Thanks to AI, structured data, and big data, Quicktext is active in the fields of sales, marketing, communication, and hotel operations.

Want a Demo?
Mama Shelter Los Angeles (Accor Hotels)


Thanks to AI, structured data, and big data, Quicktext is active in the fields of sales, marketing, communication, and hotel operations.

Want a Demo?
Mama Shelter Los Angeles (Accor Hotels)

Q-SERVICES: A new dimension in the hotel industry thanks to AI and big data

01. Data Management

  • Q-Brain+: The AI dedicated to hospitality.
  • Q-Data: Structured data management.
  • Q-Sales: Lead and reservation management.
  • Q-BI: Business Intelligence.

02. Connectivity

  • Q-Hub: Instant messaging management.
  • Q-Connect: Centralised management of connectivity.
  • Q-Automate: Email automation manager.

03. Big Data

  • Q-SEO: Search engine optimisation powered by big data.
  • Q-AD: Optimisation of retargeting campaigns.
  • Q-Dynamic: Dynamic website by predictive model.
  • Q-Verse: Integration in Metaverses.


Introducing artificial intelligence (AI) into any application requires both a very good understanding of deep (DL) and machine learning (ML) and also years of development to acquire data, train models, and deploy them.

Q-Brain+ is the first and only AI specialised in the hospitality industry, and as such is the brain behind Velma.

Q-Brain+ is composed of the best of both worlds of AI, both a classical conversational AI layer and a generative AI layer designed to handle complex answers.


On average, a hotel contains more than 1700 data points: the temperature of the swimming pool, the price of a babysitter, the height of the car park, or the location of electric car charging points. 

Q-Data allows you to merge, structure, and distribute all this data to :

  • instantly communicate this information to your visitors thanks to AI. 
  • feed the hotel's information sources (web, app, CMS, communication media).
  • feed external media (Google, Facebook, etc.).


Q-Sales allows in real-time to:

  • List, value, analyze and segment reservation requests,
  • Extract confirmed requests generated by Velma, the reservation service, or the call center,
  • Associate tags with each contact according to the content of their conversations,
  • Build waiting lists,
  • Generate reports and trends by hotel, city, category, and country in PDF or XLS format.


Q-BI allows you to add new data categories to your business intelligence (BI):

  • Bookings and qualified leads generated,
  • Conversions per pixel, Google Analytics, call center, booking service,
  • Conversation volume per channel (live chat, Facebook, Google, Instagram, WhatsApp, etc.),
  • Lead times,
  • Most frequently asked questions by language, country of origin, date, time, etc.


Q-Hub collects your customers’ messages on a single interface. Manage easily your Live Chat, WhatsApp, Line, Google Messages, Facebook Messenger, SMS, and Booking.com communications for one or several hotels.

Thanks to a smart Q-Connect PMS & CRM connectivities, Quicktext also enables you to send automated messages to your guests at key moments of their journey.


Q-Connect allows you to connect all the hotel's third-party applications

  • CRM, PMS, 
  • UP-sales software,
  • Task manager,
  • Call center (Zendesk)


Q-Automate analyses booking requests and connects to your CRM to automatically generate re-engagement emails to customers who have not completed their booking online.


Conversation data collected via Velma Hotel chatbot allows customer interactions to be segmented by country, city, device used, date and time of connection. 

Q-SEO anonymises and records these criteria in order to obtain traveler profiles and anticipate their needs. This data is used in real-time to improve the referencing of the website.

Do you want to know more about SEO for hotels and how it works?


The conversational data generated is segmented according to the following criteria: country, city, device used, date, and time of connection.

Q-AD records these criteria after having anonymised them, in order to obtain multiple personas. These criteria allow advertising campaigns to be optimised in real-time by personalising them.

Q-Dynamic (2024)

A New Yorker and a Parisian visiting the website of a hotel in London do not have the same interests but will see exactly the same thing.

Q-Dynamic uses a predictive model based on 6 years of data to adapt the website in real-time for each visitor ( recommendation system for hotels).

Q-Verse (2024)

Q-Verse is based, in the first place, on Velma's accumulation of experience over the last 6 years and also on development around expressions, gestures, and lip-synching for more real emotions in the Metaverse for hospitality.