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How Hoteliers Can Get Started With Data To Win The Online Battle For Customers

JodyP 6 September 2019
How Hoteliers Can Get Started With Data To Win The Online Battle For Customers

Richard Wheaton, UK MD of Fifty-Five, a data company that works with hotel brands like Hilton to improve their digital performance.  Fifty-five London is one of only a handful of Google approved recommended data partners

Smart use of digital data is one of the key tools that digitally advanced brands use today to get ahead of the pack. Here we bring to life how some of the techniques can be used by hoteliers, with practical examples and pointers to get you started.

The first point to make is that when guests search for a hotel room, they leave a trail of signals throughout the process. As they view media and visit your website, you can gather data to tell you a lot about them. For example, you can identify whether the visitor is loyal to your hotel or chain, or whether they are a new prospect. Whether they are part of a family, a romantic couple, or a business traveller. Whether their interest is in spa, tennis or other facilities. Or whether their focus is purely on price… All of these signals are used by today’s smart hotel companies to profile the prospective guest and shape the next message to help close the deal, whether by tailoring the next webpage the guest sees, or sending them a targeted email, or targeting them with a specific offer on their Instagram feed.

Let’s review some of the data collection techniques and give practical examples and tips to hopefully inspire you to investigate the possibilities and start leveraging data to improve your online performance.

Using data to find customers most likely to book:

For travel, a deep level of consideration in the purchase process is standard for most customers. Some people visiting your website are just browsing, and do not intend to book soon. The proportion of such browsers will vary, but we might say that 10% of your visitors are about to book in the next seven days, these are people who we identify as red-hot prospects, in-market for an imminent hotel booking. How can we identify them, and how can we make smart investments to get them to book at our hotel instead of someone else’s?

As set out above, savvy online travel brands use the data signals that the browser leaves during that person’s one or many visits.  Their websites and apps are tagged to collect this information – which might include the source of the visit or the keywords used by the guest to find the website – and it is processed using data science to cluster certain patterns of customer behaviour and build these as key data segments in the web analytics tools, such as Google Analytics or Adobe Analytics.

Once the segments are established in the analytics tools, they can easily be integrated into your marketing implementation tools – for example, paid and social advertising, CRM, and website personalisation – for accurate targeting of the appropriate offer, message or prompt.

Targeting people who have abandoned their shopping basket:

No hotelier likes an abandoned basket, but intelligent responses to bookers who have filled and abandoned their booking form is an easy win. It is a common behaviour of the hotel shopper to fill in a booking form to check prices and details before deciding. This browsing behaviour identifies prospects who are clearly very like to make a purchase in the near future, so travel brands build bespoke programmes to use this with lead-scoring signal data to try to win the sale.

This abandoned basket targeting data can be used by the hotelier to send emails, place banner ads on Facebook or Instagram, or adjust their search bidding strategy to lure back this hot prospect.

Making smarter decisions on how to plan your marketing spend:

Due to the time-sensitive nature of travel booking, travel brands tend to get sucked into regarding the last ad the customer saw or clicked on as the one and only cause of the booking. This is a seductive and clearly flawed analysis, because we all know that guests’ decisions are not based on viewing one ad, or making one search. We call this adjusted reporting ‘Attribution analysis’ because we use data to, literally, re-attribute value to the digital channels that really drove the conversion based on a large scale data-driven analysis of the thousands of ads and content views along the guest’s journey toward the final buying process.

Many travel companies today use DDA (data-driven attribution) programmes to help them ‘attribute’ value more accurately, and hence better allocate budgets towards some of the earlier touch points in the customer journey. In this way they can make sure they maintain investments for filling the upper funnel of the prospecting pool with new recruits, rather than just mining the bottom of the funnel for guests, especially customers at the lower end of the funnel who have probably already decided to book at your hotel anyway!

Data for faster and better reporting and planning:

For national and international hotel chains, the processes for collecting performance data and apportioning value and insight to decisions is important and time-consuming. Often the process of collecting past data is so onerous on marketing and IT teams that it leaves no time for proper planning for the months to come.

Global reporting platforms can now be built to automate the collection of online and commercial data for standardised reporting across cities, countries and regions for better roll-up reporting, for investment and cost allocation purposes. These can be large-scale programmes of development because the digital process impacts people across commercial, ecommerce, marketing and advertising teams. But the results can be spectacular: we have recently implemented such a platform for a global hotel chain, including over 550 hotels, reducing their reporting time from two months to minutes, and reducing the risk of human error.

We hope that these examples have given some ideas and encouragement into how data can help you compete for bookings in a market that is increasingly driven by online searches.