Personal information is collected every time we use a loyalty card, shop online, click on a news of sports article or sign up to an online service, with the information around our preferences, choices and consumer habits all collected by myriad of companies.

There is no doubt this intelligence is highly valuable to companies - valuable to those wishing to sell us goods and services, valuable to those looking to predict our future transactions or valuable to those wanting to personalise experiences for us, based on the things we like most, while not bothering us with products or services we have no or little interest in.

The ideal is that in a time-poor world, we become more efficient.  Choices are easier and satisfaction guaranteed.  That's the ideal.  But, we still have a little way to go and there are times when data mismatches occur, or predictive advertising can feel a little creepy or simply wrong.

There are examples where online recommendations can fail us, for example one technology colleague often buys books on business strategy and computer science on Amazon.com.  Amazon is not only famous for being the company owned by the world's richest man (Jeff Bezos), but for also being one of the first websites to use a sophisticated recommendation engine to predict future products you may like.

The issue is that one day my friend bought Harry Potter books for his nephew and quickly found that Amazon recommendations started treating him like a Harry Potter enthusiast, even thought he has little interest in the subject.

Personally, I know that when I've been searching for a flight, a pair of running shoes, or present for the children, everywhere I click, up pops an ad showing me that the very item I had been searching for and it seems to be following me across the web.

What can be equally as frustrating, is after you have actually bought the item online, the same ad continues to follow your online surfing.  I'd like to believe that if the data is clever enough to know what you like, it should be clever enough to know when I have bought it, and then offer me something complementary.  So, if I buy running shoes, maybe suggest some socks or a nearby running festival I could be part of.

That's attribution where modelling comes in, where and how do you attribute that sales to in a fragmented world that sits between physical and the digital stores.  To be at its most effective, you need to link online search and social, with outdoor advertising, radio, print and TV, and with point-of-sale purchase, regardless if you buy online or in-store (the holy grail of commerce).

There is plenty of talk about the "ultimate personalised experience", but if you ask the average customer what that meat, they'd probably say its face-to-face contact with someone who greets me, ask me enough questions to know what I want, show me options (including things similar, but different to what I was originally thinking), give me a discount, and sign me up for more offers.  Pretty simple.

The world's leading Customer Relationship Management (CRM) software provider, Salesforce describes it thus: "Personalisation is about customers being recognised as individuals and treated in a way that makes them feel appreciated, unique and understood.  The challenge for most retail businesses is replicating this kind of approach consistently and at scale across the mix of clicks and bricks channels."

Earlier this year, a Digital Summit survey for Shop.org revealed 46 per cent of marketers do not personalise email copy, and 49 per cent described their marketing efforts as "one-size-fits-all", with many blaming data sources as the main culprit stopping personalisation.

The big advantage we have in clubs, is that we are member-based and have the ability to personalise customer experiences in-venue and keep that communication going online and via mobile.  Some in clubland already know this well and are exploring opportunities to personalise member experiences.

While we're not quite there yet, one thing digital history tells us is that the technology will continue to improve at a rate of knots, getting better quickly until it integrates seamlessly into everyday life.

Think of Uber and what a foreign experience it used to be to find a stranger on an app to drive us from A to B in their own car.  It rapidly became a creditable alternative to the taxi, but more importantly included features we now expect as every day, such as car tracking and instant credit card payments without even presenting a card, taking all the friction out of the established cab ride.

So, what does the future hold in a predictive data-led consumer world?

It all comes back to the ability to capture information in an accurate and timely manner, then importantly providing a better service back to customers.  Maybe that's a better price, maybe it's more choice, it can even be a product or service which others have rated highly and you trust their judgement.  In modern business, this information intelligence isn't a debatable, it's a must-have and thankfully the club industry has started taking the right steps to put personalisation front and centre of the data conversation.

(SOURCE: David McGrath, ClubsNSW Chief Digital Officer, ClubLIFE June 2018)