Compass combines a rigorous Bayesian marketing mix model with a suite of AI agents that draft, review, and improve marketing output. Defensible budget decisions on one side. Compounding content and campaign systems on the other. Same review discipline across both.
B2B SaaS marketing leaders are stuck between attribution dashboards that can't see anything but the last click, and enterprise MMM engagements priced for Fortune 500 brands. Neither fits a company with a six-month sales cycle and $2–10M in annual paid spend.
By the time pipeline turns to revenue, the original marketing touch is far outside the attribution window. Last-touch and multi-touch dashboards systematically under-credit the channels, events, podcasts, brand, that warm the deal in the first place.
Off-the-shelf marketing mix models assume an 8-week attention span and a DTC channel mix. They literally have no way to model field events, SDR outbound, or the way a LinkedIn ad in March still influences a deal that closes in September.
CFOs don't want a number. They want a number with confidence around it. The Excel models marketing teams use to defend budget can't express "ROI between 2.4× and 3.8× with 90% probability", so the conversation defaults to "trust me."
Compass fits a Bayesian hierarchical model with Hill saturation and 26-week geometric adstock tuned for B2B sales cycles. Every channel gets a posterior response curve, not a point estimate, so you can see exactly where each channel is under-invested, healthy, or past the knee.
Compass runs a Budget Optimizer on the fitted posterior and returns the budget reallocation that maximizes incremental pipeline subject to per-channel floors and ceilings. You don't get a recommendation pulled from a spreadsheet, you get one backed by thousands of posterior draws.
Every per-channel ROI lands with a 90% credible interval. Every recommendation comes with a posterior distribution. Compass's analyst console shows the full math behind every number, so when finance asks "how sure are you?", you have a real answer.
Measurement tells you where to spend. The Command Center is where the work actually gets made. AI agents draft your comparison pages, paid creative, lifecycle email, and content. A shared Playbook grades every draft against your brand and channel rules before a human sees it. You review, approve, or reject. Every rejection gets logged. Overnight, a Marketing Systems Agent turns recurring rejection reasons into proposed Playbook updates that a Director approves. The system only ever gets more specific, never looser.
Delivered as a 30 to 45 day engagement. Your version of the seven-tab Command Center, tuned to your funnel, channels, review criteria, and approval tiers. Available as a design-partner engagement or a standard commercial build. Post-delivery retainer optional.
No SaaS sign-up, no integrations to wire. For our first five design partners, getting started is two days of CSV prep on your end and a full model fit on ours.
Weekly paid spend per channel, weekly pipeline created, and a few simple controls. Six quarters of history minimum, most CRMs export this in under an hour.
Compass runs a Bayesian hierarchical fit with B2B-tuned adstock (26-week memory). Four MCMC chains, full convergence diagnostics, sensitivity analysis on every channel.
A 30-minute screen-share readout of the channel-by-channel response curves, the optimizer's recommendation, and the one-page brief you can take straight to your CFO.
Compass fits a Bayesian hierarchical marketing mix model with Hill saturation curves, geometric adstock, and geo-level pooling. Every channel gets a full posterior response curve, not a single point estimate, so you see the range of plausible outcomes for each budget scenario rather than a false-precision number.
The model is tuned for the workloads that legacy MMM tools miss. B2B SaaS channels including paid search, LinkedIn, field events, podcast, content syndication, and SDR outbound. A 26-week adstock memory calibrated to real sales-cycle lag. Pipeline-created as the primary KPI instead of closed-won revenue, so you can act on the model before the deal closes six months later. Same underlying rigor when we run the model on D2C accounts, with the channel registry and adstock retuned for shorter conversion cycles.
Compass is a founder-led platform in its early customer phase. Two engagement types are open right now. Both include a fully custom Compass instance tuned to your funnel, channels, and review criteria. The right fit depends on how much you want to shape the product versus how much you want a turnkey delivery.
Reduced-price engagement for teams who want to help shape Compass. Best fit for marketing leaders who have opinions on how MMM and AI agents should work in their industry.
Standard commercial engagement. Best fit for teams who want a scoped, priced, dated deliverable without a longer product-partnership commitment.
For Compass we recommend at least 18 months, ideally 24, of weekly data with reasonably consistent channel mix. That's roughly what a Bayesian MMM needs to identify Hill curves and adstock decays separately for each channel. If your channel mix changed dramatically inside that window (a brand new motion, a paused channel), we'll surface that as identifiability uncertainty in the response curves rather than pretend the model is more confident than it is.
Recast is an excellent product, they pioneered modern MMM for digital-native brands. Their core focus is DTC and consumer brands, and their pricing reflects the enterprise contracts they sign. Compass is positioned for B2B SaaS specifically: pipeline-created as the KPI instead of revenue, 26-week adstock for long sales cycles, and field events / SDR outbound as first-class channels. If you're an omnichannel DTC brand, Recast is probably the better fit. If you're a Series B-D B2B SaaS company, we're built for you.
Same answer with a slightly different shape: Prescient's core focus is DTC and omnichannel consumer brands, and they're excellent at it. Their case studies, integrations, and pricing all reflect that ICP. Compass is wedged into B2B SaaS, a vertical no modern MMM platform is seriously chasing yet.
Two ways. First, the dependent variable is weekly pipeline value created, opportunities generated, not deals closed. Pipeline sits 1–4 weeks after a marketing touch instead of 3–9 months, which gives the model enough signal to fit. Second, adstock max_lag is set to 26 weeks (vs. 8 in a default DTC model), so a LinkedIn ad seen in March can still be credited for a deal that closes in September.
One row per week, with columns for: week-starting-Monday, weekly pipeline value created (the KPI), weekly spend per paid channel, and a few simple controls (price index, holiday flag, competitor index). Most B2B SaaS companies can export this from Salesforce + their ad platforms in under two hours. The full schema is available on request, email contact@compass-mmm.com and we'll send it.
We're not publishing public pricing yet, partly because we want design partners to influence it, partly because the right price for a $50M ARR Series C is different from a $200M ARR Series D. For comparison, Recast and Prescient are typically in the high-five-figure to low-six-figure ARR range for B2B SaaS scale. We expect to come in materially below that for design partners and modestly below it for general availability, but the exact number depends on what we build in the next six months.
Five design partner slots open for Q3 2026. Apply now to get a full model fit on your data and the brief you'll wish you'd had at the last board meeting.
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