It's not what they do, its why they do it.

One of the biggest opportunities in customer experience is moving beyond understanding what people do to uncover why they do it. 

I once worked on a brand strategy project to grow a UK hotel business, and we knew that unlocking growth meant appealing more to the motivational drivers behind taking UK short breaks.

Through customer research, we segmented the UK short break market into motivations, for example:

• Exploring – city breaks, countryside escapes, coastal visits.

• Relaxing – spa, wellness, recharge time.

• Entertainment – whether that was daytime activities or buzzing nightlife.

This market research provided a strong framework of consumer motivations, but there was a problem. While the research provided fantastic insight into the market as a whole, it sat separate to the day-to-day reality of our marketing operation. We knew the key motivations driving people to take short breaks, but how did we use this knowledge to engage with our own customers?

Segmentation is only as powerful as your ability to execute on it. Without this, it risks remaining a glossy slide deck: great for strategy presentations, but disconnected from your operating model. We needed a way to tag all our customer bookings with a motivational driver.

That’s where the challenge lies: how do you translate broad motivational segments into something practical and dynamic inside a customer database, so it can guide marketing and shape experiences?

This is where data science came in. By building data dimensions from our qualitative and quantitative customer research, we were able to translate customer behaviours into motivations. For example:

• If a guest showed no transactional data during the day in the hotel, we could infer they were out exploring the local area.

• A shorter lead time to booking often signalled a guest looking for relaxation or a spa retreat.

• Higher spend on food and drinks, until late into the evening - these customers wanted to be entertained.

I admit to hugely simplifying the above, but the point is, by combining these dimensions, we could tag every customer booking with an underlying mission. Suddenly, we weren’t just looking at bookings, we were looking at customer intent.

This shift unlocked huge opportunities. We could:

• Talk to guests more effectively in our marketing communications

• Tailor operational experiences to their motivations

• Offer more relevant, personalised experiences during their stay

The result was a business not just reacting to customer behaviour, but anticipating it.

Data becomes far more powerful when you translate it into human terms. It’s not just about the “what”, it’s about uncovering the why. And when you understand your customer motivations, you can meet them with the right message, at the right moment, in the right way.