Leveraging Data Analytics in Hospitality

Here’s my hack to use ChatGPT to create industry-specific insights from a dense study: This research offers a framework to optimize online content for generative search - a question I’m asked a lot! I pasted the link into Chat (paid version) and asked, “What could a destination marketing organization do to capitalize on these findings?” The output was four broad approaches suggested by the study to use stats and attribution to improve credibility with generative search engines. I then asked Chat to break down each of the approaches into actionable steps for a DMO: ✨ Identify High-Interest Topics: Research frequently asked questions about the destination that travelers often seek. Use tools like Google Trends, keyword research platforms, or insights from social media and travel forums. ✨ Incorporate Clear, Reliable Citations: Ensure all facts, statistics, and claims are backed by reputable sources. Generative engines favor content with authoritative references, so use links to official sites, government data, or well-regarded publications. ✨ Use Structured Data: Implement schema markup on your web pages. For DMOs, relevant schemas might include “TouristDestination,” “Event,” or “Place.” Structured data improves how well content is indexed and featured in GEs. ✨ Create Data-Rich and Visual Content: Include statistics about visitor numbers, spending, or local trends that GEs could pull directly into results. Visual elements like graphs or maps can be described with alt text to enhance GE indexing. Give this a shot and let me know how it turns out - and try asking for specific examples for your destination or business! #destinationmarketing

For years, companies have been leveraging artificial intelligence (AI) and machine learning to provide personalized customer experiences. One widespread use case is showing product recommendations based on previous data. But there's so much more potential in AI that we're just scratching the surface. One of the most important things for any company is anticipating each customer's needs and delivering predictive personalization. Understanding customer intent is critical to shaping predictive personalization strategies. This involves interpreting signals from customers’ current and past behaviors to infer what they are likely to need or do next, and then dynamically surfacing that through a platform of their choice. Here’s how: 1. Customer Journey Mapping: Understanding the various stages a customer goes through, from awareness to purchase and beyond. This helps in identifying key moments where personalization can have the most impact. This doesn't have to be an exercise on a whiteboard; in fact, I would counsel against that. Journey analytics software can get you there quickly and keep journeys "alive" in real time, changing dynamically as customer needs evolve. 2. Behavioral Analysis: Examining how customers interact with your brand, including what they click on, how long they spend on certain pages, and what they search for. You will need analytical resources here, and hopefully you have them on your team. If not, find them in your organization; my experience has been that they find this type of exercise interesting and will want to help. 3. Sentiment Analysis: Using natural language processing to understand customer sentiment expressed in feedback, reviews, social media, or even case notes. This provides insights into how customers feel about your brand or products. As in journey analytics, technology and analytical resources will be important here. 4. Predictive Analytics: Employing advanced analytics to forecast future customer behavior based on current data. This can involve machine learning models that evolve and improve over time. 5. Feedback Loops: Continuously incorporate customer signals (not just survey feedback) to refine and enhance personalization strategies. Set these up through your analytics team. Predictive personalization is not just about selling more; it’s about enhancing the customer experience by making interactions more relevant, timely, and personalized. This customer-led approach leads to increased revenue and reduced cost-to-serve. How is your organization thinking about personalization in 2024? DM me if you want to talk it through. #customerexperience #artificialintelligence #ai #personalization #technology #ceo

Stop Sponsoring Events Just for glossy photos — Start Demanding Real Data Too many brands are throwing money at events without a clue about the ROI. They’re happy with a slick reel, a few polished photos, and a flashy logo plastered across the venue. But the real question isn’t how good it looks—it’s whether it’s actually working.  Shiny Content Isn’t ROI   Here’s what brands should be asking for: hard data. Who exactly is attending these events? Where are they from, what age group are they in, and—here’s the kicker—how many of them are even familiar with the brand? If brands only care about surface-level content, they’re missing the whole point. Data-driven sponsorship means diving into the demographics, geographics, and psychographics of event attendees, which tells you if you’re actually reaching your target audience or just the most conveniently available crowd. Brand Awareness and Perception  Knowing how people feel about your brand matters more than a photo op. Events should be providing detailed analytics on brand awareness and brand perception—both before and after. If you’re a CPG brand, it goes further: are people even trying your product? Do they like it? Do they care? We’re talking about behavior metrics. Events shouldn’t just be content factories; they should be a platform for tracking real engagement and gauging whether your product is making a memorable impact. The Problem with Just Showing Up Here’s where many brands fall short: they’re okay with just “being there.” They put their name on a festival banner without any plan to dig into the details of what that exposure means. A big logo on a stage is nice, but if it’s not moving the needle, it’s nothing more than an expensive placeholder. If you’re not taking the time to measure how attendees actually interact with your brand, you might as well be invisible. Demand Data or Don’t Bother   To fix this, marketing leaders need to make data a non-negotiable part of any sponsorship deal. Before signing on, get specific about the analytics you expect. Whether it’s demographic insights, behavior tracking, or post-event follow-ups, know exactly what you’re getting and make sure it aligns with your goals. It’s time to prioritize substance over appearance and demand data that tells you whether your sponsorship dollars are really working. What to do about this nonsense? In today’s world, event sponsorship without data is just noise and wasted cash. It’s time to demand more than glossy photos. Get the insights, understand your impact, and make sure your brand is getting more than just a fleeting spot on someone’s Instagram feed. When done right, event sponsorship can be transformative—but only if it’s backed by data that actually means something.

Oh the irony.....AI might be the best way to bring humanity back to hospitality. I know, that sounds backwards. But think about it. Most hotels are drowning in data they can’t use. Fifteen different systems, each hoarding a piece of the guest story. So when a loyal guest walks in for the fifth time, they’re still asked: “Is this your first stay with us?” That’s not hospitality. That’s a missed opportunity. That's a disappointed guest. Here’s the twist: AI can fix this. Not by replacing people, but by giving them what they’ve been missing: context. Imagine a simple dashboard that tells the front desk: ✔️This guest prefers a cold room and two extra pillows. ✔️ They celebrated an anniversary here last year. ✔️ They had an issue with the Wi-Fi on their last stay. Now your staff isn’t starting from zero. They’re starting from recognition. From connection. From humanity. The catch? AI can only help if your data is in order. If your data is accessible. So here’s a bit of advice: if your systems are fragmented or hard to use, getting them unified and data is actionable is step one. At Hapi, we exist to help with exactly that... making it easier for your team to turn insights into genuinely personal guest experiences. Giving your team the ability to make a human connection. The winners in this industry will be the brands that stop treating AI as a gadget and start using it as a tool for their teams to be more… well, human. https://lnkd.in/dyRdnxMy

How we discover what to do and where to go is rapidly changing. AI-driven generative search overlays have revolutionized how people seek instant answers, rendering traditional SEO strategies inadequate. To stay visible and competitive, destinations must adapt their information for conversational AI interfaces. Here's how integrating a Conversational AI Chat Platform can elevate your visibility and engagement: - Structure Your Content for AI: Ensure your content is real-time, well-organized, and optimized for AI retrieval. Dynamic FAQs, event schedules, and local tips should be tailored for AI compatibility. - Visibility Across Search Platforms: By leveraging a conversational chat platform, your destination becomes not only searchable but also responsive in AI-generated results on major search engines like Google, Bing, and various social media platforms. - Zero-Party Data: Each interaction presents an opportunity to gather valuable insights into visitor preferences, enabling you to refine marketing strategies and enrich visitor experiences. - Offer Instant, Tailored Responses: Use AI capabilities to provide immediate directions, ticketing information, event updates, and personalized recommendations, keeping potential visitors engaged. Embracing AI-driven conversations is pivotal for tourism companies aiming to excel in the evolving search environment. If you're still reliant on static web content for traditional search rankings, it's time to embrace this transformative shift. #TravelTech #AIChat #GenerativeSearch #DMO #TourismInnovation #SatisfiLabs #Destinations #Attractions #Touroperators

Hotels Are Leaving Millions on the Table Without Realizing It! I was working with a luxury resort that was fully booked, had strong guest satisfaction scores, and a great brand reputation. On the surface, they were doing everything right. But when we dug deeper, we found six hidden revenue opportunities that weren’t being optimized. ✅ Guests were willing to spend more, but weren’t given the right offers at the right time. ✅ The F&B team was focused on service but not strategic upsells. ✅ High-margin experiences were under-promoted. ✅ Room upgrades were not being offered effectively during the booking process. ✅ Their spa had peak-time bottlenecks but underutilized low-traffic hours. ✅ A high-spend segment of guests was being treated the same as everyone else, missing out on VIP-tier monetization. After making small shifts, the resort saw a 7-figure revenue boost in under a year WITHOUT raising prices or increasing operating costs. And here’s the thing: most hotels and resorts have these untapped opportunities sitting right in front of them. 3 Questions for Any Hotel GM or Owner to Ask Right Now: 1️⃣ Are we offering upsells and experiences in a way that feels natural, not forced? 2️⃣ Are our highest-spending guests getting a differentiated experience that drives more loyalty and spend? 3️⃣ Are we treating revenue like a hospitality first strategy or just a numbers game? The best revenue strategies aren’t about charging more they’re about helping guests spend happily. Would love to hear from fellow hospitality leaders: What’s one guest experience change that made a major financial impact at your property? #hospitality #hotels #revenuegrowth #guestexperience #hotelleadership

How One Event Marketer Got a Promotion—While Another Lost Budget (and Credibility) What if your event budget was cut in half? Or better yet—what if it doubled? Lisa and Mark, both experienced event marketers, had very different experiences when it came time to justify their event investments. Lisa’s Story: Data Saved Her Career Lisa managed her company’s annual customer summit, and this year, she decided to do something different—she built her event strategy around metrics that actually mattered to leadership. Instead of just focusing on registration numbers, she tracked: 1. Pre-event engagement: How many high-value accounts interacted with event promotions? 2. Customer retention impact: Did attendance correlate with renewal rates? 3. Session value: Which topics led to the most follow-up meetings with sales? Her report showed clear business impact: 1. 40% of attendees were existing customers, and 75% of them renewed within six months 2. 30% of net-new pipeline was influenced by event-sourced leads 3. Post-event surveys revealed that keynote sessions drove a 50% increase in product demo requests Her leadership team didn’t just approve next year’s event—they increased her budget and asked her to build an event strategy for the entire company. Mark’s Story: A Harsh Reality Check Mark also ran a high-end executive dinner for top prospects. The venue was stunning, the guest list exclusive, and the feedback was glowing. But when his leadership team asked about measurable outcomes, Mark could only say: “The energy in the room was amazing.” “We had great pictures for social media.” What he didn’t track: How many attendees actually followed up with sales Whether the event influenced renewals, upsells, or new deals If the dinner actually moved the needle on business objectives Without data, his budget was cut in half, and leadership questioned whether events were worth the investment at all. Your leadership team doesn’t just want to hear that your event “felt great.” They want proof that it drove real business results. If you’re not tracking both business impact (pipeline, retention, customer growth) and emotional engagement (brand sentiment, product perception), you risk losing not just your budget—but your credibility. -------------------- Hi, I'm Jay Designing experiences for events that drive ROI for our clients. #business #branding #sales #marketing #eventprofs 

🔥 Your casual dining restaurant has a frequency problem. You're not alone. 80% of casual dining brands are seeing fewer visits per guest compared to 2019. YoY comps are down across the board at casual concepts. But here's the thing... Your data already holds the key to fixing this. You just haven't unlocked it yet. A regional chain boosted their frequency by 22% in just 90 days using their existing customer data. Here's a peek at what was discovered: 1. The "Golden Hour" Pattern We found that guests who visit during specific 2-hour windows are 3x more likely to become weekly regulars. But hardly anyone was targeting these periods. 2. The Menu Multiplier Customers who try items from 3+ menu categories in their first two visits have 40% higher lifetime value. Yet most marketing focuses solely on entrees. Think offering a cross menu offer! 3. The Social Proof Secret Guests who dine with 3+ people are 2.5x more likely to return within 14 days. We turned this insight into a game-changing promotion. What about a group dining incentive? The best part? All of this data was sitting in their POS system, loyalty program, and reservation platform. They just needed the right lens to see it. Want to know how we turned these insights into actionable campaigns that drove real results? Drop a 🍽️ in the comments if you want to learn more! #RestaurantMarketing #CustomerRetention #DataAnalytics #Hospitality #CustomerExperience P.S. This isn't theory. These are real results from real restaurants serving real guests. The future of dining is data-driven, and the pioneers are already feasting on the results.

We just found $2M+ in missed revenue for hotels in a single weekend. I'm shocked so many businesses are making this simple mistake. I decided to test a theory during Labor Day weekend in NYC - high demand, limited supply, the perfect pricing laboratory. I scraped pricing data across an entire market to see who was winning. The data revealed a massive intelligence gap: Hotels with real-time pricing data: - Chain hotels using AI optimization: captured 40-60% premiums during peak demand - Luxury properties: maintained $700+ rates while hitting 84% occupancy - Properties with revenue teams: dynamically adjusted hourly based on competitor moves Hotels flying blind: - Independent properties: kept flat rates while missing the $388 city average - Boutique hotels: stuck at $250-300 while comparable rooms sold for $500+ - Small chains: no visibility into what competitors were actually charging Here's what shocked me: Manhattan hotel occupancy hit 89.3% in Q4 2024 - essentially back to pre-pandemic levels. Revenue per room jumped 11.7% year-over-year. The hotels with data access had one key advantage: they could instantly process competitive intelligence from multiple sources, while others were stuck doing manual research. This is exactly the type of data processing problem Structify was built to solve. While those hotel owners were manually checking competitor sites and copying rates into spreadsheets, the winners had automated systems extracting pricing data in real-time. We turn that same manual data work into automated intelligence. What used to take 45 minutes per document now happens in 30 seconds. Whether you're analyzing competitor rate sheets, processing customer feedback forms, or extracting insights from market reports - Structify automates the data work that bogs down entire teams. The same document processing capabilities that give big companies their competitive edge are now accessible through simple API calls. Stop hiring armies of people to copy data from documents. Start automating it.

From Gut Feel to Data-Driven Hospitality ✨ Hospitality has always been about people. The warm welcome, the intuitive service, the memorable stay. But today, the foundation for those magical experiences is increasingly data — harnessed in real time to anticipate needs and unlock value. 🔹 Predictive Demand Forecasting No more relying only on historical booking curves. With AI, hotels and resorts can factor in weather, events, and even airline capacity to predict demand with precision. The result: smarter pricing, staffing, and inventory — improving both RevPAR and guest satisfaction. 🔹 Hyper-Personalized Journeys Guests expect the same personalization from hotels as they do from Netflix. Loyalty data, past stays, and real-time IoT signals (from mobile check-ins to room preferences) help create curated experiences that feel tailored, not templated. 🔹 Revenue Beyond the Room Dynamic pricing is expanding to spa bookings, dining, and excursions. By using data to optimize the whole guest wallet, leading brands are driving new growth while deepening loyalty. 🔹 Operational Excellence Digital twins aren’t just for cruise ships. Resorts and hotels are modeling energy use, predictive maintenance, and workforce scheduling — running leaner, greener, and reinvesting savings into guest experience. ⸻ 💡 At Cognizant , we see this transformation first-hand. We’re proud to be the Data & AI partner for 50% of the properties on the Las Vegas Strip — as well as other leading hotel brands worldwide. The takeaway? Data-driven hospitality isn’t about replacing human warmth with algorithms. It’s about equipping teams to serve smarter, not harder. When the tech fades into the background and the guest feels uniquely understood — that’s when hospitality truly shines. #Hospitality #AI #TravelTech #CustomerExperience #DataDriven