[00:00:00] Speaker A: Foreign welcome to the Loop Marketing Podcast where we dive into the latest trends, challenges and opportunities shaping the marketing landscape. I'm Elise Stieferman and today we're talking about one of the most valuable yet underutilized assets in marketing data. And joining me for the conversation today is Rodney Perry, President of Kwaeke Canada. Rodney is a digital marketing Expert with over 20 years of experience, having led teams at Chameleon Digital Media in Zaxis where he managed programmatic media and delivered business intelligence. He's also worked with top tier clients like Ford, held key
[email protected], rogers.com and Group M agencies. And with his deep expertise in data driven marketing, Rodney knows firsthand how brands can turn raw data into actionable insights that drive smarter marketing decisions. So why do we think this conversation is so important right now? The world of marketing is rapidly shifting as we're seeing changes in privacy regulations that are tightening and brands can no longer rely on just those broad audiences that are, you know, from external sources and aren't really reliable and they need to take control over their own customer insights. But collecting first party data, that's really just the beginning and the real challenge and opportunity that we're seeing here is the ability to really unlock that full potential of our data. Ronnie, welcome. Thank you so much for joining us here today. We're excited to have you because first of all, you are a wizard at creating data strategies and have been doing so throughout your entire career. But we all know that data strategies aren't all created equal. So to start us off, I'd love for you to explain what creating value in your data strategy really even means and why it's a critical focus for brands today.
[00:02:01] Speaker B: Great. Thanks Elise. I'm very excited about always talking about data within businesses and why I think it's critical. Talking about data strategy within business is really getting businesses to think about the data that they have and using it to drive business. The unique thing. And you realize I've been doing this for a very long time. Data is always been part of business and business decisioning. What we're now at the point and what I've seen is the data is not always used across the entire organization to then be able to use that, to be able to build the business from there. Interesting example is thinking like the inventory or the distribution teams that have data about products that are being built and where they're being sent, not necessarily always talking to the sales team or always talking to the marketing team. Well, those data connections inside organizations are very Important to be able to deliver a business strategy that incorporates what they're looking to drive the business. And that really is the core is thinking about using and creating data that is within the business to then be able to use that drive the business, business forward.
[00:03:25] Speaker A: Yeah. So I mean you, you mentioned a critical point of looking beyond just customer data, thinking about that POS data, thinking about log files, things like that.
How do we get all teams kind of aligned on all the, the data points that we need to be looking at from a marketing perspective and something that is probably even more complex. How do we work on mapping and consolidating all of this data to make it actually effective and actionable?
[00:03:54] Speaker B: Yeah, I think that's the critical part of it. And I think that is one of the things that either handcuffs businesses or slows businesses down from actually creating a data strategy or starting to work in this fashion. And the one is there's just too much, don't know where to start. And what I would say there is start anywhere really. And it really is start with the data that you know you've got on hand and start with that data working with the other teams inside the organization.
Really it is I always try and talk to him when I'm talking to clients thinking about understand your own insights first before you go out into market looking for additional insights to help drive your business.
And we're in a world where those insights are easier to find and much more nuanced. In the past, I worked in retail. Early on in my career, very easy it was to understand what stores worked well, what stores didn't based on size and sales volume. We're now at the point where we can do deep dives in data that's available at a store level to understand nuances between stores. Even if a store may only be a couple of blocks from each other, there may be nuances inside the data based on those stores that make one store slightly different than another store that can have then a business impact. Drive a sales market to a store that over indexes selling this, whereas another store may over index at selling another product. Well use that knowledge to be able to deliver business results. Whereas up to this point we only ever would have told one message out to market to try and try that business. Right. We're in a world where AI and it's the first time saying it today, but AI has the ability to help us work through all this data to be able to understand the nuance and then build strategies from there.
[00:06:02] Speaker A: Yeah. And because we have all of that data that allows us, to your point, be much more nuanced. We don't have to take a one size fits all approach to the way we're handling our marketing campaigns, and that's a huge opportunity. It's also likely for smaller teams, at least daunting, because it feels like there are so many directions, directions you could go in. But again, going back to what you said, just starting somewhere is the biggest place to start. And you know, oftentimes when we're working with brands, we're building out those measurement strategies and learning agendas. And if we build out a learning agenda where we at least have a starting point, what's the most critical question that we need to answer? That at least gives us a path forward to be able to continue to ingest more and more of those pieces of data and get smarter with our marketing and make it more actionable. But I'd love to also hear from you. I mean, I'm sure the top problem or mistake that you've seen brands take is not doing anything with their data, becoming overwhelmed and then becoming paralyzed and not ingesting it, and making smarter marketing choices. But what are some of the other big mistakes that you've seen brands make when trying to develop out those data strategies and making their organization get smarter?
[00:07:22] Speaker B: Yeah, I think that definitely the getting started is one. The second part of that is the silos inside of organizations and having those organizations work to break them down. And it may not be breaking them down from an organization structure, but it's breaking them down from a communication. So like I said, the distribution and the inventory teams making sure that there are no walls in place for the knowledge and the data that they have to move over to the marketing team, to move over to the sales team. And conversely, the sales team or the marketing team, their data needs to go the other way. If they have gathered knowledge about a specific market, a specific store or product, whatever, if that knowledge never goes back to the inventory teams, they may not be able to have the product available in the way that they want. It is something that moving data back and forth across organizations is very important. And breaking down the silos, and the silos have always been there. Our job as business owners and managers is to break them down as much as we can. The second part of that is then to build a data strategy moving forward.
So the first part is understand what we do have as current data. Mine it, understand the insights in it, and build off of that. But then the second part of it is actually create a data strategy. Identify where you don't have the data that you need to build the business and create a strategy to be able to create that data or acquire that data so it comes into the organization, so it then can be used to continue to move forward. And part of that data strategy, of course is data acquisition. Think about collecting first party data. Well, a lot of organizations challenges that they have with collecting first party data is they've collected it over years.
Privacy rules and policies have changed over years. So a lot of the data they may have may not be relevant or readily available to be used right now. And so creating that ongoing data strategy to be able to build data to be able to be used in the future.
[00:09:39] Speaker A: Yeah. So I think you're talking about a world way beyond just what marketing intel looks like or marketing intelligence. It's about business intelligence and thinking beyond just the marketing sphere and thinking about how marketing is going to impact your overarching business strategy, which I think is so critical. And to your point, the breaking down the silos is such a hard thing to do because everybody's so heads down on their day to day and it's hard to think beyond, you know, what you have to get done before 5 o'clock or before the end of your workday. But I love what you said about being able to acquire more data as well. And I think that's for a lot of digital marketers, the first place where their brain goes is customer data or being able to build out true audience profiles so that we can build a more direct relationship with those customers. So once brands are beginning to consolidate that data and acquire more data, what would you say that their best next step is in using it actionably to build a custom audience strategy?
[00:10:44] Speaker B: Yeah, custom audience strategies and using the data is critical for clients because is it allows us to match consumers directly to the business in a way that that consumer is going to engage with that business. And we know consumers don't buy the same way across any product. And so being able to talk to a consumer in a way that they're going to want to interact with their brand is what we're looking to do. So the first step, understand your existing data. The second step is then mapping that data that you have about your customers and any segmentation insights that's done in that data than mapping it to data where you can effectively find that same consumer and deliver a message to them in a way that they're going to impact the business and critical within Koagi. And one of the things that we always think about is doing that audience based Work once and then using those audiences across the entire ecosystem. Right. And there it's if gone through and done done. The data work that we want to do, I identified. Here's a customer segment that we know is very, very important to us. They've interacted with us, they're part of our socials, they've searched well, using that data, bringing it into the platforms, defining that as a single audience in an audience group that we want to target and then taking that audience group across the entire marketing sphere to be able to talk to them. So not just taking the social that we've identified and using it over on social. No, it's taking the social audience that we've identified, key customer audience, and then using it across all of the marketing that we're trying to do, including the marketing that clients do themselves, the direct mail, the customer service aspects of their business along with the mass advertising and the search based advertising that we do. It's single audience once understand your customer, move them across the entire ecosystem to be able to get the best value from it.
[00:12:57] Speaker A: Yeah. So that's not only going to impact of course the effectiveness of your campaign, but it's also going to create a more, a better experience with your customers. They're going to be able to have that message and really begin to have some sort of relationship with your brand. Of course, when you're focusing on frequency management, don't want to see the same ad 30 times in the same day. But I know that's been critical.
[00:13:22] Speaker B: Yes. And I'll also add to that, that is also part and parcel to the data strategy. In building the data strategy and upfront. Yes, you create the data strategy, understand existing data, map it to data available research, stuff like that, create that data strategy that turns into audiences that you're going to deliver messages to. Well, when you're running that campaign, the reporting that comes out of that campaign against the AUD audiences that you ran are the adjustments to the data strategy going forward. Right. If you've identified, here's our highest value customer segment, we're going to run this message to it. That campaign it runs. And the results of that campaign is the data that's flowing into the strategy that talks about that segmentation strategy against that audience and you may adjust the strategy based on what's run. So it is this circular thing of build the strategy, build the audiences, execute, but then use that data and knowledge to continue to evolve the strategy.
[00:14:28] Speaker A: And you know, businesses that have had this data strategy in place, the hope would be that they take an iterative approach that they're learning from what they're seeing from those insights and not just replicating maybe what was done 20 years ago and assuming that it still works. And you had mentioned the critical importance of refreshing your data, making sure that the customer profiles that you have in your CRM are still relevant, that they're still even a potential customer in your pipeline. But another thing to think about is oftentimes when businesses were adjusting that data back 15, even three years ago, the privacy laws were completely different. And the need to disclose how that data is being used has evolved significantly. And we're anticipating that it's going, going to continue to change at a very rapid pace. So what are some ways that businesses can continue to aggregate that business data and drive that effective media targeting, but also keeping privacy and compliance always at the forefront of everything that they do?
[00:15:39] Speaker B: Yeah, I think my honest answer there, and it's a real easy one, is consumers don't mind and understand privacy. They understand value really well. Right. So if a consumer wants to interact with your brand and they're willing to give the data to you to be able to interact with your brand, know that they're your customer. Don't do anything that's going to screw with your customers. Right? Doesn't matter what the privacy policy says. You can have the best, you can be fully aware and totally compliant with privacy policy. But if you've pissed off your customer, it doesn't matter whether you're good with policy. So the first piece comes to take care of your customers. If you're taking care of your customers, you are managing their privacy properly, they will reward you for that. Right. It's really much a common sense approach to privacy and they don't do anything that a customer wouldn't want you to do with it. They're going to support you with it and they're going to continue to through work with you. So that's the clear element in it. The, the piece that's more critical to that is understanding the existing data that they have and not using anything that is potentially at risk. So they don't put themselves in that, in those problems. It more is work on a data capture strategy. If you're worried about what's out there, work on a data capture story. Because if customers have given you their data once to be able be part of your program, even though you're not may not be comfortable using it now, likely if they were happy with it, they're going to give you that consent again very quickly. So be able to kind of do that and incorporate that into your plans. The second piece to that, and this is directly from a conversation I had with a customer who a client who did say, we don't have first party data, we're not in the business to go out collect first party data. It hasn't been part of their structure going forward. And then it was, well, you do have data that is associated with your customers that you just may not have considered first party data in the past. Start there. And there you go with log level files off of people that are coming to your website. If they're coming to your website, arguably they're either you, your customers, your employees, they're the ones that are coming there. Your competitors. Yes, we all know competitors. Look at all the sites and then your customers. So at least a big chunk of the people that are coming to your site are your existing customers. Start there with log level files. Understanding the value of those customers that are there if they have locations. Again, another source of data that we often look at in our realm is location based data. Well, if you've got a store location, there is the ability to understand the mobile devices of the people that are coming into your location. Yes, it's not considered first party data. They haven't signed up, they haven't said, yes, I am your customer, but the fact that their phone is in your store makes them your customer. Not a one to one relationship. You don't know what their name is, but it is an understanding of who that audience is. Pull all that together, analyze it, build campaigns from there and then from there. Look at, oh, how can I collect first party data? Yeah, building off of that. So there it. That's the element of just getting started because we can paralyze ourselves with. There's so much to do, you can't get started. That's the element of just get started because there's lots of data available.
[00:19:26] Speaker A: I feel like so many marketers have become again, somewhat paralyzed to the concept of attribution. I feel like, you know, if I don't have a customer email that I failed, I haven't achieved any sort of, sort of first party data acquisition. And that's just to your point, not true at all. It's a lot of finding those correlations and using modeling to make smart decisions and using the data that you have on hand. And clearly you're talking to our clients about this every single day. And we've kind of skirted around this a little bit, but I'd love for us to get a little bit more tactical and Having you walk us through Koegi's specific approach to helping guide brands through their audience strategy and data management and platform selection. And obviously we could talk about this over a three hour session. This is a, a pretty hefty topic, but if you could give us just a, a high level approach to how you're talking with our clients to guide them and in getting started. I'd love to hear that.
[00:20:27] Speaker B: Yeah, absolutely. For, for me and I, I've, I've done this in a way that it really starts with business objectives, right? It starts with where is the business at, what are the current challenges, what's working really well, what's not working well within businesses, what's the roadmap, where are the growth plans going, what are the challenges? It starts with business strategy first. That business strategy is typically informed by data, right? It's oh, those are your best stores or you're planning launching here. Well, why did you make that decision? Look at that data. That data is the formulation for do we take that knowledge into the marketing advertising ecosystem and understand the data that's there and then that's the mapping process and that's where the agencies really excel in helping out our clients, is understanding the data that they have and how it then has the ability to transform into the marketing ecosystem. Right. So taking first party data, taking log level files, taking location files or device lists from where they currently are into the advertising ecosystem. And why agencies and how we think about this is because there's not just one way to do it, there's multiple different ways to do it. Multiple different platforms to move data from one place to another, to match it up to things, while the agency has the ability to understand all of the potential opportunities to move that data, to be able to continue to use that data as it goes through. So the first is map all of the data that's there, understand privacy, understand first party data, then match it to other data that's available in the marketplace through a live ramp, a system that allows to connect directly into the buying platforms, into the data platforms that then allows us to append data on top of the data that's already there, gives us customer profiles, gives us the ability to now create audiences that we expect will drive the business in finding very nuanced audiences that will deliver the message that will deliver the business. All of that is then tied together through an entire ecosystem that you can now take that connection point, that data point and move it almost anywhere that you want, which is relevant for the customers. We know some businesses do better on Social. Some businesses do better on the end, right? Well, having the ability to identify the customer, identify that data and then move it to the appropriate platforms to be able to then deliver those messages is very important.
And it is the understanding of doing that once and moving them everywhere. We've gone from a world where we would do data work, understand the audience and then go to a provider and say, okay, this is who we're looking for. And they would then look at their data and try and recreate that person for us and say, yeah, we can target that person. Well, we don't have to do that anymore. We're living in a world where we're all interconnected and now we can do the data work and the audience work and move it through the entire ecosystem. Ecosystem.
[00:23:59] Speaker A: So you have seen this world evolve a lot. I'm sure in your 20 plus year career things are completely different. I mean, even in the last year we've seen so many changes and I feel like the world of digital is just evolving at a rapid, rapid pace. So based off of your historical knowledge and what you're seeing in the trades and what you're seeing in platform, what are some trends or future shifts that you think brands should be preparing for when they're thinking about taking a data driven approach, approach to their marketing and building out this data strategy?
[00:24:33] Speaker B: We've always used data to build media plans, right? And so what we're doing now isn't necessarily new. It's evolved. Right. When we used to choose programs Thursday night evening TV that we wanted to run the ad on, we use data to be able to make that placement, right? We used audience data from the broadcaster, we used the show, the show audience again, that to be able to deliver that placement. We're still currently doing that. We're just using a lot more data than we've used in the past to be able to do that. What that then allows us to do is get much more nuanced in our messages, much more personalized in the messages that are going to consumers that deliver the results that we need. But we do also know that we can't go totally there, right. The aspect of delivering branding, delivering that message that gets awareness out is just as important to then make sure that those messages that are very targeted at the bottom of the funnel are getting the response that they need. So it's the combination of both is what we need to continue forward in understanding that the big brand messages that are going out there are starting the conversation and are being targeted with data. Maybe not as nuanced data as when we get down to oh, that person's going to like it in blue versus red. Show them the BL one. Yes, it's still being delivered and it is the entire combination of all of that that's going to deliver the results versus one or the other. And so it's the evolution of where we were to where we're going, but they all still need to be included.
[00:26:20] Speaker A: So if you are talking to a marketer today just to wrap us up and we're helping them get down this path to preparing for this continued evolution, what are the three steps that you would tell them that they need to take in order to truly improve and have a measurable impact of using a data strategy to drive their business forward?
[00:26:44] Speaker B: Sure. So the first one would would be look internal. First spend the time, look at all the data that they have, bring the different teams together with the data that they have and analyze that it thoroughly, truly understand what's there and then identify the holes and where additional data could come in. Second step then is build the data strategy that is going to acquire the data that's needed to fill out the full strategy and also understand where and how that data is then going to be used going forward. Forward. So first look, look internal, grab the data. Second, build the strategy to be able to acquire the data you need or buy into the data that you need. And then the final piece is don't is start right away and we can paralyze ourselves with the analysis and creating the strategy that never goes forward.
Part of data strategy is running programs, getting knowledge out of those programs, generating that data and moving it back in and continuing to run. Strategy doesn't work unless something's actually happening with it. And so the real critical part is actually doing something with it and launching that first program and learning from it and then not stopping. Right. Nothing that we do based on strategy is always going to work. But. Well, what we do know is we're going to measure it and if it didn't work, we're going to adjust to be able to deliver what did work. If it did work great, we do more of it. We find additional elements to enhance it. We keep going. But for the stuff that didn't work, that's the data that comes in and go, yeah, we did that, it didn't work. Here's how we're going to adjust it or not do it again. And so it really is start today would be the final piece is just get going on. On it.
[00:28:47] Speaker A: Yeah. That data provides that transparency and it, it truly builds that trust is going to strengthen those relationships with our clients and help each other grow and get better. So, Rodney, Sorry, go ahead.
[00:29:00] Speaker B: I. I'm just going to ask add one additional comment here. And. And it is what I always want to tell clients when I talk about data in this way. Because I talk about data. We're passionate about data, how it can be used. But the critical piece to all business, it's not data. These are consumers we're talking about, right? These are their customers. It's what we know about their customers. It's what they know about their customers. It's not data, it's their customers. So treat it that way and do things that you would want to do for your customers. Deliver a message that you want to give to your customer. Yes, it's data, but it really is a customer. And so it's not just data, it's the customers that are going to drive your business. That's what we're trying to do with a customer strategy that we're building.
[00:29:48] Speaker A: I love that. I feel like we always hear the phrase humanize your brand, but maybe we should reposition it to humanize your data. Think about it as more than just a number or a data point. Think about the person behind it. So Ronnie, you've been great. Thank you so much for sharing all of your insights today. It's been a truly fantastic conversation on how brands can unlock the power of their data. And for our listeners, we really, really appreciate you tuning into the Loop Marketing Podcast. If you have any questions about optimizing your data driven marketing strategy, reach out to us. We'd love to have a conversation. Clearly, Rodney's extremely passionate about it. I know that he'd love to dive in deep with you and just be sure to follow Rodney and the Kweki Canada team on LinkedIn. They're going to keep sharing those expert insights on data strategy and media innovation and performance marketing as a whole. And if you enjoyed this episode in particular, don't forget to subscribe so you never miss an update and we'll see you next time.
[00:30:47] Speaker B: Thanks.
