How AI hyperpersonalization enables hoteliers to optimize internal revenue strategy?

Deep learning technology has enabled systems to anticipate needs based on persona.

Update: 2019-08-29 09:58 GMT
The LuxePass is currently associated with over 20 hotels across Delhi NCR and Mumbai.

Deep learning technology has enabled systems to anticipate needs based on persona. For the hospitality industry, processes that are designed around genuine pain points of guests are fantastic opportunities for ancillary revenue and optimization of the revenue strategy.

Hyper personalized content involves using consumer behaviour, and real-time data to push highly relevant communications at the right time to the right consumer. The data needed to run hyper-personalized revenue strategies may already be available across property management systems (PMS), online review platforms, and internal feedback and reputation systems. Additionally, housekeeping, maintenance & complaint management systems are also rich data sources.

Build the Foundation with Rich Guest Profiles

Oftentimes, hotels use multiple pieces of technology to run single operations, resulting in multiple versions of the same data. However, these fragmented technologies should be replaced by central data housing systems like CRM. Guest Data is already stored across various platforms including Property Management Systems and other hotel systems. Hoteliers need to bring all the data available into a central platform, from where data can then be analyzed through powerful Machine Learning and AI modules. These processes will give hoteliers new insights that can then be used to build a personalized revenue strategy.

With a single CRM that houses all guest data and is constantly adding real-time information, there can be a single version of the truth. With this ‘single version of the truth’, collected guest information can be used to power revenue management systems, upsell systems and in-stay marketing communications.

Connect with Guests through the Right Channels

After guest data is analyzed, hoteliers need to make sure that they are delivering the right prices to the right guests through the right channels. Most often, guests use platforms like SMS, WhatsApp and email. At the operational back-end, hotels need to have a technology piece in place so guest responses to communications can be continually collected and analyzed.

Any thought of building independent applications are usually a waste of time and resources, as these are not the most efficient way to communicate with guests. Hotels need to leverage existing communication channels that are widely used, and integrate these platforms into their existing systems.

Increased Conversion through Personalized Content

AI-driven content leverages all the data available through first and third party sources to intelligently deliver content to customers across channels. These types of hyper-personalized content including personalized dynamic landing pages, offers, and recommendations result in an increased conversion rate.

According to BCG, organizations that use hyper-personalization in their content and marketing are increasing their revenue by about 6 to 10 per cent, which is about two to three times faster than organizations that do not use hyper-personalization.

The sheer amount of guest data available from first-party sources (hotels) should be substantial enough that hotels can then use this data to drive highly targeted campaigns that will result in more direct bookings and increasing additional revenue.

Persona Based Pricing

You might have noticed that when browsing flights, if you linger on one page too long, or run multiple searches for the same flights, the prices dynamically increase for you, but might remain the same for someone who checks the same flight for the first time. OTAs use this type of dynamic pricing to leverage revenue opportunities based on need and behaviour.

Hotels could consider using a similar strategy for revenue maximization. For example, a family travelling with a child might be willing to spend a little extra for a better room that can accommodate their needs better, but a hotel could never figure that out without the right technology pieces tracking guest persona and behaviour. Based on collected data, hotels can continue to innovate and decide the best revenue strategies that work best for them.

By tracking and analyzing guest behaviour, AI integrated tools can automatically extend these personalized room rates to guests that are optimized for conversion and also for hotel revenue. By collecting data, analyzing it, and having the right technology pieces in place, hotels can offer potential guests room rates that have been set just for them and the services and facilities they wish to use during their stay. Additionally, hotels can allow guests to continue to personalize their stay even after the initial booking, and can even suggest third party experiences to guests based on persona.

As guest behaviour is continually monitored, AI-driven platforms get better at analyzing data and extending even more optimized prices to potential guests. With these types of platforms, hoteliers can begin to create smarter and data-backed revenue strategies, without missing out on revenue opportunities such as extending ancillary hotels services like spa packages and F&B offers.

These systems need to be set up once, and run as one engine, after which hotels can simply focus on optimizing the engine for maximum revenue. In the current scenario where user privacy is being taken seriously (thanks to GDPR), hotels need to make sure their guest communications are being run from a single console, so you guest is not overwhelmed or annoyed with multiple communications. With hyper-personalization, hoteliers can truly create and deliver exceptional experiences that will delight guests.

- Mr. Pranjal Prashar, Co-Founder & CEO, Xperium

Disclaimer: The views and opinions expressed in this article are solely those of the original author. These views and opinions do not necessarily represent those of Deccan Chronicle and/or other staff and contributors to this site.

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