Marketing analytics and reporting for B2B tech companies that need to prove revenue, not present a traffic chart.

This is exactly the problem the service is built for. In a long committee-driven buy, a deal is touched by many channels — a founder's LinkedIn post, three blog reads under no identity, a webinar, a comparison article, and finally a demo form — and last-click attribution hands all the credit to whichever channel caught the final click. We implement a multi-touch model calibrated to your cycle, so first touch, the lead-creating touch, and the closing touch are all visible and credited, and we reconcile that against self-reported 'how did you hear about us' answers and your sales team's notes. The result is credit that reflects how the deal was genuinely won, so you stop defunding the channels that quietly create pipeline.

No. We work with the CRM you already run — HubSpot, Salesforce, or Pipedrive — and the analytics and ad tooling you already pay for, because the goal is a single source of truth in the system your finance team trusts, not another tool to reconcile. If you already own an attribution platform, we set it up properly, define your funnel stages, and turn its output into decisions. If you do not, we can build robust attribution natively in your CRM and tag stack. The recommendation is always driven by your motion and what you already have, not by a tool we are trying to sell.

It is the one screen a founder can take into a QBR and defend without a story: marketing-sourced and marketing-influenced pipeline, closed revenue by channel, CAC and pipeline efficiency, and the trend against target — every number traceable back to the deal record in the CRM. It matters because the alternative is walking into a board meeting with a traffic graph and a narrative, which invites budget cuts on the channels quietly building pipeline. A revenue dashboard tied to the CRM lets you justify spend, kill a losing channel, or ask for more budget with evidence instead of opinion.

That is the normal starting point, not a disqualifier — almost every engagement begins with mis-sourced revenue, double-counted conversions, mushy stage definitions, and untracked demand. The first phase is a diagnosis precisely because the data is rarely clean: we audit the tracking, trace a sample of closed deals back through the funnel to find where attribution breaks, and rebuild the event and conversion layer before we report anything on top of it. Building a dashboard on broken data just produces a more convincing wrong answer, so we fix the measurement first. Messy data makes the work more valuable, not premature.

By building the reporting with sales in the room from the start. The disputes almost always trace to two things: stage definitions marketing and sales interpret differently, and attribution that does not match what reps know happened on a deal. We co-own the MQL, SQL, and opportunity definitions so the funnel measures the same thing both teams mean by it, and we reconcile self-reported sources against CRM stages and rep notes so the attribution survives a sales-floor sanity check. When both teams read the same funnel off the same definitions, the meeting moves from arguing about whose number is right to deciding what to do about it.

Generic analytics assumes a short, single-buyer, click-to-convert journey — which is the opposite of how B2B tech is bought. Our models are calibrated to long, committee-driven evaluations where most of the influence happens anonymously and the final click under-represents the channels that did the persuading. Because we have built the reporting layer for 60+ B2B tech companies, we know which funnel stages actually predict a close in this category, which channels default attribution reliably under-credits, and how technical buyers research before they ever identify themselves. The instrumentation is tuned to that reality, not to a consumer or generic-B2B funnel.

By whether you can make a confident budget decision you could not make before. Concretely: revenue in the dashboard reconciles with what closed in the CRM; channels that were mis-credited under last-click are now correctly sourced; marketing and sales stop disputing the funnel because they share definitions; and you can name, with evidence, which channels create pipeline versus which only close it. This is the same measurement discipline that has tracked $30M+ in CRM-attributed, marketing-led revenue across our portfolio — the test is not a prettier report, it is a decision you can defend to a board.