Is Your Big Data a Big Mess?
For a long time, companies have assumed that collecting Big Data would bring a better understanding of what works and automatically lead to greater success. However, many executives are finding that Big Data can be a big headache and result in just as many questions as answers. This challenge is complicated by rapid changes in the restaurant and hospitality industries. Guests are seeking a more convenient experience, labor costs are increasing, and new technologies continue to evolve rapidly. Each of these trends begs the question: Which new investments will truly pay back?
In order to react quickly to these industry changes, leading restaurants and hotels have been the pioneers of finding rapid ways to analyze new innovations through in-market business experimentation. For many, this approach has worked for years, but now even the most sophisticated organizations are finding it’s not enough. Here, Applied Predictive Technologies offers tips for how to take those capabilities to the next level with advanced analytics in order to succeed.
Changing Guest Preferences. As customers demand more convenience, more choice, and greater customization, hotels are adding technologies to enable mobile booking, check-in, and preference selection (e.g., having fresh flowers in your room, choosing which types of pillows you’d like, and more). Meanwhile, restaurants are launching made-to-order items available through mobile ordering and digital kiosks, faster service models, and more. Some brands are taking more radical approaches by adding completely new concepts. For instance, Quiznos recently introduced Quiznos Grill in Denver, a fast causal concept which offers a different menu and dining environment. Many hotels have been renovating locations to offer more spacious designs and communal meeting areas to create a “boutique” feel.
As hotels and restaurants respond to these new preferences, it is critical that they accurately understand the impact of each change, as even the most innovative ideas don’t always turn out to be profitable. To determine which locations and guests respond well, and which guests may be deterred by new innovations, organizations must conduct business experiments in a subset of locations before committing to the idea more broadly. Through experimentation, hotels and restaurants can quickly understand which ideas work, which ideas don’t, and which ones can be fine-tuned to maximize success.
Heightened Competition Brings New Pressures. Restaurants and hotels alike have been facing heightened pressure from new competition. The rise of fast casual players in the restaurant space has posed a big challenge to maintaining market share for quick-service and full-service restaurants. In response, many quick-service restaurants have started offering healthier menu options and revamping locations. On the other end of the spectrum, many full-service restaurant chains have made an effort to cater to guests by adding tabletop ordering and payment devices.
Similarly, innovative players like Airbnb are offering new ways to book. Airbnb is also having an impact on how hotels think about providing a localized experience for guests. Though some guest segments may never switch to Airbnb, travelers will continue to demand some of the offerings Airbnb successfully provides: a seamless booking experience and an “authentic” travel experience.
Historically, restaurants and hotels have focused their analytics solely on understanding performance within their own networks. The increase in competition, however, has necessitated a more holistic view of performance—both within and outside their four walls. Drawing on insights such as those from anonymous and aggregated payment transactions, these organizations are now getting a 360 degree view of customer spending behavior across industries, channels, and over time. These new insights – available on a continuous basis – significantly improve targeting decisions across marketing, promotional, operational, and other programs.
Technology Enables Efficient Customization. For restaurants and hotels, the demand for more customization and efficiency has left guests wanting their meals and hotel rooms to be personalized to their exact needs and desiring to save time during the ordering or booking/check-in processes. While fulfilling these requests presents operational challenges for these organizations, technology is enabling restaurants and hotels to more efficiently deliver mass personalization to consumers.
The rising minimum wage rate is also pushing restaurants and hotels to find more efficient solutions in order to manage labor costs. A few restaurant industry leaders are introducing digital ordering kiosks to allow guests to customize items and order directly from the digital kiosk, enabling companies to shift labor to new activities (e.g., delivering food to the tables). Other restaurants, like Eatsa, are pushing efficiency to a new extreme by reinventing the traditional labor model. Based in San Francisco, this concept eliminates cashiers and servers entirely by allowing consumers to order via mobile app or iPad based kiosks, and then pick up their food from a digital cubby system.
Similarly, some hotels have installed digital kiosks for check-in, and guests can receive digital keys via the hotel’s app, eliminating the need to check in at the front desk. Aloft Hotels has even started to use robots to make room deliveries.
In the coming months, expect to see even more restaurants and hotels leveraging technology in novel ways. These new innovations not only benefit the end consumers, but also provide organizations with invaluable insights in return. Restaurants can understand what combinations are most frequently ordered when guests have limitless ways to customize their meals. They can then leverage these insights to inform new standard menu items based on popular ingredient combinations. Hotels can likewise understand which specific components guests care about most to inform the amenities for a standard hotel room.
As the hotel and restaurant industries continue to evolve, it is vital that these organizations fully leverage Big Data to gain deeper insights about their guests. Advanced analytics for in-market business experimentation allows these companies to target and tailor initiatives, understand impact to market share, and uncover guest preferences, enabling these organizations to maximize profitability.
In order to react quickly to these industry changes, leading restaurants and hotels have been the pioneers of finding rapid ways to analyze new innovations through in-market business experimentation. For many, this approach has worked for years, but now even the most sophisticated organizations are finding it’s not enough. Here, Applied Predictive Technologies offers tips for how to take those capabilities to the next level with advanced analytics in order to succeed.
Changing Guest Preferences. As customers demand more convenience, more choice, and greater customization, hotels are adding technologies to enable mobile booking, check-in, and preference selection (e.g., having fresh flowers in your room, choosing which types of pillows you’d like, and more). Meanwhile, restaurants are launching made-to-order items available through mobile ordering and digital kiosks, faster service models, and more. Some brands are taking more radical approaches by adding completely new concepts. For instance, Quiznos recently introduced Quiznos Grill in Denver, a fast causal concept which offers a different menu and dining environment. Many hotels have been renovating locations to offer more spacious designs and communal meeting areas to create a “boutique” feel.
As hotels and restaurants respond to these new preferences, it is critical that they accurately understand the impact of each change, as even the most innovative ideas don’t always turn out to be profitable. To determine which locations and guests respond well, and which guests may be deterred by new innovations, organizations must conduct business experiments in a subset of locations before committing to the idea more broadly. Through experimentation, hotels and restaurants can quickly understand which ideas work, which ideas don’t, and which ones can be fine-tuned to maximize success.
Heightened Competition Brings New Pressures. Restaurants and hotels alike have been facing heightened pressure from new competition. The rise of fast casual players in the restaurant space has posed a big challenge to maintaining market share for quick-service and full-service restaurants. In response, many quick-service restaurants have started offering healthier menu options and revamping locations. On the other end of the spectrum, many full-service restaurant chains have made an effort to cater to guests by adding tabletop ordering and payment devices.
Similarly, innovative players like Airbnb are offering new ways to book. Airbnb is also having an impact on how hotels think about providing a localized experience for guests. Though some guest segments may never switch to Airbnb, travelers will continue to demand some of the offerings Airbnb successfully provides: a seamless booking experience and an “authentic” travel experience.
Historically, restaurants and hotels have focused their analytics solely on understanding performance within their own networks. The increase in competition, however, has necessitated a more holistic view of performance—both within and outside their four walls. Drawing on insights such as those from anonymous and aggregated payment transactions, these organizations are now getting a 360 degree view of customer spending behavior across industries, channels, and over time. These new insights – available on a continuous basis – significantly improve targeting decisions across marketing, promotional, operational, and other programs.
Technology Enables Efficient Customization. For restaurants and hotels, the demand for more customization and efficiency has left guests wanting their meals and hotel rooms to be personalized to their exact needs and desiring to save time during the ordering or booking/check-in processes. While fulfilling these requests presents operational challenges for these organizations, technology is enabling restaurants and hotels to more efficiently deliver mass personalization to consumers.
The rising minimum wage rate is also pushing restaurants and hotels to find more efficient solutions in order to manage labor costs. A few restaurant industry leaders are introducing digital ordering kiosks to allow guests to customize items and order directly from the digital kiosk, enabling companies to shift labor to new activities (e.g., delivering food to the tables). Other restaurants, like Eatsa, are pushing efficiency to a new extreme by reinventing the traditional labor model. Based in San Francisco, this concept eliminates cashiers and servers entirely by allowing consumers to order via mobile app or iPad based kiosks, and then pick up their food from a digital cubby system.
Similarly, some hotels have installed digital kiosks for check-in, and guests can receive digital keys via the hotel’s app, eliminating the need to check in at the front desk. Aloft Hotels has even started to use robots to make room deliveries.
In the coming months, expect to see even more restaurants and hotels leveraging technology in novel ways. These new innovations not only benefit the end consumers, but also provide organizations with invaluable insights in return. Restaurants can understand what combinations are most frequently ordered when guests have limitless ways to customize their meals. They can then leverage these insights to inform new standard menu items based on popular ingredient combinations. Hotels can likewise understand which specific components guests care about most to inform the amenities for a standard hotel room.
As the hotel and restaurant industries continue to evolve, it is vital that these organizations fully leverage Big Data to gain deeper insights about their guests. Advanced analytics for in-market business experimentation allows these companies to target and tailor initiatives, understand impact to market share, and uncover guest preferences, enabling these organizations to maximize profitability.