GOOGLE ADS CASE STUDY

LAF Tech - B2B Lead Generation

NATA Accredited Testing & Calibration Equipment

How a full Google Ads account overhaul delivered 155% more leads at half the cost – with only 22% more budget.

132.7% Increase in Qualified Lead Volume

Client Overview

Client : LAF Tech (laftech.com.au)

Industry : B2B – NATA Accredited Testing & Calibration Specialists; Laboratory Equipment Suppliers for Scientific, Controlled Environment & Contamination Control Applications

Business Model : Lead Generation

Target Market : Australia – Laboratories & Scientific Facilities (B2B)

Monthly Ad Spend : A$10,000

The Challenge

When LAF Tech engaged us, their Google Ads account was generating traffic – but very little of it was converting into qualified business enquiries. A combination of structural issues, poor audience controls, and an over-reliance on automated campaigns without guardrails had made it nearly impossible to separate wasted spend from genuine opportunity.

Key Issues Identified

Low-quality leads coming through from irrelevant searches and unqualified audiences
Ad spend leaking to international traffic outside Australia – no ‘Presence Only’ location targeting enforced
Enquiries driven by generic keywords that rarely converted
Long B2B purchase cycles not factored into campaign strategy or bidding
High cost-per-click with limited return due to poor campaign structure
Over-reliance on Performance Max (PMax) without proper asset variety, audience signals, or negative keyword controls
Brand and non-brand keywords competing in the same campaigns – brand terms dominated spend, starving new customer acquisition
No call tracking or form submission tracking in place – conversions were invisible
Broad match keywords running on click-based bidding with no CPC cap
18 – 24 age group responsible for a disproportionate share of spend – not the target demographic
Weak ad strength scores across the board with underutilised ad assets
No device, demographic, or location bid adjustments applied
Customer match lists not utilised

“Before our involvement, Sitecraft was generating leads – but not the right ones, and not efficiently. The account needed a data-driven rebuild, not just tweaks.”

Client Goals & Expectations

Our engagement was scoped around four core objectives:

Goal 1:

Increase volume of qualified B2B leads from Google Ads

Goal 2

Establish a controlled, organised campaign structure with clear segmentation

Goal 3

Eliminate ad spend wastage on overseas and irrelevant traffic

Goal 4

Develop tailored, product-specific ad copy for each core service and product category

Primary KPIs: Qualified Lead Volume | Cost Per Lead (CPL) | Form Conversion Rate | ROAS (Value-Based)

Strategy & Approach

We began with a thorough audit of the entire account before making any changes. The goal was to understand the full picture – where budget was being wasted, what was actually driving enquiries, and how the account architecture needed to change to support sustainable lead generation for a B2B audience with a long purchase cycle

Performance Max Audit & Refinement

PMax was the account’s top-spending campaign and the primary source of conversions – but it was running with significant structural flaws:

Location targeting set to ‘All Countries’ – overseas traffic consuming Australian budget
No brand guidelines or content restrictions in place
Ad headlines and descriptions well below the recommended asset count
Image assets limited and ineffective – no lifestyle or contextual visuals
No video assets uploaded
Audience signals not configured – the campaign had no intent or interest targeting to work with
No negative keywords applied to PMax, allowing completely irrelevant searches to trigger ads

We rebuilt the PMax campaign with proper asset variety, tightened audience signals, added a negative keyword list, corrected location settings, and reduced its budget share while search campaigns were rebuilt.

Search Campaign Audit & Rebuild

No structured search term analysis – large volumes of irrelevant terms had never been added as negatives
Brand and non-brand keywords mixed in the same campaigns – Google systematically prioritised brand terms, making new customer acquisition nearly impossible
Expensive, non-converting keywords had never been paused
Display expansion was enabled on Search campaigns – meaning search budget was bleeding into display placements
Bid strategies running on Maximise Conversions or Maximise Clicks with no CPA targets or CPC caps

We paused the combined Generic+Brand campaign and rebuilt the account around tightly themed, product-specific ad groups focused entirely on non-brand, high-intent keywords. A master negative keyword list was built from scratch and applied across all campaigns.

Conversion Tracking & Data Foundation

Implemented accurate conversion tracking for both form submissions and phone calls
Installed Enhanced Conversion Tracking to improve match rates and data fidelity
Connected Google Analytics 4 (GA4) for deeper behavioural analysis
Deployed Microsoft Clarity for user behaviour heatmapping and session analysis

Audience Targeting & Advanced Bid Management

Added audience lists to Search campaigns in Observation mode to gather performance data by segment
Analysed performance by income bracket and age group – identified that males aged 35–64 in higher income brackets drove the best conversion outcomes
Applied positive bid adjustments for these segments to improve ad position and Search Impression Share for the right audiences
Reduced mobile bid adjustments – mobile traffic was the dominant source of low-quality leads
Analysed day-of-week and hour-of-day conversion data – increased bids for Wednesday and Thursday, reduced bids on weekends
Implemented Customer Match Lists and Conversion-Based Customer Match Lists for remarketing and exclusion

Negative Keyword Architecture

We built a comprehensive, segmented negative keyword framework to maximise budget efficiency:

Competitor terms – prevent brand confusion and wasted spend on unwinnable queries
Non-selling product categories – filter out product lines LAF Tech does not carry
Generic terms – exclude low-intent, top-of-funnel informational searches
Non-Australian locations – remove interstate and international irrelevant geo terms
Irrelevant technical terminology – exclude searches from adjacent industries or student researchers

Tools & Technology Stack

Ahrefs – Keyword & Competitor Research	Google Ads Editor – Bulk Campaign Changes
SpyFu – Competitor PPC Analysis	Microsoft Clarity – User Behaviour Analysis
Google Ads Experiments – Bid Strategy Testing	Conversion – Based Customer Match Lists
Google Analytics 4 (GA4)	Customer Match Lists
Advanced Bid Adjustment Framework	Enhanced Conversion Tracking

Execution Summary

With the audit findings mapped out, we executed a phased rebuild of the entire account:

Complete campaign restructure - rebuilt all campaigns from the ground up with clear product-category segmentation
Conversion-focused bid strategy experiments launched on key campaigns to gather performance data before committing
Paused all expensive, non-converting keywords and completed fresh keyword research to expand reach with higher-intent terms
Updated all campaigns to 'Presence Only' location targeting - Australia only
Developed fresh ad copy for each product category; created new asset sets for PMax including image and headline variations
Implemented advanced bid management using device, demographic, location, and time-of-day adjustments
Built an extensive, segmented negative keyword list applied across all Search and PMax campaigns
Established a weekly performance review cycle - search term reports, conversion data, bid refinements
Product value-based Target CPA refinement - CPA targets adjusted to reflect the margin profile of different product enquiries

Results

Performance comparison: 01 January 2026 – 31 January 2026 vs. the same period in the prior year (01 January 2025 – 31 January 2025) – before our team took over campaign management.

+155%

35 → 90 Conversions

Total Lead Growth

-52%

A$223 → A$108

Cost per Conversion

+409%

0.93% → 4.73%

Conversion Rate

+233%

1.74% → 5.80%

Click-Through Rate

Metric	Jan 2025 (Before)	Jan 2026 (After)
Ad Spend	A$7,912.03	A$9,680.45 (+22.35%)
Click-Through Rate	1.74%	5.80% (+233%)
Total Conversions	35	90 (+155%)
Cost per Conversion	A$223.28	A$107.56 (−52%)
Conversion Rate	0.93%	4.73% (+409%)
Form Submission Leads	35	55 (+57%)

With just 22% more ad spend, LAF Tech achieved 155% more leads – at less than half the previous cost per conversion. The dramatic CTR uplift reflects the impact of new, targeted ad creative; the conversion rate improvement tells the real story of how much irrelevant traffic was eliminated.

Key Takeaways

Fixing the Foundation Before Scaling

The single most impactful change was establishing proper conversion tracking. Without it, the account was flying blind – optimising toward no measurable outcome. Installing both form and call tracking created the data foundation everything else was built on.

Location Targeting Was a Silent Budget Drain

Switching all campaigns from broad international targeting to ‘Presence Only – Australia’ immediately stopped budget leaking to countries where LAF Tech had no ability to fulfil or sell. This one change freed up meaningful budget for qualified local traffic.

Separating Brand from Non-Brand Campaigns Is Non-Negotiable in B2B

Running brand and non-brand keywords in the same campaigns meant Google’s algorithm almost always prioritised brand terms – the path of least resistance for conversions. Splitting them gave non-brand (new customer acquisition) campaigns the budget and priority they needed to perform.

Audience Refinement Transformed Lead Quality

Reducing mobile bid adjustments and applying positive bid modifiers for males aged 35–64 in higher income brackets significantly shifted the composition of incoming leads toward the actual B2B buyer profile. Less volume, more quality – and ultimately more conversions overall.

PMax Needs Guardrails, Not Autonomy

Performance Max is a powerful tool when properly configured, but it had been running with no audience signals, no negative keywords, and no location restrictions. Adding structure to PMax – not removing it from the mix – was the right call for this account.