First-Party Data and Your Brand
Matt Broekhuizen joined VCCP in 2022 from Table19, an independent agency that he founded in 2008 with a specific focus on Loyalty and CRM. He has 25 years of agency experience working on data driven marketing programmes across a world-class client roster which includes Sainsbury’s, Sky, BlackRock, Currys, TalkTalk, Virgin Atlantic, BBC and BlackBerry (remember them?!!).
Matt now leads the Loyalty and CRM team at VCCP and has overall responsibility for its client roster which includes: Canon, LEGO, Sage, Fortnum & Mason, Direct Line Group, White Claw and TfL.
LBB> What’s the number one question that clients are coming to you with when it comes to how they can better use data to enhance the creativity of their content and experiences?
Matt> The most common question is: ‘How can we access and use our data to understand our customer audiences and create more personalised content?’. Sadly this has been the most asked question for many years now, mainly because most organisations have been slow to realise the value of their customer data and change their technologies and operating models. Things are slowly changing and some clients are already capitalising, but many are still trying to figure it out.
LBB> How can you make sure that data is elevating creative rather than forming a windtunnel effect and knocking all the interesting or unique edges off that make something distinctive?
Matt> Data doesn’t stifle great ideas and creativity, it enhances them. During the creative process, data driven insights need to be balanced with human insight and creative intuition.
Data is essential in making sure your ideas are delivered in highly personalised ways and are seen by your most relevant audiences. That’s when it comes into its own.
LBB> Can you share with us any examples of projects you’ve worked on where the data really helped boost the creative output in a really exciting way?
Matt> At VCCP, we have just launched a nine-month long customer engagement programme for LEGO to celebrate its recent partnership with Formula 1.
The project is designed to tap into the strong allegiances F1 fans have with their favourite constructor or team. From the outset, we asked existing LEGO customers who had shown an interest in F1 or similar products before who their favourite team is, and then throughout the F1 season we are going to tailor their LEGO experience according to how well their team performs in each race.
This simple piece of data collection combined with existing profile and purchase behaviour data is allowing us to promote LEGO’s new F1 products in really unique and tailored ways.
For example, If a customer’s chosen team does particularly well one weekend, they will be rewarded with LEGO Insider reward points which can be used to purchase F1 LEGO products.
LBB> More brands are working to create their own first party data practice - how can a brand figure out whether that’s something that is relevant or important for their business?
Matt> In my view, building first-party data should be a priority for every brand, there's simply no good reason not to.
Certain sectors (automotive, utilities, subscription services and supermarkets) have long recognised the immense value of their first-party data. You just need to look at Tesco ClubCard and similar schemes for proof of the value in a first party data practice.
Some industries however are just beginning to grasp its significance. For example,with the upcoming HFSS (High Fat, Sugar and Salt) government legislation set to limit how FMCG brands can promote their products, many in the FMCG space are now having to turn to first-party data as a strategic investment to help them overcome these new restrictions.
Expectation amongst customers has also soared for personalisation and relevance across loyalty, digital and experiences, with various research papers over the last few years saying that customers are less loyal to brands who don’t provide these experiences. Having a first party data practice is essential to delivering these experiences.
LBB> We talk about data driving creativity, but what are your thoughts about approaching the use of data in a creative way?
Matt> Using customer data in creative ways is something we’ve been doing in the loyalty and CRM team at VCCP for many years now. It has been a really powerful way to change and influence customer behaviour, whether that be to encourage customers to buy healthier food in their supermarket shop or encourage greater use of public transport.
One of my favourite recent campaigns was a really simple idea we developed for Canon to help them sell more replacement batteries.
With Canon we have the ability to look at each customer’s camera usage data. This meant we could see when a customer’s camera battery was coming towards the end of its life and at this trigger point we offered those customers, through one-to-one communications, a motivating incentive to purchase a new battery.
LBB> "Lies, damned lies, and statistics" - how can brands and creative make sure that they’re really seeing what they think they’re seeing (or want to see) in the data, or that they’re not misusing data?
Matt> All data is open to interpretation and manipulation. It could be an intentional manipulation of what the data is saying if a creative idea has come first for example. However it could be unintentional if the wider context of the data is not considered.
For me, context is king here. Without context, the data can be open to many different unintentional misinterpretations. It’s really important for brands to ask questions of the data, be curious, challenge the insight to make sure they fully understand what the data is telling them to inform the right creative approach. Only then will you fully ensure relevance is baked in the creative.
LBB> What are your thoughts about trust in data - to what extent is uncertainty and a lack of trust in data (or data sources) an issue and what are your thoughts on that?
Matt> Trust in data is a huge issue, especially in an industry looking to put the customer at the heart through data-driven experiences and an industry talking about using data to drive AI experiences.
There is a lot of confusion and concern amongst customers in how their data in particular is powering AI and these experiences, causing a lack of trust within the industry. This is causing a lot of uncertainty and mistrust, which does affect brands working to build long term loyalty.
With any use of data to drive experiences and loyalty, if the data input is unreliable the output will be flawed, ‘garbage in, garbage out’. To rectify this, it’s important to recognise that data can be affected by biases and inaccuracies when it is collated and subsequently used. Ensuring there is clarity and transparency here in powering decisions, opens the door to reduce uncertainty and increase trust.
LBB> With so many different regulatory systems in different markets regarding data and privacy around the world - as well as different cultural views about privacy - what’s the key to creating a joined up data strategy at a global level that’s also adaptable to local nuances?
Matt> From my perspective it's about delivering the standardised approach at a global level that considers the broader regulatory policies, such as EU GDPR, whilst allowing for flexibility for customisation at a local level that aligns with regional regulations.
Within the entirety of the data strategy, the key to this is to always think about the customer first when you are using data focussing on building trust with your customer. So many organisations need legislation to make sure they are using data ethically, but if you are single-minded in your approach, always making sure you do right by the customer, then I don’t think you can go far wrong.
The key to this is making sure you have permission to use your customers’ data in the way you want to use it, ensure there is transparency with the customer, make sure you’re not invading their privacy, make sure you’re not contacting them too often and make sure you’re only talking to them about things you know they are interested in.
LBB> What does a responsible data practice look like?
Matt> In today’s world a responsible data practice has to be transparent on how you are collecting data, the governance around how it is stored and validated, and how the data is then used.
In terms of data collection, it’s all about relevancy and having clear strategies that underpin this are crucial. Only collecting necessary data, rather than collecting data because it ‘might’ be useful one day.
In terms of how the data is used, AI adoption is a common methodology here. Although AI has been around for a long time within data, it is still the buzz word amongst both clients and their customers. With that comes the added weight of responsibility and transparency within a responsible data practice to allay the fears of misuse. Gone are the days of having a magic data black box.
Ultimately, for me a responsible data practice is a data practice that allows the customer to control the use of their own data with ease and clarity. This ensures and builds that trust that is so so important!
LBB> In your view, what’s the biggest misconception people have around the use of data in marketing?
Matt> The more data we have, the more chance we have of finding the right answer.
People often think that the more data research you do, be it in different facets of customer data or from third party sources, the more insight you will find and the more likely you are to find that golden nugget of information. The reality is that there is a point when you get oversaturated with data and information, that you end up generating the same insight you have already found and it is easy then to start going down the wrong rabbit holes from too much detail. To avoid this, it’s so important to set out your core questions or hypotheses you are looking to answer and validate, and keep referring back to them.
LBB> In terms of live issues in the field, what are the debates or developments that we should be paying attention to right now?
Matt> I know this is an obvious answer but it’s a development that is here now and is only going to get bigger, and that is how AI is using data. AI models can rely on live data and biases in their models can lead to some dark places like fake news and discrimination.
One debate AI has created, is the debate on the use of synthetic vs real data within marketing. Synthetic data is AI driven and allows marketers to mimic real-data without the risk of compromising customer data, for example in using it to create audience profiles and personas. However, can the efficiencies that can be gained in using synthetic data outweigh the accuracy risks?
Another big AI debate more from a customer lens, and I have touched on it previously, is how AI is using customer data. This might not be a new development, but it is one that is hanging around with customers concerned about their data privacy. It is so crucial for brands to be transparent with customers and use AI for good in driving those exciting, engaging experiences.
My two pennies is that AI and the efficiencies that can be benefitted should be embraced. All of the major tech companies are backing it, it’s not a fad that will be going away. But it can only work with accuracy alongside a human brain who knows the client, knows the brand, knows the data to guide the AI and we have an incredible team at VCCP that does just that.
