Spark executive Matt Bain shares how New Zealand’s biggest telco and digital services provider is handling the complex topic of data collection | Content partnership
When I talk to people about data, most of them understand that every time we download an app, order an Uber, scroll through social media, GPS the fastest way home, or simply search online, we leave a data trail behind.
And research tells us that typically, people don’t mind sharing their data - so long as there is a mutual benefit.
The reality is our data is out there and it’s helping us in a thousand different ways. Yes, if it isn’t managed or used correctly it can be annoying or even harmful. But the truth is that good, bad or irritating, our lives run on it. So, the issue for New Zealand companies is how can we ensure we’re keeping our customers’ data safe, improving business outcomes, while at the same time benefiting the end user?
First, I think the conversation needs to become more nuanced. A lot of what we hear and read about data collection is binary: companies love it, customers hate it. That narrative is promoted by organisations building their brand on the idea that the practice of collecting data is mostly creepy and should be feared. And of course, then there are companies which have shown the world what happens when their customers' data isn’t used responsibly.
However, as is usually the case with binary arguments, there is a middle ground worth considering. A world where businesses and individuals have an equitable data exchange – where both parties get value out of the way data is used, and where the individual has a choice around what happens to their data.
Every great relationship has to be founded on trust, and mutual benefit and, as the Harvard Business Review article (above) concludes, the customer and business relationship around data collection is no different.
Rethinking advertising to be a service
Just over three years ago, as the new marketing director for Spark, Aotearoa’s largest telecommunications and digital services provider, I realised just how many data touchpoints we have with our customers across our operations. Also, just how hard we have to work to ensure our systems and platforms are equipped to manage this data in a way that helps us serve our customers better.
A few years ago, we were limited to a view of line numbers and connections - meaning we knew we had a certain number of mobile, landline and broadband customers, but we didn’t have a clear understanding of a customer and the various services they purchased from us. This limited our ability to serve our customers.
We now have a more complete understanding of our customers – the ability to recognise all the products and services they purchase from us in one place, for example, enabling us to be more responsive to their needs – or at least that’s our intention.
For example, if a customer calls us because they are experiencing a broadband fault, and we can see they’re also a mobile customer, then we can apply extra mobile data to keep them connected through their hot spot while the fault is repaired. Or, if we can see that there are multiple Spark customers in one household, and they all love gaming, then when we launch 5G in their area we can proactively offer them a plan better suited to their lifestyle - and throw in a deal through our partnership with Xbox.
We work from the premise that understanding our customers’ preferences allows us to better serve them – and that is a net positive for the customer and the business. In telco, as an example, only 1-2 percent of New Zealanders are in the market for our services at any one time – so it is much more efficient for us to advertise directly to those people through our app, email, or a targeted advertisement than the traditional approach – advertising to every single New Zealander through a mass national advertising campaign.
We would argue this doesn’t just save the business dollars by better targeting marketing spend, but also gives customers information that is more likely to be relevant and useful.
I know receiving targeted advertising probably doesn’t get your adrenaline pumping. But it can drastically reduce the noise, and when done right it can even feel like a service – especially when the combination of data and technologies like Artificial intelligence (AI) enable an organisation to understand and predict what people want and when more accurately.
Imagine you’ve got an old iPhone that’s started to slow down, the battery runs out after an hour, and you can’t take any more pictures because storage is maxed out. You’ve been intending to upgrade but with work and the kids you haven’t had a chance to go out and find a suitable option.
Rather than continually bombarding you with information about every service we offer, wouldn’t it be far more beneficial if we got in touch with a tailored offer when you needed that upgrade – saving you time and money? With good customer insights and AI, this kind of ‘advertising as a service’ could become fully automated.
And hey, because we know you love music, we could recommend a mobile plan that includes Spotify, and throw in 200 Airpoints so you can fly up and see The Backstreet Boys live at Spark Arena.
Build a better future with data
The benefits of data extend far beyond targeted advertising. At Spark we are using data to improve diversity and inclusion in our business.
We have around 5,000 employees nationwide and we want our organisation to reflect the ethnic diversity of Aotearoa and be a place where every person feels able to bring their whole self to work.
But to do that we need to understand the ethnic make-up of our business, so we can target interventions in the right way and, importantly, co-create those solutions with our people. So, data must be our starting point.
Like most other businesses in New Zealand, we have a limited view of the ethnic diversity in our workforce – with a low percentage of people sharing this information with us.
We know there are a range of reasons why people choose not to share their ethnicity - and that’s okay. But for many people, knowing how the information will (and won’t) be used is a major factor.
So, through an internal campaign called Whole Hearted, we are encouraging our people to tell us more about themselves and most importantly, explaining how their ethnicity data helps us to improve inclusion, and outlining exactly how we will use it. We only launched the campaign in November and data capture has already increased 12 percentage points.
The use of “data for good” also extends beyond individuals and can have massive benefits on society more broadly. As one example, our subsidiary Qrious has been working with MAUI63 to use data to protect the rarest species of dolphin in the world – the Māui dolphin.
The MAUI63 team need to know the precise location of these dolphins, but also where they are likely to go in the future. The way this was done historically was through a large drone that would fly across thousands of square kilometers of ocean to identify Māui dolphins and follow them.
Today, based on data collected from historical sightings and the application of AI, the drone can follow a heat map of probability – dramatically increasing its ability to locate and change course to follow the Māui dolphins.
Data Innovation = Privacy Innovation
Data presents huge opportunities for both businesses and their customers, but a more sophisticated use of data brings with it responsibility and a requirement for a more sophisticated approach to privacy.
Ten years ago, when it came to marketing, privacy was all about customer lists, marketing opt-outs and competition T&Cs.
Today, in an increasingly digital world, Spark is managing more information than ever before and opportunities for how we might innovate with data are growing too. At the same time, our customers have very wide ranging views about how they expect us to use and manage their data. All of this brings with it new challenges for how we make decisions around data usage.
At Spark, we don’t want to just be compliant with privacy laws and regulations, we want our customers to think of us as a brand they’d most trust with their data.
Last year we introduced a set of actionable values, endorsed by all members of the executive team, to set out what we stand for in privacy and provide clear guidance to our people when they are making decisions, over and above legal requirements.
Embedding these values across Spark needed innovative thinking. We already had company-wide privacy training, but upskilling every Spark person to be a privacy specialist wasn’t going to be feasible. At the same time, we needed our people to be ready to make sound, values-driven decisions about new data uses – and we needed to be able to do that at scale.
So, we set up a privacy model that leverages the smarts of our people, with support from an automated decision-making tool designed here at Spark. We’ve recruited and trained individuals across different parts of the business to use this tool along with their own expertise to act as privacy ambassadors – helping teams to navigate decisions based on Spark’s privacy policy and values.
As a result, when a team has a new idea they’d like to use data for, they must submit an online privacy review request which will be first assessed by one of our privacy ambassadors with the help of the tool, and if required passed to Spark’s privacy team for more advice.
We’re committed to do more to improve the value and benefits customers get from their data, and we’ll continue to strive for New Zealand-leading privacy practices.
We believe it’s our responsibility to strike that middle ground - to not just keep our customers’ data safe but to use it to better serve our customers and find new ways to help individuals and businesses have a better relationship with their data.
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