Marketing Audit
The truth about what your marketing is actually doing.
A full audit of campaigns, channels, attribution, and spend efficiency, delivered as a clear action plan, not a status report.
Most marketing reports show what happened. A marketing audit shows why it happened, whether it should have happened, and what needs to change. It covers every layer of the marketing system: campaign structure and bid strategy, signal quality and attribution accuracy, CRM hygiene and lead quality, content effectiveness, and the alignment between marketing activity and revenue outcomes. The output is not a summary of what you already know, it is a diagnosis of what is silently costing you.
The difference between an audit and a performance report
A monthly marketing report answers the question of what happened. A marketing audit answers why it happened, whether it was good enough given the investment and business objectives, and what needs to change. The distinction is in the diagnostic depth. A monthly report shows that Meta spend produced a certain number of leads at a specific reported CPL. A marketing audit examines whether those leads converted to customers at a rate that justifies that CPL, how the cost compares to the previous 12-month trend and to the expected range for the ICP and offer type, whether the conversion event being used for platform optimisation actually represents the business objective, and whether the CPL calculation is built on clean attribution or on data that over-credits Meta by including view-through conversions from buyers who would have converted through a different channel regardless. The audit produces a finding and a recommendation, not a chart. That is the structural difference between reporting and diagnosis.
Signal quality: the hidden cost layer most marketing audits miss entirely
The most commonly overlooked dimension in a marketing audit is signal quality: the accuracy and completeness of the conversion data being received by ad platforms, analytics tools, and the CRM. If a significant proportion of form submissions are not being captured by GA4 because of a tag firing error introduced during a site update, every funnel analysis built on that data is incorrect. If CAPI is sending purchase events to Meta with a match rate below the recommended threshold, Meta algorithm is optimising on a partial signal that does not represent the actual customer population. If the CRM lead source field is unpopulated for a large portion of contacts, every pipeline attribution report from that CRM is unreliable. Signal quality failures are typically invisible in weekly reporting because the reporting is built on the assumption that the underlying data is complete and accurate. An audit that examines data quality at the source layer is often the first time these gaps have been made visible to the team.
From audit findings to a ranked intervention plan
An audit report that lists 25 findings without a prioritisation framework produces a daunting list that is unlikely to be acted on systematically. The action plan that accompanies the audit ranks every finding by estimated revenue impact and implementation effort. Revenue impact is estimated by modelling what the improvement would produce if the issue were resolved: if CAPI match rate improved from below the recommended threshold to above it, what is the estimated improvement in signal quality and what does that imply for algorithm optimisation and CPL? If the attribution gap in the CRM were closed by improving UTM capture, how many pipeline deals would be correctly attributed to their originating channel rather than reported as direct? These estimates are directional rather than precise, but they are sufficient to rank the interventions in an order that maximises the value recovered from the team implementation time. The debrief session then ensures the leadership team leaves with a shared understanding of the three to five interventions most likely to produce visible impact in the following 30 days.
Campaign structure, bid strategy, audience architecture, and creative performance reviewed for each active channel, with specific findings and recommendations.
Signal quality assessment across Meta, Google, GA4, and CRM, identifying every gap where conversion data is missing, duplicated, or misattributed.
True CAC by channel and campaign, incremental ROAS where measurable, and a ranked assessment of which spend is creating value versus capturing credit.
Lead source coverage, field completion rates, lifecycle stage accuracy, and attribution data quality, so you know if your CRM is telling the truth.
Landing page performance, lead magnet conversion, email open and click-through rates, and content attribution to pipeline, with specific improvement recommendations.
A ranked list of the highest-leverage changes to make, each with the specific finding, the expected impact, and the implementation steps.
- 01Access: gain read access to ad platforms, GA4, CRM, and any other relevant systems, so the audit is based on actual data, not self-reported information.
- 02Data pull: extract 12 months of performance data from every channel and build a unified view of spend, leads, pipeline, and revenue.
- 03Qualitative layer: 2–3 interviews with the marketing team and sales team to understand what the numbers are not capturing.
- 04Gap analysis: compare current state against what the system should look like given the company stage, budget, and objectives.
- 05Delivery: written audit report with findings by layer, ranked action plan, and a 90-minute debrief session.
Ready to get started?
Book a 30-min call