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Excerpt from Founder profile interview with LaderaAI CEO Dave Goulden from Ivana Johnston of Puzzle Partner. What do you see as the biggest problem Ladera solves today for hotel owners and operators? Hotel owners are scrutinizing management companies harder than ever. Every decision gets questioned: Why this marketing spend? Why that rate strategy? Why didn't we see this problem coming? Management companies are drowning in requests they can't answer fast enough because they l

The greatest concierges in hospitality history shared one quality that had nothing to do with charm. They always knew. Before you asked which restaurant to book, they knew your preference for quiet tables. Before you mentioned the early flight, they’d already arranged the car. They operated with complete context — your history, your patterns, your needs — assembled invisibly, always current, never requiring you to repeat yourself. Hotels have spent a century perfecting that s

Thirty years ago, hotel operators ran on gut and spreadsheets. Today, they're drowning in data from disconnected systems. That's about to change, just as the internet changed everything. When the internet arrived, people who understood it saw the same future immediately: one day, connectivity would be like a dial tone. Invisible infrastructure. Always on. Everyone gets it. Nobody thinks about it. That day arrived. And it changed everything. We're at that same inflection point

It was never that good anyway. If it were, the BI industry wouldn't exist. Tableau wouldn't exist. The entire third-party dashboard market — billions of dollars — exists precisely because native reporting in your PMS, your POS, your CRM was always an afterthought. A checkbox. Not a capability. So stop waiting for it to get better. It won't. It was never the point. Here's what's actually possible now. Every system you run generates raw data — reservations, spend, cancellations

Every week, hotel commercial teams burn 15 to 20 hours pulling numbers from five or six systems that were never designed to talk to each other. PMS says one thing. The marketing platform says another. POS data sits in its own world entirely. The team stitches it together in spreadsheets, makes their best guess, and walks into the ownership meeting hoping nobody asks the question they can't answer. Here's what that actually costs: your best campaign might be driving bookings t

For decades, the best tool that management had was a well-built dashboard. Pull the data. Format it. Present it. Repeat next week. It was progress. Real progress. But it always stopped at the same place. The harder questions were left to human judgment, institutional memory, and whatever bandwidth the analyst team had left after building the report. Why did this happen? What does it mean? What should we do? Those questions went into a queue. Got scheduled. Got answered days l

Sabine Filoni 's recent article nails half the attribution problem — hotels are paying Google and Meta for customers they already won through their own marketing. Last-click attribution has turned into an expensive shell game, and the industry keeps playing. But there's a bigger issue hiding in plain sight, and it's costing hotels even more than wasted ad spend. Here's what I mean: most hotels measure marketing success at the reservation and move on. But that booking isn't r

Your revenue manager just spent four hours building a report that's already outdated. Not because they're slow. Because pulling data from your PMS, reconciling it with your POS, cross-referencing your CRM, and synthesizing it into something actionable takes four hours. Minimum. By the time they're done, the window to act has closed. Your systems work perfectly. The data is pristine. The problem isn't collection — it's the wasteland between "we have the data" and "we know what

Watch What It Does. The AI community is tied up in knots over whether AI has "judgment." Wrong question. Here's what happened last week: A hotel GM was facing ownership with a year-over-year decline in room nights. Not the conversation you want to have. LaderaAI  didn't just dump data on them. It dug through the noise and found the story: Direct sales up. Corporate and group business stronger. ADR increases that more than offset the occupancy dip.  It positioned the presentat

Aditya Agarwal  built Facebook's first search engine. Spent years as Dropbox's CTO. Then he used AI for a weekend and felt "profound sadness" for all the years he'd lost to manual work. Over the next five days, he shipped more code than in the previous five years. He noticed something else. When hiring for AI-native roles, traditional credentials predicted nothing. Years of experience? Worthless. What predicted success? Personal projects. Side builds. Evidence of someone who