There’s no question that the move off of third-party data exclusively is a good thing. And there’s no question that moving closer to originally-sourced customer data is a good thing. But there is a distinct difference between what’s being called “Zero-Party” data and data that has been given freely as part of a transparent value exchange. That data, known now as fully-permissioned customer data, has its roots in conversational, gamified exchanges between brands and customers and its utility, as you’ll see in this interview, extends WAY beyond the metrics of traditionally-sourced customer data.
We’ve written extensively about the fully-permissioned data phenomenon, and we’ve even field-tested it ourselves on in-house initiatives here at TheCustomer. In this interview, we talk with two people who are arms-deep in the actualization and analysis of this data to get a better, if not broader look at how transparently-sourced data can multiply engagement, lifetime value and overall ROI.
Marc Shull is an occasional contributor to TheCustomer and is CEO of Marketing IQ, a boutique big-data analysis agency. Will Stuart-Jones designs the engagement mechanics for 3radical, the source platform for the data universe at the center of these conversations. The video is fairly short-and-sweet and has been edited for brevity. The complete transcript of our conversation is below.
The Utility of Fully-Permissioned Customer Data – A conversation with Marc Shull, CEO of Marketing IQ, and Will Stuart-Jones of 3radical.
Hi, everybody, it’s Mike Giambattista. I’m the publisher of TheCustomer. And today I’m here with will Stewart Jones from 3radical and Marc Shull who is consultant at large to 3radical among other people. But he’s got a deep history in big data. And we wanted to have a conversation today to kind of unwrap and unpack the ideas behind permissioned customer data. And what you actually do with that, because it’s becoming a topic that’s gaining some buzz amongst all the other party data questions like third party, second first party and third party data, what and where does fully permissioned customer data fit in the mix? And what do you do with it?
So Marc, will Thanks for joining us, no problem. I’m just gonna throw this out there because both of you have your arms deep into the data world, especially as relates to fully-permissioned data. I’ve seen some of this stuff anecdotally, but you guys work in it daily. Can we talk a little bit about what it is, first of all, and then why it might be more useful to brands that traditionally sourced customer data? Marc, I’ll let you go first. And then Will, maybe you can chime in?
Sure. It’s important for a few reasons. Most of them aren’t going to be really surprising to anybody. When it comes to the customer experience. You’re talking things like relevancy, which always drive better results when, you know – you send me an email or a text message, and I actually care about something right. On that level, I think it’s more and more important. From a trust perspective, I think there’s a growing importance we’ve seen over the last several years. Brands that align politically or ecologically with certain segments, certain customer segments, that helps create some additional value, and then that resonates better. But when it comes to some of the legislation coming down the pipeline, and the restrictions on third party data, the ability to not only capture it as zero or first party where and they know they’re giving you the data, or they are giving it to you directly. There’s greater security in that, for brands to be able to use that data. So there are a lot of things in play.
Will, from your perspective, you know, arms deep, as I said, in the mechanics of this, how do you see fully-permissioned data differing from, say, traditional sources of customer data?
So the thing that I would stress is you’re getting the data from the horse’s mouth so you’re trying to take the guesswork out of where this data is coming from. You know what we provide it through 3radical is a platform where we can effectively incentivize people for providing data, we quite often refer to it as “owned” data. And as I say, you’re gaining that directly from the consumer – you’re not gaining from to a third party. You can be sure about where that data has come from, why it’s been provided to you. And it’s quite easy. Funny enough, I had a bit of a bit of a run-in from somebody from an agency other day. We work with a dining chain – Zizzi’s – in the UK, pizza chain. And they use our mechanics to capture data from people directly. Things like, have you got any special requirements? Are you vegan? You know, do you drink soft drinks, all that sort of good stuff. And the guy said to me, “Well, you know, I can get that sort of data from the transactional data.” I said, Well, not really, you know, you might get it for a part of people at the table. You don’t know who specifically said they’re a vegetarian or Vegan. And you know a lot by going and getting that data directly. As Marc said before, it’s then about using that.
So they’re going to be sending out an offer on a Friday night, run a image of a meat feast pizza, if you know people have got special requirements, you can tailor the offers accordingly.
So that’s transactional data. It applies to a lot of other data, data sources as well. You think about clickstream data, somebody’s going to a website, an enterprise browsing around maybe looking at mobile phones. You might know what handsets they’re interested in or what type of contract you’ve got no context. Am I buying it for my kids because they’re going to high school or you know, because my dad’s in lockdown in the UK still? By acquiring that data directly, you take the guesswork out of it, and you can adjust the personalization you deliver off the back-end which should be much more effective as a result.
Do you have specific examples off the top of your head where you have seen differences in engagement levels and then maybe differences in the utility of that kind of data from your own personal experiences because you both look at this from the same coin different sides I would say.
I mean, from a practical perspective, you know, somebody like Zizzi’s that I’ve just mentioned there they’ll quite often use this strategy for what they describe as “digital hand raises” so people that are in-store you know, they potentially not leaving any sort of digital footprint if they’re paying by cash and then booked in advance. So they’ll typically use these mechanics to get people to provide data while they’re waiting for their food to appear. And then they’ve provided little value exchange. Maybe it is your scratch card with your fortune then you went about you’ve had a fun experience. It’s been memorable. Your foods arrived.
Marc, you may have been behind the data that I saw – I think your name was attached to it. But we ran tests on our side and it looked to me, if I interpret this correctly, like engagement levels were astronomically higher in the tests we ran, and the analysis you did, but maybe you can speak to that a little bit. What have you seen?
In particular, what we saw was when somebody started to engage with mechanics, there’s a dialogue that goes back and forth. And there’s perceived value that goes both ways. It extended the data for that brand 32 times, I think it was something like 10 days versus 330 days, somewhere around there. Which, you know, the factor I think, was a little surprising. But the direction was absolutely not. You know, if a brand can communicate with a customer or a prospect in a way that they care about that they’re interested in, it creates that dialog.
Will’s example of people who were using the mechanics while they’re waiting for their food to arrive – maybe it’s the value of distracting the kids at the table, maybe it’s thinking about, you know, should I get that appetizer or not? While we’re on kind of a budget, “Oh, I just got a free appetizer with my little app here.” All the sudden, that experience, you know, there was they get something for giving something. And I think that creates a much better balance of relationship building and sales promotion that we don’t necessarily see as often as we wish we would as consumers.
And, you know, there’s always that pressure to sell now, increase revenue now and especially with the economic turmoil around COVID there’s (the question of) “How do we recover from the worst q1 and q2 we’ve seen in ages?” And, we’re seeing more and more brands, when they don’t have strong relationships – they’ve been commoditized in the mind of the consumer. And that’s now the opposite of paying dividends. It’s hurting them because all of a sudden, the loyalty isn’t there. It’s a very transactional relationship.
So what we are seeing is that the ability for brand to extend and create real relationships is paying dividends. And there’s definitely a niche of marketers that have bought into it, they’re reaping the benefits, and then there’s other ones that are trying to figure out how to do that now.
I just gotta extend what Marc was saying. So you create mechanics that reward people incrementally the more they engage. So the beauty of that is, as I say, if you fill in a gap in between in-peak infrequent purchase cycles, you‘re staying in front of mind, so that when you next hit a purchase cycle point, you’re more likely to pick that brand, particularly if you potentially earn something you can use.
So, you know, that could be answering little pop surveys, you know, when some sort of reward to capture more of that data to personalize the columns. It could be sharing that so it could be referring or sharing experience with Friends and you earn some sort of reward if people sign up and play as well.
And as Marc mentioned with the data, what we find with these mechanics, if they are designed to drive that repeat engagement, you’ve got people coming back to a website, even a fairly boring location, like a utility website that we’ve worked with in the past, many times in a short period. And every time they come back, based on insight of the data you’re feeding in, you can be teasing people or encouraging people to complete other actions at every visit.
One of the things that has come up in other conversations was that, in theory, fully-permissioned data seems to fulfill the promise of CRM that was laid out years ago for us, that we could finally start to have one on one conversations with customers at scale. And I think that one of the things that has prevented this from quicker adoption was that there was no real, cost effective way of doing this? Or if there were, they were kind of hidden. And it seems to me, especially with platforms, like 3radical, you guys have somehow figured out how to deliver that for brands at scale. Can you talk a little bit about that because you’re dealing with all kinds of different companies with all kinds of different customer aspects and qualities. How does that work? And how can that work at scale?
But, in the past, you would typically go to digital agency, give them a brief and they probably take quite a lot of time and burn quite a lot of money building something bespoke for you. And when you when you’ve used that, you know, your money spent and you know, arguably your customers, you’re in a bit of a cold spot. I use this analogy that we’re like a box of digital building blocks where you can create your experiences by pulling different blocks off the shelf and combining them together to create different types of experiences.
But the analogy is that when somebody uses that the old way of doing it’s a bit like a medieval Bible. So when he wants you to rewrite the Bible, in the past, you had to pay somebody a lot of money and it took a long time to create another copy and something was lost in translation between the two. The beauty of what we brought to the table is a SAAS platform with all of these building blocks. Now business users, rather than expensive coders can assemble these experiences, they can still be on-brand with imagery and text and all that good stuff.
But then the velocity with which you can release experiences increases, you can start to take people on a journey. You might have experiences tied to major above the line campaigns throughout the year. But also, from that data perspective as well, if you’ve got a hit list of 10, or 15, or 20 data points that you want to capture. And when somebody engages with the first experience, they’re giving you the first five, the next experience that draws the same people in, you could carry over that insight. And you can then be targeting the next five data points.
Or it could be that you’ve got enough data and now you have decided that you’ve modeled that person’s a good cross or upsell prospect. So the next thing you want to incentivize is actually a mini journey around, okay, “How do I get this person to learn about that product?” You know, maybe there’s some way that they can test it out – incentivizing it but still within a framework of whatever the wide experience might be. So they might be earning prize drawer entries for completing a test run.
So although we started out in consumer marketing, what we quickly realized was the same techniques can be applied to pretty much any audience engagement problem. So since then, we’ve used the same techniques to work with very large financial organizations are trying to make things like cybersecurity training more fun and engaging. So completely other end of the spectrum. In that case we’re not necessarily creating a lot of additional content, but we’re just adding an element of fun and some rewards so that if you engage in all of that content, there’s a central hub that learns and could offer up new recommendations.
But you’re potentially turning all of that engagement into something that has value to your consumers, or in this case, an employee. So one of the one of the ones I really liked from that example is, you can actually turn your points that you earn for engaging with content into having coffee with somebody from the executive team. It’s a big incentive for someone who is young and up-and-coming – they’re probably not going to get any airtime with somebody senior like that, so it’s kind of really neat way of packaging up something else that’s got value.
I want to thank you both for this conversation. I think it’s a conversation that can be extended in so many different directions. We are all three in the midst of many conversations about customer data – its utility, its value, its cost, its management, its dangers and the weight of it. And I think that platforms like 3radical are starting to allow brands to approach customer data in much more transparent, honest and open ways and we’re all about that. Look forward to where this goes next. But again, thank you both for the conversation and hopefully we’ll be talking about this again soon.