Jon Parsons
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Travel Tech

Why travel search and sort is a product problem, not just a data science problem

Search and ranking in travel marketplaces sit at the intersection of customer intent, commercial strategy and technical capability—and product leadership is what connects them.

In travel marketplaces, search and sort are often treated as a data science or engineering problem. Models, features and ranking algorithms matter—but the biggest commercial gains usually come when product teams own the problem, not just the implementation.

Search is a customer journey, not an algorithm

Travellers arrive with intent that is often fuzzy: dates flex, party size changes, location preferences shift. Search and sort shape:

  • What customers see first
  • How quickly they find relevant options
  • Whether they trust the results
  • How likely they are to convert

These are product decisions with direct commercial impact, not secondary outputs of a model.

Where product leadership adds value

Effective product involvement in search and sort includes:

  • Defining success metrics — conversion, revenue, relevance and customer satisfaction, not just model accuracy
  • Balancing commercial and customer goals — inventory visibility, margin and customer trust often pull in different directions
  • Prioritising opportunities — not every ranking tweak deserves the same investment
  • Translating ML capability into journey improvements — making technical work legible to stakeholders and customers

Data science teams build the engine. Product teams decide where to drive.

Common failure modes

Teams struggle when:

  • Ranking work sits in a technical silo without clear product ownership
  • Success is measured by model metrics alone
  • Commercial trade-offs are discovered late, after significant build effort
  • Customer-facing changes are not tested with the same rigour as conversion experiments elsewhere

A better framing

Treat search and sort as a product surface with measurable commercial outcomes. Bring together product, data science and engineering around shared goals: relevant results, confident customers and sustainable conversion growth.

In travel tech, getting this right is rarely about the smartest model in isolation. It is about connecting customer intent, commercial strategy and technical capability—and that is fundamentally a product leadership problem.

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