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Make it Personal

User personalisation for your Destination website. Without breaking the bank!

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Written by:

Will Wright, Managing Partner at DestinationCore

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Imagine a website where the entire content was completely personalised to your specific tastes, requirements, interests and budget. Where you could see not only the things that interest you now, but also accurately predict and adapt to changes in personal circumstances as well as make unerringly precise recommendations about things you might also like, but had not yet considered – allowing you to uncover content that would otherwise be hidden to you. Does this sound like website utopia? If so, I’d encourage you to think again.

As marketeers, complete personalisation of website content in the way described above is generally considered the holy grail – but of course it can’t be achieved without the collection of considerable amounts of personal data – including preference, behavioural and transactional. And it’s no good just collecting the data. You have to cross reference the various data sources to draw out the rich personalised insights required to truly enhance the user experience and benefit your business too. Sounds expensive though…and normally, it is.

But fret not destination marketeers, there is a way to achieve what I’ve just described – and you could argue that it actually provides a better overall user experience too.

The trouble with all this big data stuff is that if you don’t get it right, you’re left in a position that actually damages the user experience rather than enhances it, having a negative impact on the user behaviour and your brand. So instead of encouraging users to take the actions which will benefit both you and them, you’ll actually drive them into the hands of a competitor. For example, imagine making a recommendation to visit an attraction or event, based on assumed data that was both out of date and inaccurate - we humans have a tendency to change our minds after all, constantly refining our tastes, preferences and behaviours on a regular basis – you’d be right in thinking this kind of mistake would drive users away, rather than attract them to your destination.

Avoid risky assumptions

So, instead of making risky assumptions based on the (often incomplete, or inaccurate) data you do hold, try a different approach, one that does not involve any legacy data at all, one that could actually engage users on a far deeper level. An approach that answers a deep-seated social need for human interaction.

Ask a question…and wait for a response. And most importantly of all..listen.


Now I’m not talking about chatbots (although if implemented correctly those can be effective user engagement tools too), I’m talking about something much more ‘basic’ and cost-effective to implement.

At DestinationCore we refer to these tools as ‘Decision-Trees Filters’, and they offer the kind of tried and trusted functionality that has been in existence for many years (sounding low risk so far? Good. It should). If implemented correctly they offer the user a sense of personalisation and discovery that was mentioned at the beginning of this article – but in a way that feels more natural and ‘human’.

Mainly because it’s a two-way exchange. Which feels like genuine communication, rather than creepy stalking.

If you’re not familiar with the term decision-tree below are some links to websites that use this type of functionality really well.

Miami and Beaches. - scroll down the home page to the Personalise Your Experience’ section. Whilst the execution of this is quite elaborate the level of personalising offered is superb.

i-escape. - very simple to use. One-click and you’re away. Straight into recommendations that match your desired experience. You can deepen the experience by using the filters available on the right-hand side of your results page to drill down further into location, date, budget etc.

Open table. - click on the ‘Find your restaurant matches’ button near the Need Some Inspiration message about halfway down the home page. Easy to use eight-step filter which feels like you've walked through the process of finding the perfect table for you.

So why are decision-trees and filters better than data driven personalisation?

First of all, they put the user in charge – meaning you don’t have to try and figure out what kind of mood they are in, they’ll tell you. Today they want to eat Chinese, next week might be Indian – no guessing. It’s much more empowering for the user. Change in circumstance – no problem. The user has been given a promotion at work and now has a slightly bigger budget. That’s okay, decision trees mean the user can self-select the budget, according to personal circumstance, or even how close to payday it is.

It gets even better, Discovery is in-built – when a decision-tree or filter is well designed it makes it easy for the user to find out what happens to the results if they change one of the answers, you can even add some ‘you might also like’ functionality to the results when they are displayed to add to the sense of discovery.

And the best bit of all – if well designed and fun decision-tree filtering is much more engaging. It will keep the user coming back for more. And we all want engaged users – that’s ultimately the holy grail. Who knows you may even create some brand advocates, those users who tell their friends, who then tell their friends, who then tell their friends…you get the picture.

So, forget personalisation, think user experience.


How does this sound to you? Do you think it’s better than a ‘passive, but pretending to be personalised to your needs based on the data we hold about you’ approach? Which, of course, may or may not be accurate? It does? Great! Destination marketeers jump on board.

To find out more about DestinationCore’s ‘Content Finders’ – our very own decision-tree style modules take a look at our Module Marketplace.

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Want to know more about DestinationCore? Call, email or fill in the form.

Will Wright | Managing Partner

Tel: 0203 780 7187

Jane Petrucci | Customer Relationship Manager

Tel: 0203 780 7187

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