How hotel tech companies handle data today vs what is possible
How we help hotel tech companies drive sales and growth
Through our work we have found that very often we can help our clients not only by delivering high quality data, but by also helping them raise overall data awareness in their organizations.
Becoming data-driven, for all its buzz-worthiness of recent time, is most definitely a complex process, requiring transformation of teams and business processes alike.
A company's stakeholders have vastly different ideas about what is possible with good data. The first step towards a data-centric organization is to open their eyes to the possibilities.
In the context of hotel tech companies, let's look at scenarios with and without accurate hotel data.
Our perspective is based on observations we've made with clients as well as our own experience working with hotels.
How data is handled in many hotel tech companies today
Let's use as an example a random, general hotel tech company of today.
Pretty much every company out there will inevitably have an internal database of hotels that is cross-utilized by multiple teams.
This database will include their own clients but also hotels in the open market, and if there's not a data engineering team on-site data is usually kept in a standard CRM system.
The quality of the existing data in the company systems will depend on a lot of factors, such as the method and accuracy of acquisition, data hygiene over time, whether there is a dedicated data team in charge of database maintenance and many others.
The data in the company database will consist of internally generated and externally acquired data.
One way to think about it is that internal data is created and affected by the company's own activity and interactions with a specific hotel entity.
Usually this will be their existing customers who generate data on a daily basis. This can include platform or product usage, support interactions, customer success data etc.
A second common type of accounts are prospects they have engaged with sales and marketing activity.
A smart company will keep the entire user journey, pre and post-conversion, in the same database.
This enables them to analyze customer churn, identify brand ambassadors and excellence examples, and to improve success predictions all the way to the sales and marketing teams.
The externally acquired data is on the other hand data about the hotel market, new prospects in it, and provides as wide a view into the global market as possible.
Each hotel within this dataset has to be represented by as many data points as possible, in order for the database to be useful for driving insights and new ways of thinking. This data generally is not affected by the company's activity until they start to engage the entities in it.
In order for market data to be useful it needs to empower more teams than the internal one, in this industry anyway.
For most hotel technology companies, potential customers are strewn across the globe, especially as we enter the age of more personalization and highly targeted strategies.
Finding ten ideal-fit clients in a sea of millions is worth more to a growing company than a hundred sloppy ones that will drop off in six months. This is the way.
For the external data we at MetricsDriven have two more dimensions to consider when we collect and measure our datasets, that are quite specific to the hotel industry and hotel entities: Fast Data and Slow data (explained in detail below).
All of these types of data interact with each other, and have deep implications on how often they are collected, the business decisions that stem from them, and the insights they provide based on their changes over time.
This is the general hotel firmographic and technographic data, which changes relatively slowly over time (think about room counts, star counts or booking engines - hotels don't really add floors every day, do they?)
Slow data when seen in the context of millions of hotels is what enables incredible market segmentation, and when it does change, like branding or technology changes, it provides massive opportunities - if detected in a timely and accurate manner. This is *the* superpower our clients gain.
This is where things go into uncharted territory, and where we're pushing the boundaries of innovation.
Fast data represents the highly dynamic rates and channels data.
MetricsDriven has built a unique technology that can scrape the rates of any hotel worldwide in under 3 seconds, without any necessary interaction with the hotel itself, for all the OTAs selling the hotel - and this for every single day forward for whichever time period we pick.
We have proven, as the first ones in the industry, how fast this data really changes, through our separate product over on ratedefence.com.
You are welcome to jump over to Ratedefence, the home of the rate scraper, and play around with the demo hotels to see how it works.
This tech is highly early in the eyes in the industry but we're having a lot of fun identifying new patterns and opportunities for its use.
Teams making use of the hotel database in our theoretical company could be:
The effect of data-enablement usually spreads throughout a business like wildfire.
Here are the teams that usually benefit the most.
Business Intelligence
This is a fairly obvious one, data teams are usually our first line of contact anyway and tend to generate a wealth of new business value or translate the possibilities to the rest of the organization.
Predictive analytics can only work with large datasets like the ones we provide.
Product Development
They might look into how current and prospective clients use different technologies, including their own, to shape new products and product features. Enrichment of even their own customer's profiles can provide massive benefits in understanding possible new product features.
Sales and Marketing
These teams that probably gain the most from the new external data. Enhanced segmentation, targeting, and prospect profiling as resulting from a high-quality dataset bring an inevitable rise in conversions. Especially when the sales teams are properly trained to understand and use the incredibly rich hotel profiles provided to them.
Customer Success
They may get additional insights once the profiles of hotels who are already customers of the company are extended. Insights into why some hotels are more successful than others or more at risk than others can easily pop-up when you have an ability to segment them by many more factors than before.
New path with MetricsDriven as your data provider:
Let's look at how it would look when you work with us, supposing that your current status resembles as described above.
We would start (after the usual scope and project discovery) by building a clean, extensive dataset as per your needs and specifications.
This can be anything up to two+ million hotels - a global dataset. We source data from many sources, and coordinate with you on particular ones of interest. In addition we obsessively keep adding sources and extending the profiles in our datasets all the time.
This new or updated data would consist purely of what we called "external data" above.
It would be freshly acquired, relevant and as complete as possible, both in the scope of the entities and the breadth of their individual data points.
Now we would usually have two options to proceed:
01
The data can be merged into your existing database
Benefit: your teams keep the old interactions or history of the individual hotel entities.
Flaw: old data is more often than not just a detriment and a data debt that doesn't carry enough value to justify the amount of additional work required to effectively merge it.
For this option MetricsDriven provides a number of unique identifiers that should provide at least some ways to merge the data back into your system:
- OTA IDs (often over 30 if it's a developed hotel), accurate phone numbers, address, website, place IDs, GHA ID, or a combination there-of
We can deliver data in any variety of formats or via API.
CRMs tend to be inflexible in the number and type of fields that are possible and delivered, so a refactoring and re-evaluation is usually necessary.
Example:
What if your sales team could step into the conversation knowing the strengths and weaknesses of that hotel, who is the person answering guest reviews, whether that hotel has a tendency to attract business guests etc etc.
How would you show all this for them in your current CRM setup?
A fresh new instance of your CRM or database is initialized that will host the brand new data
This method effectively erases the data debt mentioned above, though the old instance can of course remain accessible for archival purposes and the two can coexist.
It gives the relevant teams, who depend on recent and accurate data the most, a fresh and unencumbered start.
It allows BI teams to extremely quickly re-segment the market and kick-start fresh new sales and marketing campaigns based on much better indicators than before.
02
MetricsDriven Tip:
We usually advise the second option, if at all possible.
For the simple reason that the new data will inevitably be vastly superior in hotel firmographic and technographic data, with the sole exception of hotel executive staff and possible historical interactions with them.
However given how insanely fast hotel staff changes positions, and how rare it is that companies track persons as they jump from hotel to hotel, a vast majority of this historical staff data is outdated within 6 months anyway.
In most cases if a company hasn't touched an account for 6 months their outreach is already a shot in the dark.
Starting with a fresh database of hotels effectively reboots the sales process with power-upgrades for anything but leads that were deep down the funnel already.
before
- Scenario: Your product works best for coastal boutique hotels with under 30 rooms and promises a large increase in direct revenue provided the ADR is over 300$ and not exposed to too much seasonality, and depends on the hotel already being digitally aware at the very least. Your sales team has to research geographically, then build profiles of hotel's sizes and character, then learn to recognize the tech value deployed by the hotel to approximate if they might be able to afford your product before even engaging them. They focus on a certain tourist area only to learn, after a lot of time wasted, that almost all hotels there are chains so the region doesn't make any sense. What little there are are highly seasonal and can't afford your product. The whole exercise was a waste of time.
- Scenario: A big OTA announces they're shutting down a free product. You have a product that acts as an entry level for your bigger suite of products and perfectly fits in to the market gap left by the discontinued one. Problem is - even if your Marketing team creates the offer they still need to target the hotels that were users of the OTA one. The OTA obviously won't give up the user list just like that. If only you could quickly find all the hotels using that web-facing product faster than everyone else and pitch your offer, enriched by more insights that make the offer more valuable.
- Scenario: Covid killed one of your competitors, which is now for sale. In the meantime their support is non-existent and their users are angry. You could easily scoop up those users, if only you could identify them, and they are all around the world. There are 5 data points clearly identifying their users. If only you had a global dataset with hundreds of data points per hotel, those 5 included, to create this segment.
after
- Scenario: Find all hotels in the dataset that are between 50-100 rooms in North America, that have 4+ stars, ADR of min 200$, use more than three distribution channels and use one of 10 preferred booking engine partners of your company. BI analyzes the segment, finds patterns in the data, passes these over to Sales and Marketing who create a multi-touch strategy based on it and launch it together. Target accounts receive messaging and outreach that is scoped to them, conversion rate skyrockets.
Congrats, your sales and marketing finally work together.
- Scenario: Enterprise accounts - find all hotels belonging to a hotel group, their contacts, location, reputation, size, distribution strategy, technographics and optional deep competitive research provided by us. Evaluate if groups are worth engaging, evaluate their business performance, identify entry points and engage enterprise accounts through ABM strategy.
Congrats, you've just saved months of engagement.
- Scenario: Sales reports an increase of complaints from customers of a certain competitor that mainly operates in three European countries, with hotels under 50 rooms, and most commonly partners with five booking engine providers. Speed is of the essence, because your company can offer better terms and convert these accounts easily, even open new partnerships with the booking engines to preserve their own reputation. How do you find the hotels? Easy, in our dataset you find the hotels of the appropriate size, and if we need to re-scrape the countries to find exactly those 5 booking engines in that segment to make sure the data is 100% fresh - we arrange and it do it fast. Sales and Marketing in the meantime coordinate to create messaging for this exact segment for the campaign. Booking engines see your success and happy customers, decide to support your partnership.
Congrats, you've pretty much cracked that market in one swoop.
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tl;dr version of how you win with our help:
Time-Saving
Gathering data on hotels is usually a time and money-consuming process, but with our datasets, you'll have one process and one team building your pipelines, providing consistent results.
Cost-Effective
With our data services, you can save both time and money by eliminating the need to hire researchers or buy multiple sources of information.
Accurate and up-to-date
We take great care to ensure that the data in our datasets is accurate and up-to-date. You can trust that you're getting the most accurate and relevant information available.
Comprehensive
Our datasets contain a wealth of information on hotels, providing a complete picture of each entity. You will be able to make better business decisions through this process, better segment your markets, find those elusive ideal customers, and drive innovation within your organization.
Adaptable
We offer customized datasets to fit your specific needs. Your datasets can be tailored according to your goals based on the data points most relevant to your business.
Global Coverage
Data comes from a wide range of sources and covers hotels on a global scale. This allows you to get a complete picture of the market and identify opportunities across the world.
Highest quality
Our data is carefully curated to ensure its accuracy and relevance. We use strict quality control measures to ensure that our datasets provide the most reliable and comprehensive information available.
MetricsDriven is a data services provider out of London, UK.
We're forged from a unique combination of coding, marketing, scientific and technology backgrounds.
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