When a DTC brand comes to me with a paid media problem, the diagnosis usually takes about two hours. Not because I am particularly fast, but because the same structural mistakes appear in almost every account. Audience overlap on Meta. Broad match terms burning budget on Google. Platform ROAS numbers that look healthy but are 40% higher than what the bank account confirms. Creative running six weeks past its effective life. Budget allocated to campaigns that have not generated a single purchase in three weeks.
None of these are catastrophic individually. Put them together in an account that has not been structurally reviewed in 90 days, and you typically find 20-35% of total spend delivering nothing. Not underperforming. Nothing. You are paying for activity that has zero causal relationship to the revenue you are generating.
This is the audit framework I run on every brand before we touch a single campaign. It takes 48 hours to complete properly. Everything else, the creative strategy, the audience restructure, the channel mix, comes after this. Because there is no point optimising a leaking pipe before you find the holes.
Start here: the MER gap test
Before opening a single ad manager, calculate your Marketing Efficiency Ratio for the last 30 days. MER is simple: total revenue from your Shopify store divided by total paid media spend across all channels in the same period. This number is the only paid media metric that cannot be gamed by attribution windows, view-through conversions, or multi-touch credit.
Now pull your platform-reported ROAS figures from each channel and calculate a blended number, weighted by spend. If your Meta ROAS is 4.1x and you spend 70% of your budget there, and your Google ROAS is 6.2x on the remaining 30%, your blended platform ROAS is roughly 4.7x. Compare that to your MER.
A gap of 0.5-1x between blended ROAS and MER is normal: organic revenue, direct traffic, and email will always contribute to total revenue without being counted in paid media spend. A gap of 1.5-2x or above means your platforms are claiming credit for revenue they did not generate. Customers who would have bought anyway. Multi-platform attribution where both Meta and Google claim the same sale. Extended attribution windows picking up purchases that happened ten days after the last ad click.
The MER gap is the single most important number in this audit. Everything else you find is either a cause of that gap or a separate waste problem. Keep this number in front of you throughout the 48 hours.
The Meta audit: 6 signals your account is leaking
Meta accounts accumulate structural problems silently. The dashboard still shows spend and impressions and clicks. The ROAS line holds because the attribution window is doing a lot of work. But the underlying structure, the audience architecture, the creative rotation, the campaign hierarchy, is usually a mess within 60 days of the last proper review. These are the six signals to check.
Audience overlap above 20%
In Meta Ads Manager, go to the Audiences section and run the Audience Overlap tool on your active ad sets. Any audience pair with overlap above 20% is competing against itself in auction. You are bidding against your own campaigns, which inflates CPMs and fragments your data. This is the most common structural problem in scaled Meta accounts.
The fix is consolidation, not exclusion. Exclusion layers slow down learning and add complexity. Consolidate overlapping ad sets into a single, broader audience with higher creative diversity. Meta's own data shows that fewer, larger ad sets outperform fragmented audience structures at spend levels above £5K per month.
Creative running past the frequency cliff
Export your last 30 days of ad performance. Filter to active creatives. For each, note the frequency and the cost per purchase. In most accounts, creative performance begins to deteriorate meaningfully above a frequency of 2.5 to the same audience in a 7-day window. Above frequency 4, you are usually spending into diminishing returns and should have rotated the creative out.
The second signal is the week-over-week trend. A creative that generated a 3.8x ROAS in week one and a 2.1x ROAS in week three is not a bad creative. It is a fatigued creative being left in rotation too long. Most DTC brands rotate creative based on feelings, not frequency data. Set a frequency trigger of 2.5 as your rotation signal and stick to it.
Broad campaigns spending without conversion signal
Sort your campaigns by spend, then filter to campaigns with zero or fewer than 3 purchases in the last 14 days. In most accounts, there are one or two campaigns in this category that have been running for weeks, labelled as prospecting or awareness, with no accountability to a conversion outcome.
The question to ask is simple: if this campaign stopped spending tomorrow, what specifically would we lose? If the answer is vague, the campaign is likely burning budget. Awareness spend is legitimate at scale, but it needs to be sized against your MER, not treated as a cost-free hedge. For most DTC brands doing under £100K a month in revenue, pure awareness spend is premature. Convert it to a conversion objective or cut it.
Retargeting audiences including purchasers from 90+ days ago
Check your retargeting audience definitions. Many accounts include all website visitors from the last 180 days, all video viewers, and all Instagram engagers, without excluding purchasers or segmenting by recency. A customer who bought 120 days ago and has not returned is a win-back candidate, not a retargeting target. Showing them the same product ads they already converted on is wasted retargeting budget.
Tighten retargeting windows to 7-14 days for high-intent signals like add-to-cart and checkout initiated. Exclude purchasers from the last 60 days. Separate your 3-7 day website visitors from your 30-day visitors and weight budget to the shorter window. Retargeting audiences that are too broad are expensive, slow to optimise, and include a large share of people who are not in any active buying window.
Multiple campaigns targeting the same outcome
Look at your campaign list and note how many are optimising for the same conversion event on the same audience type. Four campaigns all set to purchase conversion, all targeting UK cold audiences, with different names but functionally identical structures, are not a portfolio strategy. They are the same campaign fragmented five ways. Each has a smaller budget, slower data accumulation, and a longer path to exiting the learning phase.
For most DTC brands, one primary prospecting campaign with multiple ad sets testing creative variables performs better than three separate prospecting campaigns with separate budgets and structures. Fewer campaigns with more budget concentration means faster signal, faster learning, and a shorter time to reliable optimisation data.
Attribution window mismatch
Go to your account settings and confirm your attribution window. Meta's default is 7-day click and 1-day view. The 1-day view attribution is the quiet inflation engine in most DTC accounts: it counts a purchase as Meta-attributed if someone saw your ad in the last 24 hours and then purchased through any channel. If your email, organic search, and direct traffic are healthy, you are almost certainly double-counting a significant share of conversions.
Switch to 7-day click, 0-day view as a test for 30 days and compare total attributed purchases to actual Shopify order volume. The gap is your view-through attribution inflation. You are not removing any real attribution; you are removing the credit for conversions that would have happened without the ad impression doing any real work.
The Google audit: where search budgets disappear
Google waste is usually less about audience structure and more about match type discipline and campaign segmentation. The Search Terms report is the most valuable document in any Google Ads audit. Most DTC brands check it infrequently, if at all. Here is what to look for.
Run the Search Terms report for the last 30 days
In Google Ads, navigate to Keywords, then Search Terms. Export all data for the last 30 days. Sort by spend. Your job is to find every query that has spent more than £5 with zero conversions. These are your immediate negative keyword candidates. In a typical DTC account with broad match keywords and no recent negative keyword hygiene, this list is often 40-80 terms long and represents 8-15% of total search spend.
Check your match type distribution
Pull a breakdown of spend by match type: exact, phrase, and broad. If more than 50% of search spend is in broad match and you do not have a comprehensive negative keyword list actively maintained, you are buying irrelevant traffic. Broad match in 2026 is more intelligent than it was three years ago, but it still follows budget, not intent. High broad match share plus a thin negative keyword list is the most reliable predictor of wasted search spend.
Audit Performance Max asset group performance
If you are running Performance Max, go to the Asset Group performance tab and look at asset ratings: low, good, and best. Any asset group where the majority of text, image, and video assets are rated low is a signal that Google cannot find a combination worth serving at scale. Review the Search Terms insight for your PMax campaigns to understand what queries are actually triggering spend. Cross-reference with your Search campaigns to check for cannibalisation: if PMax is capturing your branded queries and search intent that your manual search campaigns should own, you are paying a premium for traffic you would have captured at lower CPC.
Check geographic spend concentration
Pull a geographic breakdown of spend and conversion rate by region. Most DTC brands have regions where they consistently spend but convert below their account average. If Greater London is your highest-converting area but your spend is distributed roughly evenly across the UK, you are misallocating budget. Geo bidding adjustments of -20% to -40% on low-converting regions and +10% to +20% on high-converting regions is one of the fastest levers in a Google account, and one of the least frequently used.
The cross-channel trap: where attribution hides real waste
The most dangerous type of wasted spend is the kind that looks like it is working. When Meta reports 4.2x ROAS and Google reports 5.8x ROAS and your Shopify revenue is growing, it feels like you have cracked the channel mix. But if your MER is 2.8x, both platforms are sharing credit for the same revenue pool. You are not running two profitable channels. You are running one pool of revenue being claimed twice.
This is particularly common in brands that run Meta and Google simultaneously without a clear channel role for each. Meta drives discovery and intent. Google captures it. But without careful attribution management, Google claims the branded search conversion that Meta created, and Meta claims the same sale via a view-through attribution that fired because the customer saw an ad two days before their Google search.
The practical test: run an incrementality experiment. For a 2-week period, cut your retargeting spend on one channel by 70%. If total revenue does not move materially, that retargeting budget was not incremental. The channel was collecting conversions that would have happened without it. This is uncomfortable to discover, but discovering it is worth several months of wasted spend.
The post-purchase survey is your other tool here. Klaviyo or a simple Typeform embedded on your order confirmation page with the question "How did you hear about us?" takes three minutes to set up and generates attribution data that is completely free of platform bias. When you have 200+ responses, compare the distribution to your platform attribution model. The gaps tell you who is overclaiming.
The 48-hour audit schedule
This is the sequence I follow. It is designed so that each step informs the next, and so that by the end of 48 hours you have a prioritised list of fixes ranked by estimated budget recovery, not just a list of observations.
MER baseline and data collection
Calculate your MER for the last 30 days and the last 7 days. Export your platform ROAS from every active channel. Document the gap. Pull your Shopify revenue source breakdown. Export ad spend by campaign from Meta and Google for the last 30 and 7 days. This is your before data - you will compare everything else against it.
Meta structural audit
Run audience overlap on all active ad sets. Export creative performance sorted by frequency and cost per purchase. Document every campaign with spend but fewer than 3 purchases in 14 days. Check attribution window settings. Review retargeting audience definitions and exclusion layers. For each finding, estimate the spend affected and the likely waste percentage.
Google structural audit
Export the Search Terms report. Identify negative keyword candidates. Document match type distribution. Pull PMax asset group ratings and search term insights. Run the geographic performance breakdown. Check for branded query cannibalisation between PMax and Search campaigns. Estimate budget affected by each issue.
Cross-channel attribution analysis
Compare blended ROAS to MER and document the gap. Review your attribution window settings on each platform. Pull post-purchase survey data if available and compare to platform attribution. Identify your top 10 customers by order value from last month and check their attributed journey in both platforms. Note where the same customer appears in multiple platform attribution reports.
Prioritise and quantify
For each finding, estimate three things: the spend currently affected, the percentage of that spend you assess as non-incremental or wasteful, and the confidence level. Rank your findings by estimated budget recovery. High-confidence, high-value fixes go on this week's list. Lower-confidence findings become hypotheses to test. This step is where the audit becomes a plan.
Implement quick fixes and brief the rest
Implement the top 3-5 changes immediately: add negative keywords, tighten retargeting windows, turn off the campaigns with zero conversion signal, adjust attribution windows. For structural changes that require more careful execution, write a one-paragraph brief for each. Set a 14-day review date to measure the impact on MER. If MER improves, the waste was real. If it does not move, your hypothesis was wrong and you have learned something equally valuable.
What to do when the audit finds more than you expected
Most founders who run this audit for the first time find more waste than they were expecting. The immediate instinct is to cut aggressively, pause everything problematic, and restart with a cleaner structure. This is usually a mistake.
Pausing campaigns resets learning. Cutting audiences too aggressively reduces signal. Meta and Google both need a certain volume of conversion data to optimise effectively, and a sharp restructure that reduces data volume can cause short-term performance regression even when the structural changes are correct. The audit tells you where the waste is. The pace of changes is a separate decision.
The rule I use: changes that reduce waste without touching campaign learning (adding negative keywords, excluding purchasers from retargeting, adjusting attribution windows, pausing creatives with frequency above 4) can be made immediately. Changes that affect campaign structure (consolidating ad sets, changing campaign objectives, restructuring audience hierarchies) should be phased over 2-3 weeks to preserve learning data.
Measure every change against MER, not against platform ROAS. Platform ROAS will move for all sorts of reasons. MER is the number that tells you whether real revenue relative to real spend improved. A 10% improvement in MER from the same spend is worth far more than a 0.5x improvement in a platform ROAS number that was already inflated.
Get the audit done for you
The free scorecard covers paid media efficiency alongside email, conversion rate, and unit economics. Three minutes to complete, and it will show you where paid media ranks against your other growth constraints.
If you want the full audit run on your actual account, the Brand Growth Audit covers your Meta and Google structure, your MER gap analysis, your attribution model, and your cross-channel efficiency - alongside CRO, email, and unit economics. Three days, Loom walkthrough, prioritised findings report. You leave with a ranked list of fixes and the context to understand why each one matters.
Frequently asked questions
How do I know if my DTC brand's paid media is wasting budget?
The clearest signals are a rising cost per acquisition with no change in creative or audience strategy, a gap between your platform-reported ROAS and your blended Marketing Efficiency Ratio, more than 30% of ad spend sitting in campaigns or ad sets that have not generated a purchase in the last 14 days, and a high share of budget in broad or low-intent audiences without a corresponding conversion rate. A simple MER calculation - total revenue divided by total ad spend across all channels - is often the fastest diagnostic. If your MER is significantly below your blended platform ROAS, you have attribution inflation hiding real waste.
What is the most common source of wasted spend in Meta ads for DTC brands?
The most common sources are overlapping audiences across ad sets competing against each other and inflating CPMs, over-saturated creative running past the point of diminishing returns without being refreshed, spending into broad audiences at a scale the creative cannot support, and retargeting audiences that are too large and include people who purchased months ago. Audience overlap and creative fatigue together typically account for 40-60% of identifiable waste in Meta accounts that have not been audited in the last 90 days.
How do I audit my Google Ads account for wasted spend?
Start with your Search Terms report: export all search queries that triggered your ads in the last 30 days and sort by spend. Identify terms with spend but zero conversions - these are immediate negative keyword candidates. Then review your match type mix: if more than 60% of budget is in broad match without a strong negative keyword list, you are paying for irrelevant traffic. For Performance Max, check the asset group breakdown and the search terms insight report to understand where Google is actually spending. Finally, check your geographic performance report for regions where you are spending but seeing conversion rates significantly below your account average.
What is the Marketing Efficiency Ratio (MER) and why does it matter more than ROAS?
The Marketing Efficiency Ratio (MER) is total revenue divided by total ad spend across all paid channels. Unlike ROAS, which is calculated per platform using that platform's own attribution model, MER is channel-agnostic and cannot be inflated by multi-touch attribution or extended attribution windows. A brand with a reported Meta ROAS of 4.2x and a Google ROAS of 5.1x may have a blended MER of only 2.6x, because both platforms are claiming credit for the same purchases. MER is the only paid media metric that is immune to attribution gaming and should be checked weekly alongside platform ROAS.
How often should DTC brands audit their paid media accounts?
A full structural audit - covering campaign architecture, audience strategy, creative performance, match types, and attribution - should happen every 90 days. A lighter weekly check, reviewing spend by campaign against conversion data and flagging any campaign with significant spend but no purchases in 7 days, should be standing operating procedure. The 90-day full audit is particularly important after any major platform update or when scaling spend by more than 30% from one month to the next.
Can I run a paid media audit myself or do I need an agency?
You can run the core audit yourself with access to your ad manager accounts, Shopify analytics, and a spreadsheet. The key reports - Search Terms, Audience Overlap, Asset Performance, and your MER calculation from Shopify revenue data - are all available without specialist tools. Where founders typically struggle is in interpreting structural implications: knowing whether a high CPM is a creative fatigue issue or an audience saturation problem, for example. Start with the MER gap, the 14-day zero-conversion check, and the Search Terms export - those three alone will surface the majority of actionable waste.
About the author
Caner Veli founded and exited Liquiproof, scaling from zero to 3,000+ retailers globally in under 6 years. He now runs Purposeful Profits, a focused growth consultancy for founder-led DTC and CPG brands. 12 named sprint clients. 518% average growth. 27x highest ROAS. Read more about Caner →