serving as a matchmaking environment for those smaller, more exclusive meetings.

Each event type had a different role, a different cost profile, and a different return on investment expectation.

The Community Gotcha

At Nexus, Lauren applied the same structural thinking to an even faster-moving build. In six to nine months, the team grew the network from zero to 3.5 million users contributing computing power from their individual devices, and built followings of more than 250,000 engaged contributors across Discord, Telegram, and X.

The tactics were layered. Ambassadors were hired in key regions, including Nigeria, Indonesia, Vietnam, and Korea, with budgets to run grassroots events locally. Gamification was embedded into the network backend. Programs called Node Runner and Node Rush rewarded users for contributing computing power and sharing content. And critically, Lauren worked closely with the product team to reduce the technical barrier to entry from a complex command-line installation to a single click.

“One of the big ways in which we’ll be able to scale our network in theory over time is by collecting proving power from all these people all over the world.”

The click-to-earn entry point made that feasible at speed.

But Lauren is direct about the structural tension embedded in crypto community building. A large portion of early crypto communities forms around what is known as token farming: users follow pre-launch projects in anticipation of receiving airdrops, tokens gifted at or around the time a company lists, then sell those assets immediately after listing. The result is downside price pressure that undermines the project’s credibility at the moment it matters most.

”Communities are super fickle and crypto things can turn on a dime.”

The gotcha, in her framing, is believing that community momentum is durable without actively managing the composition and motivation of that community. Revenue and product adoption are the only sustainable anchors. “If you’re focusing too much time on community building among these audiences that can’t necessarily contribute to the overall product and ecosystem development, then you’re distracted,” she says.

Right Story, Right Person, Right Place

Lauren’s content philosophy has not shifted meaningfully since her days writing for developer trade publications covering Visual Studio, Java, and Ruby on Rails. “I’m old school,” she says. “Right story, right person, right place. It’s really just about hitting all three levers at the same time.”

What has changed is the execution environment. AI has accelerated distribution, lowered the cost of producing content at scale, and introduced a homogenization problem that Lauren views as a genuine strategic opening for skilled marketers.

“AI does have a tendency, we already see it on LinkedIn, to be very homogenous. The language is overly polished. Everyone is kind of saying the same stuff.”

In that environment, taste and voice become the scarce resource. The ability to identify a genuinely differentiated angle, to resist the pull toward the obvious framing, and to ensure that content resonates rather than simply distributes, is not something a large language model can reliably replicate when every competitor is working from the same tools.

Her practical response combines leaner in-house teams, Claude, Anthropic’s AI assistant, for content development and operational tooling, Grok on X for platform-specific search and research, and Sprout Social for share-of-voice measurement. Alongside those tools sits advocacy management: ensuring that credible voices in the ecosystem are amplifying key moments rather than leaving organic reach to chance.

“You need the right people following you on a platform like Twitter, and those people are amplifying and actually contributing in meaningful ways to the content you’re producing. That gives you more reach.”

The Smaller Team Paradox

Lauren’s view on team construction runs against the instinct to scale headcount in parallel with ambition. AI, she argues, does not reduce the importance of the people on the team. It increases it, while reducing the total number of people required.

“You are going to have much smaller marketing teams because AI is enabling so much of the execution work behind the scenes. But the team in place is going to be more important than ever because they’re going to be the tastemakers.”

The downstream effect is a growing role for outside expertise. Agencies and fractional consultants, she believes, will become a more consistent part of the operating model as in-house teams reach the limits of their internal differentiation and need fresh creative or strategic perspective without committing to a full-time hire.

“I think you’re going to see the rise of agencies and consultants being more important. You’re going to have smaller in-house teams and then you’re going to have individuals, or networks of individuals, that you go out to.”

Her read on the broader industry is equally direct. Crypto is in a bear market, and the industry is, for the first time, moving toward measuring itself against ARR and adopting more traditional marketing playbooks. Meanwhile, AI companies are exhibiting many of the same patterns that characterized Web3 at its most speculative: significant funding, experimental use cases, and business models still working toward sustainable footing. “From a marketing perspective,” Lauren says, “I think it’s very similar to where Web3 and crypto was, even just in the last couple of years, where you’re still trying to figure out what the use cases are and what the sustainable ways of investing in marketing activities are.”

The Practitioner’s Edge

Lauren’s practitioner insight is a grounded one. In a landscape saturated with AI-generated content, the marketers who can still ask the right question before producing anything at all will hold the real advantage. Who are we actually trying to reach? What do they already believe? What would change their behavior?

“If you want to tell a good story and your resources are typically individuals, you need to think through ahead of time: who am I trying to reach with this content I’m developing? And what are the things that they’re going to be most interested in?”

The research that surfaces those answers, she adds, is increasingly something AI can support. The judgment about what to do with them is not.

Reverse-engineer the story before you tell it. Then listen well enough to find out where your thesis was wrong.

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Vivek Girotra has spent years inside fintech and consumer products, building growth systems where the real work begins after the first transaction.

Most growth teams treat frequency, habit, and loyalty as variations of the same problem. Vivek has spent enough time inside high-trust financial products to know they are three entirely different challenges.

“Frequency only tells you that a behavior is happening,” he explains. “It doesn’t tell you whether there’s any real attachment or preference underneath it.” Someone might repeatedly open your app because a support ticket has been left unresolved for days. That is activity. It is not growth.

Habit is one layer deeper. The behavior has become automatic. The user no longer reconsiders. “Someone may go to the Starbucks on their way to the office and open the app because that is just what they do.” Strong behavior. But it does not prove the customer has any real affinity for the brand.

Loyalty is the layer most teams never reach. It is, in Vivek’s framing, a chosen preference under competition. When the customer has real alternatives and still picks you, that distinction shapes revenue. In high-trust categories, especially fintech, the difference is between a product people use and one people defend.

The Roots of a Customer-First Instinct

Vivek began his career at Ogilvy, where his earliest work included copywriting and proofreading. There was hell to pay if even a comma was out of place. That discipline still anchors his practice. Decades later, in an age of large language models and autonomous agents, he still returns to the same first principles. Who is the audience? What are their pain points? What is the message that creates an emotional connection? What form does that take across available touchpoints?

The sharpest illustration of that instinct came early in his career, working on a consumer electronics account in India. A manufacturer had two refrigerator lines: an older direct-cool model that accumulated ice in the freezer, and a newer frost-free model. The newer product was technically superior in every dimension. Yet in smaller cities, the frost-free units wouldn’t move.

Rather than adjust the advertising, Vivek’s planning team went directly into those tier-two towns to observe. What they discovered was something no dataset could have surfaced. Power cuts were frequent, often running four to five hours at a time. The ice that accumulated in the older freezer actually helped preserve food during outages. Customers were not being irrational. They were solving for a real constraint that the marketing brief never acknowledged.

“This is the job of a marketing professional,” Vivek says. “Going deep and figuring out things that even the best AI tools can’t yet surface on their own.” Going to where the customer actually lives, before building any system around them, is the foundation of everything that follows.

The Lifecycle Architecture: Where Growth Actually Lives

Vivek has applied this principle at scale in consumer fintech, where the product is not a transaction but an act of trust. Customers are not buying virtual gold coins at $2 a pop. They are moving money that may feed a family or cover a medical bill on the other side of the world.

In that context, the repeat behavior matters more than the first conversion. The compounding value of a well-designed product is what makes the unit economics work: convenience, confidence, and value that improve together over time.

Building the system to capture that compounding value starts with what Vivek calls hygiene. Event tracking must be set up correctly before anything else. Some events fire from the app. Some are server-side. Some occur asynchronously across payment rails. Creating the plumbing to capture all of it reliably is, as he puts it, “a non-trivial exercise that people consistently underestimate.”

Once the data foundation is sound, the lifecycle architecture can begin. His framework for getting started is deliberately simple. Define your key milestone events first. For a money transfer product, the chain looks like this: app install, sign-up, completion of Know Your Customer (KYC) verification, bank linking, and first transaction. Build the first version of the journey system against those milestones. Get data. Then go finer.

“You’ll find people who perhaps submitted a KYC, but it failed. You need a journey that sends them a deep link with correct feedback so they can retry.”

For the lifecycle infrastructure itself, Vivek’s team works with CleverTap, a customer engagement platform that consolidates event tracking, segmentation, funnel analytics, and multi-channel messaging (email, WhatsApp, and SMS) into a single system. Having a single place to track behavior and trigger campaigns removes the coordination overhead that bogs most teams down. But the platform is only as useful as the journey logic behind it.

Vivek resists the impulse to over-engineer before gathering evidence. “Lifecycle marketing is always a game of inches. You’re rarely going to make one change that gives you a 30 percent lift. It’s always going to be: I made this small change, I improved conversion by 2 percent. I added this journey, I improved the next stage by another 3 percent.” The wins accumulate. The starting point matters less than the commitment to iteration.

The Product-Marketing Handshake in Practice

The org chart draws a clean line between marketing and product. Reality does not. In Vivek’s experience, the teams that win are the ones that stop arguing about ownership and start operating on shared terrain.

His framing is precise. Marketing sets the expectation. It determines who arrives, what they believe they are getting, and what value they are mentally prepared to accept. The ad, the landing page, the app store listing: all of these shape a user’s mental model before they ever touch the product.

Product either proves or breaks the promise. If the onboarding is muddled, if the value moment arrives too late, the mismatch registers immediately. That damage doesn’t stay on the product side. It feeds directly back into growth efficiency.

The overlap zone (activation, onboarding, referral, retention) belongs to neither team exclusively. The strongest organizations treat it as a shared operating responsibility, and as Vivek frames it, everyone has to own the customer experience, not just the team whose name is on it. In practice, this has meant that lifecycle marketing teams sit within his marketing organization, not product, because retention is too central to the growth outcome to be housed anywhere else. The entire funnel, from impression to install to first and second transactions and so on, is mapped and managed as a unified system.

Brand Is Not a Logo

Vivek is pointed when the conversation turns to brand. Teams routinely reduce it to its most visible artifacts. The logo. The color palette. The tagline. His operating definition is broader. “Everything is brand. Your App Store page is brand. Your customer support experience is brand. Your onboarding flow is brand. Every time the customer touches your product or your company, they are forming a view of what your brand actually is.” In his view, consistency is built through every customer experience, not just through aesthetics.

Personalization That Actually Changes Behavior

When it comes to personalization, Vivek is precise about what the word actually means. Real personalization matches the journey, message, and timing to the user’s actual context: where they are in the lifecycle, what they are most likely to do next, and what friction stands between them and that action.

“I have never converted better because someone mentioned my name in the first line of an email.” The valuable form of personalization is contextual, rooted in the user’s actual situation.

A user who signed up and stalled at KYC needs reassurance around trust and process. An active user who has already transacted needs a different message entirely, one tied to timing or rewards or a shorter path to their next action.

“AI will make it easy to produce more variants more quickly,” he notes. “It still won’t answer the harder question of what should vary and why. Dario Amodei at Anthropic made this point about engineering: even when AI writes 90 percent of the code, the humans focusing on the remaining 10 percent become more leveraged, not less relevant. The same applies to lifecycle marketing. AI will produce the variants, but knowing which moment matters, which segment to treat differently, and when to leave something alone is where that leverage lives.”

The Distribution Problem Nobody Has Solved

As AI tools commoditize content production, Vivek is watching a common misunderstanding take hold. Distribution is increasingly confused with visibility. An entire generation of vibe coders is finding this out the hard way: building the product was the easy part. Now they’re app marketers, and they didn’t sign up for that.

“If distribution were just spraying AI spam all over the internet, we would all be multimillionaires by now.” The substance of the problem has not changed: a real distribution system requires unit economics that work, attribution you can act on, and a monetization layer that funds the next cycle of growth. The tools for executing each piece are cheaper than ever, but cheaper execution just raises the bar on everything around it.

Vivek thinks about AI adoption in three layers. The first is delegation: routine production tasks handed off entirely. His team already has all copywriting done by AI. The second is augmentation: using AI to surface deeper insights into audience behavior, predictive modeling, and segmentation that would take a human analyst weeks to assemble. The third, and the one he’s building toward, is autonomy: agents that monitor lifecycle performance, flag opportunities, and act on them independently.

That has been the through line of Vivek’s career: not the tools, but the system around them. From a freezer in a tier-two Indian town to autonomous agents managing marketing journeys, the starting point has always been the same. Go to where the customer is. Understand what they actually need. Then build the system around that.

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In this Episode

The transition from high-stakes marketing to the invisible architecture of global finance requires a specific type of intellectual recalibration. For Katie Perry, the shift from the retail investment frenzy of 2021 to the infrastructure layer of digital assets was not a retreat from the spotlight but a move toward the “plumbing” that makes the spotlight possible. During her tenure as the first marketing hire at public.com, she navigated the volatile intersection of social sentiment and market mechanics during the GameStop era. That period defined a generation of retail investors. Today, as the Chief Marketing Officer of zerohash, Katie focuses on the exacting task of building the infrastructure that allows banks, brokerages, and fintechs to embed digital assets into their own ecosystems.

The inception of this current phase followed a two-year period of fractional consulting. During that time, Katie operated a lean business, scaling high-margin clients by using agentic systems to bridge the gap between high-level brand strategy and the technical execution of complex ad campaigns. This period of independence allowed her to observe a recurring friction in the market. Companies wanted to offer digital asset functionality but were hindered by the technical and regulatory complexity of doing so. When she encountered zerohash, a company that had operated for eight years without a formal marketing organization while securing clients like Morgan Stanley and Franklin Templeton, she identified a rare instance of product-market fit that lacked only a narrative architecture.

The Uncovered Profile

Outside of infrastructure, Katie operates with a rhythm defined by high-intensity curiosity and a preference for the unscripted. Her mornings frequently begin at 6 a.m. in places like the Ginza district of Tokyo, where the cold air of a Japanese winter serves as a backdrop for endorphin-heavy runs. This discipline carries over into her intellectual habits; she is a self-described “sponge” who uses her evenings to build deep-dive dossiers on topics as disparate as 18th-century infectious diseases or British period dramas. She possesses a natural inclination for the “edge case” about to go mainstream, a trait that manifests in her professional choices and her personal fascination with subcultures.

Her ideal environment is one of functional contrast. While she maintains a professional studio in a Midtown Manhattan Regis office, half-office and half-production suite, she finds equal value in the raw, unpolished energy of a NASCAR race at Talladega. This duality reflects a marketer who values the logical and the strategic but remains deeply grounded in the human element. Whether she is listening to an AI-generated audio summary of medical history before bed or taking partners to the World Cup, Katie’s persona is anchored in a belief that while technology can automate the task, it can never replace the human instinct to explore, learn, and connect.

The Mechanics of the Build

zerohash operates as the infrastructure layer for digital assets; it provides the technology and licenses necessary for companies to offer crypto functionality without building the stack from scratch. Katie describes the company as the “plumbing” of the industry. This role is frequently invisible to the end user but essential for the operation. To explain this, she uses the analogy of YKK zippers. They are ubiquitous, they are essential, and they are only noticed when they fail to work. For zerohash, success is defined by high uptime, compliance, and seamless integration into the partner’s user experience.

The operational architecture of the business rests on three distinct product pillars. First, the company enables trading, allowing platforms like interactive brokers or E-Trade to offer digital assets to their users. Second, it facilitates transactions, specifically through stablecoins, which allow for instant cross-border payments and settlement. Third, it manages tokenization, an emerging field that financial institutions are increasingly exploring for asset management. Katie notes that the demand for these services is rising; stablecoin transaction volumes have increased by 170 percent year over year within their ecosystem, and requests for information regarding stablecoin payments have increased fivefold in the same period.

The Logic of the Pivot

The transition from B2C to B2B marketing involves a shift from wide-reaching data science to surgical, relationship-based strategy. At public.com, Katie managed a diverse user base ranging from day traders to first-time investors. The messaging had to appeal to a broad demographic without alienating specific segments. In the B2B environment of zerohash, the target audience is nearly 1,000 potential decision-makers. The marketing must be surgical; it requires an understanding of what will help an executive get promoted or solve a specific operational burden.

Katie argues that empathy is the commonality across both disciplines. Effective marketing requires identifying the specific anxieties that keep a customer awake. In B2B, this often means understanding the regulatory and compliance hurdles that a partner faces. zerohash holds licenses in 52 jurisdictions within the United States, a feat that took years of manual paperwork and trust-building. This regulatory moat is a core part of the product story. By assuming the technical and compliance liability, zerohash allows its partners to focus on their primary user experience.

AI in Marketing

The integration of artificial intelligence into the marketing workflow has changed the definition of an “entry-level” role. Katie acknowledges that the manual tasks she performed early in her career, such as reformatting award submissions, are now handled by LLMs. However, she maintains that these tools require an architect. The machine can identify patterns and themes within hours of research, but the human marketer must coach the system to know which “synapses” to fire.

At zerohash, Katie uses AI to pressure-test ideas. She frequently prompts systems to act as a “hater” or a skeptical lawyer to identify weaknesses in a campaign before it is launched. This “inversion” technique allows her team to address counter-arguments in minutes rather than through weeks of legal review. Despite this technological leverage, she is finding that she works more hours than before. The efficiency of the tools has not led to more leisure time but to a deeper exploration of possibilities. If a task that once took months now takes two weeks, the team can simply produce more thoughtful, high-fidelity work, such as the 60-page book on stablecoins they recently produced from end to end.

The Future of Finance

The long-term trend in finance is the convergence of traditional finance and decentralized finance. Katie observes that the narrative is shifting from “us versus them” to a collaborative model. Large institutions like BlackRock and WorldPay are not merely observing the space; they are actively investing in the infrastructure. This shift is supported by a growing coordination between builders and policymakers. Unlike previous eras of tech regulation where a gap in understanding hindered progress, the current fintech landscape involves a more sophisticated dialogue regarding how digital assets move and settle.

As the industry matures, Katie is leaning into offline, high-integrity human experiences. While the “agentic” world allows for infinite digital variations of a message, it cannot replace the trust built during a small dinner or a shared experience at an event like the World Cup. For zerohash, the goal is to remain the invisible, trusted backbone of these transactions. Success means that the partner remains the hero of the story while the “plumbing” functions without friction.

“The LLMs need to be organized, architected. There needs to be a system and a way of thinking that you apply to how you’re using them. I’m ideally trying to train these things to have very broad knowledge of our business and our partners’ problems, broader than I could ever have as a single human.”

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The Technical Marketer’s Moat

Tenzin Rose does not view B2B SaaS as merely a software category. He describes it, with a hint of sarcasm that only an experienced operator can muster, as the pinnacle of human achievement.

After taking a year off to travel and nearly reaching enlightenment, he realized his true calling wasn’t in a mountain retreat, but in the high-stakes world of B2B sales and marketing. This grounded perspective, a blend of existential calm and a maniacal focus on revenue, defines his approach at Vooma, an AI-driven platform transforming the archaic world of freight brokerage.

Tenzin’s career has been a study in speed and adaptability. From navigating Fastly’s pre-IPO growth to founding his GTM-tooling startup, Tali, he has witnessed the shifting mechanics of growth across multiple cycles. Today, he states that the traditional marketing playbook, which is often siloed into MQLs and top-of-funnel noise, is obsolete. In its place, he is architecting a GTM strategy where marketing, product, and sales collapse into a single mission: the capture and preservation of institutional memory.

Meet Tenzin

If you want to understand what drives Tenzin, look to a nondescript beach with white sands and perfect water. His ideal scene involves a day spent surfing, followed by a campfire with close friends, sharing a beer, and “laughing it up.” It is a minimalist vision that mirrors his professional philosophy: to strip away the “fat and heavy” layers of corporate execution to find the 1% gains that compound into market dominance.

Meet Vooma

AI Inside a Fragmented Supply Chain

Vooma operates inside freight brokerage, a market most people never think about but depend on daily. Nearly everything in a room arrived by truck. Freight is foundational to the economy.

The market is massive and fragmented. Thousands of brokerages sit between shippers and trucking companies. Their job is coordination. Communication. Negotiation. Speed.

Much of that work still runs through email, phone calls, and manual systems. Margins are thin. Timing determines who wins a load. Institutional knowledge lives in individual brokers’ heads.

Vooma builds AI agents that sit inside those workflows. The product integrates with transportation management systems and helps brokerages quote faster, negotiate more consistently, and manage communication across the lifecycle of a shipment.

The promise is not just efficiency. It is leverage. A brokerage can grow without simply adding more headcount to handle volume.

But the deeper value, as Tenzin sees it, is institutional memory.

When negotiation history, pricing intuition, and lane-specific insights flow through a central system instead of individual inboxes, knowledge compounds. When a top broker leaves, the playbook remains.

In a volatile market where capacity shifts quickly and regulations change overnight, that continuity matters.

The 1% Rule: Compounding Speed in Product and Marketing

At Fastly, he learned a difficult lesson about the cost of standing still. When a company has a lead in the market, it is easy to become complacent. However, he maintains that the speed of execution, particularly in product development, is exponential.

“If you’re a percentage point faster on a month-to-month basis, that over the course of time can move very fast,” he explains. In the age of AI, where development cycles have shrunk from years to months, this speed is the only durable advantage.

At Vooma, this means responding to market shifts in real-time. When freight capacity leaves the market due to regulatory changes, Tenzin’s team doesn’t just wait for a quarterly roadmap update. They iterate. This requires a tight handshake between engineering and sales. He ensures his engineers are on sales calls, not as observers, but to catch the “puddles of demand” that are often invisible to those removed from the front lines. The trade-off is clear: you sacrifice perfectly polished long-term roadmaps for the ability to solve the customer’s “hair on fire” problem today.

Verticality as a Shield Against LLM Commoditization

One of Tenzin’s most contrarian views centers on the “build vs. buy” paradox facing modern marketers. He watches the rise of horizontal AI powerhouses like Claude and OpenAI with a wary eye. He believes that horizontal SaaS players, even successful ones like Clay, are at risk of being “gobbled up” by foundational models.

“Non-technical people can just point these models at a problem and build out a workflow,” he notes. If your product offers a horizontal solution that an LLM can replicate with a clever prompt, your moat is disappearing.

The defense, Tenzin says, is radical verticalization. By focusing on the niche complexities of freight brokerage, a 10% slice of the global GDP that is still reliant on manual emails and tribal knowledge, Vooma builds a moat of subject matter expertise. Dentists, freight brokers, and specialized manufacturers aren’t spending their days tinkering with Claude Code. They want a solution that understands their specific load life cycles, from quoting to document delivery. His strategy is to niche down until the “horizontal giants” find the market too small to bother with, but the value for the customer remains massive.

The Custom Agent: When Pricing Forces Innovation

Tenzin isn’t just a strategist; he is a practitioner who “vibe codes” his own solutions. He recently encountered a friction point with a major lead-enrichment SaaS provider regarding enterprise pricing for a specific LinkedIn Ads integration. Instead of accepting the 5x price increase, he used Claude to build a custom agent.

The Rose Automation Stack:

1. Input: HubSpot contact data filtered for relevance.

2. Processing: A custom workflow hosted on Render that hashes personal emails.

3. Output: Dynamic syncing with LinkedIn and Meta ads to target only active, high-intent accounts.

4. Feedback Loop: Data flows back into the outbound motion, allowing sales to reach out to people already engaging with the brand’s content.

This “agentic” approach to marketing operations is a glimpse into the future. He asserts that SaaS providers can no longer charge exorbitant fees for simple integrations. If the cost of the software exceeds the “time-to-build” threshold of a technical marketer, the marketer will simply build it themselves. This puts a ceiling on SaaS pricing and forces vendors to provide deeper, more integrated value that goes beyond simple data movement.

The TJC Framework: Taste, Judgment, and Creativity

As Tenzin restructures teams for the AI era, he has moved away from evaluating people based on their ability to execute menial tasks. Instead, he looks for the three vectors where humans remain indispensable: Taste, Judgment, and Creativity (TJC).

“Everything else in my mind should be automated off to AI,” he says. He envisions the “employee of the future” as a systems builder. This person doesn’t just write copy or manage a CRM; they have a conversation with an AI, recognize what should be delegated, and apply their judgment to the five options the AI presents.

This shift requires a move away from “comfortable” work. He admits that it is often easier to hide in menial tasks that feel productive but don’t move the needle. He challenges his team to be maniacally focused on P&L impact. If a task doesn’t require TJC, it is a candidate for delegation to a computer.

Capturing Institutional Memory in a Relational Industry

In the freight industry, “tribal knowledge” is both a blessing and a curse. Top brokers often carry their negotiation strategies and market intuitions in their heads. When they leave, that value walks out the door.

Tenzin has positioned Vooma’s AI as a tool for “institutional memory.” By funneling communication, whether it is voice, email, or Slack, through a central AI layer, Vooma codifies the intuition of the best operators.

“The value of AI is the visibility it provides into the operations,” he explains. It allows a brokerage to execute the same negotiation strategy repeatedly, regardless of who is at the desk. This is the ultimate product/marketing handshake: the marketing team sells the promise of a “smarter” brokerage, and the product delivers it by turning fragmented human conversations into a searchable, repeatable knowledge graph.

Brand as an Emotional Anchor

In a market where a new “AI for Logistics” company pops up every week, Tenzin believes brand is the only way to remain on the “shortlist” during a crisis. He rejects the idea of sterile, institutional B2B marketing.

To stand out, Vooma created a parody video of The Wolf of Wall Street. It was unconventional, a bit risky, and designed to make people laugh. “The memory centers in our brain are tied directly to emotion,” he says. If he can associate a positive emotion with Vooma, he wins the battle for mental availability.

When a broker’s “hair is on fire” because a truck driver just abandoned a load on the side of the road, he wants Vooma to be the first name that comes to mind. That isn’t achieved through white papers; it’s achieved through creativity and a brand that feels human in a digitized world.

Looking Ahead: The Meditative State of Marketing

Tenzin’s long-term vision for the industry is surprisingly humanistic. He hopes AI will free people from the drudgery of “punching stuff into CRMs,” allowing them to focus on building relationships and solving interesting problems.

His final insight reflects his travel year. He imagines a device that helps people tap into a meditative state, a felt sensation of focus and calm. In many ways, that is what he is building at Vooma: a system that removes the noise and chaos of global logistics, allowing operators to find their own “flow state” in the pinnacle of human achievement—B2B SaaS.

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Liza Moiseeva does not view marketing as a game of capturing attention through the highest bidder. She views it as an exercise in mission alignment.

Throughout her career, which spans Moscow to the Bay Area, she has operated exclusively within the guardrails of mission-driven organizations. From microfinance networks to fair-trade subscription models, the throughline has remained constant: you cannot simply sell a product; you must sell a purpose.

At Commons, a fintech app designed to help users “buy less and buy better,” Liza faces a unique practitioner’s paradox. She is marketing a free tool that saves users money and reduces their carbon footprint, yet she must overcome one of the steepest friction points in digital finance: the trust required to connect a bank account.

To solve this, she made a high-stakes operational bet. She paused the majority of the company’s paid acquisition spend and pivoted the entire organization toward a content-led, educational engine. The result was not just a surge in followers, which grew from 6,000 to over 400,000 on Instagram, but a fundamental shift in how the brand establishes credibility before the first transaction ever occurs.

Meet Liza

Liza is a former competitive swimmer who has traded the chlorine of the pool for the open waters of the Pacific. “I spent so much time with chlorine, I do not want to be anywhere close to pools anymore,” she laughs. Her ultimate happy place is in Hawaii, specifically Maui, where the sound of whales and the warmth of the water provide a stark contrast to the structured, high-pressure environments of Moscow and D.C., where she began her journey. When she isn’t navigating the complexities of sustainable fintech, you can find her in her garden, a passion she shares with much of her team, grounding her mission-driven work in the literal earth.

Meet Commons

A Fintech App for the Planet

Commons operates at the intersection of personal finance and climate impact. The product is a mobile app that allows users to connect their bank cards and view not only how much they spend, but what that spending supports.

At its origin, Commons focused narrowly on carbon tracking. Users could measure the estimated emissions associated with their transactions and optionally offset them through curated climate projects. Over time, the company expanded its scope. Measuring carbon alone proved too abstract for mainstream adoption. Many consumers either mistrusted offsets or lacked context for what the numbers meant.

The evolution was pragmatic. When users connect their card through Plaid, Commons can analyze transaction categories and provide a broader picture of financial behavior. It now combines spending insights, sustainability brand ratings, and carbon offset options in one place.

The brand ratings are central. Commons evaluates companies based on publicly available sustainability disclosures and third-party certifications, then guides users toward higher-rated alternatives. The logic is straightforward: money is a signal. If millions of small transactions shift, supply chains eventually respond.

The app is free to download. Revenue currently comes primarily from voluntary carbon offset subscriptions and from a B2B climate services arm that works with high-net-worth individuals and companies. Consumer monetization is planned but secondary to growth.

The immediate goal is scale. Not passive downloads, but connected users who trust the platform enough to link financial data.

That trust requirement shapes everything.

The Pivot from Measurement to Money

When Commons first launched five years ago, the value proposition was rooted in carbon measurement. The idea was to help users understand their emissions based on their spending. However, Liza and the leadership team recognized a significant market reality: most consumers in 2026 still find carbon offsets and emissions data abstract or even untrustworthy.

The strategic shift was to move the focus from the “planet” to the “wallet.” By framing Commons as a tool to save money and spend better, the team lowered the barrier to entry. “Everybody cares about saving money,” Liza notes. “This is our way of bringing people into the fold.”

This transition required a total overhaul of the product’s communication. Instead of leading with a carbon survey, the app now leads with sustainable brand ratings, using publicly available data and third-party certifications to guide spending. This is a practical framework for utility: move from a complex, invisible problem (carbon) to a tangible, everyday decision (spending).

The Content-First Growth Framework

Liza’s most significant operational decision at Commons was the move away from paid-ad dependency. While many growth executives treat Meta and Google as the primary levers for scale, Liza viewed them as secondary tools for testing.

The “Content-First” framework she deployed is built on three specific pillars:

1. Platform-Native Entertainment

Liza rejects the “utility-first” approach to social media. “On social media, it’s all about entertainment,” she explains. “We aren’t going to be posting ‘Download the app, here’s our new feature.’ Nobody cares about that.” Instead, the team creates content optimized for virality and engagement, such as deep dives into the environmental impact of major corporations like Amazon or Target. By leading with entertainment that resonates with the audience’s values, the brand earns the right to eventually ask for the app download.

2. The 80/20 Channel Split

Knowing your audience is a prerequisite for resource allocation. At her previous startup, GlobeIn, Liza focused heavily on Facebook because her core demographic was women aged 35 to 80. At Commons, where the audience is significantly younger, Instagram is the primary theater of operations. She explicitly chose not to prioritize TikTok for conversion, noting that while the reach is high, the algorithm is a “closed loop” designed to keep users on the platform rather than driving them to an app store.

3. IRL Culmination

To solidify the online community, Commons hosts an annual Earth Summit during San Francisco Climate Week. This is not just a networking event; it is an “IRL culmination” of a year’s worth of content. It serves as a high-fidelity touchpoint that transitions digital followers into brand advocates.

Bridging the Fintech Trust Gap

The central challenge for any fintech app is the “card connection.” Commons uses Plaid, the same infrastructure that powers Venmo and PayPal, but Liza knows that technical security alone is not enough to win the customer. There is a “trust gap” that can only be bridged through consistent, educational marketing.

She views the marketing team’s role as performing “unscalable” work upfront to enable scalable growth later. By providing free value through brand ratings and the Second Nature podcast, the team builds goodwill. When a user is finally asked to link their financial data, they aren’t doing it for a stranger; they are doing it for a brand that has already spent months educating them.

The AI Magic Wand: A Sustainability Dilemma

As a CMO in the Bay Area, Liza is acutely aware of the pressure to automate. However, for a brand built on sustainability, AI presents a profound ethical conflict.

“We have to grapple with the fact that our most popular Instagram post ever was about the water usage of AI,” Liza admits. This awareness led to the creation of the Commons Responsible AI Statement, a public document outlining how the company measures and reports its AI usage.

Liza uses a powerful metaphor to describe the competitive necessity of AI: “It’s like being Harry Potter trying to fight Voldemort without a magic wand.” Because sustainable brands already operate under more constraints than their “regular” competitors, they cannot afford to ignore tools that increase efficiency.

Her framework for AI is one of Net Positive Impact. The team uses AI for research and data collection to scale their brand ratings faster, believing that the environmental benefit of a million people spending more sustainably outweighs the carbon footprint of the LLM used to generate that data. It is a calculated trade-off, one that requires constant measurement and public accountability.

Marketing as Capital Allocation

Liza treats marketing resources with the same discipline her mentors in microfinance treated capital. She acknowledges that paid ads have a place, but primarily as a laboratory. “Paid ads is the best way to test things quickly, test messages, and see what messaging angles help us get the highest quality user,” she says.

By using paid spend to validate hooks and then deploying those hooks into organic content, she creates a flywheel where the cost of acquisition (CAC) is subsidized by the viral reach of her community. This protects the company from the volatility of ad auctions while building a “stickier” user base that joins the app through belief, not just a banner ad.

Looking Ahead: The Stakeholder Shift

Liza points to Patagonia’s 2022 announcement, in which the company declared Earth its only stakeholder, as the gold standard for the industry. For Liza, the future of CMO leadership is not about managing a department; it’s about managing a brand’s legal and ethical status as a “public benefit.”

Her recommendation for future leaders is a rigorous critique of how wealth and power influence change, citing Anand Giridharadas’s Winners Take All as a foundational text. Her takeaway is a warning for the industry: “By corporations not making the right ethical choices as a business to begin with, they create the problems that they afterwards resolve through CSR.”

For Liza, the goal is to build a company where the marketing and the mission are indistinguishable. At Commons, she is proving that you don’t need a massive ad budget to scale if you have a community that trusts your data as much as they trust your “magic wand.”

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The Cost of a Click and the Value of a Brand

Casey Akerblom does not think about marketing as a debate between brand and performance. He thinks about it as a capital allocation problem.

Earlier in his career at Zillow, he watched a fully optimized performance engine operate at scale. Creative testing, incrementality experiments, channel structures, and cost controls were rigorously managed. Yet one metric dwarfed everything else: brand-driven demand.

That insight sharpened during COVID, when Zillow paused paid media for several months. “We paused all of our media spend,” he recalls. “Not only did things not fall back, we hit all-time highs and we gained market share.” Performance marketing did not disappear, but it was not the underlying engine of demand. Brand was.

For Casey, that experience reframed the role of marketing. “Instead of going to Google and the vending machine and paying a hundred-dollar crazy cost per click because they’re wielding their monopolistic power, if you can trade a hundred-dollar competitive auction click for a couple of pennies or a dollar per click on your own branded terms, that’s a trade-off you’re going to make 99 out of 100 times.”

Brand, in that sense, is not philosophical. It is financial. It lowers the long-term cost of acquisition and protects the business from auction volatility.

That framing now shapes how he leads marketing at Bluevine, the largest small business banking platform in the United States.

Meet Casey

A few years ago, Casey was in Kiawah for his father’s seventieth birthday. He played a round of golf with him, just the two of them, and they finished the day sitting on the porch with a cocktail and lunch, watching other groups come in. “That’s a pretty special one,” he says. Time with family, on a celebratory moment, without distraction. It is a revealing answer from someone whose professional philosophy is rooted in long-term value.

Investment Thinking Applied to Marketing

Before entering growth roles, Casey began his career in investment research at what he describes as an outsourced CIO firm. The team built endowment-style portfolios for high-net-worth families and institutions, allocating capital across hedge funds, venture capital, and private equity. The work was bottom-up and long-term by design.

Starting during the financial crisis sharpened that discipline. Every thesis had to be tested against real volatility.

Sitting across the table from fund managers, Casey listened to them describe businesses with durable competitive advantages and compelling growth stories. Eventually, he found himself asking a different question. Why am I on this side of the table listening to growth stories instead of helping build them?

He went to business school and joined Zillow in its early performance marketing days. Over nearly a decade, he helped scale the paid media organization from a small team to thirty-seven people spanning performance and brand channels. The throughline from investing remained intact: compounding matters more than short-term wins.

That philosophy looks different depending on the business model.

At Zillow, LTV was largely transactional. Consumers do not move homes frequently, and the monetization engine was marketplace-driven. “The LTV was really about optimizing the market,” Casey explains, noting that bringing incremental customers into an already healthy market did little to shift the overall economics.

Bluevine is structured differently. It is relational, not transactional.

Checking as Entry, Lending as Expansion

Bluevine offers business checking, lending, and payments within a connected platform built for small business owners. Many customers enter through checking because eligibility is broader and underwriting constraints are lower. “The primary source of growth for us right now is the checking business,” Casey says. “Most anyone can come to Bluevine and open a business checking account as long as they have a real business that they’re running.”

From there, the opportunity is to deepen the relationship.

Once customers begin using sub-accounts for employees, activating fraud controls, connecting their accountants through view-only dashboards, and leveraging payment tools, the platform becomes embedded in daily operations. Lending then becomes a natural extension for growth or short-term cash flow support.

Internally, the language might be cross-sell and up-sell. Casey frames it differently. “A lot of LTV and loyalty is the same. Loyalty is essentially LTV but expressed in behavioral terms. They’re actually using the products that you have that you’re offering.”

In that view, retention is not a campaign lever. It is a byproduct of product adoption and real value creation. The marketing function is responsible not just for acquisition, but for educating customers about the full scope of what the platform can do for them.

The Limits of Clean ROI

Casey holds a view that can be difficult to defend inside performance-driven organizations: the most impactful growth investments are often the hardest to measure through clean, direct ROI. Digital marketing has trained teams to expect tight attribution loops and immediate feedback, and that expectation can create a kind of institutional bias toward what is easiest to quantify. “That can make CFOs incredibly queasy,” he says. “They want to see everything with a clean, tight ROI.”

In his view, the issue is not measurement itself but overreliance on the most convenient form of it. Performance channels are seductive precisely because they are so measurable, but harvesting existing demand is not the same as building future demand. The work that compounds over time often operates one layer removed from last-click attribution.

Before asking what the ROI will be, Casey believes teams should start with a more fundamental question: what constraint are we actually trying to remove? “Is it that our customers don’t understand what we offer? Is it that they don’t know who we are? Is it that they may have heard we offer it but they haven’t cared so we haven’t yet emotionally resonated with them? Or is it that we’re just not showing up enough?” Until that problem is clearly defined, ROI becomes a premature proxy for strategy.

Once the constraint is identified, measurement can be designed around progress toward that outcome. It may not resemble the neat efficiency metrics of paid search, but it can still be rigorous. The real mistake, he argues, is confusing ease of measurement with strategic importance.

Category Creation and Emotional Imprint

Casey is particularly drawn to brands that reshape categories rather than compete narrowly within them. Airbnb stands out. A decade ago, the idea of staying in a stranger’s home felt uncomfortable. Today, it feels normal, even aspirational.

The shift was not achieved through rational feature comparisons. It was achieved through emotional reframing.

He contrasts that with brands that over-index on technical specifications in top-of-funnel advertising. He recalls seeing repeated ads for an ergonomic chair during MLB playoff broadcasts. The spend was clearly significant, yet the message focused heavily on specifications and comparison points. “The only reason I remember it is that I remember thinking to myself they must have paid such an exorbitant amount to have that much frequency and reach, and yet I still have no idea what the brand was.”

Rational persuasion has its place. But memory and preference are often built through emotional resonance. If a brand fails to create an imprint, frequency becomes expensive noise.

Direct Mail and Structural Advantage

In fintech and other regulated categories, digital targeting has tightened. Platforms have become more conservative about targeting options, particularly around sensitive financial attributes. When targeting entrepreneurship as an interest, Casey notes that the audience may range from a teenager imagining a future startup to a seasoned operator running a decade-old business.

Direct mail offers structural precision. It allows targeting based on time in business, credit profile, and operational maturity. “It’s quite an expensive channel to run,” he says, because cost is evaluated per mailer rather than per thousand impressions. But in higher-LTV segments such as lending, the precision can justify the cost.

Direct mail is not nostalgic. It is a tool deployed when structural economics favor accuracy over cheap reach.

Owning the Narrative Through Data

In a landscape flooded with AI-generated content, Casey believes brands must create their own news rather than compete on commoditized output. “There’s this land grab that’s going on right now where folks are leveraging AI to produce tons of content,” he says. “A lot of the glossary-style content is just regurgitating something that already exists.”

Bluevine’s BOSS Report and State of Small Business Report rely on proprietary data and customer insights. By analyzing internal trends, such as growth in new account creation by geography, the team can surface stories that matter locally. When Indianapolis shows strong growth, local journalists see a headline, not just a data point.

Brand mentions compound over time. They build credibility, improve visibility, and increasingly influence AI-driven discovery environments. Digital PR, in this context, is not vanity coverage. It is a strategic distribution of differentiated insight.

AI and the Preservation of Judgment

While many conversations about AI focus on role elimination, Casey focuses on skill evolution. “I think it’s the wrong focus,” he says. The more relevant question is which capabilities become more valuable.

At Bluevine, AI is used to streamline execution rather than replace strategic thinking. The team ingested SEO data, web traffic data, and performance metrics into custom GPT workflows and agentic solutions that generate reports and surface opportunities more quickly. This accelerates the middle steps of analysis.

What it does not do is decide where to win.

Humans still determine where product-market fit is strongest, how trade-offs should be assessed, and where creative differentiation can create advantage. “It’s about getting the middle steps faster and more streamlined so that then you can have deeper discussion around how to win, where to win, and how we apply creative solutions.”

The premium skill set, therefore, shifts toward first-principles thinking and constraint identification. Execution becomes more automated. Judgment becomes more valuable.

Marketing as Portfolio Construction

Across Zillow and Bluevine, across performance and brand, across direct mail and digital PR, the underlying philosophy remains consistent.

Marketing should behave like an investment portfolio.

Some efforts harvest demand. Others create it. Some reduce long-term acquisition cost. Others deepen lifetime value. The role of the CMO is not to win channel debates but to allocate capital in ways that compound advantage.

When a brand reduces your exposure to volatile auctions and lowers the effective cost of acquisition, it is not a soft metric. It is a strategic asset.

For Casey Akerblom, that is the job: to ensure that marketing decisions withstand both the CFO’s scrutiny and the market’s volatility, not by chasing clean attribution at all costs, but by building durable demand that makes the next click cheaper than the last.

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