The questions B2B SaaS leadership teams actually ask.

An Ideal Customer Profile (ICP) is the customer for whom your product is the unambiguous best choice — grounded in your closed-won data, validated against your losses, and committed to by sales, marketing, product, and customer success without disagreement.

A real ICP is operational, not aspirational. You can allocate sales capacity to it, build a marketing budget around it, and write a product brief that doesn't pretend to serve everyone. If yours can't do those three things, what you have is a description — not a target.

A buyer persona describes an individual decision-maker — their role, motivations, and pain points. An ICP describes the company that decision-maker works at — the firmographic, behavioral, and use-case profile of the account most likely to close, expand, and retain.

Buyer personas help you write marketing copy. ICPs determine where you allocate sales capacity. Both are useful. They're not interchangeable.

AI has dropped the cost of building software significantly. Competitors can match features in weeks, not quarters. Switching costs are falling. Acquisition channels are getting more expensive. The advantages B2B SaaS used to lean on — product depth, contractual lock-in, scaled distribution — are all eroding at the same time.

In a leveled market, the companies that win are the ones with the sharpest understanding of who they serve, and the discipline to serve them better than anyone else can. ICP isn't a marketing artifact anymore. It's the strategic substrate of the business.

Five symptoms reliably indicate ICP drift: win rate has trended down for two or more quarters; sales and marketing disagree on what makes a lead "good"; rep performance varies more than 2× across the team; early churn is rising in segments you thought were ideal; pipeline forecasting accuracy is getting worse, not better.

If two or more of these are true, ICP is almost certainly contributing. Companies with a clearly defined ICP see 68% higher win rates than those without (SiriusDecisions/Forrester). Below-benchmark win rate is rarely a sales execution problem — it's a targeting problem.

A four-week, evidence-backed engagement that gives B2B SaaS leadership one ICP the whole company commits to. Four lenses applied in sequence: win/loss pattern analysis paired with cross-functional alignment review, customer interviews to pressure-test the hypothesis, segment scoring and sharpening, and activation playbook delivery. Senior-led from kickoff to executive readout.

The output is a scored ICP definition, a segment prioritization map, a one-page brief your team signs off on, and a 90-day activation plan. Not a report to file — a foundation your sales, marketing, and product motions get built on for the next two years.

Four weeks from kickoff to executive readout. Week one: data analysis and cross-functional alignment work run in parallel. Week two: customer interviews. Week three: segment scoring and the alignment lock-in. Week four: activation playbook and executive readout.

We deliberately don't run longer engagements for the core diagnostic. Internal ICP projects routinely take quarters and get shelved; the four-week constraint forces structured progress and produces a result your team can act on while the urgency is still real.

Seven deliverables:

A scored ICP definition built from your closed-won data and validated against both your losses and your strongest retention cohorts. A segment prioritization map ranking which segments to pursue, hold, or exit. A win/loss pattern report. A customer interview synthesis from 8–12 conversations across wins, losses, churned accounts, and high-NRR expansions. A one-page ICP brief that sales, marketing, product, and customer success all commit to. A 90-day activation plan that turns the new ICP into measurable pipeline movement this quarter. A live executive readout — leadership in the room, decisions made, next steps owned.

We work exclusively with B2B SaaS companies. The diagnostic methodology is industry-agnostic within that category — we've applied it across vertical SaaS, horizontal SaaS, infrastructure, data platforms, security tooling, and developer products.

The work is most effective at $5M–$50M ARR, post product-market fit, where ICP clarity is the highest-leverage move on the table. We don't take on pre-PMF companies, B2C, or non-SaaS engagements.

They could, in theory. They almost never do, in practice. Three structural reasons.

First, RevOps teams are inside the political gravity — challenging the ICP carries a cost they can't afford to pay. Second, RevOps teams are working with one data set; we work with many, which means pattern recognition they can't access. Third, internal ICP projects routinely take quarters, get reorganized halfway through, and end up shelved. Ours don't.

The work that determines who your company sells to for the next two years is too important to assign to people who are also running quarterly board prep.

Three differences.

First, scope: we do one thing. The diagnostic is built for ICP clarity specifically, not as a module inside a broader transformation engagement. Second, time: four weeks, not four months. We don't bill against a research phase that takes a quarter. Third, who does the work: the people you meet on the discovery call are the people running the engagement. No partner-and-team-of-associates model. The senior operator who scoped it is the one delivering it.

Maybe not. Two diagnostic questions: when was your ICP last validated against closed-won data, and would sales, marketing, product, and CS describe it the same way if asked separately? If the answer to either is unclear, your ICP is older or fuzzier than it should be.

We offer a two-week Validation engagement specifically for teams who want their existing ICP stress-tested rather than rebuilt. If the validation confirms your ICP is sound, we'll tell you that — and we won't sell you a full diagnostic you don't need.

If the answer were obvious from internal data alone, you would already have it. It almost never is.

Three things obscure it. Selection bias — companies look at who closed, not who didn't, and miss the customers they should have been targeting. Recency bias — recent big deals get treated as the pattern, even when they're outliers. Political bias — internal stakeholders interpret the data through the lens of which segments they want to be the answer.

External analysis cuts through all three. The pattern in your data is usually not what your team thinks it is.

AI can surface patterns in your closed-won data faster than any human. We use it. You should too. But the pattern is the easy part.

The hard part is the part AI can't do. Sales is reading the data one way. Marketing is reading it another. Product has a third interpretation rooted in roadmap priorities. CS is looking at retention cohorts and seeing yet a fourth pattern. Each function has internal politics, incumbent assumptions, and a budget at stake. AI doesn't sit in a working session with four senior leaders and pressure-test which interpretation actually holds up against the data — and then get all four of them to commit to one answer they'll operate against for the next two years.

That commitment is the whole point of the engagement. Without it, a perfect AI-generated ICP gets ignored the moment it conflicts with the segment a function had already decided to chase. The diagnostic isn't really about discovering the ICP. It's about making it impossible for the organization to keep operating as if there isn't one.

It's often both — but ICP is almost always the deeper cause. Sales execution problems compound when reps are working against the wrong target. Win rates that look like a coaching problem are frequently a fit problem. Below-benchmark win rates trace to targeting the wrong companies in the first place far more often than they trace to how reps are selling.

We'll tell you on the discovery call if your situation looks like a pure execution issue. If it does, we're not the right firm. But the diagnosis is almost always more layered than it first appears.

Less than most companies expect. Closed-won and closed-lost deal data from your CRM over the trailing four to eight quarters. Customer firmographic data — company size, industry, geography, tech stack where relevant. Churn data for the last 12–18 months. Sales pipeline data for the current and prior quarter. Stakeholder availability for five to seven structured interviews across sales, marketing, product, and CS.

We don't need a clean data warehouse. We can work with imperfect, messy, partial CRM data — that's usually what we get.

One executive sponsor — typically the CRO or CEO. One operational point person who can pull data and coordinate scheduling. Five to seven leadership interviews across sales, marketing, product, and customer success (one to two hours each, spread across weeks two and three). A two-hour executive readout in week four with the full leadership team in the room.

Total time commitment for your senior team is roughly 15 hours across four weeks.

Your team owns the playbook. The deliverables aren't ours — they're yours, to use however you choose. We're available for follow-on questions during the first quarter post-engagement at no additional cost.

Teams who want embedded execution support during the activation phase can extend the engagement with a 90-day Activation add-on. Teams who want to run the activation internally can do so with what they leave the engagement holding.

Pipeline composition shifts within the first quarter post-engagement, in our experience. Win rate movement typically shows up within two quarters as new ICP-fit deals work through the funnel. Net revenue retention improvements take longer — six to twelve months — because they reflect the customers you signed under the new ICP reaching their first renewal.

The fastest signal of success is leadership friction dropping in pipeline reviews. That happens in weeks, not quarters.

A boutique advisory firm founded by senior operators with direct B2B SaaS and EdTech experience.

Managing Director Rob Strulowitz is a 25+ year product and GTM executive and M&A strategic advisor in the EdTech and Workforce Learning sector, having led the Global Compliance Training divisions of NAVEX and LRN — two of the largest GRC providers in the sector.

Senior GTM Advisor Sara Haynes brings 20+ years of software product marketing and management leadership experience, including senior product leadership at a Vista Equity Partners portfolio company.

Engagements are senior-led end to end. No associates learning on your engagement.