There’s no shortage of buzz around AI, and it’s easy to get swept up in the excitement—chatbots, automated reports, predictive pricing, and yes, even those quirky AI-generated photos for a new headshot.
But to make sense of what actually drives value, especially in the hospitality space, it helps to break AI into three buckets: what happened, what will happen, and what to do about it.
Let’s unpack that.
1. Business Intelligence (BI): What Happened
Most hotels are familiar with business intelligence platforms. The most popular BI report hotels rely upon is STR reports. Additionally, the usage of Power BI, which is a visualization tool to display BI data. For marketers, Google Data Studio is a powerful tool for BI.
These tools tell us what happened—last month’s occupancy, last month’s spend and click through rates or YoY brand.com contribution.
They’re vital for measuring performance, but they’re inherently backward-looking. They help answer:
- How did our paid search campaign perform?
- What was our conversion rate in Q1?
- Where did we lose share to the comp set?
Cogwheel Analytics consolidates fragmented data so hotel teams can spot trends across channels and benchmark against other hotels. But BI is only the starting point. It’s descriptive and backward-looking. Helpful for learning, but limited for decision-making.
2. Machine Learning & Prescriptive Analytics: What Will Likely Happen
Enter the realm of machine learning and prescriptive analytics. These tools are all about identifying patterns to forecast what’s likely to happen next.
In hospitality, that might look like:
- Forecasting what rate changes a hotel should make in RMS systems
- Understanding correlation of reviews on conversion rates
- Recommending media spend shifts based on historical gaps on the STR report
Machine learning thrives on structured data and repetition. It learns from past inputs to predict future behavior. The upside? You can define correlation, and help understand what did or did not work. The downside? It still relies on historical patterns—meaning it can become ineffective when market dynamics change (hello, 2020).
This is why commercial strategy alignment between sales, marketing and revenue to understand the full picture.. Think: not just “what tactics do I need to activate,” but “how successful were the tactics that I deployed.”
3. Generative AI & LLMs: What Should We Do?
Now we’re stepping into the future. Most everyone has used a Large Language Models (LLMs), even if they don’t know. Think ChatGPT, Perplexity, and Gemini that help move us from prediction to prescription. They don’t just look at data—they interpret it. These tools are capable of recommending actions based on thousands of inputs and scenarios, often in natural language.
But, it needs to be trained and given guardrails to reduce hallucinations. Taking the data the LLMs already know plus then feeding it both the historical BI data and the prescriptive data to understand how to interpret the data specific to our industry, the LLMs can make powerful analysis.
For hotel marketers and commercial teams, this means:
- Writing personalized email subject lines based on booking behavior
- Identifying shifting market trends and opportunities
- Recommending messaging shifts based on forecasted compression nights
In other words: LLMs help answer “What should we do?”
The value here isn’t just automation—it’s augmentation. LLMs can distill layers of data into strategic options. And when integrated with tools like Cogwheel Analytics, they can even propose next best actions for hotel marketers.
4. Agentic AI: Implementing it All
As AI evolves, agents will be built to execute on some of the basic, repetitive tasks.
While not meant to replace humans, it will streamline our daily duties and elevate how we spend our time..
Wrapping It Up: Strategy Over Software
Too often, hotels invest in tools without understanding their function in the bigger picture. Here’s the cheat sheet:
| Platform Type | Purpose | Role | Example Use in Hospitality |
| Business Intelligence (BI) | What happened | Descriptive | STR reports, attribution dashboards |
| Machine Learning | What will likely happen | Predictive | Rate Forecasting, Reviews Correlation, Suggesting media spend |
| LLMs / Generative AI | What should we do | Prescriptive | Content creation, market strategy recommendations |
You don’t need to chase the shiniest tool. But you do need to know what questions you’re trying to answer—and which technology best supports that level of insight.
Using all 3 in hotel marketing to help define and understand success, helps augment strategy and support data driven marketing.
Let’s make smarter hotel marketing decisions.