DATA DISCREPANCY ANALYSIS

Your UK Ad Platforms, GA4, and CRM Are Not Telling the Same Story

Google Ads reports one conversion count. GA4 reports another. Your CRM shows a third. And none of them reconcile with actual revenue. For UK businesses operating under Consent Mode v2, the gap between modelled conversions and real outcomes has widened further — yet most reporting frameworks never acknowledge that the numbers disagree.

Request a Data Discrepancy Audit → View the evidence →

This is for you if

Who This Is For

Marketing directors at UK businesses with £10,000–£200,000/month in paid spend — You are accountable for paid performance but the numbers coming from Google Ads, Meta, GA4, and your CRM consistently disagree. You have been told the discrepancy is normal. You suspect it is not. You need an independent analysis that maps exactly where the gaps are, quantifies their scale, and gives you a defensible methodology for reporting that everyone — finance, commercial, marketing — can agree to use.

Head of growth or digital at a UK e-commerce or B2B business — Your revenue reporting lives in Shopify or a CRM. Your ad platform reporting lives in Google Ads and Meta. GA4 sits in the middle and produces a third set of figures. You have never managed to reconcile the three into a single view and you are not confident that decisions about channel budget allocation are being made against accurate numbers. The discrepancy analysis establishes where the gaps originate, what is causing them, and how to build a reporting framework that closes them.

CFOs and finance leads at businesses where paid acquisition is a significant cost line — You are reviewing paid acquisition spend and the figures your marketing team reports do not align with revenue data you can verify. You are not sure whether the problem is attribution, tracking, or reporting methodology. You need a structured audit that traces the data from ad platform click to CRM record to revenue entry and identifies every point at which the count diverges.

What's broken

What's Broken

Consent Mode v2 modelled conversions counted as real

UK businesses using Consent Mode v2 receive modelled conversion data from Google for users who decline consent. This modelled data is presented in Google Ads reporting alongside real, observed conversions with no clear distinction between the two. When marketing teams report these combined figures as measured performance, they are presenting a blend of real and statistically inferred data as if it were entirely factual. The gap between modelled and actual conversions is rarely surfaced, let alone quantified.

Google Ads and Meta both claiming the same conversion

Cross-platform attribution overlap is endemic in UK accounts running both Google Ads and Meta. A customer clicks a Meta ad, returns three days later via Google, and converts. Meta claims the conversion. Google claims the conversion. Both are counted in their respective dashboards. Blended reporting adds both figures without deduplication, producing a conversion total and revenue figure that is systematically higher than what actually occurred.

GA4 conversion counts that do not match ad platform counts

GA4 operates on a different attribution model from Google Ads by default, applies session-based deduplication differently, and counts conversions at the session level rather than the event level in some configurations. The result is a GA4 figure that consistently differs from Google Ads by a margin that is rarely explained. When businesses use GA4 as the source of truth for one report and Google Ads as the source of truth for another, the two reports are measuring different things.

CRM revenue that never reconciles with ad platform ROAS

The final gap is between ad platform reported revenue and CRM or finance system actual revenue. Returns, cancellations, credit card disputes, and payment failures reduce actual revenue below what ad platforms count at conversion time. In businesses with meaningful return rates or subscription cancellations, the ROAS figure reported from Google Ads or Meta can be materially higher than the revenue that actually persists in the business.

What we engineer

What we find in 90% of discrepancy audits

Platform-to-platform gap mapping

We pull data from every active measurement layer — Google Ads, Meta Ads, GA4, call tracking platforms, form submissions, CRM records, and revenue data — and map the conversion and revenue count at each layer. We produce a gap matrix that shows exactly where the count diverges between layers, by how much, and in which direction. This is the foundation of the audit: a factual picture of where the discrepancy exists before any root cause analysis begins.

Consent Mode v2 analysis

For UK businesses using Consent Mode v2, we analyse the proportion of Google Ads conversions that are modelled versus observed. We document how Google is presenting this data in reporting, whether the modelled proportion has changed over time, and what the practical difference is between the modelled total and the observed-only figure. This gives you an accurate view of how much of your reported Google Ads performance is measured and how much is inferred.

Root cause identification

Once the gap matrix is established, we trace each significant discrepancy back to its origin. Common root causes include duplicate conversion action firing, cross-platform attribution overlap without deduplication, GA4 attribution model mismatches, Consent Mode modelling, missing offline conversion imports, and CRM-to-ad-platform data gaps. Each root cause is documented with evidence from the data and linked to the specific gap it produces.

Reconciliation methodology

We develop a reconciliation methodology specific to your platform stack. This is a documented set of rules for how each data source should be used, which numbers should be treated as authoritative for which decisions, and how figures from different sources should be adjusted or weighted when they are compared. The methodology is practical — designed to be usable by your team in routine reporting, not just by analysts running one-off investigations.

Unified reporting framework

We build the structure for a unified reporting framework that draws on each data source appropriately and presents a single reconciled view of paid acquisition performance. This covers conversion counting, revenue attribution, cross-channel deduplication, and the treatment of modelled versus observed data. The framework is designed to produce numbers that marketing, finance, and commercial teams can agree to work from.

Request a Data Discrepancy Audit →

What changes

What Changes

Before

After

Before Discrepancy audit report

After You receive a structured written report that documents the gap matrix across all measurement layers, the root cause of each significant discrepancy, and the revenue impact of each gap. Every finding is supported by data pulled directly from your platforms. The report is written to be understood by a marketing director, a CFO, or a board member — not only by a data specialist.

Before Reconciliation methodology document

After Alongside the audit report, you receive a documented reconciliation methodology that your team can apply to ongoing reporting. This is not a one-time fix — it is a durable framework for how to handle data from multiple sources in a way that produces consistent, defensible numbers.

Before Unified reporting framework

After You receive a framework specification for a unified reporting view that draws on all relevant data sources and presents reconciled performance figures. This can be implemented in your existing reporting tool — whether that is Looker Studio, a spreadsheet, or a BI platform — using the specification we provide.

Before Decision confidence

After After the audit, budget allocation decisions, channel comparisons, and performance reviews are made against numbers that have been checked, reconciled, and documented. You will know what is being measured accurately, what is modelled, and where the remaining uncertainty lies — rather than reporting figures you cannot fully account for.

Common questions

FAQ

What is a data discrepancy audit and how is it different from a standard paid ads audit?

A data discrepancy audit is a structured comparison of conversion and revenue counts across every measurement layer in your paid acquisition stack — ad platforms, GA4, CRM, call tracking, and revenue data — to map exactly where the figures diverge, by how much, and why. A standard paid ads audit reviews account structure, bidding, and creative. A discrepancy audit specifically addresses the measurement layer: whether the numbers you are reporting are internally consistent, what is causing gaps between platforms, and how to produce a reconciled view that holds up to scrutiny.

How significant is the Consent Mode v2 issue for UK businesses?

Consent Mode v2 has been mandatory for Google Ads in the UK since March 2024. For businesses with meaningful proportions of users declining consent — which is common on UK sites with compliant cookie consent implementations — a substantial share of Google Ads conversions may be modelled rather than directly observed. The proportion varies by site and consent rate, but we routinely find that 15–30% of reported Google Ads conversions in UK accounts are modelled data. This does not make them wrong — but it does mean they should be labelled and treated differently from observed conversions in reporting.

Can you reconcile data if we do not have a CRM?

Yes. The audit can be conducted against whatever measurement layers exist in your business. If CRM data is not available, the reconciliation focuses on the layers that are: ad platforms, GA4, form submission records, and revenue data from your e-commerce platform or payment processor. The audit documents what is measurable and what is not, and the reconciliation methodology is built around the data sources you actually have.

How long does the discrepancy audit take?

The audit is delivered within 5 business days of receiving access to all relevant platforms. The timeline depends on the complexity of the measurement stack — businesses with more data sources take slightly longer to map. In most cases the full report, reconciliation methodology, and reporting framework specification are delivered on Day 5.

Will fixing the discrepancies make our reported performance look worse?

In most cases, yes — the corrected figures are lower than the previously reported figures, because inflated conversion counts and cross-platform double-counting are reduced. This is not a sign that performance has deteriorated. It is a sign that the previous reporting was overstating results. Decisions made against the corrected numbers are more reliable, and budget is allocated to campaigns that are genuinely producing outcomes rather than to campaigns that appear to perform well because of measurement errors.

Our team

The people behind the work

Not a black box. Real specialists you can call, with their names on the work.

Niraj Raut

Founder — Ecommerce SEO

Keshab Joshi

PPC Expert

Hawrry Bhattarai

Google Ads Expert

Arogya Rijal

SaaS SEO Expert

About Us →

Start here

Get a clear, reconciled view of what your data is actually saying

The discrepancy audit maps every gap between your ad platforms, GA4, CRM, and revenue data. It identifies the root cause of each divergence, produces a reconciliation methodology your team can apply to routine reporting, and delivers a unified framework that gives marketing and finance a single set of numbers to work from. For UK businesses navigating Consent Mode v2, the audit also clarifies exactly how much of your reported performance is modelled versus observed. No retainer is required.

Request a Data Discrepancy Audit →

Platform-to-platform gap mapping · Root cause identification · Unified reporting framework