Dev Basu

The default reaction is to launch more campaigns and content. Dev Basu argues for repairing the foundation first: audit what is actually happening, align both teams on lead quality, set up attribution, and only then drive traffic.

The 100-day plan breaks into phases.

• Days 1-30 audit and diagnose: review closed-won deals, map channels against pipeline, check the real MQL-to-SQL rate, audit attribution, and talk to the last five sales losses.
• Days 31-60 define and align: align ICP with sales, set up three-source attribution, agree on what a good lead looks like, and choose one North Star pipeline metric.
• Days 61-90 launch and capture: bottom-of-funnel content and landing pages, paid on BOFU keywords, reactivate cold CRM leads, and fix the demo page before traffic.

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A CMO under quarterly pressure cuts everything that does not convert within 90 days and spends only on those in-market buyers.

• That works for about three quarters, Dev Basu writes, and then there is nothing behind it.
• The pool of in-market buyers is fixed, so Dev Basu starts engagements at the bottom of the funnel because that is where revenue is immediate, but calls the bottom of the funnel "the floor."
• The money and data from capturing existing demand are meant to fund demand creation for the other 95%.

Dev Basu asks readers to think about their own last software purchase and how long they knew about the vendor before filling out a form.

• The line that sums up the priority: "Short-term performance gets you the quarter.
• The system gets you the next 3 years."

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Most reports answer whether people saw the marketing, while the board is asking whether it made money.

• Dev Basu's version of a real report shows how marketing activities contributed to revenue.
• Related advice includes triangulating attribution across the CRM, ad platforms, and a self-reported form field, and measuring pipeline and CAC rather than traffic alone.

In the reporting post, Dev Basu says CMOs should not walk into a board meeting with only a follower count. In the demand-generation list, the final move is to measure pipeline and CAC because "you can't take traffic to the bank."

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Most marketing teams build content for only one of them, which is why deals stall. The companies closing complex deals create content for every stakeholder, use case studies with specific ROI, build objection handling into the funnel, and arm the internal champion.

Dev Basu lists the questions: the champion asks how to sell this internally, the executive asks about strategic impact, finance asks about ROI, IT and security ask whether it is secure and integrates, operations asks who implements it, and legal asks about terms. Six different questions require six different pieces of content.

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Buyers ask ChatGPT for vendor recommendations, check Reddit for social proof, skim the website for fit, and book a call already partly convinced.

• The website's job is now to confirm what buyers already believe, not to sell from zero.
• In a related post, Dev Basu calls being cited in LLMs the B2B game and recommends asking buyers what they searched for, rebuilding the cited page around those answers, and iterating.
• The stated caveat is that this only compounds if the company is having buyer calls; without inbound conversations, the team is back to guessing at intent.

Three recent clients found the agency by asking ChatGPT for the "Best B2B demand gen agency," checking Reddit for social proof, then visiting the website and looking for logos similar to theirs. If the agency does not show up in the LLM answer, Dev Basu writes, "it's game over."

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The problem, in this account, was that nobody could explain why results varied, so nobody could repeat them.

• Teams were running campaigns, social posting, SEO, and AEO as disconnected activities rather than as parts of a system.
• Dev Basu built the agency around that missing element and calls the approach the Predictable Growth Methodology.

The named client examples are Elastic, Varonis, SentinelOne, Fortra, and Basecamp. The contrast Dev Basu draws is between unpredictable monthly results and a system that connects the activities.

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The most common is high traffic with low-quality pipeline, where the business ranks for learning-stage queries rather than buying-intent queries. The first step is knowing which quadrant the business is in.

Dev Basu calls high traffic with low-quality pipeline the hardest to defend in a board meeting because every number looks good except revenue.

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It gives a concrete, phased sequence that a general reader can follow to understand how Dev Basu thinks about repairing marketing-to-revenue alignment.

Dev Basu describes what new CMOs typically inherit: misaligned sales and marketing, no shared definition of a good lead, and a broken marketing system.

• Instead of launching more campaigns, he recommends fixing the foundation first.
• The plan breaks into four phases: days 1–30 audit and diagnose (review closed-won deals, map channels to pipeline, check MQL-to-SQL rate, audit attribution, talk to recent sales losses); days 31–60 define and align (align ICP with sales, set up three-source attribution, agree on a good lead, define one North Star pipeline metric); days 61–90 launch and capture (BOFU content and landing pages, paid on BOFU keywords, reactivate cold CRM leads, fix demo page before traffic); day 91 onward measure and report by repeating the audit steps.

For brands planning a campaign

For a B2B SaaS company assessing Dev Basu, this provides a ready-made 100-day foundation plan that can be adapted into a campaign brief or advisory engagement.

Start here to understand why LLM visibility and Reddit presence matter to Dev Basu’s demand generation approach.

Dev Basu contrasts the old buyer journey—search Google, compare vendors, look for social proof, fill out a form, book a call—with how three recent clients actually found his agency.

• First they asked ChatGPT for “Best B2B demand gen agency” and received a shortlist; if you are not in that LLM answer, “it’s game over.”
• Next they checked Reddit for social proof.
• Then they skimmed the agency website for fit, looking for logos similar to theirs.
• Finally they booked a call.
• The website’s job is now to confirm what buyers already believe, not to sell from scratch.
• Being visible in LLMs is described as a must.

For brands planning a campaign

For a B2B SaaS company, this directly shapes an LLM citation strategy and social proof plan. It also suggests auditing where the brand appears in ChatGPT answers and Reddit threads.

It explains, in a compact list, why one-size-fits-all content fails and what a multi-stakeholder content library should include.

Dev Basu notes that a typical B2B deal involves six or more stakeholders, each with a different pre-purchase question: the Champion asks how to sell internally; the Executive asks about strategic impact; Finance asks about ROI; IT and Security ask about security and integration; Operations asks who implements; Legal asks about terms.

• Most B2B marketing teams build content for only one stakeholder, which is why deals stall.
• Companies that close complex deals create content for every stakeholder, case studies with specific ROI, objection-handling built into the funnel, and sales enablement that arms the champion.

For brands planning a campaign

For the brief on multi-stakeholder content strategy, this is a direct blueprint. It can be used to audit existing content coverage by stakeholder and to plan missing pieces.

It gives the origin story and philosophy behind the tactics, which helps a newcomer see the through-line in their other posts.

Dev Basu recounts saying in 2009 that they would never start an agency.

• What changed their mind was observing, while working with Fortune 1000 and entrepreneurial companies since 2006, that almost every company had talented people, good technology, and a budget, yet results were unpredictable—one month good, the next terrible.
• Nobody could explain the reason behind results, so nobody could repeat them.
• The constraint, Dev Basu writes, is that most teams run a collection of random activities that are not part of any system.
• They launched the agency around the missing element: system.
• This became the Predictable Growth Methodology, which they say has been used to help companies including Elastic, Varonis, SentinelOne, Fortra, and Basecamp.

For brands planning a campaign

The named methodology and client list provide credibility markers for fit assessment. For a B2B SaaS company, it signals a systems-first approach that can be evaluated against internal marketing operations.

Start here to understand why Dev Basu insists on funding the 95% of buyers who are not ready yet.

Dev Basu argues that B2B CMOs are not chief revenue officers but often become them, and that this stalls pipeline.

• When a CMO is expected to hit quarterly KPIs, they cut everything that does not convert within 90 days and spend only on buyers who are in-market today—about 5% of the market.
• That works for about three quarters, but then there is nothing behind it.
• The pool of in-market buyers is fixed; you can capture it but cannot grow inside it.
• Dev Basu starts every engagement at the bottom of the funnel because that is where low-hanging fruit is, but calls the bottom of the funnel “the floor.”
• Capture demand first because it funds the next move; then use that money and data to build demand.
• Short-term performance gets you the quarter; the system gets you the next three years.

For brands planning a campaign

For a brief about marketing-to-revenue alignment, this frames the budget tradeoff. It can be used to argue for a two-layer approach: capture existing demand first, then invest in demand creation.

Start here for a quick map of Dev Basu’s operating priorities.

Dev Basu lists seven demand generation priorities: build bottom of funnel first because that is where revenue is now; capture demand sitting cold in your CRM before paying for new demand; unblock AI crawlers before writing new content; pay most for leads that become best customers, not for leads that are easy to get; define what a qualified lead is and align marketing and sales; triangulate attribution across CRM, ad platforms, and a self-reported form field; and measure pipeline and CAC because you cannot take traffic to the bank. The post ends by asking readers what they would add.

For brands planning a campaign

Useful as a diagnostic checklist for a B2B SaaS company. Each move can be turned into an audit item or a campaign planning input, especially the CRM reactivation and attribution steps.

The next phases align ICP and sales, define a good lead, set up three-source attribution, and choose one North Star pipeline metric. Later phases launch bottom-of-funnel content and landing pages, run paid BOFU keywords, reactivate cold CRM leads, and fix the demo page before driving traffic.

For brands planning a campaign

A brand can use this as the basis for a foundation-first engagement: diagnose where pipeline is broken, align sales and marketing on lead quality, and launch BOFU assets before funding broad campaigns.

Examples: Source 1

The post frames this as capturing demand first, then using the money and data from that work to build demand for the other 95%. The tradeoff is that short-term performance wins the quarter, while a demand system is what carries the next three years.

For brands planning a campaign

This approach suits brands that need near-term pipeline but do not want to abandon longer-term brand building. A campaign brief could pair a BOFU demand-capture sprint with a follow-on plan funded by its results.

Examples: Source 1 · Source 2 · Source 3

Basu's 100-day plan includes agreeing on lead quality, and his demand-generation list includes defining a qualified lead and aligning it across both teams. The buyer-journey post adds that a website should confirm what buyers already believe, not start the selling from scratch.

For brands planning a campaign

A brand should ask for a shared lead definition and a clear handoff between marketing and sales before scaling campaigns. This is especially relevant when the current problem is uneven pipeline quality rather than simple lead volume.

Examples: Source 1 · Source 2 · Source 3

The report should show how marketing activities contributed to revenue, because boards ask whether marketing made money rather than whether people saw it. Related advice includes triangulating attribution across CRM, ad platforms, and a self-reported form field, and measuring pipeline and CAC rather than traffic alone.

For brands planning a campaign

A brand can evaluate Dev Basu for work that changes reporting toward pipeline, CAC, and revenue contribution. A campaign brief might require an attribution plan that combines CRM data, ad platform data, and buyer self-reporting.

Examples: Source 1 · Source 2 · Source 3

The website needs to confirm existing beliefs rather than introduce the company from zero. In a related post, being cited in LLMs is described as the B2B game, and the recommended loop is to ask buyers what they searched, improve the cited page around that language, and repeat.

Ask buyers what they searched for, not just where they found the company, then rebuild the cited page around those answers.

The post notes this only compounds if the company is having buyer calls; without inbound conversations, there is no raw material and the team is back to guessing at intent.

For brands planning a campaign

A brand can use this for an AI visibility and demand-capture campaign, especially if it can supply buyer-call access and a willingness to revise web pages based on actual search language.

Examples: Source 1 · Source 2

Most marketing teams build for only one of these roles, which is why deals stall. The companies closing complex deals create content for every stakeholder, use case studies with specific ROI, handle objections inside the funnel, and arm the champion.

For brands planning a campaign

A brand selling into a multi-stakeholder buying committee can evaluate Dev Basu for a content strategy that maps one asset to each role rather than producing more top-of-funnel material.

Examples: Source 1

The most common is high traffic with low-quality pipeline, where rankings come from learning-stage queries rather than buying intent. The first step is becoming aware of which quadrant a business is in.

For brands planning a campaign

A brand can use this diagnostic to decide whether its problem is visibility, intent, or scale. It is useful as an early scoping exercise before committing to a content, SEO, or paid demand program.

Examples: Source 1

The underlying problem, in this account, is that teams run random activities such as campaigns, social posting, SEO, and AEO without a system connecting them.

• The Predictable Growth Methodology is presented as the agency's answer, built around the missing element of system.
• The post names Elastic, Varonis, SentinelOne, Fortra, and Basecamp as companies the agency has helped.

For brands planning a campaign

A brand looking for an agency-led system rather than a one-off campaign can evaluate this methodology as the organizing approach. It fits a brief where the problem is unpredictable results across several disconnected channels.

Examples: Source 1

For brands planning a campaign

A brand can use this list as a practical scorecard for evaluating a demand-generation plan. It is especially useful for checking whether a proposal covers immediate revenue capture, CRM reactivation, AI crawler access, lead quality, attribution, and revenue metrics.

Examples: Source 1

The post does not name the agency or describe the scope, terms or dates of the work.

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The post does not name the agency or describe the scope, terms or dates of the work.

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The post does not name the agency or describe the scope, terms or dates of the work.

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The post does not name the agency or describe the scope, terms or dates of the work.

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The post does not name the agency or describe the scope, terms or dates of the work.

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Both push back on last-click numbers and platform-reported conversions, and both use AI tools to get there.

Strambach stays closer to paid-media and analytics execution, with prompt-level workflows and a humorous account of how media plans break in practice. Dev Basu writes at the strategy level about demand systems, marketing-sales alignment, and where budget should sit.

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Kim also assesses where AI will and will not help a team, which parallels Dev Basu's interest in what AI changes for buyers and go-to-market teams.

Kim works inside sales execution, leadership readiness, and rep coaching, mainly for healthcare SaaS companies. Dev Basu frames the same failure from the marketing and demand-generation side.

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Those are the same attribution arguments Dev Basu makes, aimed at the same mid-funnel stall.

Bennett is a hands-on operator, sharing exact workflows such as matching G2 reviews to Salesforce opportunities or attendee lists to deal accounts. Dev Basu writes as an agency strategist about the wider demand system and the order in which to fix it.

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Strambach's posts show how to connect attribution data to Claude and then ask the questions most dashboards avoid, such as which campaigns closed the most revenue, return on ad spend counted on signed deals only, every touchpoint behind a deal that closed yesterday, which ad sets spend budget without ever reaching a demo, and cost per qualified lead by channel.

• A second post catalogs the gap between the paid-media plan and what happens in practice: budgets tripled because a competitor's ad was spotted, the same ad running for four months, audiences defaulting to a broad job title, and the platform reporting 47 leads while sales says it received three emails.
• For a company whose board asks whether marketing made money and whose only answer is platform conversions, this is closer to the problem than a foundation audit.

The tradeoff is scope.

• Both posts stay inside measurement, reporting, and paid-media discipline.
• They do not cover aligning marketing and sales on a lead definition, building bottom-of-funnel demand capture before broader brand spend, or writing content for a buying committee of six roles.
• Dev Basu's material starts from that foundation and the buying-group content, so if the real problem is misaligned teams and an undefined qualified lead, better reporting will expose the gap without closing it.
• The evidence for Strambach is two posts, with no client outcomes or commercial terms.

Examples: Source 1 · Source 2

Kim when the sales process, not the marketing foundation, is the bottleneck.

• The post "Sales Isn't a Funnel.
• It's a System." describes healthcare SaaS companies pouring money into more leads, more tools, and more headcount while revenue stays flat, because there is no consistent messaging, qualification framework, or coaching cadence, and reps freelance their way through deals that should have been disqualified in week one.
• The follow-on post offers a free AI Readiness Assessment for sales teams and sales leadership, covering where AI could genuinely move the needle, where data, process, and adoption gaps block value, and what to prioritize instead of chasing every new tool.
• For a B2B SaaS company whose pipeline problem is inconsistent qualification and no onboarding or coaching for new reps, this goes deeper into the system underneath the funnel than a 100-day marketing audit does.

The tradeoff is the marketing half of the brief.

• Kim's material is oriented to sales-team readiness and process, with healthcare SaaS named as the context, and does not cover attribution, demand capture, board-level reporting, or content built for multiple buying roles.
• If the company needs marketing to demonstrate revenue contribution and arm a champion across champion, executive, finance, IT and security, operations, and legal audiences, this evidence will not supply it.
• The company would pair Kim's sales-system work with a separate content and measurement plan.
• The evidence is two posts, one of which describes an assessment rather than results from it.

Examples: Source 1 · Source 2

One post describes inheriting 12 G2 reviews and zero pipeline, and argues customer marketing should own mid-funnel proof rather than collecting surveys and website badges.

• The workflow exports G2 review data, matches the previous tool replaced against the primary competitor on active Stage 2 or higher enterprise opportunities, and posts a short peer-proof note on the CRM record, with an example of a $110K deal where a VP of Marketing at a 350-person SaaS company switched because custom reporting broke during quarterly planning.
• A second post covers $1.6M a year on events with no proof any of it worked, matching attendee lists back to account pipeline and reporting $14M in closed-won revenue touched and $60M in active pipeline influenced, plus a three-question framework on which open accounts had an executive in the room, whether stage progression changed in 30 days, and what the buyer said on the closed-won call.
• For a company whose stakeholder-content problem is that evaluators raise migration risk or a legacy competitor and reps lack specific peer evidence, this is more directly usable than a general stakeholder content map.

The tradeoff is narrowness and dependency.

• The approach assumes a working pipeline, review-platform data, a CRM with competitor fields populated, and event attendee lists; it accelerates deals already in play rather than building the foundation or generating demand.
• Dev Basu's material covers the earlier work this workflow takes for granted: auditing closed-won deals, defining a qualified lead with sales, and capturing bottom-of-funnel demand before spending on the 95% not yet in market.
• The case numbers are a described program, not independently verified results, and the evidence is two posts.

Examples: Source 1 · Source 2