47 ways to make big data work for your hotel

the hotel internet booking engine is dying 2017

Why stop at 47? An overdose of big data and its immense possibilities I suspect! I had to stop and take a break, but in no doubt more ideas will get added over time 🙂

On this page, you will find a comprehensive list of ideas and examples of how to use data better to maximise revenue and guest service at your hotel. While some require complex technology and therefore can be expensive, others require curiosity and an analytical approach to get started.

Before you get started though, it’s important to ensure that you have covered the basics!

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? 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, booking patterns
  • Distribution channels – information like channel 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. 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… it is equally important then to understand the data management process

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, Central Reservations (CRS) systems 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.

Data would be extracted from the PMS, Central Reservations (CRS) systems 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 & customer loyalty, price & 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% 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.”

The BIG list of big data ideas for your hotel

So 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, you will find below some specific ideas and inspiration to get you going!

While the temptation was great to try and sort these ideas into neat little sections under sales, marketing, pricing, yield etc, the very fluid nature of data and its impact on the customer prevents it. The convenient silo approach must give way to a more holistic (as much as I dislike the rather overused word) route to making use of information.

So, here they are, in no particular order, but each one important and powerful in its own way.

  1. Use big data to initiate timely hotel marketing campaigns based on weather, airline and web-shopping data
  2. Use big data to micro-segment customers at your hotel for maximum impact
  3. How big data can make in-hotel marketing opportunities more effective
  4. Improve hotel guest recognition and experience during stay with big data
  5. Improve e-mail targeting with moment of open personalisation using big data
  6. Use big data to prioritise customers based on their history in real time
  7. Apply big data to market your hotel at the right time with location-based marketing & geo-fencing
  8. Use big data to do more with hotel website visitors, cookies and retargeting
  9. How to better use website conversion rate for your hotel
  10. Best ways to analyse and segment hotel website abandonment rate
  11. Big data and its role in wearable technology and personalisation at your hotel
  12. What can text analytics of customer reviews tell about your hotel?
  13. How big data can help with even more dynamic pricing for your hotel based on customer profile
  14. Manage hotel availability based on local events
  15. Judge the impact of rate changes at your hotel before you do it
  16. Monitor and analyse channel profitability data and productivity for your hotel
  17. Analysing reservation call metrics at your hotel
  18. Big data and its impact on tradeshow participation and ROI for your hotel
  19. Study social media for insights into your market
  20. Use social media as a diagnostic to figure out problems with initiatives and programmes of your hotel marketing
  21. What can you learn from Point of Sale (POS) Data at your hotel restaurant?
  22. How can big data help with hotel guest sentiment analysis?
  23. Use big data to identify patterns in hotel guest activity
  24. Connect other loyalty programmes with your hotel’s (or with rate offers)
  25. Use big data to develop an in-depth understanding of your hotel competitor
  26. Use big data to identify outliers and target them in marketing efforts
  27. Combine key data available for a certain time slot
  28. Big data can improve security at your hotel
  29. Big data and the future of interactive personal assistants, chat bots and robots at your hotel
  30. Use big data to help match skill sets of hotel employees better with guest needs
  31. Big data can help identify training needs and recommend content and schedule
  32. Develop new products and services for your hotel with big data
  33. Digital marketing – the science of marketing (no longer the art)
  34. Use big data for better operational readiness against marketing campaigns
  35. Role of big data in identifying new hotel trends (like day use rooms)
  36. Finding more value for hotel corporate clients/bookers using big data
  37. How big data can help incorporate more valuable and relevant information into group proposals
  38. Improve internal communication using messenger apps and bots
  39. Maximise the impact of hotel sales and account management with big data
  40. Big data and its impact on online distribution for hotels
  41. How hotels can upsell at more touch points with big data
  42. Big data can help your hotel hire better and faster
  43. Achieve better expense management at your hotel with big data
  44. How to improve inventory management at your hotel with big data
  45. Reduce hotel energy bills with big data
  46. Achieve better on-time hotel maintenance with big data
  47. Use big data to reduce employee turnover

Have more ideas and suggestions? Post a comment below to keep the conversation going!

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Tags: Big data, Distribution strategy

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