Lessons from Our First 1,000 Conversations: What Travelers Really Ask AI

When we launched Search Spot , we weren’t trying to compete with traditional booking platforms. We wanted to solve a very different problem - one that most travellers don’t realize exists until they’re overwhelmed by filters, tabs, and options.

That problem? Discovery.

How do you actually find a stay that fits your needs—not just in price and location, but in experience, vibe, and purpose?

After facilitating over 1,000 real user conversations on SearchSpot.ai, we’ve learned a lot about how travellers think, how they search, and what they truly care about when planning a stay. Below are the key takeaways, organized not as vanity metrics, but as insights into real-world behaviour that’s shaping the way we’re building our product.

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1. Travellers Want Context, Not Just Filters

Most booking platforms ask users to choose from a set of filters - price, rating, amenities, etc. But our chat-based interface revealed something different. Users weren’t searching with filters. They were asking questions like:

• “What are the best beach resorts in Goa for couples under ₹4,000?”

• “Which properties are pet-friendly and walkable from the beach?”

• “I want a place with a private pool and decent Wi-Fi, not too far from cafes.”

This showed us that people don’t think in checkboxes. They think in scenarios. Context matters. And our AI needed to interpret not just keywords but intent.

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2. Price Isn’t Everything

Price sensitivity matters - but it's rarely the first thing asked. Our early assumption was that most queries would start with price brackets. But users prioritized other concerns:

• Experience type (peaceful, lively, scenic, “Goa vibe”)

• Location precision (near Anjuna, away from crowds, close to parties)

• Group suitability (family, couples, solo travellers, workcations)

Only after that did they ask: “What’s available under ₹5,000?”

It became clear: the booking decision isn’t driven by cost. It’s driven by confidence in the experience.

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3. Hotel Names Mean Very Little

We observed that brand recall in this category is low. Travellers aren’t searching by property names, even when those properties are ranked or rated well elsewhere. Instead, they describe types of stays:

• “Villas with sunset view”

• “Treehouse options in South Goa”

• “Places that allow parties but are still private”

This insight shifted how we designed our response system. It wasn’t about highlighting names. It was about mapping user intent to property attributes in a meaningful way.

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4. Trust Grows When AI Explains Its Reasoning

We initially experimented with shorter, cleaner responses—just a list of recommended stays. But users asked follow-up questions like:

• “Why did you pick this?”

• “Is it really close to the beach or just says that?”

• “How did you know it allows pets?”

We started integrating transparent reasoning behind each suggestion: “This stay was selected because it’s 400m from Anjuna beach, allows pets, and has a private balcony.”

This improved trust. And we learned that AI doesn’t need to be perfect—but it needs to be explainable.

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5. Travellers Don’t Want to Scroll. They Want Answers.

Traditional travel platforms load hundreds of options. But in our conversations, we found that users rarely ask for more than five options. In fact, 70% of our users click into the first or second recommendation if it’s contextual and well-explained.

This doesn’t mean we’re building a minimal results engine. It means the quality of top results is far more important than the volume.

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6. Booking Is Secondary to Discovery

Another surprise: most users didn’t book immediately. They were exploring. They were using SearchSpot.ai to plan, compare, and narrow down. Only after one or two follow-up queries did booking become a focus.

This validated our core belief: great discovery precedes great conversion.

That’s why we don’t see ourselves as just another affiliate layer. We’re building a discovery engine where search is conversational and results are not just transactional—but contextual, explainable and personal.

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Moving Forward: From Conversations to Capabilities

These 1,000+ chats have helped us evolve the product in real-time. Based on what we learned, here’s what we’re building next:

• Airbnb integration for more diverse stay options

• Collapsible logic in chat so users can explore how results were chosen

• Context compression to support multi-turn, deep queries

• Shareable chat links for trip planning with friends or partners

We’re also gradually shifting away from paid acquisition. Organic users—those who come via word of mouth, Reddit, or travel forums show 3x the retention. They’re more engaged, more curious and more likely to return.

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Final Thoughts

Building SearchSpot.ai in public has helped us stay close to what really matters: the user’s mental model of trip planning. It’s messy, personal, emotional—and deeply contextual.

If you’re building in this space, one piece of advice: stop thinking in filters. Start thinking in questions.

Because that’s what travellers are actually asking.

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Follow our journey as we continue building in public at searchspot.ai or connect with us on X and LinkedIn. We’ll keep sharing the numbers, the learnings and yes - the failures too.