The whole conversation around big data is exhausting. The possibilities are endless. But here we are, every day, worried that we are sitting on a mountain of data but doing very little with it. But is it paralysis caused by these overwhelming possibilities? Or do you just think big data is best left to big hotels and chains? But then are even the big chains doing much with it?
Big data is best worked on in little chunks – and if you have a clear understanding of what your hotel objectives are, you may just discover that big data is not the beast it is made out to be, so if you are wondering where to get started, here is a basic plan.
Establish clear objectives for data management – set a data management strategy.
Ensure that you have clear answers to.
Why is it important to our hotel/s?
What can it improve in terms of guest service?
What are the different ways in which it will increase hotel revenue?
How can it help reduce costs?
Can we afford not to do this?
Identify all sources of data in your hotel.
Start by looking at and identifying as many data sources as possible.
Where is your guest data and where is it being captured? Is it just in the Property Management Systems (PMS) like Opera? Is it in your Central Reservations Systems (CRS)? Or also in the Customer Relationship Management (CRM) system like Salesforce? Or do you need to look elsewhere?
Traditionally, guest data typically covered name, contact details and high-level demographic information. But we now have so much more information available from a far wider range of sources. Let us take a closer look as to what some of them could be.
In the data world, all data is classified into first party data (typically gathered directly from hotel guests) – from CRM’s, PMS’s, website sign-ups etc., second-party data (typically gathered from partnerships) – with airlines, credit card companies and third-party data (purchased data).
Listed below are some possibilities – where you look for data should depend on your overall objectives.
Website – subscriber lists, cookies and booking patterns.
Distribution channels – information like channel delivery and profitability.
Social media channels – followers, competition participants, evangelists, bookers.
Restaurant Point of Sale (POS) systems – spending patterns of guests staying in the hotel as well as from non-residents.
Restaurant diners – collecting business cards or similar information through competitions.
Events at hotel – events where individual participation is needed.
Tradeshows – visitors at the stand at a travel trade fair like ITB or Confex.
Spa – information on guests usage from both residents and non-residents.
Sales teams – from account management activities.
Reservation teams – from all enquiries, individual and groups, with call centre logs.
Wi-Fi – from free Wi-Fi access to visitors using the dining areas in exchange for an e-mail address.
Reception – check-in and check-out data.
Concierge – typical local reservations made before arrival and after arrival.
External data – data that has been purchased from external sources for marketing campaigns.
Partnerships – Official partnerships and joint promotions with industry partners eg: an airline can yield
additional customer data.
And the list can go on – from here, it is equally important then to broadly understand the data management process.
Understand the data management process
Traditionally it looked something like this. Data would be extracted from the PMS, CRS and CRM into a centralised database, referred to as a data warehouse. It is here that the data would be collated, filtered, deduped and segmented before being shared with the business owners and managers in a usable/understandable format. In many instances, there was a lot of human intervention to get usable data output. It was mostly reactive.
I remember the days not so long ago where data would be manually extracted from hundreds of PMS’s and entered into a Cognos data warehouse and subsequently matched with sales accounts from Salesforce CRM to understand revenue generated from major accounts. But today a large part of this can be assembled, segmented, analysed and applied pro-actively without human intervention. And the example above is just a fraction of what has changed.
Despite all changes, it is important to establish the relevant data and what happens to it and when by linking it to the overall data strategy answering questions like, “Why am I doing this exercise?”
Companies and solutions in hospitality data management
The hotel data analytics space has big corporations like IBM and Accenture as well as well as small specialised players. Here are a few to give you a flavour!
Snapshot: One of the newest entrants. “SnapShot Analytics is made for hotels of any size, from single hotels to large chains, to make the most of their hotel data.”
SAS: “The SAS hospitality analytics solution helps hoteliers in marketing and customer loyalty, price and revenue management, data management, operations analytics, digital marketing and more.”
Triometric: “XML analytics solutions help hoteliers meet revenue challenges such as getting the best price for available inventory (before the sell-by-date), optimising the channel mix to focus on those delivering the highest returns, understanding where bookings are coming from, at what cost and how they can be influenced.”
Neubrain: “Neubrain’s Business Analytics for Hospitality solution combines the entire Profit and Loss (P&L) planning and Sales and Operations planning (S&OP) processes into one integrated framework.”
Duetto: Another relatively new entrant primarily focused on revenue and yield. “Duetto Edge delivers powerful insights on pricing and demand through a 100 per cent cloud-based application.”
Guestware: “Guestware® CRM Software helps you optimise workflow and operations to create a proactive and responsive environment for delivering exceptional hotel guest service every time.”
nSight for Travel: “Hotel nSight is a Saas-based intelligence application gives you power you’ve never had before. We leverage 30+ billion data points from online travel consumers to help hotels make smarter revenue and marketing decisions.”
Big data ideas for your hotel
Once you have set the data management objectives, identified sources of data, have a fair understanding of the high-level process and the tools that can help, here are some possibilities that open up with having the right access to your big data.
Your hotel can use big data to:
Generate timely hotel marketing campaigns based on weather, airline and web-shopping data.
Micro-segment customers at your hotel for maximum impact.
Make in-hotel marketing opportunities more effective.
Improve hotel guest recognition and experience during stay.
Improve e-mail targeting with moment of open personalisation.
Market your hotel at the right time with location-based marketing and geo-fencing.
Do more with hotel website visitors, cookies and retargeting.
Trial wearable technology and personalisation at your hotel.
Do text analytics of customer reviews.
Even more dynamic pricing for your hotel based on customer profile.
Learn from Point of Sale (POS) Data at your hotel restaurant/s to maximise profitability.
Manage hotel availability based on local events.
Judge the impact of rate changes at your hotel before you do it.
Monitor and analyse channel profitability data and productivity for your hotel.
Analysing reservation call metrics at your hotel.
Use social media as a diagnostic to figure out problems with initiatives and programmes of your hotel marketing.
Help match skill sets of hotel employees better with guest needs.
Incorporate more valuable and relevant information into group proposals.
Personalised upsell at more guest touch points.
How to improve inventory management at your hotel.
Reduce hotel energy bills.