[00:00:00] ​Intro [00:01:00] Phil: What’s up everyone, today we have the pleasure of sitting down with Ana Mourão, CRM, Customer Data and CDP Advisor. [00:01:15] About Ana --- [00:01:15] Phil: Ana started her career in the financial services sector before moving to field marketing and ecomm partnerships. She then spent 5 years as a Marketing leader at 3M. She created the Experimental Marketer framework to help marketers take ownership of martech. Today Ana is CRM, Customer Data and CDP Advisor working with Fortune 500 customers advising on data architecture, [00:01:37] digital engagement and customer journeys. Ana thanks so much for your time today. Really excited to chat. [00:01:42] Ana: Thank you for having me. I'm very pumped to be here with you among so many people that I admire. That have been on the podcast as well, so thank you. [00:04:05] Phil: Awesome. Yeah, I appreciate you saying that. I'm a huge fan of the experimental marketer framework that you put together. Spent a lot of time reviewing it and studying it ahead of our chat today. So I feel like there's a lot of jumping off points from the framework that you created there, but maybe we can start by. [00:04:22] Chatting a bit about this, like strategic angle that you were trying to permeate through the framework itself. I think you've made it to help marketers have a more strategic view, be more hands on with Martek, but also this idea of becoming better allies and using and working together. Getting like the most value as possible from our tech. [00:04:41] Martech Leaders Must Become Systems Architects --- [00:04:41] Phil: when I was reading through it, the framework seems to be promoting a mindset shift from being a specialist in certain Martech tooling, like knowing the tech to taking a step back a little bit, like being more bird's eye view and understanding systems thinking and marketing, but also like other business applications, [00:05:00] we're moving beyond like the typical advice of how to be better in Martech. [00:05:04] Learn to code or get these certifications in these three tools to focusing more on becoming strategic architects, if you will. is that a fair assessment? Why walk us through your thoughts [00:05:13] Ana: Yes, absolutely. The idea of the framework, which was really based on my own professional experience, and everything that I have been doing professionally, is really to give that very systemic view. Help marketers really see my tech as a tool that can help them not only achieve their objectives in terms of customer engagement, conversion activation, but also in terms of improving the marketing processes themselves, right? [00:05:44] Helping the marketing teams and helping other teams that are involved. So it's really a framework to help marketers lean in. Into those conversations instead of just leaning out and leaving to the other stakeholders, leaving to IT or just [00:06:00] leave it to ops because the marketer will have a better view of the processes. [00:06:05] that could be improved with the technology, for instance. So that's where I came from with the framework. [00:06:13] Phil: Very cool. [00:06:13] Lessons from Stanley Black & Decker's Data Template --- [00:06:13] Phil: Can you maybe like share, a story of a marketing team that Transform, if you will, like this idea of just collecting tools and building a stack to actually building systems that are interconnected and it's not just for marketing, like what key shifts are like supposed to take place in that, like thinking and operation, that you think made a difference there, like curious if there's like a story that, that jumps to mind. [00:06:38] Ana: Sure. in one of my most recent experiences, the idea was to implement a Martech that would help the company collect end user data. So here we're talking about a B2B company and this B2B company really never had a lot of information about the end user, the person going to the distributor or going to a [00:07:00] retailer to buy the product itself. [00:07:02] But then they realized that if they had this information, not only they could generate demand on behalf of those retailers and distributors, but could also tap into this end user data when developing new products. Or when doing the go to market strategy, right? So by having that information, we could be more, more strategic. [00:07:27] Because we had different teams in different markets, working with different brands from the same company, and we needed to empower them, but we also needed to give them freedom within a framework. [00:07:39] So even if they didn't have a specific. Budget to go and develop an email from scratch. They could still sending you and they could still generate the demand on behalf of their local partners, local retailers, etc. So that's how it all started. And at the beginning, we had our marketing [00:08:00] automation tool. [00:08:00] At the center off that stack, and we thought that would be enough for us. And then we realized that it wasn't right. Because on the marketing automation platform, you usually have the latest data on the customer, for instance, which is the data that you're going to use for the activation. Perfect. But for standard black and Decker, in this case, we realized that The most important part for the company was really understanding that end user and having that 360 view of the user, right? [00:08:33] And that's when we realized, okay, so we need a de facto database at the center of the stack. And at the time I was working very closely with the team that used to be called the data science team for the company. And because all the questions that we had about the database or around the database were marketing related questions, right? [00:08:55] The team. Ended up deciding that a customer data platform would [00:09:00] be the best database because it really helps answer marketing questions, right? Because the users would really be marketing or marketing adjacent teams, e commerce teams, et cetera. So that's how we started this MyTech and then we brought the CDP to the center because we could then get information from different sources of data and unify it. [00:09:25] So that we can use that unified view for the activation, right? So that we know that if Anna joined a year ago and she's more into e commerce emails, so that can help us better cater the emails to her. Or we can have specific journeys for people that are in this cohort with Anna, right? So that's when we started to be able to see those things. [00:09:49] And again, because the Martech stack was really agile, So It allowed us to also customize for different brands and markets.Because some of those [00:10:00] may have even like different data points that they're collecting or different sources of data. And that's okay, because the CDP can ingest that data. But then we also created the whole data governance approach, which what really changed, in my opinion, what really helped the CDP implementation was the data template. [00:10:21] our agreement. With them was the following the data template is the language that the CDP understand that's the only language that the CDP understands. So if it doesn't come formatted in that language, we won't be able to see it. The CDP won't understand it. That doesn't mean that the data is lost. [00:10:39] The data won't be lost. The data will be on ingestion table in the CDP, but it's going to be there. It's not going to make its way to the Centralized or unified profile for the end user, right? So with that and by sharing that responsibility and by Going through the data template with [00:11:00] our business stakeholders, the marketers, the e commerce managers, that was really what made a big difference because then they became owners of that data collection and that data activation. [00:11:11] And then they understand that if they set up the form right at the beginning and they use the data template, labels that we have defined in the data template, then the data will flow automatically from the CDP or to the CDP, from the data source to the CDP. Awesome! You don't have to do anything. Right? [00:11:30] 24 to 36 hours, the data will be there, unified in the marketing automation tool. Go for it. But if you don't, if you just leave that form for a vendor to do whatever they want with it, I don't care. That's too technical for me. then the data won't be on the unified profile. There is a do over, so we can do a do over. [00:11:54] No worries, we'll help you. But then you will need to format. You need to go to that [00:12:00] source of data, download, format in a very specific format that we have for you, and then we'll do what we call the manual upload into the CDP, and the data will be there, but it's going to take more of you, and then you will need to go to e commerce manager. [00:12:14] So that was the agreement. Implicit agreement, and that made a huge difference because with that they really understood that it pays to pay attention to some of those details, like the data labels on the forms at the beginning. Because then once that's done, it's a gift that keeps on giving. It's going to be there for you. [00:12:36] And I also worked with them to make sure that they understood that the data template is a living document, right? It's not supposed to be like super, how can I say, static. No. There's a new, oh Ana, we need to, you know what, we need now to collect the occupation, because that's important to us, if you're an electrician or a construction. [00:12:57] manager or what have you. That's fine. [00:13:00] Let's do it. Totally. Then we get together, we decide what's going to be the data point, which options we have, we record that, we can translate those data options into whichever language we have and we're going to use so we can define it in English and then translate into Portuguese, Spanish, Korean, etc. And then that's it. We are, and that also allows for our senior leadership to compare things, comparing apples to apples. [00:13:30] And now there is a minimum Set of data, which and that's also something we define. What is the minimum criteria? What are the minimum number of data points that we need? in order for an end user to be in our database and be able to receive email communication. So we need the explicit consent, for instance, right? [00:13:52] We need the opt in. okay, let's make sure that the opt in is always there on the form. So does your form have the opt in so that we know that [00:14:00] they consented? So those were the changes that really took place. And the beauty of it is that this took place. Few years ago for a region like Latin America and nowadays they already know they go to the data template, they create their form. [00:14:14] So it requires minimum interaction with me. I barely review those things anymore [00:14:21] We can do more, be more experimental, be more innovative. But if anything, we can also keep the lights on. We don't need to turn it off. [00:14:30] So all this experience actually informed the experimental marketer framework. And that's how I got to the framework, going through this experience first. That's how it came to be. [00:14:42] Phil: Very quiet, really appreciate the practical and full story there. there's a lot of jumping off points, that I'm really curious to ask you about. There's, one that kind of stood out, [00:14:51] How Data Governance Creates Marketing Intelligence Systems That Scale --- [00:14:51] Phil: I feel was like the thesis of your example is like data governance and getting data as clean as possible at the point of collection. [00:14:59] Like you [00:15:00] talked about forms a lot and. Obviously the folks working in the marketing automation tools, the point of collection is going to be the form figuring out what are the fields and standardizing that, like you talked about, but typically for a CDP implementation or even like adding a new tool or new features to an automation platform, data collection doesn't just include form stuff, right? [00:15:22] There's like a whole bunch of other first party data. We're talking about like web activity. We're pairing that with product activity. Are they viewing certain pages on this site? We want to append that information when they're created in the database. So I'm curious to ask you,I know that based on that experience, like you, you've got a lot of experience at, cleaning that stuff up. [00:15:42] Can you explain maybe like, how do you design. Those feedback loops, not just with the marketing teams, creating the forms themselves, but maybe the data engine team who's set up with all of the tracking codes from the CDP on the site or, the product team, who's also [00:16:00] adding the CDP tracking code to the product pages themselves, like what patterns have you seen be successful with data governance systems outside of just forums and like data engineering teams? [00:16:10] Sure. So yes, I started with an example that includes collecting attributes, right? But, as you mentioned, we also can collect behaviors as the example you mentioned. And those are also Documented in the data template in this case, right? So what that helps is that the business stakeholders understand how the, how that behavior is named inside the CDP. [00:16:38] Ana: So they understand how they can segment based on whichever behaviors we are collecting. And then when it comes to an analytics team, for instance, they also have access to it because they also understand how they can pull the data. For segmentation and for reporting and in the case of when we first implemented this smart tech with [00:17:00] the CDP at the center, we also had some reporting that we did. [00:17:03] And we started with very easy reporting like Google sheets, people tables, just at the beginning as almost as a proof of concept. So you don't need to go fancy or anything, but the data needs to be easy for Business stakeholders, for instance, to see and say, Oh, okay. I see the data flowing. I see now new end users coming into the database because I have a score card and I go to the score card and I can see my market. [00:17:32] I can see my brand. And if that score card's not growing these days and I have a campaign going on, for instance, then I know that is an issue. And then I can go back to Anna, for instance, and say, Anna, I think that I messed something up and the data is not being collected properly. Or conversely, I can see the data and I understand that if I want to compare the performance of a given campaign throughout different markets, because that also [00:18:00] happens. [00:18:00] We have a new product that was launched in different markets worldwide, and we want to see the behavior of people interacting with that content. Perfect. And then when we see it, if we see that the content, that content is packed or named differently, throughout those markets, it's going to make it harder for us. We can do it, of course, but then again, it requires more, how can I say intervention versus something that it's easier to see. So let's say we have someone who is in charge of deploying those campaigns with the new product. And it's easy for that person to say, okay, I see how that Canada and U. S. [00:18:41] are performing because it's the same tracking. Everything is the same. So it's super easy versus, Ana needs to be there. Someone needs to go there and translate what happened in Canada so that I can compare to the U. S. or vice versa. [00:18:54] That's very important. So the feedback loop would be, the [00:19:00] reporting. [00:19:00] So that's a very important part. So they need to see to help catch and understand, right? They need to go through the process of putting together a report that may be harder because things were not properly tagged at the beginning, right? So that we can say, you know what, if we tag it properly from the get go, cool. [00:19:18] You don't have to do this work. Imagine if, every Monday you can just, pull up the report without having to do any interventions and be able to report on that easily. Instead of going through those interventions, or even worse, I've been in situations where when a stakeholder had such a question, someone would call a vendor, and the vendor would prepare like a PowerPoint, and now, and then you end up with PowerPoints from different vendors in different markets. [00:19:47] And how do you compare those, right? how do you know if the data is really, you're really seeing the data as it is, or if you're seeing the data as the vendor wants you to see the data, [00:19:57] Phil: yeah, hahaha, [00:19:59] Ana: [00:20:00] discussions, those are a lot of the discussions that I bring along with the process, with the governance. [00:20:04] because those are the pros. Yes, it's gonna be hard at the beginning. a lot of governance, especially for MARTEC, has a lot of, front work, as I call it. I don't think that's the proper nomenclature, but you upfront your work, right? You do the work at the beginning, and then that work keeps on giving. At the end, because if you have campaign tagging nomenclature that is used and it's just modified according to the campaign, but it's the same one for all brands, all markets, or all business units inside a company. Awesome. Because then you did the work of creating that formatting, but then from there, it's going to be super easy. [00:20:43] You can have the intern creating your tagging, or you can have the director creating your tagging. And we'll work the same. Perfect.Or you can have a vendor helping, but then we can pull the data ourselves and check them. The vendors work as well. [00:20:57] Phil: So there's a lot of those [00:21:00] discussions because my experience actually is with like older companies, not digital companies, not the software service industry. [00:21:10] Ana: And in those cases, a lot of the marketers or marketing adjacent positions are not as close. to understand those things yet. So there's a lot of education there as well. [00:21:23] Phil: education and change management and introduction to new ways of doing work and graduating from legacy tech. I'm sure there's a long list of stuff there, but I feel like one thing that comes out of your answer that resonated with me, you're also, you're almost like building this thesis that It's incredibly important for marketers at digital companies or like older companies to take ownership of customer data instead of just leaving it to technical teams. [00:21:51] I think like forms is a bit more approachable for marketers, but all of that other box of first party data, like tracking stuff, especially when we're talking about [00:22:00] CDPs, usually the it team is like Picking up that stuff or like the data team or the technical team. ​ [00:22:05] [00:23:00] [00:24:00] [00:24:06] Phil: [00:24:06] How to Improve Your Customer Data Literacy Without Learning Python --- [00:24:06] Phil: what advice do you have for marketers to like marketers listening right now, or just like Phil says this all the time that like marketers need to get closer to the customer data and pick up better data literacy, but they're super busy already with a bunch of stuff on their plate, they're focused on promotional, their growth, like that already have a bunch of operational and technical responsibilities. [00:24:26] How can, what advice do you have for marketers to like, Take first steps at developing a more holistic view of marketing and rev tech, and especially folks that are maybe a bit earlier in that, like customer data literacy journey. [00:24:39] Ana: I would say go talk to the IT teams, to your Ops team, so that you can understand how the data is collected and unified. and then again, you don't need to go and understand if they're using Python or whatever language, no. You need to understand, okay, I get data from those data sources. They [00:25:00] come to a place where they're going to be unified. [00:25:02] first of all, and that's a question that I was asked. If we collect data from different sources of data, is there a hierarchy of those sources of data, right? Is there one that is more reliable than another?in some cases, we would say, you know what, if we have data coming from customer service, from a Zendesk, let's say, That would be preferable than the data that comes from a giveaway promotion, because people that are looking for customer service, they're going to give more data or more truthful data or what have you, than someone just going for a freebie, [00:25:34] Phil: Yeah. [00:25:35] Ana: right? [00:25:35] But those things are things that the marketers are the most prepared to discuss. And that's the thing. Marketers are, and I used to be on that camp as well. Oh no, things are just resolved like magically. And then I had the technical people asking me, telling me like, no, there is no magic. [00:25:53] There's a lot of decisions and those decisions are really going to impact the way you work. So [00:26:00] are you sure you don't want to be part of those conversations? And I'm like, yeah, you're right. Let me be part of those conversations. So that's how I got involved because at the beginning, I also thought no, you decide and they're like, but what if I'm not, the information that I'm prioritizing is not the most reliable source of data, wouldn't that affect your activation, your promotion? [00:26:20] Yes, it would. So why are you not here with us? So that's how I got involved. And that's what I would suggest. I know people are super busy. And I know that marketers nowadays are very involved in promotion, right? And sometimes in the acquisition piece. okay, I acquired. Yay. Awesome. Next. But if you take the time just to understand how this data comes and how it is unified so that when you are doing your campaign planning, you know if you can tap into that data and what that data can bring to you and how it can help your campaign and your promotion. [00:26:58] That already puts [00:27:00] you way ahead of a lot of other marketers, a lot of other professionals, because a lot of people are not doing it. [00:27:07] And you don't need to invest a lot of time. You don't need to know programming. You don't need a such and such certification to do that. You just need to be curious, to knock on people's door and ask, I just want to Have a look here. [00:27:20] And what happens is that when you do that, you also contribute to the technical people, to the IT team, or to the ops team, right? Because sometimes they are making those decisions on their own without guidance from marketers because the marketers are like, okay, that's not my thing. You take it right. and. [00:27:38] They're making those decisions sometimes prior to an error because they're not the ones activating the data. They're not the ones collecting the data. They're not close to the campaign as the marketers are. Right? And that's exactly what I want to change. It's that mentality that, oh, I can just leave it to my vendor or leave to IT or to ops and they can do it [00:28:00] and my campaign will perform and that's it. [00:28:01] No, let's make sure that we understand. [00:28:04] Give Your Privacy Policy the Love it Deserves --- [00:28:04] Ana: And the other thing I would say which that one, I think it's going to be like a hot take, but I would strongly suggest for you to read your Privacy policy. Read privacy policy, people, and nowadays you can throw it on quad or on chat to TP and have it like bring the highlights to you. [00:28:24] No worries. It's [00:28:25] Phil: Remove the law beak out of [00:28:27] Ana: Exactly. give it to me easy and simple terms. You can totally do that, but the importance is that you understand what the expectations are from the customer point of view, [00:28:39] Phil: Because a lot of times when we talk about, let's add a new point of data to our CDP. Okay. Are we, do we have content against that point of data? [00:28:50] Ana: So if I collect, I can use to improve your experience. In our digital properties. No, we don't. So maybe it's not time to collect that [00:29:00] data yet. The data point yet. Let's hold off, right? Because the data privacy policy says that we only collect data that we can use to improve your experience. No more, no less, right? [00:29:13] And sometimes with marketers, especially Oh, I want all the data today. Oh, let's ask everything more is more. And it's yes and no. Because expectation is that we're going to use this data to improve the experience. And if we don't, then we are not delivering on our promise.So even those things, I was like, let's read it. Let's make sure that we understand that. So a lot of times when we get together to discuss those new points of data, that those are the points that I'm going to bring back. and a lot of times I'm like, Oh yes, that's right. We need the content. [00:29:43] So then they work on the content, why we are starting to. Develop or to collect the data. That's fine, too. We can do things in parallel. But then soon enough, we'll have content to then customize your experience in our digital properties using the data you gave [00:30:00] us.So those are the two main points, which again, I know it's usually not what marketers like to hear or not what they do, but it's what can differentiate you. And all that, a lot of the, Governance. I actually came up with it by discussing with it by discussing with the data scientist or the data integration engineers, right? Because any good data integration engineer, when they see that what they do all day long is just to clean data and reconcile data that comes like all messed up because business stakeholders do not bother. [00:30:35] So not even try to collect this cleaning, that's when they're like, okay, that's not the place for me. I don't want it. No professional would like to spend their time just cleaning data and reconciling data, right? Versus the data comes in as clean as possible. So it's really about connecting new sources of data. [00:30:55] It's really about how is it that we can prepare better data. Data sets for [00:31:00] reporting. How is it that we can start thinking about being predictive in any way we want, right? So let's see how much data we need to feed those models, etc. Those are the conversations that usually data integration engineers or data ops people like to have. [00:31:16] But if they're just dealing with like messy data because marketers cannot bother in tagging their campaigns correctly. Fixing a form, right? Then it's harder. It's harder even to develop that relationship, that partnership with those teams, right? So the moment I was like, okay, I understand that. So rest assured that we are going to be the front line to stop like unclean data. [00:31:44] We will make out the most in our power to make sure that they're gonna come as clean as possible so that we can really go to the next level. That really strengthened our partnership, because they're like, okay, I can count on them. They are partners [00:32:00] with us in collecting and reconciling and unifying that data. [00:32:04] It's not oh, you take here and do whatever. no. We're invested. We have skin in the game. So that also helps a lot. And it helps a lot with analytics teams as well. The teams that are going to put together the dashboards. [00:32:17] Phil: come to you and you can say, okay, those are the business rules. [00:32:21] Ana: This is how the data is collected, right? So business rule, for instance, Oh, anytime we have a campaign that is e commerce, the word e com will be on the tracking tag. So whenever we talk about e commerce related campaigns, make sure that we pull the e com out of the tracking tag and you're going to be good throughout the many markets, many brands. [00:32:41] So we document those things and it makes it their work also much easier. And then it gets more interesting because we can do the fun stuff, right? The promise of Martech is really to help marketers and the other stakeholders involved in being more strategic, in being more predictive, right? [00:32:59] [00:33:00] Nowadays, clean data also feeds systems. like reinforcement learning or AI or casual AI, you name it, all those systems, they need data and they need clean data. Otherwise, it won't make sense. Or you will spend a lot of time cleaning the data in order to make sense to see if it was worth it. Is I know, right? [00:33:21] Let's make it easier so that we can then realize that value. Oh, we can already be predictive or we can save money on our campaigns and make our little budget go a little further. All those things. So that's pretty much the, I would say the essence of the experimental marketer framework. [00:33:40] Phil: Very cool. I think that's great. Great advice. I feel like that's, it's a bit of a two-way street. Like I think, obviously marketing ops folks, Martech folks, they need to be. Curious to, like you said, knock on those doors from the it teams. And, I've had differing experiences there too. there are some it and data teams that [00:34:00] are more open to opening those doors and having those conversations with the Martech folks. [00:34:04] And,it's different with data scientists and we talk about, the analytics team as well. [00:34:10] How Marketing Ops Became Department Translators in the Enterprise Jungle --- [00:34:10] Phil: Like you've got a lot of experience with bigger companies and all of those separate departments there. And I feel like that's what makes. The role of the Martech pro really interesting in that, like they're almost like a pseudo product manager with all the stakeholders and all the areas of collaboration that they have. [00:34:28] Like you just said, the role of marketing ops is supporting marketing and all of the other stakeholders that. Are part of this journey of implementing Martech. It's not just supporting marketing. so I'm curious to ask you, like with your experience of working with these bigger teams, all these cross functional teams, how do you help teams assess potential ripple effects across stakeholders of Martech changes? [00:34:54] Like what's your framework for impact analysis of changing something on [00:35:00] the collection side of data or the activation side, like how do you just help All these stakeholders bridge the gap, between these different teams during like big hairy Martech projects. [00:35:11] Ana: So a way of doing this is really again, leaning in, talking to those teams and asking them. So what is the pain point, right? Because a lot of the, so again, if we collect data that is not clean, we're increasing the pain point for IT or data ops.So moment that we improve our process as marketers, that is going to positively affect the other teams down the road as well. [00:35:37] And if everything's well documented, it's much easier, versus finding people throughout, I don't know how many platforms, different sources of data, different data points named differently, it's much harder. So all the, so by helping in. What seems to be like something very simple and lineal. Markers can help all the [00:36:00] way through IT, through Ops, all the way to the lawyers, all the way to data privacy and data security. [00:36:06] But in order to know that, you have to go and ask. You have to lean in, right? You cannot say, oh, that's not, no. I can be bothered. I'm doing the campaign, but I can be bothered. No, let's try to be that partner, right? I want marketers to be good partners to IT, good partners to marketing ops. good partners to the lawyers, right? [00:36:28] Because what happens is that when you're talking to those people, they make a lot of fun of marketers. And a lot of the jokes, I'm like, Oh my God, it's true. I cannot even complain because it is true. that is the case, unfortunately. So in order to not be that Gilbert cartoon type of stereotype of marketers,Let's be more hands on. Let's be more proactive. And let's be there. And again, I don't know how to code Python. I don't have any fancy enterprise [00:37:00] certifications. You can even look at my LinkedIn. I have some stuff that I've learned, but it's not there. It's not what I go by. But I still can help because I know marketing processes. [00:37:11] I know pain points. I know how hard it is for marketers to understand those things and to get started so I can be the one helping them get started and then they take it on. It's easy. Once it's in place, it's easy for them to take it on and be those very proactive partners, not be the stereotype marketer anymore. [00:37:34] Because they know, and then they can be in meetings with technical people and hold their ground and have meaningful conversations. And it's a beautiful thing when that happens, because on the technical side, also, they get so happy when you explain that it's a campaign where we lower the cost of acquisition because the data was so well managed. [00:37:55] They get so happy and usually they don't even have that feedback. It doesn't make it back to [00:38:00] them. So sometimes in a lot of calls with DataOps or IT, it's about telling them what our idea is, what type of engagement we want to bring, and what type of data we want to use, and they get so happy. so excited. [00:38:12] They're like, Oh, that's so interesting. And what happened? And then the next call they will ask me, what happened with that campaign? Did it perform good? How was it? And what are your thoughts? So it's so interesting when you connect those two things, they work so well together. Unfortunately, there is still far away in company and again in large companies or in legacy companies that are not digitally native, right? [00:38:37] Because I understand like companies that are digitally native or smaller startups, they may be tighter and the marketers in there may be more hands on. But in my world, in my experience, it's not there yet. [00:38:50] Phil: Yeah. I've definitely have more experience on the startup side and the digital native side, but I think that's something that still happens regardless of the size [00:39:00] of company is you just said there, this idea of holding your ground and like something, there's a lot of positive stuff, [00:39:06] Dealing With Conflict in Martech --- [00:39:06] Phil: but sometimes there is conflict when it comes to Martech implementation. [00:39:11] And this is something that I've pretty much like all of my past roles. Like it's, like we're implementing something new or we have a problem. We're trying to find a solution. I, as the person who's heavily involved with Martek, and sometimes I was the marketer on the marketing team, I've done my research, like I've chatted with other experts who face this problem. [00:39:30] Problem. I've read a bunch of guides. I read other people's frameworks. I did my own research. I have my own past experience. I have a good idea of how something should be solved, but sometimes this idea isn't shared with other technical counterparts who maybe didn't do the same research or don't have the marketing use case or background that I do. [00:39:51] What's your playbook for getting alignment between marketing and technical teams when it comes to conflicts like this? Like, how do you help both sides [00:40:00] understand each other's constraints and requirements before conflicts arise? Other than obviously knocking on doors and having those conversations, like what else comes to mind? [00:40:10] Ana: So what I also like to do is to start small.for instance, with implementing the CDP, we started with a POC, a proof of concept that was super small, was we got two markets, one brand each market. That's it.So one of the markets we got one that in this case, Brazil, because for one of our brands, Brazil has a specificity that it's only theirs. [00:40:36] We don't have in the other markets. So we're like, okay, let's get that case. That's a little harder for us to test just to make sure that we're kicking the tires in the best way possible here. And then we could see. Okay, so we did the POC and we were able to see the data coming, right? I was able to see the data unified. [00:40:58] I was able to help on unification [00:41:00] again, prioritizing which sources of data, etc. And then the data was ready for me to use in the marketing automation platform. So there we could already test against a lot of the pain points we had. The pain points on data, cleaning and unification, and the pain points on us having the data ready for activation. [00:41:20] And it worked well. Okay, so we were able to take those pain points from the different teams. Yes. And that also helps us with data privacy and their security because we did it with API's and everything was done properly, etc. yay. Okay, so we got that done. Is that okay for everybody? before implementing anything big, anything major, we always do something smaller. [00:41:47] And then we kick the tires, and we reconvene, and we analyze it against the criteria we had when we first selected. we had a list of criteria. That's what we want to do. We did the POC, went [00:42:00] back to those criteria, checked against our repaying points. And then it worked. And then we proceeded to implementing to all like 20 markets for brands each back then, right? [00:42:12] And then, okay, because if we had any comments or any issues or any questions, we would say, you know what? We did the POC. And that's what we saw, and that's why we are where we are now in the implementation. Is that okay? Yes. [00:42:24] Phil: Yeah. [00:42:25] Ana: So that's how we [00:42:26] Avoiding an Endless Rabbit Hole of POCs --- [00:42:26] Phil: POCs at the same time? what if the technical team is just I don't want to do a POC for that thing. I think the solution is something completely different. And is there ever an area where you're doing one POC for this one side of the conflict? And we see how that works. [00:42:41] We take notes and We don't make a decision until we do another POC. Like how many POCs do we do to satisfy conflicting opinions before we just put a line in this and say this is what we're going to go to bat with. [00:42:55] Ana: right? So it really depends on so the most important part here is to [00:43:00] define what you want to achieve with the platform through the POC, right? So in our case, we wanted to have that unified view. So that was. One of the most important criteria. We need to have that information over time. [00:43:13] Over time is important to us because we don't know the end user. We are not used to have this data. So we need to know when Anna became part of the database, etc. So that I have that more detailed view. So that was first one, right? Because otherwise we wouldn't need the POC. We could be just using the marketing automation platform and sending the latest data or relying on real time use cases. [00:43:40] A lot of companies do, and that's fine. But it was not our case, specifically here. So we need to define that. We also took into consideration the pain points. So that's what I want, like what we want to achieve, and then the pain points. So the pain points, we have small teams at this point, right? So we need to make sure [00:44:00] that we also automate some things that allow us to move. [00:44:04] At a good speed, a timely fashion speed with the teams as they are now, without a lot of dependencies on vendors, consultants, because we don't know if we're going to get that budget at this point. Does that check? Check. yes.So a lot of, it really comes Down to having that list, but to get to that list, you need to have a lot of conversations with the stakeholders, and you need to have some conversations where I was like, okay, so tell me what the pain point is. [00:44:33] I didn't ask in those terms, but it was a lot of discovery to understand where the resistance was. Resistance was because sometimes the resistance was on this, oh my goodness. They think they're gonna start sending me a lot of unclean data, and I need to be cleaning data. I need to hire someone. I don't know if I have the budget. [00:44:51] What if I don't have the budget? But sometimes the person has all that knowledge, but she's not bringing it to the call.So a lot of it was also me [00:45:00] probing a little bit. So what is the concern here? It's the concern that the data won't come clean because that can be resolved. It can be accommodated. [00:45:08] We can help. Give us an opportunity to test that and we can show you that we can do that or put that as a constraint. So whenever we are analyzing those platforms, I know that I cannot even think of increasing the team to ingest or digest data. Okay. In order to get a platform, if it requires for us to grow the team, it's not a good platform for us. [00:45:32] Remove it. One of the criterias also that we had with the CDP back then was that the company, the CDP company needed to guide us. Because some CDP companies that we saw back then were very,self service, right? Which then it works super fine if you have a team of developers. But we didn't. We had two. [00:45:53] So that was one of the criteria that we put there. We need the handholding because otherwise we're going to be running circles [00:46:00] for too long. And that's not advisable at this point. So all those things we had to have, we had very, How can I say Frank conversations, And it took us a while to get there really a while. but it was a lot of back and forth, right? A lot of, so in our case, when we got to the POC, we already had selected a tool because it had already met the criteria. So the POC was really to kick the tires and make sure that at the end of day, on the day-to-day basis, it would really meet what we needed. [00:46:32] And you did awesome. Otherwise, we would have to go to the runner up or we start the process all over again and see if we could find another vendor or if another type of platform that would meet our needs, but there's a lot of conversations here and a lot of so I think that. I would say for marketers, if you bring the pain points, if you bring the issues that you have in your team and you open that up to the other stakeholders, that is very [00:47:00] helpful, right? [00:47:00] Because then they can understand, you know what, the issue for us is that we have very limited teams. We have a limited budget. So anything that helps us decrease the cost per acquisition will help. It's going to be awesome because that's a pain point for us. We need to do more with less or more with the same, right? [00:47:21] Or conversely, I need the teams to be able to do their own stuff or to tweak a template inside the platform in a way where I can review. Or in a way where that is recorded because if there are any errors, we can catch it and rectify it, right? So when we bring that up to the other teams, they're like, oh, okay, I understand. [00:47:44] So my team also has those type of pain points or limitations. So we need to take that into consideration too, right? And those conversations, of course, you can have external Consultant vendors helping, but a lot of those [00:48:00] conversations really need to take place within the company, right? So what are the teams are going to do on a day to day basis with those? [00:48:07] Because the consultant won't have that view a lot of times, or the vendor won't have that very in depth view, but you do. So that's why I tell. Marketers, lean in because you are the one who knows those things. You live and breathe that. Don't let someone else decide. Don't let a vendor come or a consultant come and decide that for you without your input. [00:48:30] Go and make yourself heard. Bring your experience. Bring your processes. And that is how you can contribute without knowing how to code or etc. That's the point. [00:48:42] Phil: no, I think your advice is really spot on there. I love the point about bringing the pain points and not just like complaining about stuff, but like explaining why this is a pain point. not just, I hate this tool, I hate this tool because I am limited in my ability to be able to do [00:49:00] this, or it takes a lot more time to be able to do this, or the data is a lot like, I really liked that point. [00:49:05] Cause I think marketers are really good at pointing out problems, but don't spend enough time explaining why this is a problem and assuming that everyone knows that The world of a marketer, right? there's a lot of assumptions there. And this has been a super fun conversation. I there's a lot of jumping off points. [00:49:20] We didn't get to touch, but I think that, you brought a lot of practical examples and real world stories here. folks are going to really appreciate that. [00:49:29] The Real Cost of Always Being On as a Marketing Leader --- [00:49:29] Phil: I got one last question for you. We ask, This question to everyone on the show. You're a CDP advisor, obviously a marketing leader, a keynote speaker, an author, a mentor. [00:49:36] You're also a mother, a home Baker, an amateur photographer, and a busy cat mom these days as well. how do you find balance between all the stuff that you're working on while staying happy? [00:49:47] Ana: That's a very good question. SoI like to, I have the moments of, for instance, my weekends, my nights, I like to dedicate to my family, to my baking, to the [00:50:00] kitties, to relaxing. But on the other hand, I'm always on the lookout as well. Because I like connecting dots. I think that a marketer's work is largely about connecting dots. [00:50:11] especially when you work for large corporations like myself. So I'm always on the lookout as well. So even if I'm like relaxing and like reading the newspaper or just browsing through LinkedIn, I may read something and I'm like, Oh, That is interesting. That connects to that conversation or to that issue that we were discussing. [00:50:31] So that may be an interesting hypothesis for us to test in order to improve the issue. So I'll save that as well for later conversations. So it's, I don't know if I have exactly like a proper balance, but I think that I can go on and off.Enough that I can connect the points without burning out. I'll put it this way. [00:50:55] Phil: Great advice. Yeah, definitely like the connecting the points advice there. Sometimes you [00:51:00] discover those points to connect when you're not doing work, like physically sitting in the office, you're going outside, walking or listening to podcasts or something. It's like a completely random, like fictional story or book. [00:51:12] And you're just like, Oh, wow. Like this could be applied to this. Yeah. And this is super fun. I really appreciate your time. I'm going to link out to your newsletter. As well as the framework for folks. So I'll probably put it up for the folks watching on YouTube. I'll have it up while you're going through it there, but really appreciate your time and thanks so much for [00:51:30] Ana: Likewise. Thank you for you. It's been amazing.