A printed binder cannot tell you whether anyone opened it. Most digital guidebooks only tell you that a guide was opened. Tabellara measures the guide the way you would want to improve it: which pages, by which visitors, arriving through which QR code, in what order.
Four tiles tell you delivery is working (guide opens), how many actual people looked (unique visitors), how deep they went (item opens), and how many arrived through a frame. Below them, two rankings: the ten most-read cards in your guide, and the ten deep-link QR codes that get scanned most. If guests read the hot tub card forty times and skip your fifteen recommendations, your guide just told you what to fix. If the coffee-maker QR gets scanned every stay and the laundry one never does, you know where the next code goes.
Every session is a row: when, an anonymous visitor ID, device and platform, city and state, the deep link or frame they arrived through, and how many pages they read. Click a row to see the exact order they read them in.
One box searches visitor ID, city, state, deep link, and frame name. Type a city and get that city; type a two-letter state code and get exactly that state, so “CA” finds California, not Chicago. Type “coffee” and see everyone who arrived through the coffee-maker QR. Click any visitor ID to follow that guest across their whole stay.
Every header sorts: newest first, most pages read, by state, by frame. Twenty-five rows per page so the table stays readable at a hundred stays or a thousand. And Export CSV downloads the whole filtered set, not just the page on screen, with a column listing every page each visitor opened, ready for a spreadsheet, a report to an owner, or your own analysis.
Name each frame by where it hangs, Kitchen Bar, Entrance Wall, and every arrival through it is labeled. Print a QR next to the hot tub that opens straight to the hot tub card, and the deep link column shows exactly that. You learn which placements guests actually scan, and where the next one belongs. On a Tabellara TV, every scan also ties to the specific reservation.
8:42 AM: opened Checkout steps
8:41 AM: opened Getting in
8:40 AM: arrived via Kitchen Bar (frame)
7:15 PM: arrived at /house-manual/hot-tub (deep link)
7:14 PM: opened 🗺 Map
Quick links put your website, direct booking, and early check-in offers on the guide's home screen, and every tap is measured. When a guest hits “Book direct next time”, you see it: the clearest revenue signal a guidebook can give you.
Reviews are revenue: Cornell's Center for Hospitality Research found that raising a review score by one point on a five-point scale lets a property charge about 11% more without losing occupancy, and studies of Airbnb reviews consistently rank host communication among the strongest drivers of guest satisfaction. Guests who find answers without asking are guests who review well; analytics show you whether they are finding them.
See engagement across every property at once, or focus on one: seven days, thirty, ninety, or all time, or any date range you choose. The same table, the same search, the same export, whether you run one cabin or fifty.
Guests never create accounts or hand over personal information to read a guide. Visitor IDs are anonymous, derived from a one-way hash; no IP address is ever stored. Reservation linking uses an opaque token from the code on screen, never the guest's identity. You learn what content works; your guests stay guests, not data points.
Publish a guide today; know what your guests read by the weekend.
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