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Consumer Trend Data for 2024 Reveals Hotel Executives Should Focus on Customer Service, Digital Support

A hotel's digital experience should be looked at as an engine for retention and loyalty, not just customer acquisition and conversion.
Gen Z hotel guests
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Earlier this month, Qualtrics announced the top consumer experience trends for 2024.  The report identified 4 key trends that will define the consumer experience in 2024:

  • Human connection is the foundation of a winning AI strategy. 
  • Great service beats low prices in the battle for customer loyalty. 
  • Digital support is the weakest link in your customer journey. 
  • Consumers don’t give feedback like they used to, so companies must listen in new ways. 

To learn  how these trends will affect hoteliers, Hospitality Technology reached out to Qualtrics and spoke with Sid Banerjee, Chief XM Strategy Officer. 

Which of these data points are most important for hotel executives to pay attention to? Why?

Two key trends that hotel executives should pay attention to are: 

1) Great service beats low prices in the battle for customer loyalty: Despite economic headwinds, low prices came third after product quality and customer service as top drivers for influencing consumer purchase decisions. So, investing in good customer service just makes good business sense, especially in the hospitality industry ​​where experience is everything. 

However, frontline workers – often the only direct human connection a customer has with a company – have the worst morale among all employee types. They are less satisfied with their pay and development compared to non-frontline staff, and they feel a lack of support to do their job effectively. Companies looking to invest in great customer experience must first focus on these employees' needs.

2) Consumers don’t give feedback like they used to, so companies must listen in new ways: Consumers are shifting away from direct feedback. According to our data, since 2021, the share of consumers providing feedback directly to the companies they buy from after a bad experience has fallen by 7.2 percentage points. Two-thirds of consumers will no longer share when they’ve had a bad experience, and half will either reduce spending or stop entirely after a bad experience.

This has huge implications for the travel industry, where reputation and customer reviews rule. At the click of a button, travelers can compare millions of options and hear firsthand from guests about the experience. Word of mouth spreads quickly. One subpar experience, shared around the world on social media, can have a huge impact on a brand. 

Hotel execs must ensure their teams are armed with the capabilities to listen to consumer feedback coming from review sites, social media, chats, and customer service calls not just following a stay, but DURING the customer journey, whether it’s in the booking, check-in, in-stay, or post visit, so they can understand the guest experience in a more real time way and can improve the experience in the moment.  Doing this allows operators and executives to better understand operational, location-specific, and broader CX trends that can suggest ways to drive  long-term loyalty and revenue. 

How can hoteliers use this data to make informed decisions when it comes to their AI/customer service strategy?

The data shows that consumers are on the fence about interacting with an organization’s AI – 43% are concerned about the lack of a human to connect to and 45% are worried about poor quality of interactions and loss of employees’ jobs. 

A travel experience is the sum of many parts – from finding a destination and booking your package to the experience you have when you arrive. Every moment is an opportunity to delight and build lifelong loyalty so travelers come back time and again, and some of these moments will require a greater human touch while others can be automated with the right technology in place. 

Hotel execs need to be realistic about what their AI solutions do and don’t do well and align those capabilities with consumer preferences. For example, 62% of consumers are comfortable using a brand's automated system for simple, transactional activities like booking an airline ticket. However, they are averse to using it when the stakes are high—only 27% of consumers would prefer to engage with a chatbot or self-service channel to resolve an issue with a bill. 

Importantly - AI technologies needn’t only be applied to direct company-to-customer interactions. Companies can use AI agents, bots, and recommendation engines to empower their frontline customer service teams and improve the entire customer experience. AI-driven insights can now help managers better serve their teams and boost employee well-being, as well as provide more precise coaching to frontline employees to better serve their customers.

By deploying AI in the right places, like automating administrative tasks and processes, frontline customer service employees can devote more time to human connections with customers, creating a better customer experience. 

AI solutions benefit from continuous analysis, continuous improvement, and continuous evaluation of customer experience feedback. This can come from surveys, but also from analyzing how customers interact with AI solutions with AI-powered listening and analysis techniques that measure the accuracy, responsiveness and even empathy of AI solutions. 

What are some major misconceptions around AI and customer service?

There is a misconception about AI making customer experiences less personal, but in many cases, it is the opposite. Instead of posing a threat to humans’ jobs, AI can enhance many roles, allowing frontline agents to spend less time on administrative tasks and more time handling complex issues or providing genuine, human interactions with customers. 

If you look at specifically customer support interactions, AI can now instantly generate summaries after every single call or chat, automatically create support tickets based on a real-time understanding of each issue, measure the emotion and sentiment of the customer and proactively recommend actions to agents and chatbots tailored to each customer’s unique situation. 

It can even create new support articles and FAQs using generative AI, identifying common customer issues, establishing the most common fixes, and then instantly updating knowledge base articles and other resources to help other customers self-serve. It’s a game-changer for organizations that spend millions on service recovery every year

Some companies are also using AI to provide frontline managers with things like personalized AI-driven coaching plans and tailored recommendations that highlight the most impactful things they need to focus on to improve the guest experience.

What's one piece of advice you would give to hoteliers based on this data set?

In the hospitality industry, customer journeys are increasingly multichannel. Searching and reserving is typically done via digital channels (web, mobile), or telephone (reservations contact centers). Checking in is increasingly digital. And even the in-stay experience is often digital, with the accelerating deployment of in-stay conversational channels like mobile app chat, or use of messaging applications like Whatsapp, Telegram, or SMS, RCS, or iMessage. While these channels create efficiency, a single bad experience may show up in one or more channels before it is resolved, and customers typically desire resolution in the moment, not after a stay.  

Our data shows that hotel leaders must not ignore the digital support experience. As consumers go from making a purchase to resolving an issue online, the journey breaks down –with satisfaction 22% points lower compared to making a purchase. The brands that get digital support right can reap huge rewards. Customers are 2.7x more likely to return after a positive digital support experience — the highest of any channel and journey we looked at. A hotel's digital experience should be looked at as an engine for retention and loyalty, not just customer acquisition and conversion. This is an area where advances in AI will help companies make huge improvements. 

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