Transcript

Unqualified Leads – Episode 014 Highlights

Hosts: Harry Hughes & Dan

Topic: A case study on launching paid media from zero for a UK-based pricing + data intelligence agency, why an “MQL-style” approach actually worked here, how events and gated data became the growth lever, and what this teaches about adapting strategy to the buyer journey (not the other way around).

Why This Case Study Matters

This episode intentionally breaks the show’s usual pattern.

Most of the time, the podcast argues for moving away from MQL volume and toward demand gen + SQL outcomes.

But this business was different:

• Their product was proprietary data (not easily commoditised content)

• Their market bought on information advantage

• Their funnels had multiple valid conversion points (events, resources, contact routes)

Result: parts of the classic MQL playbook were not only acceptable, they were strategically correct.

The Business Profile

• UK HQ, global delivery

• Pricing + data intelligence agency (owned/controlled industry pricing data)

• ~£10–£20M ARR

• ~200 employees

• 10+ years operating history

• Recent successful acquisition

• No paid media history (no paid search, no LinkedIn ads, no digital paid campaigns)

The unusual constraint: no baseline performance data inside ad platforms. Everything started from scratch.

The Starting Problem: Too Many ICPs, Too Many Products

Dan probes the ICP question quickly: was it one core buyer, or multiple?

Harry explains the challenge:

• 15–20 product/service variations (pricing models)

• Same industry, but very different end users

• No clean “top 100 closed-won by segment” dataset

• Sales knowledge existed, but structured ICP intelligence did not

Decision: start broad (against preference), then refine once data exists.

The Strategy Constraint: Budget Dilution Across Geos + Markets

Even after “cherry-picking,” targeting still looked like:

• Europe (most)

• North America

• Some Africa / Middle East depending on market

Dan calls out the ideal structure:

One ICP + one geo + one core offer → then test angles and messaging.

But this situation forced multiple variables at once:

• Multiple markets

• Multiple ICPs

• Multiple geos

• Multiple conversion actions

So the strategy became: broad first, insight later.

Foundations: Attribution and Tracking Before Scaling

They implemented a foundational attribution approach:

• UTM framework

• First-touch, conversion-touch, last-touch tracking stored in CRM

  
  

Dan notes why this matters:

• Budgets were too low for expensive multi-touch tools

• You can still measure paid impact properly with strong fundamentals

  
  

Harry adds what they didn’t implement initially:

• Self-reported attribution (planned, deprioritised due to build pressure)

A Major Complexity: Too Many Conversion Paths

The business offered many ways to engage:

• Webinars (free)

• In-person events (free)

• Global paid conferences (ticketed)

• Multiple downloadable resources

• Multiple contact forms

• Email contact routes

• Samples / agendas / documents

  
  

Normally, they’d reduce CTA sprawl. Here, they had to track everything, because they didn’t know:

• which actions users would take once paid traffic started

• which CTAs would become the dominant path

Events: Educational Value, Not Hard Selling

Dan challenges the “event = pitch close” model.

Harry confirms these were genuine industry events:

• Webinars were reactive to market changes

• Paid conferences were multi-speaker, multi-day market events

• Not “sell from stage” formats

But: they couldn’t quantify downstream influence properly because:

• no historical dataset linking event attendance → closed-won rates

• no self-reported attribution in place early on

So the operating metric became: Drive registrations and attendance first, measure revenue influence later.

LinkedIn: The Key Discovery — Instant Forms Beat Website Conversions

They tested multiple LinkedIn approaches for event acquisition:

Website conversion campaigns

• Performed poorly

• Low CVR

• High CPA

Instant Form campaigns

• Performed significantly better

• Much lower friction (no leaving LinkedIn)

• Auto-filled fields increased completion

Dan asks the key question: did show-up rates collapse?

Harry: no—drop-off exists, but overall performance was far better than website routing.

Paid Conferences: “MQL” as a Practical Sales Motion

For ticketed events:

• Instant Form used to request the agenda

• Sales followed up with agenda + ticket options

• This produced:

  
  

  • ticket deals

  • sponsorship conversions (large deal sizes)

  
  

Not product revenue directly, but meaningful closed-won revenue tied to the motion.

The “MQL Game” Worked Here Because the Asset Was Proprietary

Their product was exclusive data, so gated content wasn’t a gimmick.

Key execution:

Document Ads

• Only first 2 pages visible:

  
  

  • cover

  • contents page

  
  

• No real data revealed upfront

• Docs were often timely (market changes)

• Run for 3–4 weeks while relevance was highest

• Delivered via Instant Forms + sales follow-up

  
  

Why it worked:

• information not available elsewhere

• speed-to-market beat competitors

• demand created by topical urgency

Thought Leader Ads: SQL Motion Worked “Overnight”

After a few months, they layered in thought leadership:

• leveraged employees who were already industry “influencers”

• boosted best-performing organic posts

• CTAs placed at the bottom with tracked URLs

• drove to highly specific product pages

• CTA: book a demo / speak to sales

  
  

Outcome:

• demos booked rapidly after switching on

• strongest signal of “in-market” buyers already following credible voices

Targeting structure often used 3 parallel campaigns:

1. Match list (sales-selected accounts)

2. Job title (tight)

3. Job function + seniority (broad)

   
   

Then they killed underperformers over time.

Retargeting: Low Spend, High Impact

Retargeting audiences were built by market, not “everything lumped together”:

• ad engagers & Video Views

• landing page viewers

• HubSpot MQL lists (by market)

  
  

Creative tactic:

Direct Message Ads

• highly specific

• sent from credible internal persona (e.g., senior analyst)

• personalised to the segment (“we’ve found X, relevant to your exposure”)

These worked:

• very well for retargeting

• and surprisingly, also worked to cold audiences (higher CPA, still viable)

Paid Search: Simple Demand Capture, Clean Feedback Loop

Google Ads was used primarily to capture existing demand in core geos:

• 1 geo per campaign (mostly)

• ad groups = product/service markets

• tight keyword sets

• high-intent

• mostly exact match

They also:

• imported HubSpot lifecycle stages back into Google Ads:

  
  

  • SQLs

  • opportunities

  • closed-won

  
  

• ran a small brand campaign that captured meaningful deals

• used sitelinks heavily (including events)

Big turning point:

Landing page rebuild

• original pages converted poorly

• improved pages (clearer offer + better CTA + more upfront info) lifted CVR noticeably

They also tested “new” geos with low competition and found pockets of cheap demand.

Results: Pipeline Impact from Zero

Starting from no paid media baseline:

• ~£400,000 pipeline generated in 4 months

• on relatively low ad spend

• efficiency described as very high

Core Lesson: No Cookie-Cutter Strategy

Dan summarises the real insight:

• the strategy was shaped by:

  
  

  • the market’s relationship with information

  • the buyer journey

  • friction tolerance

  • credibility channels (events + thought leadership)

  
  

• value was delivered first, sales was introduced at the right moments

Harry closes with a concrete example:

• competitor search campaigns work well elsewhere

• here they flopped (high costs, no conversions)

The takeaway:

You can’t reliably copy/paste playbooks across industries.

Similar mechanics may apply, but the buyer journey sets the rules.