Introducing GAIL: Great Wolf Lodge’s AI for pinpointing guest sentiment

Great Wolf Lodge (GWL) is using artificial intelligence software to better understand its guests’ experiences at its adventure-themed lodges. The effort is a part of a sweeping digital strategy that incorporates cloud and SaaS technologies, as well as new property management and CRM systems.

“We want to better engage with guests at all points,” CIO Edward Malinowski, who joined the company from Shangri-La Hotels and Resorts in 2017, tells CIO.com. Technology is also a critical element in assisting GWL employees, also known as “pack members,” to make that happen. 

A proliferation of digital technologies is enabling hospitality chains to triangulate how guests feel about their services. And while social media and review websites offer a wealth of information about brand sentiment, accessing that data is a chore. Employees often spend hours combing through Twitter and Facebook, as well as Yelp, TripAdvisors and other reviews-focused websites for perspectives that can help a company address its strengths and weaknesses.

Automating these tasks would provide a big efficiency boost and CIOs today have at their disposal a number of options, from robotic process automation (RPA) to machine learning (ML) and AI.

Fine-tuning AI for hospitality

Embracing the latter practice, Malinowksi and his team created Great Wolf’s Artificial Intelligence Lexicographer, or GAIL, which sifts through large amounts of comments guests have posted in monthly GWL surveys. Such unstructured data would take humans hours to pore over. “Doing it with AI can help you make a wide cut through it, so that you can drill into the data,” Malinowski says.

And GAIL parses the data in seconds, thanks to natural language processing (NLP), a branch of AI that deals with the interaction between computers and humans using the natural language. In effect, GAIL “reads” and renders opinions on comments as to whether the authors are likely to be a net promoter, detractor or neutral party.

GAIL, which runs in the cloud and uses algorithms GWL developed internally, then identifies the key elements that suggest why authors feel the way they do about GWL. This in turn helps the business operations team refine GWL’s services, says Malinowski. Training is a critical task in any AI endeavor, and to do so GWL engineers fed GAIL more than 67,000 reviews, which helped the tool make determinations with 95 percent accuracy, Malinowski says. GWL uses more traditional text analytics on a very small subset of information that GAIL can’t yet understand. 

GWL engineers prototyped an early version of GAIL that analyzed brand sentiment from social media channels, using Amazon Web Services (AWS) Comprehend, an NLP tool that unearths insights from text. But Malinowski says GWL elected to build a tool internally that was “fine-tuned for hospitality.”

Corporate investments in AI, whether built internally or procured from a vendor, are at an all-time high, with advancements driving double-digit, year-over-year spending into the next decade, according to IDC. Worldwide spending on AI systems could top $35.8 billion in 2019, an increase of 44 percent over the amount spent in 2018, fueled by initiatives to optimize operations, transform the customer experience and create new products and services, says IDC analyst Marianne Daquila.

AI comprises a portion of GWL’s digital efforts. Over the past two years, Malinowski has also overseen the construction of a new analytics architecture, anchored by a data lake.

GWL engineers use AWS Spectrum and Athena to perform ad-hoc SQL queries directly from the lake, while business analysts visualize data and derive insights using Tableau. GWL also modernized its Salesforce.com CRM, with targeted campaigns driving a 20 percent boost in traffic to its website, and upgraded its Oracle property management system to comply with PCI encryption.

These tech migrations are core to GWL’s organizational transformation, which garnered a 2019 CIO 100 Award in IT Excellence. Malinowski also built a shared services model to enable IT to remotely support GWL lodges, including its 18th, slated to open in Scottsdale, Arizona, next month. This is part of an operational efficiency play to centralize and codify repeatable business processes.

“The 18th lodge shouldn’t take the same effort to build as the first few,” Malinowski says. “There is a real value in centralization and using the cloud.”

More broadly, the IT transformation is helping GWL IT evolve from being order takers to business co-creators, or thought leaders who can solve business problems. For example, IT created a tool to track towels in its water parks, a project that will reduce costs by $1.5 million. This do-it-yourself approach underscores how GWL’s pack members are seizing the opportunity to create projects that impact operating revenue. 

It also validates the idea that three-quarters of CIOs are driving business innovation and focusing on cultivating business strategy, according to IDG’s 2019 State of the CIO report, which polled 683 IT leaders.

Lessons learned

Malinowski offered some tips for IT leaders interested in taking similar tacks.

Avoid tech for tech’s sake. Pick tools that strike the right balance of tech and practical utility. “You have to be careful of what’s gimmicky and what’s a solution in search of a problem,” Malinowski says.

Tech must deliver ‘memorable moments.’ Tools and solutions should be aligned with meeting business objectives, Malinowski says. For example, the company is looking into chatbots that answer guests’ frequently asked questions about GWL services, which could reduce calls to GWL pack members.

Reskilling is critical. To get staff moving in lock-step toward the future GWL envisions, Malinowski spent a good amount of effort training up employees in cloud computing and other modern technologies, as well as shifting IT away from the keeping-the-lights-on mentality.

“In that mode of operating, it’s difficult to see the horizon,” he says. “It’s important to take the moment to remind them that they do have the tools, and capabilities to move mountains. Seeing that swagger return to the team has been fantastic.”