Daytrip
D2C Travel Platform • 120+ Countries
How We Saved $2.7M by Working WITH Google's Algorithm
Operating across 110 countries with 60,000+ routes, Daytrip's Google Ads account had spiraled to 17M keywords and 63K campaigns. We built a proprietary route scoring system blending backend profit data, PPC performance, and SEO search volume-transforming 99% complexity reduction into 85% POAS improvement.
The Challenge
When I logged into the Daytrip Google Ads account during the interview process, I saw archaeological layers of 6 years of continuous campaign creation, built on top of each other without a single layer being removed.
For context, a large e-commerce account might have 50-100 campaigns. A complex multi-country operation might push to 500-1,000. This was 63,846.
Three Critical Problems
1. Algorithmic Concentration
Google's algorithm naturally pushes 80% of spend to the top 20% of performers within any campaign. With 60,000+ routes mixed together, the algorithm decided where money went-not the business. High-potential routes never got enough budget to prove themselves. Strategic business priorities were ignored.
2. No Connection Between Ad Spend and Business Value
A high-margin route in a strategic new market would get the same treatment as a low-margin route in a saturated market. There was no system connecting backend profitability data to advertising decisions. The team was optimizing for POAS, but POAS doesn't tell you if you're making $10 or $100 per booking.
3. Google's "Other Search Terms" Black Box
Approximately €1.5M in annual spend was going to searches we couldn't see, performing 32% worse than the searches we could see:
The Algorithmic Concentration Problem
Google's algorithm naturally applies the 80/20 rule. You can't fight it-but you can control WHERE it happens.
💡 The Breakthrough
You can't stop the 80/20 rule-it's fundamental to how machine learning works. But by segmenting routes into separate campaigns, you control which 20% gets the 80%. The algorithm's natural behavior now works FOR your business strategy, not against it.
The Solution
The answer wasn't in Google Ads data alone. It required building a custom scoring system that blended multiple data sources to give us a holistic view of route performance and potential.
Route Segmentation Framework
Blending backend profit data, PPC performance, and SEO search volume to classify all 60,000+ routes into strategic segments
Cash Cows
Proven winners • High revenue & margin • Consistent POAS >150%
Maximize investment • Never miss traffic opportunities
High Potentials
Strong margins • Good signals • Limited data but promising
Scaling candidates • Tomorrow's Cash Cows
Low Score
Underperformers • Low margins or poor POAS • Limited demand
Minimal maintenance • Test occasionally
Sleepers
Never advertised • Zero historical data • Unknown potential
Controlled exploration • Discovery pipeline
Routes move between segments based on performance. A Sleeper that performs well gets promoted to High Potential. A High Potential that proves out becomes a Cash Cow. The system continuously adapts to align budget with actual business value.
Transformation Timeline
From unmanageable chaos to strategic control in 4 phases
Immediate Cleanup
Paused 11,000 poor-performing campaigns. Killed phrase match. Split brand campaigns by region. Implemented regional tPOAS targets.
Build Route Scoring
Blended backend profit data (BigQuery), Google Ads performance, and SEO search volume into proprietary scoring system.
Strategic Segmentation
Classified all routes into Cash Cows, High Potentials, Low Score, and Sleepers. Separated into dedicated campaigns.
Domain Migration Launch
Complete rebuild during domain change. Parallel run strategy. New structure: 127 campaigns vs. 63,846 old campaigns.
The Transformation in Scale
From unmanageable chaos to strategic control
Less complexity = cleaner signals = better optimization
The Results
By week two after the domain migration launch, the algorithm started finding its footing. Spend stabilized. Conversion rates improved. POAS climbed. By week four, we were exceeding previous performance levels.
Eliminated approximately $15,000 in daily wasted spend through route scoring and strategic segmentation.
From ~115% to ~213%. Algorithms finally had clean signals within strategically-defined segments.
Cut total ad spend by 40% while maintaining year-over-year growth through major disruption.
Increased absolute gross margin by focusing budget on high-margin routes (Cash Cows and High Potentials).
Key Takeaways
Multi-Source Data Beats Single-Source Data
Google Ads data alone is insufficient at scale. We blended backend profit data (BigQuery), PPC performance, and SEO search volume for holistic route scoring. High POAS but low margin? Not a Cash Cow. Low data but high search volume + good margin? High Potential.
Work WITH the Algorithm, Not Against It
Google's 80/20 concentration is inevitable-you can't fight it. But you CAN control WHERE it happens. By segmenting routes into separate campaigns (Cash Cows, High Potentials, Low Score, Sleepers), the algorithm's natural behavior now aligns with business priorities.
At Scale, Less Complexity = More Performance
17M keywords sounds impressive, but 99.85% never converted. They were just noise preventing algorithms from optimizing effectively. The 99% complexity reduction didn't lose performance-it gained it.
Algorithms Optimize for the Past. Strategy is About the Future.
The route scoring system worked because it combined algorithmic optimization (within segments) with human judgment (defining the segments based on business strategy). Don't confuse the two.
Ready to Transform Your PPC Strategy?
Whether you're drowning in complexity or just want to align your ad spend with business value, let's talk about how multi-source data scoring can transform your performance.