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Evidence and diagnostics

Ad fraud detection resources

Browse all 28 guides by task: campaign diagnosis, lead quality, attribution and evidence-led measurement. Categories help you find the right starting point without changing each guide's topic.

11 guides

Google Ads

Audit Search and Performance Max, compare sources and prepare evidence for platform review.

AI Max Search traffic audit

AI Max Invalid Traffic in 2026: How to Audit Search Campaigns

Audit AI Max traffic quality using Search settings, query and landing-page evidence, qualified leads and controlled comparisons, not assumed fraud rates.

Performance Max diagnosis

Performance Max Fake Leads: How to Diagnose the Source Before Changing the Campaign

Investigate fake leads in Performance Max using campaign, placement, session and CRM evidence. Review forms and conversion goals before changing controls.

Network and placement quality

Google Search Partners and Display Network: How to Audit Invalid Traffic

Audit Search Partners and Display traffic using network, placement and qualified-lead evidence. Understand reporting coverage before changing exclusions.

Google Ads lead quality

Google Ads Fake Leads: How to Diagnose Bots, Spam and Invalid Conversions

Getting fake or spam leads from Google Ads? Learn how to separate bots, invalid submissions and poor-quality leads using campaign, session and CRM evidence.

Platform filtering and lead validation

Invalid Clicks vs Fake Leads: What Google Filters — and What It Doesn't

Compare invalid clicks with fake leads in Google Ads. Understand billing filters, form submissions and the first-party evidence needed to validate outcomes.

Competitor-click evidence

Competitors Clicking My Google Ads? What to Do Next

Suspect competitors are clicking your Google Ads? Learn which patterns justify investigation, why IP alone cannot identify an actor and what controls fit.

IP exclusions and risk

Why IP Blocking Alone Doesn't Stop Click Fraud

Understand Google Ads IP exclusions, including account-level PMax coverage, shared networks, rotating proxies and the risks of relying on IP blocking alone.

Audit scope and deliverables

Google Ads Traffic Quality Audit: From Paid Click to Qualified Outcome

Plan a Google Ads traffic quality audit from paid clicks to qualified outcomes. Define evidence, baselines, coverage limits and a report your team can use.

First-party investigation workflow

How to Investigate Suspicious Google Ads Traffic Using First-Party Evidence

Investigate suspicious Google Ads traffic with campaign IDs, request logs, session records and CRM outcomes. Build a reproducible finding before acting.

Google investigation evidence

How to Prepare Evidence for a Google Ads Invalid Traffic Investigation

Prepare a Google Ads invalid traffic investigation with dates, campaign IDs, GCLIDs, request logs and lead outcomes. Know what the evidence cannot prove.

Billing adjustments and evidence

Google Ads Invalid Activity Credits: What They Show — and What They Don't

Understand Google Ads invalid activity credits, adjusted metrics and campaign/network breakdowns, and why billing credits do not measure total lead quality.

5 guides

Lead Quality

Separate accepted forms, genuine enquiries, qualification and fabricated records.

Lead outcome classification

Fake Leads vs Bad Leads: How to Tell Automation From Poor Lead Quality

Separate fake leads from genuine but unqualified enquiries. Compare contactability, qualification, sales acceptance and revenue before making a fraud claim.

Lead outcomes and conversion feedback

Qualified Lead vs Converted Lead in Google Ads: What to Measure

Choose meaningful Google Ads lead outcomes, from form submission to qualified lead and revenue. Review offline feedback, enhanced conversions and data quality.

Form safeguards and lead quality

Why reCAPTCHA Does Not Guarantee High-Quality Leads

Understand why reCAPTCHA cannot guarantee genuine leads. Combine token checks, server-side validation and CRM outcomes without treating every bad lead as a bot.

Backend acceptance and measurement

Server-Side Lead Validation for Paid Campaigns: What Marketing Teams Should Measure

Measure server-side lead validation for paid campaigns: contact checks, duplicates, velocity, campaign IDs and CRM acceptance, without claiming fraud from one rule.

Business cost and qualified outcomes

The Real Cost of Fake Leads: Media Spend, CRM Pollution and Sales Capacity

Calculate the cost of fake leads across media, CRM, sales workload and reporting. Separate verified outcomes, estimates and recoverable costs without promising savings.

3 guides

Attribution

Connect paid activity to observed sessions and outcomes without inventing missing associations.

Paid click to CRM evidence

GCLID, GBRAID and WBRAID: How to Connect Paid Clicks to CRM Leads

Map GCLID, GBRAID and WBRAID from paid visits to CRM outcomes. Review field capture, matching limits, consent and the current Data Manager API path.

Measurement discrepancy diagnosis

Google Ads Clicks vs GA4 Sessions: When Is a Discrepancy Suspicious?

Investigate Google Ads clicks versus GA4 sessions: metric definitions, consent, redirects, missing IDs and tracking errors before suspecting invalid traffic.

Conversion signal integrity

How Fake Conversions Can Distort Google Ads Smart Bidding

Understand how fake or incorrectly tracked conversions can distort Google Ads Smart Bidding. Review conversion goals, qualified outcomes and CRM feedback.

1 guide

Programmatic & Affiliate

Start with inventory misrepresentation and attribution-fraud definitions. Dedicated affiliate investigation guides are not yet published; this is foundational coverage, not a claim of a complete specialist library.

Ad fraud fundamentals

What Is Ad Fraud? Types, Warning Signs and Detection

Learn how ad fraud differs from invalid or low-quality traffic, which warning signs matter, and how to build an evidence-led detection process.

7 guides

Measurement Standards

Definitions, research limitations and practical audit methods. Editorial reporting templates are guidance, not accredited measurement standards.

Measurement definitions and report language

Bot Traffic vs Invalid Traffic vs Ad Fraud: A Practical Measurement Taxonomy

Distinguish bot traffic, IVT, GIVT, SIVT and suspected fraud. Use definitions and evidence scope that keep an audit report from overstating its findings.

Benchmark scope and methodology

Ad Fraud Statistics 2026: What the Numbers Actually Measure

Read 2026 ad fraud statistics with their event, period, denominator and vendor scope. Compare impression-based IVT datasets without treating them as your fraud rate.

Bot traffic diagnostics

Ad Fraud Bot Detection: Signals, Limits and Response

Learn how ad fraud bot detection combines campaign, network, browser, behaviour and outcome signals, including the limits of IP and user-agent rules.

Control validation and false positives

False Positives in Click Fraud Detection: The Cost of Blocking a Real Customer

Measure false positives in click fraud detection. Review shared IPs, VPNs, thresholds, holdouts and rollback criteria before blocking genuine customers.

Software procurement and evaluation

Click Fraud Protection Software: How to Evaluate Detection, Blocking and Evidence

Evaluate click fraud protection software by classification scope, signals, enforcement, exportable evidence and false-positive handling, not headline savings.

Agency audit and client reporting

Click Fraud for Marketing Agencies: How to Audit and Report Client Traffic Quality

Build an agency traffic quality audit and client-ready report with lead-quality metrics, evidence categories and clear limits, without assuming fraud.

Audit procurement and pricing factors

How Much Does an Ad Fraud Audit Cost? Scope, Deliverables and Pricing Factors

Understand ad fraud audit pricing factors, client data requirements and report deliverables. Compare a one-off audit with ongoing protection before a quote.