Vector's VP of Marketing skipped messy UTMs for her influencer pilot. Instead, she tracked success by setting up alerts in their call recording software (Fathom) for mentions of influencer names, coupled with a "How did you hear about us?" form field.
Related Insights
Critical buying journey insights are hidden in unstructured data like Gong transcripts. 2X CMO Lisa Cole notes that AI can surface mentions of communities, analysts, or even other AI tools that influenced a deal—signals invisible to traditional marketing attribution tools.
Go beyond simple affiliate tracking by using vanity URLs (e.g., brand.com/creator) to tag incoming users. This allows you to analyze the long-term value and performance of different creator cohorts months or even years later, informing future partnership decisions.
In the beginning, don't get lost in the weeds of perfect analytics and UTM parameters to track every subscriber source. It's a form of procrastination. For attribution, just add a simple question to your welcome email: "Where did you find the newsletter?" This is all the data you need early on.
Not all brand campaigns have direct, measurable ROI. Justify their cost by tracking "soft ROI," such as increased employee pride and retention (e.g., employees on billboards), positive candidate feedback during interviews, and using tools like Gong to track how often the campaign is mentioned in sales calls.
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.
Don't abandon attribution; evolve it. The old model of single-touch software attribution is outdated. A modern approach triangulates data from software (GA4), self-reported forms ("How did you hear about us?"), and conversational intelligence tools, using AI to identify common buying journey patterns.
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.
Jess Cook executed a three-month pilot with seven micro-influencers (average 12-13k followers), resulting in 45 ICP demos and over $1M in pipeline without using direct CTAs or UTM tracking.
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.
