Are brands that lack a robust Customer Data Platform strategy losing the ability to deliver seamless, personalized customer experiences in an increasingly data-driven world?
Today, we’re joined by Beth Scagnoli, Vice President of Product Management at Redpoint Global, a company at the forefront of data-driven customer experience solutions. Beth’s expertise spans Customer Data Platforms (CDPs), data quality, and marketing automation, making her uniquely positioned to discuss how organizations can harness the power of clean, observable, and composable data to create transformative customer experiences.
About Beth Scagnoli
Beth Scagnoli is a seasoned technology executive with over 20 years of cross-functional experience driving innovation, growth, and product adoption in the marketing technology space. As Vice President of Product Management at Redpoint Global, Beth spearheads the development and execution of product strategies that empower organizations to connect with their audiences through data-driven insights and personalized engagement.
Prior to Redpoint Global, Beth held leadership positions at the Smithsonian Institution as well as Blackbaud. With a proven track record of launching successful platforms and fostering cross-functional collaboration, Beth combines deep technical expertise with a passion for solving customer challenges. A frequent speaker and thought leader in the MarTech industry, Beth is committed to advancing the capabilities of modern marketing tools. Beth resides with her family north of Boston and in her free time enjoys fitness, dance, and obsessively honing her skills in Wordle and other NYT Games.
Resources
Redpoint Global website: https://www.redpointglobal.com
Connect with Greg on LinkedIn: https://www.linkedin.com/in/gregkihlstrom
Listen to The Agile Brand without the ads. Learn more here: https://bit.ly/3ymf7hd
Don’t miss a thing: get the latest episodes, sign up for our newsletter and more: https://www.theagilebrand.show
Check out The Agile Brand Guide website with articles, insights, and Martechipedia, the wiki for marketing technology: https://www.agilebrandguide.com
The Agile Brand podcast is brought to you by TEKsystems. Learn more here: https://www.teksystems.com/versionnextnow
The Agile Brand is produced by Missing Link—a Latina-owned strategy-driven, creatively fueled production co-op. From ideation to creation, they craft human connections through intelligent, engaging and informative content. https://www.missinglink.company
Transcript
Note: This was AI-generated and only lightly edited
Greg Kihlstrom: Are brands that lack a robust customer data platform strategy losing the ability to deliver seamless personalized customer experiences in an increasingly data-driven world? Today, we’re joined by Beth Scagnoli, Vice President of Product Manager at Redpoint Global, a company at the forefront of data-driven customer experience solutions. Beth’s experience spans customer data platforms, data quality, and marketing automation, making her uniquely positioned to discuss how organizations can harness the power of clean, observable, and composable data to create transformative customer experiences. Welcome to the show, Beth. Thank you so much. Yeah, looking forward to talking about all this with you. Before we dive in, though, why don’t you give us a little more about your background and your current role at Redpoint Global? And for those less familiar with Redpoint, can you talk a little bit about what you offer?
Beth Scagnoli: Yeah, absolutely. I’ll start with red point, my current role. Like you said, VP of product management, which ultimately means responsible for product vision and strategy and all that comes with it. Making sure that we continue to align with our customers and what they need and what they want to do. around the CDP space. I’ve been at Redpoint for 10 years this month. I think I’ve done all the things. I started in sort of operation service desk, moved into services, some account management, we’re dabbling in training. So I do think I have a pretty holistic view, let’s say, of our customers. So I’ve been here a while. And really, Redpoint was founded back in 2006. with the goal of, let’s call it driving personalization at scale, right? That’s really what everyone wanted to do, but it was sort of done in, you know, sort of a bifurcated way is what we had found. So we wanted to create this customer data platform product suite to solve that, you know, call it the CX challenges, right? Across data, insight, action. you know, kind of the theme that you’re probably seeing across the board at CDPs. So, what we provide are capabilities around sort of the end-to-end. So, when thinking about CDPs, it’s data ingestion, quality, identity resolution, segmentation activation, Geordie orchestration, all the way down, right? As well as real-time personalization. And really, what we lean into is Liberation of data, if we are obsessed with data, potentially to a fault. So really thinking about how we can ensure that all of our customers, all of our users are making the best use of their data and really understanding why data is so critical. And having our sort of composable model, which we can talk about later, as well as a deployment model that’s pretty flexible, we allow for even regulated industries to use our solution, right? We can be SaaS, we can be private cloud, we can be hybrid. So really as an organization, we are trying to be the best fit for the organization wherever they are. So meet them where they are and continue kind of down that path.
Greg Kihlstrom: Great, great. Well, you are definitely the right person to talk with about this topic. So let’s dive in here. And we have talked about customer data platforms on this show, but I think with everything moving so quickly, and to your point, the pressure really to deliver on personalization at scale. I think it continues to be a timely topic and really much at the forefront in a lot of marketers’ minds. From your perspective, and kind of just to start from with the basics, so to speak, what makes a customer data platform so integral to delivering a great customer experience?
Beth Scagnoli: Yeah, I mean, I think at the most basic level, understanding your customers, your constituents, and communicating with them the way that they want to be communicated with is paramount to that business model. And if you have six versions of your customer, right? You have Beth in your e-com, you have Beth in your CRM, you have Beth in your web data. you are never really going to know the true Beth, right? Who is Beth? What does Beth actually want? So sort of the main premise of a customer data platform is, yes, sort of consolidating that data and creating a hub from which all other marketing activities can extend. But it’s even beyond that consolidation, right? It’s not just throwing things in a pile. I think, you know, anyone that has children, you ask them to clean their room, they throw it in a pile. It’s not cleaning, right? That’s not helpful, right? We want to make sure that when you bring all the data together, then you’re also thinking about data hygiene, data quality, identity resolution that is correct. You need to make sure things are always on. So I think, you know, customer data platform that is done correctly, right, that’s bringing the data together correctly is then going to allow you to know Yes, this Beth on Ecom is this Beth in my ECRM, is this Beth over here on the web. And we’re going to be able to see that full picture and really deliver the experience that Beth wants, not each of these individual little Beths along the way.
Greg Kihlstrom: Yeah, yeah. Well, and I think Couple things there. I mean, so, you know, I work with a lot of enterprise brands on things related to customer data. And, you know, so two things here that I see. I mean, one, there are software platforms that are called CDPs. There’s also this concept of like a customer data platform may extend beyond a single platform. But there’s also the bad part of that is we’ve got many data systems and siloed data systems that, you know, it’s one thing to have a broad sense of a customer data platform. It’s another to have a bunch of disconnected and siloed systems. When businesses start making the switch from so many siloed and start consolidating, what are some of the most immediate benefits that they can expect from implementing a cohesive CDP?
Beth Scagnoli: Yeah, I mean, I think it’s having the right information about someone, right? I think there’s a few different aspects to having those silent systems. Like I said, one is you don’t have that holistic view, that unified profile, I know who this person is. You know who they are in different segments and different parts of their journey. But then, you know, additionally, it’s thinking about latency, right? If you have your e-comm system, and so you can see that I made a purchase, but then getting that information about my purchase over to, you know, whoever I’m using for email or for push notifications, is that 24 hours later? Is that, is that safe? 60 hours later, is that 10 minutes later, right? So I think with a CDP done properly, you should be able to get to real-time or near real-time, which I think that improvements in data clouds, right, like the Snowflake model and otherwise, have made a huge difference here in terms of, you may have all these different systems, but if they’re all pushing data ultimately to the same place, and that data is constantly being refreshed and updated, and that profile is constantly being updated, you’re gonna know that Beth has made a purchase, I’m going to send a thank you for your purchase, I’m going to remove Beth from any of my Google ads, my Facebook ads and otherwise, right? So some of that additional spend, that additional overhead on making sure that we are communicating with people on the right channels, that will go away, right? Because you know now you have that corrected version of the customer, of the constituent, It’s up to date, it’s in real time or near real time. And now you can focus your attention on other things as opposed to shifting and moving data back and forth and kind of hoping for the best.
Greg Kihlstrom: You recently wrote a blog about data observability, and you mentioned how critical it is to ensure quality and accuracy. What is data observability? I think it’s some of what you’ve already mentioned, but what’s the definition of data observability, and how does this support the effectiveness of a CDP?
Beth Scagnoli: Yeah, yeah, you know, thrilling stuff, DataObserver.
Greg Kihlstrom: To some of us, you know.
Beth Scagnoli: I think it’s thrilling. I will say I did write down, so I think Gartner actually has a nice definition, which is the continuous monitoring and analysis of data pipelines and data quality to ensure data is reliable, consistent, and usable for business purposes. So it really covers kind of the full gamut. It’s the timeliness, the accuracy, the completeness of your data, and making sure that, you know, are those processes in place to ensure that that is happening, but also make that available to an end user, right? You can be confident, marketer. You’re sending to the right Greg because look at all the things we’ve put in place to kind of make sure of that. Right. And I think that’s baseline just to a solid customer experience, you know, no matter what, right. Send me the right email with the right personalization, but, but frankly, it’s required. in a lot of regulated industries, right? You can’t send a prescription reminder to the wrong person about it, right? You have to really think about, you know, with especially, you know, new security and privacy compliance laws always coming down the pipe, right? You need to make sure that the data you have is fit for purpose in that way. I really, you know, I talk about it as the foundation, like a house. We use a lot of analogies at Redpoint. Pretty cool like that. And we always talk about, you know, good data, then those data observability concepts are the foundation, right? So you’re building a house, you pour a foundation. Could you decide to pour only half? Yeah, use Play-Doh? Sure. Probably not great ideas. Don’t care how clear your design is, your furniture, everything else. If you don’t get that foundation correct, everything is going to crumble. So really a lot of what we think about with data observability is, yes, making sure we have the ability to put those processes in place to make sure they’re there and always on, but also how can we let people know and not just say, trust us, it’s happening, right? How can we show that? How can we prove that all of this is going on behind the scenes?
Greg Kihlstrom: Yeah, because I mean, isn’t that I mean, there’s lots of reasons for data silos and and, you know, people doing one off things. But I mean, one of the reasons for that is you hit on it already is marketers or those those dealing with customer data just don’t necessarily trust the source of that data. And so that’s what I like about the observability concept is Yes, it’s also about accuracy of the of the information, but it’s it’s the it’s kind of the work about the work. Right. So it’s like, here’s here’s why you should trust it to be accurate. Right.
Beth Scagnoli: Uh huh. Yeah, exactly.
Greg Kihlstrom: Yeah. So how do companies start here or, you know, if they’ve already started, you know, how do they continually identify and address some of these gaps in data observability so they can, you know, build towards what we’re talking about here.
Beth Scagnoli: Yeah, and I think, you know, continually is a key word that you said there, right? So, I mean, you start with the basics, right? Look at your current, the data that you have, right? Look at your, you know, if you have a CEP or something similar, right, where you’re consolidating data, you know, what is that process? Do you know where everything’s coming from? Do you have access to all the data that you need to support whatever business outcomes you are trying to achieve? Do you know when that data is coming? Do you have always-on data quality? Does identity resolution, is that using probabilistic and deterministic matching, right? You can get super granular. Of course, I could talk for 10 to 15 business days about this, but really, start with the data. Start with understanding the landscape of your data and creating some sort of cohesive data strategy. I would encourage that to be done, not just in the IT vacuum. Even though IT, they’re the ones you go to about data generally, we need to start extending this into business users into marketing teams and beyond so that they also can really understand and weigh in on, no, I need this data because this will support X, Y, and Z. So that initial audit is, of course, my recommendation. And then really from there, leaning into the basics and making those basics programmatic, making them automated. Like I said, always on data quality, always on identity resolution. Data is fluid. You can’t do this once and be like, cool, we’re done, everything’s great. It needs to be a continual evolving process.
Greg Kihlstrom: Yeah, yeah. So another topic, top of mind for a lot of organizations now is composability. Composable being talked about a lot and not just in CDPs, but a lot of areas of MarTech and the enterprise. Written about composability as well and talked about a flexible approach to managing customer data. How do you see a composable data strategy empowering Brands to be able to, you know, do, do all the things they need to adapt quickly, adapt to changing customer expectations and even, you know, other, other technology opportunities that arise.
Beth Scagnoli: Yeah, sure. I mean, composability on its face sounds great. You’ve swapped things in and out. It’s Legos. It’s super easy. I pick what I want and I just pop it in. What could be hard? And I think that could be the case, right? I think that composability, just level set where I think about it, it’s just that modular approach, right? I got to build a solution. I want to use best-of-breed. If anyone’s seen that with the Scott Brinker MarTech map that is just mind-blowing with proliferation of just stuff. Yeah, I want to be able to get the cool, the newer, the faster, the better, the cheaper. But composability does come with risks, right? Composability then you need to have an IT team, especially in this case, that really does understand API-driven architecture, how different applications integrate with each other, right? Composability can be great if you want to say, I want to use one tool for my segmentation, and I want to use a different tool for my identity resolution. Great. Have at it. That’s wonderful. That’s not going to be super helpful if the tool you’re using for identity resolution, it’s six-day latency between getting that unified data over to the segmentation tool. Really, yes, they can be super adaptable if you select the right solution that does, either from a single vendor or multiple vendors, allow you to expand and contract and expand vertically and horizontally across different you know, areas of a CDP, because you can, right? I think especially in the case of those downstream channels, right? As new ways of communicating pop up, being able to bring in those communication channels pretty easily, right? I think push-button connectors, that’s where I think, you know, composability does have the greatest advantage. It can be dicier, I wouldn’t be swapping in and out your underlying data model and data ingestion processes on a daily basis. But I think thinking about data as the hub, and then those composable aspects as the augmenters, the senders to the various channels, I think makes a lot of sense.
Greg Kihlstrom: We’ve talked about observability and some of those challenges there. Let’s talk a little bit about, you wrote a blog as well about marketing automation and the importance of clean data. And so, you know, we’ve talked about observable data. Okay, now it’s gotta be clean too, right? So, you know, how do you look at this, you know, and clean data’s ability to influence ROI and other benefits?
Beth Scagnoli: Yeah, I mean, I’m a broken record, right? But ultimately, without that clean data that has, yes, it’s clean, but also has been properly unified, you could buy the coolest automation tool on the planet. You could have the finest content that money can buy, but if you are you know, servicing that content to a consumer that does not care about it because you don’t have all the information about that person, it just doesn’t matter, right? So ultimately the return on the investment, you need to have the basis in your data, in your data strategy in order to then leverage all of the benefits of a marketing automation tool or otherwise.
Greg Kihlstrom: Yeah, yeah. And so one of those benefits is certainly personalization. As we talked about at the top of the show, delivering that personalization at scale is certainly top of mind. I feel like we’ve been talking about personalizing and one-to-one and stuff for decades at this point. Maybe it’s been a decade, but we’ve been talking about it for a while. But I do feel optimistic that you know, with everything from some of the benefits of like Gen AI and some other things, like we’re looking at really being able to make this happen. How, what part does the CDP play in, there’s lots of, there’s obviously lots of tools, you know, at play in one-to-one personalization at scale, but what’s the role of the CDP to help to, you know, deliver across all those touch points and everything like that?
Beth Scagnoli: Yeah. And I think, you know, a lot of this depends on who you ask about the definition of a CEP because I see that as being a moving target too. But, you know, I’ll say obviously the unified profile is the first step, right? So that you know, everything there is to know about this particular customer. But then I think most CDPs, at least at this point, do have the concept of dynamic segmentation, right? So you’re not building segments once a month and then, you know, kind of hoping that they don’t buy anything because they’re in the lapsed per segment or something, right? So you should, as a part of your journey orchestration, how you manage your campaigns, be able to have that level of dynamic segmentation that is then based on that. updated in real-time or near real-time unified profile, right? So we should not have to think about how old my data is when I am thinking about, you know, more of always-on type campaigns, evergreen, like a welcome message, or your strategy with Google Ads, with Facebook Ads, and otherwise, right? CDP should manage that for you. You should feel confident that whatever I deploy today Everyone who’s in that targeted audience is going to be, you know, qualified. They make sense to appear in this audience. Right. So things like abandoned cart. Right. You don’t want me to put things on my cart. And then 10 days later, you’re like, hey, girl, sorry, there’s some things in your cart. I’m like, what are you? That was 3 a.m. I don’t even remember that. Right. You need to be making sure that cadence at which you communicate can be aligned with what the customer is expecting. And that won’t happen unless you have your data correct, you have that dynamic segmentation, and you have the ability to then communicate with those downstream channels, you know, really as quickly as they can be communicated with. And I agree, I think that, you know, thinking about segments of one, you know, we’re seeing especially at Redpoint, you know, the idea of micro segments and really getting down to, you know, you don’t need to use just the straight up RFM type scores anymore, right? We can really shrink this and get to what does Greg want to see right now, today, as we’re recording this, what would make you go ahead and click that call to action? And I think that’s going to keep getting to your point with Gen AI more and more important. We can’t expect anything to be static ever again.
Greg Kihlstrom: Yeah, well, and the, you know, the, the end result there, obviously, you know, if you sell products, it’s, you know, you want to sell more of them, but I think, you know, the end, the end goal is really it’s loyalty, right? It’s, it’s customers that buy more, buy more often and refer others and stuff. So for those that may be. I don’t know if there’s skeptics so much as there’s a lot of priorities in an organization. So those that are not prioritizing this, you know, how do you make the case for just the connection between this clean data, observable data and available data to things like customer loyalty?
Beth Scagnoli: Yeah, I mean, you know, we talk a lot about this with our existing customer base, right? You know, we, we talk about, you know, what are your goals? How do you, you know, what do you want to do with your customers? And I think one thing, just as an example, that comes down a lot is sort of a reduction in friction. And a lot of that comes down to call it, you know, call center engagement or front desk or other clientele, right? How annoying is it? If you call somewhere, you give your information, and then you’re transferred from here to there to there, and you’re giving the same information over and over. It’s just like, what is happening? How am I down in this seventh circle of hell? So for example, we have a hotel chain that uses our GDP data within their journey really to reduce that friction when you come to the hotel. right? So we are driving communication on check-in. We are sending you push notifications like, hey, it’s happy hour. We know that you enjoy a happy hour. We’re sending you receipts on checkout. We’re sending you follow-up emails for, hey, you forgot to pay your bar tab last night, right? So none of this maybe is a specific NPS score on, you know, your bar tab on paid email. But knowing, you know who I am, you know, within reason, not creepily, right? And I’m not repeating myself constantly, providing IDs, providing my phone number 15 times is going to make me a more loyal customer. It just is, right? I think about my, even my local mechanic, right? You know? Is he the cheapest in town? No. But every time I call, he says, hey Beth, he knows exactly what I drive, exactly what sorts of problems I have. And that’s going to make me go back to him because I trust him. All of it is leading up to, do I trust this brand? And I think CDP plays a huge role in that level of trustworthiness between a consumer and the brand they’re dealing with.
Greg Kihlstrom: Yeah, yeah. So we’ve touched on a little bit, but I do have this, I should just codify the rule here, but we’ve got to talk about AI because it’s- Of course we do. In 2024, it was like, we had to, we still do, it’s 2025 now. You know, what what do you see? You know, we’ve we’ve touched a little bit on this. And, you know, there’s AI is a very broad, you know, umbrella. But, you know, we touch a little bit on Gen AI. There’s obviously some other AI tools at play with with some of the data tools and everything. Where do you see, you know, given it’s 2025 now and, you know, we’ve we’ve been talking about at least Gen AI for a couple of years now. Where do you see some of the role of AI playing in enhancing a CDP capabilities?
Beth Scagnoli: Yeah. So AI, not gen AI, but AI machine learning, it’s been around for 50 years or something. This needs to be there. You should have AI as a function of identity resolution. AI as a function of machine learning for generating models. So predictive analytics, yes. I think that what I’m seeing now is previously you’d send out your data, and then a month later you’d get it back scored. And it’s like, cool, I hope nothing’s happened in that month, but here we are, right? So I think that it’s becoming table stakes, right? You need to kind of come bearing gifts of here’s the five different models we’re going to score your data on. Are they all going to be relevant? Probably not. As a generic model, a good idea? Probably not. But again, we need to have a starting point, especially for, you know, those organizations that maybe are just starting, right? They’re just evolving their MarTech stock, they’re dipping their toes into the wonderful world of MarTech. How can we start to help them understand their data? So I do think, yes, hopefully, you know, genericization of models will become less generic, right, using AI. But ultimately, that does need to be a part of a standard CDP, I think. And I think from a Gen-AI perspective, it’s trust, but verify, right? We all use Gen-VPT and Cloud and otherwise, and it’s great, and it is insane. same sometimes, some of the things that it comes up with. So I think that what we did at Redpoint is really thinking about AI to augment what you already have, right? So using natural language to generate a segment, right? If you’re someone, you’re a business user, you don’t know relational databases, ands, and ors, and parentheses. I don’t want to write code. I just want to tell you what I want. and I want you to show me what you built. I think that kind of a use case makes a lot of sense. And I think, you know, content generation, or at least as a starting point, right? Write me a cool Black Friday email, make it moderately funny and less than 300 characters or something like that, right? I don’t want to put anyone out of business, but I think some of the overhead that comes with A-B tests that is just, you know, a variation on a subject line, how can we use AI to start to augment that a little bit more as well?
Greg Kihlstrom: Yeah. Yeah. Well, and, and where do you see the future of CDPs? I mean, you know, as a, they’ve been, I know the, the, the magic quadrant hasn’t been around for that long, but CDPs have been around for, um, sorry, Gardner, but, um, the, the, the CDPs have been around for, you know, over, over a decade at this point in some, in some capacity, what do you see on the horizon for, you know, what, what will a CDP look like in, you know, in a few years?
Beth Scagnoli: Yeah, I mean, a lot of the same to the extent that the basic functionality, I do think, yes, there will be more AI, you know, both for the hype, but also as AI gets better and as things like Snowflake Cortex, right, where it’s just sort of built into the product, so why not use it? I do think there’s going to be more of that, more of kind of chatting with your CDP, letting your CDP tell you more about your data as opposed to kind of, you know, vice versa. And I think privacy, right? I mean, more and more, you know, there is this hypervigilance around privacy and data regulation and security and compliance. I think there’ll need to be more of an evolution around that to make sure that you can very confidently saying, yes, my data is being handled securely and it’s compliant and it’s ethical and making that available in the context of the CDP. Again, similar data observability as opposed to just trust us. No, show me, show me how this is happening. And then, you know, real-time forever, right? Real-time, who knows what that means, right? Real-time can mean that day. It could mean within 30 milliseconds. We’ve seen it both ways. We should be able to handle it both ways. So as, you know, maybe if TikTok may be going away, who knows? But thinking about the attention span of consumers, you can’t wait a week. You can’t make me wait a minute for something, right? I need something immediately and when I want it. So I think moving, you know, continuing to move toward improved real-time data processing, especially, is definitely something that we are heading toward, among other things.
Greg Kihlstrom: Yeah, yeah. Well, I love it. Well, thanks again for all your insights, Beth. One last question for you. I like to ask everybody, what do you do to stay agile in your role, and how do you find a way to do it consistently?
Beth Scagnoli: Yeah, I mean, I read the things, I listen to the podcasts, right? I think that, you know, LinkedIn, as much as it can be a bit of a cesspool, sorry, LinkedIn, there are a number of, I guess, influencers that I do follow that have interesting thoughts on the evolution of product management. especially as it starts to merge or unmerge in various places with product marketing. I think that role in and of itself is shifting and really just talking to others like me. I’m in a number of sort of product management focus groups and women in product and that sort of thing. And I think just talking to real people doing real jobs is another way that I try to stay on top of things, but otherwise it’s yeah, chatting with customers, reading the books, listening to the podcasts like this.