In this episode of Unqualified Leads, we break down incrementality testing, what it is, how it works, and when B2B teams should (and shouldn’t) use it. While attribution shows where conversions come from, it often fails to show what actually caused them. Incrementality testing fills that gap by measuring true cause and effect.

We explain the core differences between attribution, incrementality testing, and marketing mix models, and why correlation alone can lead to poor budget decisions. You’ll learn how control groups and holdouts work, what sample size and spend levels are required, and why timing and organisational buy-in matter just as much as the data itself.

We also cover real-world scenarios where incrementality testing becomes essential, rising CAC, overlapping channels, brand and retargeting over-credit, and leadership pressure to justify spend. Finally, we outline the practical prerequisites, common pitfalls, and how modern teams can run incrementality tests without massive data science resources.

If you’re making high-stakes marketing decisions and want confidence that your spend is truly driving incremental revenue, this episode is essential listening.

In this episode of Unqualified Leads, we unpack what we’ve been calling the attribution trap, the illusion of accuracy that marketers fall into when they over-rely on what’s measurable and under-value what’s actually driving demand.

We break down why attribution gives a false sense of precision, why boards crave certainty even when that certainty is misleading, and how over-optimising toward “visible” channels causes brands to under-invest in the upstream work that actually fuels pipeline.

We Break Down:

• Why attribution gives marketers the illusion of control, and why that leads to distorted decision-making

• How overvaluing measurable data pushes teams to over-spend on bottom-funnel channels while underfunding the efforts that truly generate demand

• Why siloed reporting destroys marketing effectiveness and creates misalignment between teams, channels, and leadership

• The dangers of making decisions before full sales cycles play out, and how to report leading indicators without over-indexing on vanity metrics

• How signals, intent, and self-reported attribution complete the story that platform data can’t see

• Why long sales cycles require patience, better narrative reporting, and a shift away from “prove it now” marketing cultures

• How misreading channel influence leads to year-long marketing mistakes, and how to fix it with proper measurement, portfolio thinking, and (later) incrementality testing

Packed with examples from real client scenarios and practical guidance on reporting, signals, and channel mix, this episode gives a grounded playbook for avoiding attribution failure and making smarter, long-term marketing decisions.

In this episode of Unqualified Leads, we unpack how to make organic social a core part of your go-to-market strategy, not an afterthought. We break down why most B2B brands neglect organic, how buyer behaviour has shifted, and why consistent content across LinkedIn (and, where relevant, YouTube, TikTok, and Meta) is now essential for awareness, trust, and authority.

We Break Down:

• Why organic social is one of the most underused yet powerful GTM levers in B2B

• How consistent posting builds credibility, creates compounding reach, and lowers dependency on paid spend

• Why employee-led content outperforms company pages, and how to empower your team to post with confidence

• How to optimise personal and company profiles for visibility and trust

• The “Organic-to-Paid Flywheel” - using high-performing organic posts to guide and fuel your paid campaigns

Packed with real-world examples and practical takeaways, this episode shows how to build a scalable, trust-led content engine that strengthens brand visibility, improves pipeline quality, and amplifies every other marketing channel you run.

A practical deep dive into UTM parameters and attribution that actually works. Learn how to implement session-based UTM tracking, set up hidden fields and workflows for first/last touch, backfill legacy records, and standardise UTMs and naming conventions across LinkedIn, Meta, and Google Ads.

We show how to map UTMs from contacts to deals, build useful CRM dashboards, and pair machine-reported data with self-reported attribution to capture dark social, including a real example where SRA revealed paid social as the true driver behind “organic/direct” deals.