What it looks like when
behavior drives the decision.

A sales enablement platform at Series B had a familiar problem: the CRM showed 35% marketing-influenced pipeline, the board wanted proof, and sales and marketing were blaming each other for missed targets. Their existing model — built on email opens, page views, and CRM stage — was treating every prospect in "Evaluation" the same way.

Click360 identified a specific 3-step behavioral sequence — pricing page visit, return via direct URL within 72 hours, case study depth scroll — that matched 74% of their closed-won revenue from the past 8 months. Sixty percent of current pipeline accounts were showing this sequence. None of them had been prioritized by the existing scoring model because their activity scores were middling.

A B2B performance agency had been managing a flagship client for 18 months. Platform-reported ROAS looked solid. But the client's revenue hadn't moved. At the QBR, the client's CFO asked a simple question: "Which keywords are actually closing deals?" The agency couldn't answer it. The attribution model counted clicks and form fills. It had no connection to closed revenue.

Click360 connected behavioral on-site signals to the client's CRM closed-won data. The result: 76% of paid keywords had driven $0 in closed revenue — and those keywords represented 59% of the client's monthly ad spend. Budget was reallocated to the behavioral clusters that matched actual closed-won patterns. The agency had something no platform report could give them: proof tied to revenue, not activity.

A considered-purchase eCommerce brand was reporting 3.8× ROAS. On paper, things looked fine. But margin was quietly shrinking quarter over quarter. Their retargeting sequences were firing blanket discount offers at every returning visitor — including the ones who had already made a purchase decision and were coming back specifically to buy. Their "high intent" segment was built on cart adds and page views. It couldn't distinguish a returning buyer from a chronic browser.

Click360 identified five distinct behavioral clusters across their traffic. The "Active Buyer" cluster — returning visitors who had already decided — was receiving aggressive discount offers they didn't need. The "Price Hunter" cluster, which had a 9% conversion match against closed-won patterns, was getting the same budget allocation as genuine buyers. Behavioral recognition separated who needed an offer, who needed reassurance, and who was never going to buy regardless of the incentive.