The Starting Point: €45K per Month and Declining Returns
In early 2025, a mid-sized B2B SaaS company based in Munich approached me with a problem that sounded familiar: their paid advertising budget was growing, but their results were shrinking. They were spending €45,000 per month across four channels — search ads, social media advertising, display networks, and sponsored content — but their return on ad spend (ROAS) had dropped from 4.2x to 2.1x over the previous 18 months.
The marketing director was under pressure. The CFO wanted to cut the ad budget by 50%. The sales team complained that lead quality was declining. And the marketing team was convinced they just needed more budget to fix the problem. I had seen this pattern before — in fact, I see it roughly once a quarter. The issue is almost never the total budget. It is how the budget is distributed.
This case study documents exactly what I did to cut their ad spend by 40% — from €45,000 to €27,000 per month — without losing a single qualified lead. In fact, lead quality improved. Here is how.
Phase 1: The Diagnostic Deep Dive (Weeks 1-3)
Before touching the budget, I needed to understand where the money was going and what it was producing. I spent three weeks conducting a thorough audit — something many marketers skip because they feel the pressure to act immediately. Resist that pressure. Diagnosis before treatment.
What I Analysed
- Channel-level performance: ROAS, cost per lead, cost per qualified lead, and conversion rates for each channel over the past 12 months
- Campaign-level granularity: Within each channel, which campaigns, ad groups, and audiences were driving results — and which were burning budget?
- Attribution data: How were leads attributed across channels? Were some channels getting credit they did not deserve? (Understanding attribution models was critical here)
- Lead quality downstream: Of the leads generated, how many became sales-qualified? How many converted to customers? At what deal size?
- Audience overlap: Were they targeting the same people across multiple channels, essentially bidding against themselves?
- Creative fatigue: How long had ads been running without refreshment? Were frequency rates indicating audience exhaustion?
Pro Tip: Always look at cost per qualified lead, not just cost per lead. This client was generating leads at €38 each — which looked reasonable. But when I tracked those leads through the sales pipeline, only 12% were qualified. Their true cost per qualified lead was €317. That is the number that matters.
Phase 2: Identifying the Waste (Week 3)
The audit revealed three major sources of waste:
1. Channel Mismatch
They were spending €12,000 per month on display network advertising — 27% of total budget. Display was generating plenty of impressions and clicks, but the lead quality was abysmal. Only 3% of display-generated leads became sales-qualified, compared to 22% from search ads. Display was optimised for volume, not value.
2. Audience Overlap and Self-Competition
Their search campaigns and social media campaigns were targeting the same decision-maker personas with similar messaging. In several cases, they were literally bidding against themselves — one campaign targeting “enterprise project management software” and another targeting “B2B project management platform.” The audiences overlapped by roughly 40%, inflating costs without proportional benefit.
3. Creative Stagnation
Some ad creatives had been running unchanged for over 8 months. Average frequency had climbed to 14.3 on their retargeting campaigns — meaning their target audience was seeing the same ad over 14 times. At that frequency, you are not marketing; you are annoying. Click-through rates on these stale creatives had dropped below 0.3%.
The Before Picture: Ad Spend Breakdown
| Channel | Monthly Spend (Before) | Leads/Month | SQL Rate | Cost per SQL | ROAS |
|---|---|---|---|---|---|
| Search Ads | €15,000 | 285 | 22% | €239 | 3.8x |
| Social Media Ads | €11,000 | 190 | 15% | €386 | 2.4x |
| Display Network | €12,000 | 340 | 3% | €1,176 | 0.6x |
| Sponsored Content | €7,000 | 65 | 28% | €385 | 2.8x |
| Total | €45,000 | 880 | 12% | €426 | 2.1x |
The data told a clear story: search ads and sponsored content were performing well. Social media ads were mediocre but had potential. Display was a money pit. As part of the broader digital marketing strategy review, I recommended a fundamental reallocation.
Phase 3: The Optimisation Strategy (Weeks 4-6)
Based on the diagnostic data, I implemented a three-part optimisation strategy:
1. Cut the Underperformers
- Eliminated display network entirely: The €12,000/month display budget was generating leads at €1,176 per SQL with a 0.6x ROAS. No amount of optimisation would make this channel viable for their product and audience
- Paused 6 low-performing social media campaigns: Campaigns with SQL rates below 8% were paused, freeing up €4,200/month
- Consolidated overlapping search campaigns: Merged duplicate targeting into unified campaigns, reducing wasted spend from self-competition by approximately €1,800/month
2. Reallocate to High Performers
- Increased search ad budget by €3,000/month: Search was their strongest channel with a 3.8x ROAS. More budget here meant more qualified leads at efficient cost
- Doubled sponsored content investment: At a 28% SQL rate and 2.8x ROAS, sponsored content was their hidden gem. Increasing from €7,000 to €14,000/month was a calculated bet based on performance data
3. Fix What Was Fixable
- Refreshed all creative assets: New ad copy, new visuals, new landing pages. We implemented a creative rotation schedule — no ad runs longer than 6 weeks without a refresh
- Refined audience targeting on social: Instead of broad persona targeting, we built lookalike audiences from their best customers (highest LTV, shortest sales cycle)
- Implemented frequency capping: Maximum 5 impressions per user per week across retargeting campaigns
- Improved landing page conversion rates: Simplified forms, added social proof, reduced page load time. Conversion rates improved from 3.8% to 6.2%
Pro Tip: When cutting channels, do not just redirect the savings to other channels. Take the opportunity to reduce total spend and demonstrate efficiency. The goal is not to spend the same amount differently — it is to spend less and get the same or better results. That is the story that earns trust from finance teams.
The After Picture: Optimised Spend Breakdown
| Channel | Monthly Spend (After) | Change | Leads/Month | SQL Rate | Cost per SQL | ROAS |
|---|---|---|---|---|---|---|
| Search Ads | €18,000 | +€3,000 | 355 | 24% | €211 | 4.3x |
| Social Media Ads | €5,000 | -€6,000 | 95 | 26% | €202 | 3.5x |
| Display Network | €0 | -€12,000 | 0 | — | — | — |
| Sponsored Content | €4,000 | -€3,000 | 48 | 31% | €269 | 3.2x |
| Total | €27,000 | -€18,000 (40%) | 498 | 25% | €217 | 3.9x |
Yes, total lead volume dropped from 880 to 498 — a 43% reduction. But here is what matters: sales-qualified leads actually increased from 106 to 125 per month. We were generating fewer leads overall, but significantly more of the leads that actually mattered.
Month-by-Month ROAS Progression
The results did not happen overnight. Here is how ROAS evolved over the six-month optimisation period:
| Month | Total Spend | Qualified Leads | ROAS | Key Action |
|---|---|---|---|---|
| Month 0 (Baseline) | €45,000 | 106 | 2.1x | Audit started |
| Month 1 | €38,000 | 98 | 2.6x | Display cut by 50%, overlap campaigns paused |
| Month 2 | €30,000 | 102 | 3.1x | Display fully eliminated, creative refresh launched |
| Month 3 | €27,000 | 108 | 3.5x | Budget reallocation complete, landing pages optimised |
| Month 4 | €27,000 | 118 | 3.7x | Lookalike audiences deployed on social |
| Month 5 | €27,000 | 122 | 3.8x | Second creative rotation, frequency caps active |
| Month 6 | €27,000 | 125 | 3.9x | Steady state — continued optimisation |
The dip in Month 1 was expected and planned for. Cutting channels always creates a temporary gap as the remaining channels absorb the workload and new optimisations take effect. I prepared the client’s leadership for this by showing them the projected trajectory before making any changes. Managing expectations is as important as managing budgets.
The Lessons That Made This Work
Looking back at this engagement, several principles were critical to the outcome:
1. Diagnose Before You Prescribe
Three weeks of analysis before making any changes felt slow to a client under pressure. But that diagnostic period was what gave us confidence to make bold cuts. Without the data, cutting display would have felt like a guess. With the data, it was obvious.
2. Focus on Qualified Leads, Not Total Leads
This is the single biggest mindset shift in this case study. If we had measured success by total lead volume, the project would have looked like a failure — we dropped from 880 to 498 leads. But lead volume is a vanity metric if the leads are not qualified. Connecting your marketing data to sales outcomes is essential, which is exactly what data-driven marketing is about.
3. Be Willing to Kill Sacred Cows
Display advertising was a “sacred cow” for this client. They had been running display since 2020, the CMO had personally championed the channel, and the team had built expertise around it. Eliminating it entirely was politically difficult. But the data was unambiguous: 0.6x ROAS is losing money. Being diplomatic about how you present the data matters, but the data itself should drive the decision.
4. Optimise the Entire Funnel, Not Just the Top
Cutting spend was only part of the solution. Improving landing page conversion rates from 3.8% to 6.2% meant we got more results from every euro spent. Too many optimisation efforts focus exclusively on media buying while ignoring the conversion experience. Every percentage point improvement in landing page conversion is worth thousands in ad spend.
5. Prepare for the Dip
Month 1 was scary. Qualified leads dipped to 98 — below the 106 baseline. If I had not prepared the client for this, they would have panicked and reversed course. Set expectations before you start: things will get slightly worse before they get significantly better. Have the data to support the trajectory and the courage to hold the course.
Pro Tip: Document everything. I kept a detailed log of every change, the rationale behind it, and the expected impact. When the CFO asked “why did ROAS drop in Month 1?” I could point to the plan and show we predicted it. This builds credibility and buys you the time to let optimisations compound.
What I Would Do Differently
Honesty matters. Here are the things I would change if I ran this engagement again:
- Test before cutting entirely: While cutting display was the right call, I should have run a 4-week test at reduced budget first to validate the hypothesis. The data supported elimination, but a controlled test would have been more rigorous
- Involve the sales team earlier: I brought sales into the conversation in Week 4. In hindsight, they should have been involved from Week 1. They had insights about lead quality that would have accelerated the diagnostic phase
- Invest in organic earlier: The €18,000 in monthly savings could have partly funded organic content marketing, which compounds over time. We eventually recommended this, but I wish we had started the content investment in parallel with the paid optimisation
- Set up better attribution before optimising: Their attribution model was last-click, which undervalued social media’s contribution to the pipeline. We adjusted for this manually, but a proper multi-touch attribution setup would have provided cleaner data
Long-Term Results (6 Months Later)
Six months after the optimisation was complete, the results held and actually improved:
- Monthly ad spend: Stabilised at €27,000 (40% below original)
- Qualified leads per month: Averaged 128 (21% above original baseline)
- ROAS: Maintained above 3.8x (vs 2.1x original)
- Cost per qualified lead: €211 (vs €426 original — 50% reduction)
- Annual savings: €216,000 in ad spend
- Sales team satisfaction: Lead quality scores from sales reps improved from 5.2/10 to 7.8/10
The marketing director who initially feared budget cuts became the champion of data-driven efficiency. The CFO stopped threatening to slash the marketing budget and instead asked how other departments could adopt a similar approach.
Frequently Asked Questions
Is cutting ad spend always the right approach when ROAS is declining?
Not always. Declining ROAS can be caused by many factors — market saturation, increased competition, seasonal effects, creative fatigue, or targeting drift. In this case, the root cause was budget misallocation across channels. In other cases, the fix might be creative refresh, audience expansion, or landing page optimisation without reducing total spend. The key is diagnosis: understand why ROAS is declining before deciding what to cut. Sometimes the answer is to spend differently rather than spend less.
How do you convince leadership to reduce marketing spend without losing their confidence?
Data and transparency are your allies. Present the analysis clearly: here is what we are spending, here is what each channel produces, here is the waste we have identified, and here is the projected impact of reallocation. Frame the conversation around efficiency and ROI, not budget reduction. “We can generate the same qualified leads for 40% less spend” is much more compelling than “We need to cut the budget.” Also, set clear expectations about the transition period — leadership needs to understand that optimisation is a process, not an overnight change.
What metrics should I track to identify wasted ad spend?
Focus on downstream metrics, not channel-level vanity metrics. Cost per qualified lead (not just cost per lead), lead-to-customer conversion rate by channel, customer lifetime value by acquisition channel, and audience overlap across campaigns are the most revealing. High lead volume with low qualification rates is the classic indicator of wasted spend. Also monitor ad frequency — anything above 7-8 impressions per user per week typically indicates diminishing returns and audience fatigue.
How long does it typically take to see results from ad spend optimisation?
In my experience, expect a 4-6 week diagnostic and implementation period followed by 2-3 months of optimisation before you reach a new steady state. The first month after making changes often shows a temporary dip as the system adjusts. By month 3, you should see clear improvement in efficiency metrics. Full results typically materialise by month 4-6. The timeline varies based on your sales cycle length — B2B companies with 90-day sales cycles need more patience than B2C brands with shorter conversion windows.
Can this approach work for smaller budgets?
Absolutely. The principles apply regardless of budget size. In fact, budget discipline is even more important for smaller budgets because every euro matters more. I have applied similar analysis for clients spending €3,000-€5,000 per month. The methodology is the same: audit channel performance, identify waste, cut underperformers, and reinvest in what works. The only difference with smaller budgets is that you may have fewer channels to optimise and less statistical significance in your data, which means decisions require more judgment alongside the numbers.
Key Takeaways
- Declining ROAS is usually a budget allocation problem, not a total budget problem — diagnose before you prescribe by auditing channel-level performance down to cost per qualified lead
- Total lead volume is a vanity metric — focus on sales-qualified leads and cost per qualified lead to identify which channels actually drive business value
- Be willing to eliminate underperforming channels entirely rather than trying to optimise them endlessly — in this case, cutting display advertising saved €12,000/month with zero impact on qualified leads
- Creative fatigue and audience overlap are silent budget killers — implement frequency capping, creative rotation schedules, and audience deduplication across campaigns
- Prepare stakeholders for a temporary performance dip during the transition period and document your rationale for every change so you can explain the trajectory
- Optimise the entire funnel, not just media buying — landing page improvements in this case delivered a 63% conversion rate increase that amplified every other optimisation
- The €216,000 annual savings from this optimisation proves that spending smarter beats spending more — always lead with data, and always follow through with measurement
