The Challenge
This Amsterdam-based travel booking platform specialized in European city breaks and cultural experiences. Like most travel companies, their business was highly seasonal: 65% of revenue came from May–September, while October–March saw a dramatic drop in both organic traffic and paid conversion rates.
The 5-person growth team's standard approach was to cut ad spend by 50% during off-season months and wait for demand to return. But this created a vicious cycle: reduced spend meant fewer bookings, which meant lower revenue, which justified further cuts. By the time peak season returned, the team was scrambling to rebuild campaign momentum from scratch.
Leadership wanted to explore maintaining year-round marketing, but the team couldn't justify the spend: off-season CAC was 2.5x higher than peak season, and platform-native metrics showed terrible ROAS. Without deeper analytics in the travel and hospitality sector, there was no way to know if off-season marketing could ever be profitable.
The Solution
The team connected all channels to Xplainr and, for the first time, analyzed marketing performance through a seasonal lens with cohort-level LTV data.
- Seasonal Cohort Analysis: Xplainr tracked not just initial booking value but repeat purchase behavior over 12 months. The data revealed that off-season travelers had 40% higher lifetime value: they booked more frequently, spent more per trip, and had significantly lower churn rates than peak-season "deal hunters."
- Channel-Season Matrix: Aria mapped which channels performed best in each season. Google Search maintained strong intent-based conversion year-round. TikTok Ads showed 2x higher engagement in winter months (people dreaming of travel). Meta retargeting became more cost-effective as competition dropped.
- AI Budget Pacing: Instead of blanket 50% cuts, Xplainr recommended a dynamic budget allocation model: shift budget from broad prospecting to high-intent channels during off-season, and invest in content-driven TikTok campaigns to build demand for spring bookings.
- Predictive Demand Signals: Aria identified search trend patterns that predicted booking surges 3–4 weeks in advance, allowing the team to increase spend proactively before competitors noticed the demand shift.
The Impact
By maintaining strategic (not blanket) marketing through the off-season, the team achieved a 47% reduction in off-season CAC. Off-season bookings increased by 28%, recovering €220K in revenue that would have been lost to the traditional "cut and wait" approach.
The year-round ROAS stabilized at 3.1x, eliminating the previous boom-bust cycle. Most importantly, the team proved that off-season customers were more valuable long-term, shifting leadership's mindset from "survive winter" to "invest in winter." The company now treats Q4 as a strategic acquisition window rather than a cost-cutting period.