Standard attribution often credits Google due to last-click bias. To find true sources of influence, mandate that the sales team asks every new customer: "How did you *truly* hear about us?" and "Who or what influenced you to sign up *now*?". This reveals the real people and channels driving decisions.

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By measuring success on 'last lead source,' the company was incentivized to pour money into paid search for product trials—a clear final touchpoint. This model blinded them to the higher value of other lead types and actively discouraged investment in demand creation activities that build brand and generate higher-quality leads.

Standard attribution models, even multi-touch, fail to credit influential, non-clickable touchpoints like a child watching a Netflix show that inspires a purchase. This "Hot Wheels Problem" highlights the need to account for view-through attribution and the full, often hidden, customer journey.

A modern data model revealed marketing influenced over 90% of closed-won revenue, a fact completely obscured by a last-touch attribution system that overwhelmingly credited sales AEs. This shows the 'credit battle' is often a symptom of broken measurement, not just misaligned teams.

Direct attribution models are flawed because platforms like Google and Facebook use tracking pixels to claim credit for sales that would have occurred anyway. Smart marketers are returning to older methods of measuring lift from campaigns rather than relying on misleading platform data.

Relying on UTM link clicks for B2B influencer campaigns is a failing strategy, as social platforms penalize external links and users rarely convert directly. Instead, use a combination of time-series analysis (correlating campaigns to signup spikes) and self-reported attribution on forms to get a more accurate picture of an influencer's impact.

AI now enables the tracking of every customer touchpoint, including interactions outside of marketing-controlled channels. This provides a complete view from first contact to close, finally solving the long-standing challenge of accurate marketing attribution and ROI measurement.

CloudPay stopped attributing opportunities to single sources like "marketing" or "sales." Analysis showed multiple departments influenced every deal, rendering attribution a source of pointless internal arguments. They still use multi-touch attribution at the campaign level, but not to assign inter-departmental credit.

If your business relies heavily on referrals from centers of influence (e.g., consultants, agencies), reframe your entire business model. Your true customer is the referral partner. Build a 'customer journey' specifically for them, focused on making it easy and profitable for them to send you well-framed, high-quality leads.

Instead of chasing perfect attribution, recognize that customers will explicitly tell you how they found you. At Drift, prospects on sales calls would frequently mention being fans of their podcast. This qualitative data from the front lines is often the most direct and powerful measure of brand impact.

Solely judging marketing by last-touch attribution creates a false reality. This narrow metric consistently favors predictable channels like search and email, discouraging investment in brand building and creative storytelling that influence buyers throughout their journey. It's a losing battle if it's the only basis for decision-making.

Uncover True Influencers by Asking Sales Two Key Questions at Closing | RiffOn