Five steps in your data journey

It’s tempting to believe that out there, other companies are doing a much better job of managing data. I have some news for you, they’re not. Just like teenagers who believe they’re the only ones home on a Saturday night, most organisations suffer from data FOMO.

How do I know this? From experience. Right now, I’m working for Loyalty NZ which owns Flybuys, New Zealand’s largest loyalty scheme. We have a data set going back 24 years with 1.7 million households. So we have a deep understanding of our members – and how we can help Kiwi businesses reach them.

But in my experience this depth of data is extremely rare. Prior to Flybuys I was with Nike, who you’d think could lead a masterclass in customer-led innovation. As product designers, yes it can. Nike knows how to make shoes the world wants.

But while we knew a lot about the product being sold, we didn’t know who was buying it, why they liked it and what else they would want to know, try or buy. We had no visibility of our customers in brick-and-mortar stores and 75 percent of online sales were signed on as guests. Sound familiar?

We did, in the end, create an amazing data-led change which has become the much celebrated Nike House of Innovation, with flagship stores in Paris, Shanghai and New York. But we did it off a tiny amount of data and on crazy small budgets. Looking back, I can see five important steps that we took to sweat that data and build a successful outcome. If we did this with such slim pickings, you can too.

1. First, get to know your customers.

Somewhere, someone is collecting data about your customers. Find it and mine it. It could be sales data, surveys, feedback forms, Google Analytics – it doesn’t matter how small, this is your foundation. At Nike we had the personal details of 25 percent of our online shoppers and just the delivery addresses of the rest. I don’t have space to explain how we did it but that was enough to make some assumptions, launch a pilot programme in one store, and build on our ideas. It’s an amazing innovation (read a case study about it here) but the point is that any customer-focussed innovation starts with knowing your customer. Make that your mission.

• Have something to say

Data can help identify customers and their needs but it can’t design your offer. You need to know what value your business plays in their lives – and not in business-speak but in the language of your customer. Have you ever tried to sell your business’ products through a call centre or at a trade fair? The brutality of that kind of environment forces you to sharpen your act, right?

The same goes with marketing and advertising messages. If the message doesn’t work at a scale of one, then amplifying it in media just makes it a million times worse. Data can help personalise and amplify but it’s no substitute for a great value proposition.

• Become machine literate

Okay, so you know your customers and you have something to say, now it’s time to get smart. You’ve probably noticed how access to cloud-computing has changed things. But the scale and the speed of the change can still catch us by surprise. I’ll give you an example. In China, Singles Day (November 11) generated a massive US$ 38 billion in sales, up 26 percent on the previous year. That’s the size of New Zealand’s entire Covid recovery package – in one day. You’d think it would take a nation of back-office staff to handle those transactions. In fact, it took computers just one minute and 18 seconds to process $ 1 billion of them. Alipay was handling 256,000 transactions per second.

We’re not wired for exponential growth, but machines are. And the machines are getting very smart indeed. Are you aware of what’s available to you as a marketer? The tool set that can power your data is quite incredible.

• Pick a problem not a technology

That said, technology is the not the solution to your problems. So often technology and the software vendors can become the tail that wags the dog.

At the heart of your data journey is a set of business problems: who are our customers, what do they want, how often, where and at what price? And what else do they like or hate or want us to solve but never thought to tell us? How do we get intimate and close, without being creepy or costing the Earth?

A problem like customer intimacy is screaming out for data and processing power. None of us have sufficient resources to offer the level of customer service we’d like. But machines never get tired or get angry. With the right data and respectful settings, bots and AI can provide much needed alternatives for busy frontline staff.

Similarly with customisation. We love it when our local barista knows our coffee order. Machines can remember much more. Amazon and others have shown how customisation, based on permission, can provide extraordinary levels of personalisation and up-selling.

You may not be Amazon or Alibaba, but thanks to cloud computing both technologies are fairly inexpensive and easy to deploy – no matter the size of your business. And if you don’t, rest assured that your competitor will.

• Finally, don’t be evil

With power comes responsibility. Collecting data and harnessing the power of  machines means so many things are possible. But just because you can, doesn’t mean you should. Our industry is built on trust. That what brands are: trust marks. Permission and security are the hallmarks of good data-driven marketers.

So be a permissions champion and develop a set of principles about how you harvest and use data. Don’t call them laws – because circumstances change. Principles can include:

• Who can access it, share it and how we decide
• How long we keep it
• What we will use it for (and what we won’t)
• What we will collect (and why)
• What decisions we will make with it and how we will use it to make them.

It’s possible to feel overwhelmed by the impact data on business. The name Big Data is designed to frighten. So don’t think of it as big. Think of it as a piles of little data that needs tidying up. And whatever you do, don’t think that all the others have got it sorted. Everyone’s just as messy. No one’s out partying, I promise.

Brian Ferris is Chief Data and Analytics Officer at Loyalty New Zealand. Email him at brian.ferris@loyalty.co.nz to discover how you can partner with Flybuys for your next campaign.

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