Brand or Demand? Where the Next Startup Dollar Should Go

Why the “60/40” answer is not the right answer for your startup

Les Binet and Peter Field’s IPA publication The Long and the Short of It established the framework distinguishing short-term response activity from long-term brand-building — the framework most founders reference when they say “60/40” without checking whether the source they are quoting actually claims 60/40 is the right split for their situation. Binet and Field themselves are explicit that the framework is not an iron rule: the specific split varies by brand, category, situation, and other contextual factors. A pre-chasm startup with no brand recognition, a chasm-crossing startup with new pragmatic-majority prospects, and a post-chasm scale-up defending category leadership do not sit at the same point on the same curve.

The founder question is not “what is the industry-standard split.” The founder question is “which failure would kill my pipeline this quarter.” When the recognized-brand check fails and the founder still spends the next dollar on demand activation, the ad clicks convert existing branded search (people already looking for the product) rather than generating new pipeline; the founder concludes the market is small when the diagnosis is actually that the market does not yet know the startup exists. When the demand check fails and the founder still spends on brand, the awareness grows against a segment that is not yet ready to buy, and the runway funds a long-horizon investment the balance sheet cannot support. Both mistakes are common. Neither is fixed by a spreadsheet ratio.

April Dunford’s Obviously Awesome positioning framework treats positioning as the prerequisite to every marketing dollar — a brand-vs-demand allocation decision made before the positioning is defensible spends both types of dollars against a target the market does not yet recognize. The positioning is the reference point for the allocation, not the other way around; the answer to “where does the next dollar go” depends on what the buyer needs to hear before they will buy, and the buyer’s need is answered by the positioning first.

What each dollar actually buys

Understanding the brand-vs-demand distinction operationally — not just conceptually — is the prerequisite for a defensible allocation. A brand dollar buys mental availability, category association and long-horizon recognition: the reader remembers your name when the buying trigger appears months later. A demand dollar buys near-term action: the reader clicks, signs up, books a demo, converts. The two are complementary, not interchangeable, and each is measured by different metrics.

Alistair Croll & Benjamin Yoskovitz’s Lean Analytics supplies the measurement discipline. Demand is measured in near-term conversion metrics — customer acquisition cost, lifetime value, conversion rate, payback period. Brand is measured in longer-horizon metrics — aided and unaided awareness, share of voice within category, direct traffic and branded search volume, sentiment. Measuring brand as if it were demand produces misleading dashboards because the brand investment does not close deals inside a quarterly attribution window; the founder cuts brand as “underperforming” and destroys the mental availability the demand campaigns depend on downstream.

Gabriel Weinberg and Justin Mares’ Traction catalogues nineteen traction channels and provides the Bullseye framework for choosing which channels a startup tests. The brand-vs-demand distinction sits inside the Bullseye output: some channels are structurally brand-oriented (content, community, PR, business development, speaking, targeting blogs), some are structurally demand-oriented (search-engine marketing, targeting blogs — some overlap — paid social, affiliate, sales). A founder testing three channels from the Bullseye is implicitly testing a brand-vs-demand mix; the allocation question is whether the mix that emerges from testing matches the demand-recognition-runway check.

The three checks for the next dollar

The following three checks are the editorial synthesis of Binet & Field’s framework, Dunford’s positioning discipline, Weinberg & Mares’ Bullseye output, Croll & Yoskovitz’s measurement rules, and Moore’s chasm positioning. Each check is written before the dollar is committed. The checks are not a formula; they are a decision surface the founder revisits every quarter with current evidence.

Check 1 — is there current demand the activation can convert

Demand exists in the segment when prospects are actively searching for solutions to the problem, comparing vendors, and moving through evaluation processes. Evidence includes branded and non-branded search volume in the category, RFP or vendor-evaluation activity, competitors reporting healthy pipeline, and inbound requests the startup already receives. When demand is present, activation spend converts it — search advertising captures the searcher’s intent, retargeting closes the gap between consideration and decision. When demand is absent, activation spend converts almost nothing because there is no intent to capture. The check is passed when the founder can name at least three concrete demand signals in the segment; the check fails when the founder is guessing about demand from adjacent segments or general market reports.

Check 2 — does the segment recognize the brand by name

Recognition exists when buyers in the target segment can name the startup unprompted, list it among vendors they consider, or recognize it in aided-awareness surveys. Recognition is not measured by follower count or blog traffic; it is measured by whether the buyer, in the moment of a buying trigger, thinks of the startup. When recognition is present, activation dollars land on a prepared surface — the click reaches someone who already trusts the name. When recognition is absent, the activation dollar reaches a stranger whose default response is to click a competitor’s ad because that competitor’s name is familiar. The check is passed when the segment shows measurable recognition in aided-awareness or direct-traffic evidence; the check fails when the founder cannot cite a specific recognition signal.

Check 3 — does runway allow both investments long enough to see the effect

Brand investments have a longer feedback window than demand investments — mental availability accumulates over quarters and years, not days and weeks. A startup with three months of runway cannot fund a brand campaign to a legible outcome; the money will be gone before the awareness needle moves. Demand investments have a shorter feedback window but still require enough spend at enough frequency to produce a meaningful signal. Sarasvathy’s effectuation lens applies: the founder’s actual runway is the constraint, not the theoretical optimal split. The check is passed when runway supports the allocation for the length of time the effect requires; the check fails when the founder is planning against a runway that will end before the investment matures.

Check	Passes when	Fails when	Observable evidence
1. Demand present	≥3 concrete demand signals in segment (search volume, RFPs, pipeline)	Founder inferring demand from adjacent segments or reports	Search data, sales pipeline data, prospect requests
2. Recognition present	Aided-awareness or direct-traffic evidence in segment	Follower count cited as recognition proxy	Awareness survey, direct-traffic share, unprompted mentions
3. Runway allows effect	Runway ≥ feedback window for the allocation type	Runway ends before investment can be measured	Runway calendar cross-checked against brand/demand feedback windows

Where the startup sits on the chasm changes the answer

Geoffrey Moore’s Crossing the Chasm makes brand recognition a chasm-crossing prerequisite for pragmatic-majority buyers. A pre-chasm startup selling to early adopters can win on product novelty and technical intrigue; a chasm-crossing startup selling to the pragmatic majority needs the signals of credibility (case studies, category recognition, third-party validation) that only a sustained brand investment produces. The allocation shift is real: as the startup approaches the chasm, the recognition check fails more often against pragmatic-majority prospects, and the brand allocation increases in proportion.

The chasm framing changes the “next dollar” question at a specific moment in the startup’s evolution. A pre-chasm startup can defensibly spend most of the marketing budget on activation because the early-adopter segment recognizes and evaluates on technical merit; a chasm-crossing startup that carries the pre-chasm allocation forward burns money on demand activation against a pragmatic segment that has never heard of the brand. The three checks catch this drift — the recognition check that passed for the early-adopter segment fails for the pragmatic-majority segment, and the allocation shift becomes visible before the burn rate teaches the same lesson later at higher cost.

Google Performance Max: a demand tool, not a brand builder

A specific mistake worth calling out: running Google’s Performance Max campaigns as the sole marketing channel for an unknown startup. Performance Max is documented as an automated-bidding, all-inventory campaign type designed for advertisers whose primary goal is conversion. It optimizes toward conversion signals — sales, sign-ups, form fills — using Google’s machine-learning bidding across all Google surfaces. For a startup with existing brand recognition, Performance Max converts that recognition efficiently at scale. For a startup without brand recognition, Performance Max primarily converts branded search traffic (users who already know the name) and produces low-quality clicks from non-branded surfaces where the audience does not recognize the ad.

The failure mode is founders who see Performance Max reports showing conversion at the top of the account and conclude that “the ads work” without noticing that the conversions are from users who searched the brand name — traffic the founder would have received organically anyway. The three-check discipline catches this: if the recognition check fails and the demand check passes only for branded search, Performance Max is converting existing brand recognition rather than building new demand. The next dollar should go to whatever activity would improve the recognition check — not to more Performance Max spend that will produce the same misleading dashboard next quarter.

Brand-vs-demand allocation is a business-model decision

David Teece’s 2010 Long Range Planning business-model discipline is the underlying reference. The business model determines what channel mix, buying-cycle length, and revenue-capture ceiling the startup operates under, and brand-vs-demand allocation must be coherent with all three. An enterprise sales-led business investing everything in performance-marketing demand acquisition mismatches the buying cycle (enterprise buyers take months, performance ads optimize toward days); a self-serve business investing everything in brand PR aimed at CFOs mismatches the buyer identity (the SaaS buyer is often a practitioner, not the CFO). Steve Blank’s HBR 2013 essay and Shepherd & Gruber’s 2020 consolidation in Entrepreneurship Theory and Practice both treat marketing spend as hypothesis-testing artifact: the brand-vs-demand allocation is one of the highest-consequence hypotheses a founder tests, and the test requires a written scorecard rather than founder conviction.

The business-model check is often what changes the answer between two similar-looking startups. Two B2B SaaS companies with the same product feature set and same target industry can have different defensible allocations because one is priced for annual enterprise contracts (long cycle, requires brand credibility with procurement) and the other is priced for monthly self-serve (short cycle, converts on demand-generation signals). Same category, same product, different business model, different allocation. Teece’s coherence discipline names the reason.

Sixty-day brand-vs-demand allocation scenario

Assume a hypothetical B2B SaaS startup with six months of runway, a working product, current pipeline mostly from founder outbound, and a $30,000 monthly marketing budget the team wants to allocate between brand and demand for the next quarter. The scenario is illustrative — no real company is named, no specific CAC or awareness figure is invented, and every output is a written allocation brief and switch trigger rather than a promised outcome.

Days 1–14 — three-check scoring against current evidence. The founder scores each of the three checks against the segment with written evidence — search-volume data, recent prospect conversations for recognition signal, runway calendar cross-checked against brand and demand feedback windows. The scorecard is comparative: which checks pass, which fail, and which need more evidence before the founder can score them at all. The output is not a decision yet; it is an evidence base that makes the eventual decision defensible.

Days 15–35 — parallel small experiments in both allocations. Rather than picking one full-quarter allocation, the founder runs a small brand experiment (a defined content series, a specific PR effort, or a community initiative) and a small demand experiment (a targeted paid search campaign, a retargeting sequence, or a targeted-blog placement) in parallel for four weeks. The measurement framework is set beforehand: what brand metric the brand experiment produces evidence for, what demand metric the demand experiment produces evidence for, and what would count as a positive or null result. Weinberg & Mares’ Bullseye framework supplies the structure — the two experiments are picks from the shortlisted channels, not commitments to permanent allocation.

Days 36–60 — allocation decision and quarterly commitment. The evidence from the parallel experiments plus the three-check scorecard informs the allocation for the next quarter. The founder writes a one-page allocation brief — the split, the reasoning against each of the three checks, the specific switch triggers that would move the allocation in the next quarter, and the measurement framework. The brief is circulated to the team so the marketing decisions across the quarter reference the same document rather than drifting toward whichever channel produced the loudest anecdote in the last board meeting.

The purpose of the sequence is not a promised marketing outcome. The day-sixty output is a written allocation brief, a small-experiment evidence base, a set of switch triggers, and the next re-score date. The allocation remains a hypothesis the startup tests each quarter — not a strategic pronouncement that survives the arrival of contradicting evidence.

Phase	Entry criteria	Exit artifact	Owner
Days 1–14: three-check scoring	Current evidence for demand, recognition, runway assembled	Scorecard with pass/fail/unknown per check	Founder + growth lead
Days 15–35: parallel experiments	Scorecard identifies which checks need evidence	Small brand + small demand experiment results with pre-set metrics	Founder + first marketer + agency (if used)
Days 36–60: allocation brief	Experiment data and re-scored checks	One-page allocation brief + switch triggers + re-score date	Founder + growth lead + finance

When to shift the allocation — and when the request is founder anxiety

Shift triggers and false alarms

A brand-vs-demand allocation shift should be triggered by three specific signals: the recognition check has flipped (aided-awareness has grown to the point that demand-side spend now lands on recognized names, or has shrunk to the point that demand-side spend converts almost nothing), the runway has changed materially (a fundraise extends the window, a burn adjustment shortens it), or the business model has shifted (pricing, segment, buying cycle). A single lost quarter is not a shift trigger; a losing pattern across two or three quarters in a segment where the checks all pass is. Recognizing the difference between real signal and quarterly noise is what keeps the allocation question a decision surface rather than a source of quarterly whiplash.

The most common false alarm is a demand-side dip that triggers a request to “cut brand spending because performance marketing is underperforming.” The three-check framework catches this: if the demand dip is caused by a failing recognition check (the ads are reaching strangers), cutting brand accelerates the problem rather than fixing it. Cutting brand only makes sense when the demand dip is caused by a genuine demand-side problem (ad platform change, competitor bid pressure, product-market mismatch) — and even then, the fix is usually inside the demand programme rather than a punitive brand cut.

Five brand-vs-demand mistakes to skip

The following five mistakes appear repeatedly in startups that treat brand-vs-demand allocation as a formula rather than a decision surface. Each mistake has a specific rewrite.

• Applying a fixed 60/40 (or similar) split without checking whether your segment has the recognition demand-side spend assumes. Binet & Field themselves note the framework is not an iron rule. Rewrite: score the three checks against your own segment before adopting any published split.
• Running Performance Max as the sole channel for an unknown brand. Performance Max is a demand tool that assumes recognized brand demand exists to convert; running it alone converts existing branded search and produces low-quality clicks from non-branded surfaces. Rewrite: pair Performance Max with a deliberate brand-building programme when the recognition check fails, or defer Performance Max entirely until the recognition check passes.
• Treating brand as a measurement gap and demand as the only “real” metric. Brand is measured differently, not measured worse. Rewrite: instrument brand with awareness surveys, direct-traffic share, unprompted mention tracking, and share-of-voice measurement — and defend those metrics to the CFO the way demand metrics are defended.
• Cutting brand at the first pipeline dip. Cutting brand accelerates a recognition-driven demand problem rather than fixing it. Rewrite: diagnose whether the pipeline dip is demand-caused or recognition-caused before touching the brand budget.
• Letting the CAC-payback window force short-only spend when the business model requires long-term brand equity. Enterprise-sales business models require brand equity that CAC-payback measurement cannot capture. Rewrite: measure brand against the business-model horizon (annual contract value, retention, expansion revenue), not against monthly CAC dashboards.

Sources and evidence

Each source below was verified during the current production and is used in the article’s visible body. This article is educational — jurisdiction-specific advertising regulation, sector-specific consumer-protection rules, contract-negotiation terms, and platform-specific advertising policies all belong to qualified professional advisors.

• Gabriel Weinberg & Justin Mares — Traction: How Any Startup Can Achieve Explosive Customer Growth — Penguin UK.
• April Dunford — Obviously Awesome: How to Nail Product Positioning so Customers Get It, Buy It, Love It — author official page.
• Alistair Croll & Benjamin Yoskovitz — Lean Analytics — author site.
• Geoffrey A. Moore — Crossing the Chasm (3rd Edition) — HarperCollins.
• Steve Blank — Why the Lean Start-Up Changes Everything — Harvard Business Review 2013.
• Dean A. Shepherd & Marc Gruber — The Lean Startup Framework: Closing the Academic-Practitioner Divide — Entrepreneurship Theory and Practice 2020.
• Saras D. Sarasvathy — Causation and Effectuation — Academy of Management Review 2001.
• David J. Teece — Business Models, Business Strategy and Innovation — Long Range Planning 2010.
• Les Binet & Peter Field — The Long and the Short of It — IPA publication.
• Google Ads Help — About Performance Max campaigns — Google Ads product documentation.
• PitchBook & National Venture Capital Association — PitchBook-NVCA Venture Monitor — ongoing industry monitor.
• World Bank — New business density indicator — macro background.
• OECD — Financing SMEs and Entrepreneurs 2024 — macro background.

Put the next dollar where your three checks — not a formula — send it

Score the three checks in writing before every quarterly budget decision: demand present in the segment, recognition present in the segment, runway long enough to see the allocation’s effect. Where all three favour activation, spend on demand. Where recognition fails, spend on brand — even if the demand check also passes, because activation on an unrecognized brand converts existing intent rather than generating new pipeline. Where runway is short, pick the allocation whose failure would kill the pipeline first, and be honest about which failure that is.

Instrument both types of spend against the metrics they can actually produce. Brand is measured in aided and unaided awareness, direct traffic, unprompted mentions, share of voice; demand is measured in customer acquisition cost, lifetime value, payback, conversion. Presenting brand on a CAC dashboard will produce the same misleading conclusion every quarter: that brand is underperforming when in fact brand is being measured against the wrong metric. The three-check framework and the split measurement framework belong together on the same one-page allocation brief.

Two quarters of this discipline separate startups whose next dollar compounds from startups whose next dollar disappears. Put the next dollar where the three checks send it — the segment does not care about your split ratio, the CFO cares about the checks that were done before the money was committed, and the pipeline six months from now will tell you which check you skipped.

FAQ

Is Binet & Field’s 60/40 split the right answer for a B2B SaaS startup?

Not automatically. Binet and Field themselves note the framework is not an iron rule — the specific split varies by brand, category, situation, and other contextual factors. A pre-chasm B2B SaaS startup with no brand recognition and a short runway is not sitting on the same point of the same curve as the case studies Binet & Field analyzed. Score the three checks against your own segment before importing any published ratio.

How do I know whether Performance Max is actually building demand or just harvesting branded search?

Segment the Performance Max reporting to isolate branded vs non-branded conversion. If the majority of Performance Max conversions come from users who searched your brand name, the campaign is harvesting existing recognition — that traffic would likely have converted through organic branded search anyway. If conversions include measurable non-branded traffic, Performance Max is contributing net-new demand. The three-check discipline is the diagnostic: if the recognition check fails and Performance Max shows conversion primarily on branded search, the next dollar belongs in brand, not more Performance Max.

How long should the brand investment run before I judge whether it worked?

Brand feedback windows are measured in quarters, not weeks. A typical minimum is two quarters of consistent investment before the aided-awareness signal is legible against baseline. This is why the runway check exists — a startup with three months of runway cannot fund a brand programme to a measurable outcome. If runway is short, either extend runway before starting brand or focus the marketing spend on activation until runway can support brand’s feedback window.

What if my segment has no measurable branded search volume yet?

That is direct evidence the recognition check fails and the demand check also fails — no branded search means no one is looking for you by name. In that state, activation spend is expensive because it must build recognition and convert simultaneously. The cheaper path is a deliberate brand-building programme (content, community, PR, targeted-blog placement) until aided awareness is measurable, then layer activation on top. Weinberg & Mares’ Bullseye framework helps identify which brand-building channels fit the segment.

How often should the allocation be re-scored?

Quarterly is the minimum cadence for early-stage startups. Re-score also when one of three specific triggers appears: the recognition check flips (aided awareness grew or shrank materially), runway changes materially (fundraise, burn adjustment), or business model shifts (pricing, segment, buying cycle). A single lost quarter is not a re-score trigger; a losing pattern across two or three quarters where the checks all pass is.

Where does this article end and where does agency or media-buying advice begin?

This article is educational context around the brand-vs-demand allocation decision — the three checks, the measurement discipline, the business-model coherence. It is not media-buying advice, jurisdiction-specific advertising regulation guidance, or platform-specific bidding-strategy recommendation. Specific media plans, platform bidding, competitive analysis for a specific segment, and advertising-law compliance require specialized professional advisors familiar with the relevant market and platform. Use the operator brief to structure the allocation question, then extend with media buying, legal and platform-specific expertise when the decision requires actionable answers.