Start Trusting Your Data: A marketing data governance framework for CMOs

Transcript

Azure Alladin:
Welcome everyone, and welcome to today's webinar, Trusting Your Marketing Data, A Marketing Data Governance Framework for CMOs. We have a couple of speakers today, and before we kick off the discussion, we'll go through a couple of housekeeping items.

We'll have about 30 to 45 minutes of discussion, and then we'll kick it over to questions after we go through the discussion. Throughout the discussion, please feel free to drop your questions in the chat throughout the webinar. Some folks will be answering some questions and we'll save some at the end.

But, yeah. That's really all I have before we get kicked over. So, we have a couple of speakers today, like I mentioned. We have Buki and Evan, and then I'm Azure. I'm one of our Account Team Manager here in the US. But Evan and Buki, I'll go ahead and hand it over to you guys since that's what everyone is here for.

Buki Froelke:
Thank you, Azure for the introduction. I'm happy to share a little bit about myself before we get started. So, my name is Buki Froelke, and I'm a senior product leader at Google, specializing in data and analytics with a focus on marketing.

I've spent the last decade in product and leadership at startups, as a founder and now at Google. I developed a passion for marketing early in my journey. I was a youth and collegiate track and field athlete and Olympic trial qualifier, and I spent a ton of time with marketers. I was constantly fascinated by the passion they had for their brands, their ability to bring brand awareness, and the work that they could do could ultimately drive sales. So, fast-forward to today, and I now work in data analytics with a focus on marketing. So, I'll kick it to Evan.

Evan Kaeding:
Awesome. Thanks, Buki. I'm really excited to present with you today because I know that we have different backgrounds but have a similar passion for the intersection between marketing and data technology. So, always good to have a conversation with someone who matches the passion of my own in this regard.

A bit about myself. So, you might've seen me on a couple of different Supermetrics webinars. Happy to join this as well. For those of you who don't know my story, from the Supermetrics side of things, I was a Supermetrics customer for several years prior to joining the company.

So, straight out of college, I was getting involved with startups, helping launch, helping scale, and always at the intersection of marketing, analytics, a bit of sales, and a bit of customer work. I really found that Supermetrics was a tool that I could use to simplify my life, explore data, and deliver some good insights for all our customers, regardless of size.

Then, when I moved from the startup SMB side, I went to the agency side for a couple of years, where I saw Supermetrics being used for a variety of different enterprises, analytics tracking, and implementations. So, I saw, wow, this is a pretty cool tool. Love the way that it can span both to the smaller startups and deliver true value to large organizations as well. Decided I liked the tool so much, moved all the way out here to Helsinki, packed my bags, and have been here in Finland for the last around two and a half years or so.

So, it's been an excellent journey, just beginning, and I'm excited to share my experience with Supermetrics both before and during my time at the company here at Supermetrics. So, I'm excited to talk about our topic today, which is Marketing Data Governance For CMOs.

So, why exactly are we here today, and why did so many of you decide to come out to learn about marketing data governance? Not exactly the coolest sounding thing in the marketing industry, at least today, but I hope by the end of today, we'll be able to convince you that this is a conversation and a topic that you should be discussing thoroughly internally.

So, what are we actually doing here today?

So, what we've done at Supermetrics is a variety of internal and proprietary research, and one of the results of this research is the statistic you see here on screen today. So, we found that when we interviewed a variety of CMOs and marketing leaders from the industries we support, we found that at this point, over two-thirds of marketing leaders are saying to us that data's harder than ever to manage and analyze.

This isn't new, but it's growing in importance in the organization. One of the biggest reasons is that it's difficult to trust the data coming out of these systems and the result of these processes. When we look at the systems that have been built to support the decision-making that marketing leaders make, it's no wonder that marketing leaders say that this data is harder to manage than ever because a lot of the systems don't necessarily have the data collection strategy in place or the data governance to produce trustworthy data. So, this becomes a really big topic for customers we work with who want to get to the bottom of their marketing data and understand "which campaigns are most effective, where can I spend my next dollar most effectively, and how can I deliver results to the business?"

So, what we find and what we say at Supermetrics is most marketing problems end up being masqueraded as marketing data governance problems.

So, if you're not investing in your marketing data governance, it's going to be hard to measure the effectiveness of your market and your marketing and ensure that you're delivering the right solutions and the right messaging to your customers at the right time in their funnel journey.

So, that's ultimately why we're here. Buki comes from a strong background where she has a lot of experience working with teams and determining what that data culture looks like. So, keep that in mind as a theme as we move through this presentation.

We're not going to show you anything technical today. We won't show you anything that will be, by this media, by that media, or anything like that.

We're going to be talking about organizational principles, we're going to be talking about data culture, and how you can work with marketing teams and data teams to solve what we have found to be a pretty large problem in the industry.

What are the best ways to get started? So, when we look at what you're trying to accomplish with your marketing data, we recommend having an overarching data collection strategy. When we talk about marketing data governance, we first need to figure out what exactly we're going to govern, because it doesn't make sense to pull out a marketing data governance strategy if you don't know why you're collecting data in the first place.

The data collection strategy is really important because it allows you to determine exactly what you're collecting and, more importantly, why you're collecting it.

Because when we find that customers are collecting data for the sake of collecting it, give me all of the data, give me everything that you need, a lot of that data can end up going to waste. Unless there's a compelling reason for the business to collect that data, it's ultimately not result in an ROI.

Furthermore, it might muddy the waters between the data that you have that's valuable, and the data that you have that may not necessarily be producing that much value. Buki, one of the questions around this is, "Well, hang on. Maybe I want to grab all of the data, just keep it for safekeeping, but are there strategies and considerations that organizations should make when deciding what kind of data they should pull in for building their marketing strategies?"

Buki Froelke:
Great question, Evan. So, to paint the landscape of why these strategies become increasingly important. We think about consumers today. They're looking for privacy and personalization. For personalization, you have customers seeking that personalized experience that allows them to make the most informed decisions along their journey.

This will be important for marketers and will take place in their data strategy, journey, and culture. So, when we think about what's important for consumers, privacy, and personalization, we want to keep that in the back of our heads as we think about marketing data governance.

Additionally, consumers are seeking privacy, and legislation reflects that consumers desire privacy. So, when we think about what comes to mind, we think about GDPR and more.

Evan, to answer your question, you don't want to just collect all the data — what data becomes increasingly important? A critical key to navigating these challenges for marketers is their first-party data strategy. So, to answer your question, their first-party data becomes increasingly important to the strategy.

Evan Kaeding:
Certainly, yeah. You also bring up good points around the need for compliance with your local legislation, which is an important part of marketing data governance, where when you're bringing in all of that data, well, that's great. But when you're acting as a data steward, you do have responsibilities for that data as well, and you have responsibilities to your customers.

If you're prepared and need the systems in place to act as a responsible steward for that data, that data can become more of a liability than an asset in many cases. So, being strategic about the data you collect and the data you intentionally don't collect will be important for your marketing data collection strategy. I like the way you phrased that, Buki.

So, what exactly do we recommend when we talk about a data collection strategy? Broadly when we work with both brands and agencies, whether large or small, we see the following trends emerge. So, on screen, you've seen the three elements we talk about when we talk about a data collection strategy, and each one of these I'll go into has its specific benefit to the business and could have its ROI associated with it.

You'll see that this will be a key theme throughout the webinar— we don't want to do marketing data governance or anything with marketing data unless there's an ROI we can attach to it. So, let's dive into these individually.

Campaign monitoring reporting is the operational side of marketing data. So, this is building dashboards to automate the reporting associated with your paid media campaigns, search campaigns, analytics tracking, and whatever happens. The financial cost to the business, of course, you need to do reporting, which often is a manual task that can take up a lot of man hours or woman hours and can ultimately end up resulting in a significant amount of pain for the business and lost opportunity for investing in more important things. It's also going to be a bad look if you're overspending on your media or you're underspending.

Overspending is going to, well, it's going to make you look bad in front of the CFO and you're spending dollars that you don't necessarily have. Underspending is even worse because you're not delivering the revenue associated with those marketing dollars. So, you can tie a significant amount of value to ensuring that your campaign monitoring and reporting is accurate, automated, and continues to deliver insights to the business. That's the first bucket.

The second bucket is performance insights, separate and distinct from the campaign monitoring and reporting piece. Performance insights is evaluating the success of those campaigns, identifying the different audiences, the different campaigns, and the different channels that work best for your different marketing activities.

Buki, one of the things that I think a lot of people struggle with is they say, "Well, campaign monitoring and reporting and performance insights, that's kind of the same thing, isn't it?" Can you help us understand why these are different today and why maybe that wasn't the case in the past?

Buki Froelke:
Definitely, Evan, you touched on that. It's important that the idea of campaign monitoring and reporting performance insights felt like the same for the past decade. When you think of the campaign monitoring reporting, like you said, it's, where's your media being spent, how much is being spent? You step to insight and analysis and want to think of the same.

But today, with the signal loss approaching and emerging technology innovations, insights and analysis have become increasingly critical, evolved, and a separate space, than campaign monitoring and reporting. So, with that first-party data strategy, you can equip your business to be future-proofed, take advantage of emerging technology innovations, and navigate signal loss.

Evan Kaeding:
Definitely, yeah, and we're seeing marketers employ various techniques for understanding their campaigns' effectiveness. Whether that's based on their first-party data from their CRM or their transactional system, whether that's looking at in-platform or analytics-reported conversions. The whole notion around assessing the quality of campaigns and what they can deliver has changed and will continue to change as we navigate this signal loss environment. We see this as a separate data collection mechanism within your business.

The ROI associated with this bucket is fairly obvious, but I'll state it here. We can help make campaigns more efficient by delivering higher ROI or identifying and cutting underperforming campaigns. You decide what to do. If you want to reinvest in your other campaigns, that's great. If you want to save the business money and spend that elsewhere, that's also great. So, two major ways you can save and deliver value with performance insights.

Then lastly, we touch on data activation. Now, data activation is where we take that personalized, personally identifiable data, whether that's records from your CRM system or your transaction system, and we put it to use in various fashions. So, building retargeting audiences based on past purchase history could be segmenting your users for different email campaigns that get pushed out to your marketing cloud. It could be various mechanisms that push activations or push different conversions out to different conversion APIs as well. So, this is what you do when you take that first-party identifiable data and push it out to the different systems responsible for reporting on those conversions.

Now, that's going to have an ROI because it's going to make your campaign significantly more effective if you're able to deliver the right message to the right person at the right time. It's going to enable you to segment your audience and personalize those communications.

Buki, one thing we see at Supermetrics is the need for our customers today to get the right message to the right person at the right time. What data activation strategies have you seen that have effectively driven some results there?

Buki Froelke:
Evan. To touch quickly on what I love about this slide is the overarching idea of marketing data governance. We talk about data activation, that ability to take data from your CRM and email marketing platform and drive that data to other parts of the business to use that data for various things.

Like you said, segmenting your data in your CRM based on product preference. Sending personalized emails, building audiences on top of that data, and pushing that back to networks. So, marketing data governance becomes increasingly critical because a lack of strong data governance becomes a blocker very fast, for your ability to make sense of data and essentially leverage that data activation.

Evan Kaeding:
Yeah, a fantastic example. I think that this is where Google Cloud, in particular, is very well positioned, in the sense that once you have this personal data, this can reside on your cloud. That can be used for various enrichment purposes as well, where you can use tools within Google's own suite for building out clusters of users using various techniques, whether on the Vertex side of things or on the BQML side of things.

There are many pretty exciting ways to use the tools inside Google Cloud for this data activation piece. Whether that's segmenting your data or building connections to the different platforms you might have. Like Buki said, the piece that undergirds all three of these is the marketing data governance piece. If you don't have good marketing data governance, your campaign monitoring and reporting is going to be lackluster.

You might get by, and I've seen plenty of customers get by with lackluster marketing data governance.

They've still got campaign monitoring and reporting. They've still got dashboards and they managed to do reasonably okay. But as soon as those campaigns are over, how do you figure out which ones are the most effective? That's when you start to get into trouble. If you don't know which campaigns were most effective, how are you going to do performance optimization?

When we start to talk about, "Okay, well now let's figure out who our customers are, let's segment them by their purchasing behavior or their preferences, and let's activate on that." Well, you need a pretty high level of marketing data governance to make sure you're not pushing the wrong product to the wrong person at the wrong time.

In increasing levels of importance from left to right. Marketing data governance plays a foundational role in ensuring that you can deliver on these activities and get the ROI you expect here. For some examples of what we're talking about with the different kinds of data, we're collecting, campaign monitoring, and reporting. We're talking about things like campaign names for performance insights, we're talking about things like UTM tags, and for data activation, we're talking about a variety of different CRM systems or transactional systems, where you can push that data out for activation here.

Before I jump to the next slide, which is the marketing data governance piece, is there anything else Buki that we should add here before we get into the marketing data governance framework?

Buki Froelke:
Sure. Just want to quickly touch on the idea of why marketing data governance becomes so important. It's a part of the data culture of your organization. Being able to govern and control in a way that empowers segments all across the business. So, as we dive into this next section of the marketing data governance framework, we want to keep in mind how critical it is to your data culture and a reflection of it.

Evan Kaeding:
Yeah, definitely. So, let's dive in. So, after all, the title of the webinar is Marketing Data Governance Framework, so let's make sure we jump into it.

So, what are the elements of a marketing data governance strategy here? Really, these are comprised of three different elements that we talk about here at Supermetrics. We talk about data access, data quality, and data security. Let's define those quickly to know what we're talking about here.

Data access is ensuring that the right people within your organization have access to the data they need to make the most necessary decisions.

Now, let's go ahead and segment this based on whether we're talking about a large brand or whether we're talking about a large agency.

So, a brand is going to need to make sure that people have access to the data that they need to make on-the-ground decisions. Whether that's going to be a VP of marketing or A CMO, they might need some kind of high-level executive dashboard that brings in all of the spend and the different campaigns across their media footprint.

Whereas you also need data access for individual members on the ground who are buying the media, performing those kinds of optimization, and ensuring they have access to those accounts.

The data access piece of this ensures that you're getting access to the data to the right people, and importantly, you also have the set of permissions in place to ensure that that data is shared where necessary and is private also where necessary.

We'll talk a little bit about how that works with data security, as data access is fundamentally making sure people get access to the data they need, both for use and for decision-making.

Data quality ensures that when the data gets to the right person, they can interpret it and, broadly speaking, correct it. That it's corrected, it matches the company's goals and strategies. So, when we talk about data quality in the context of marketing, we're talking about do we have a unified naming structure for the paid campaigns, for the search campaigns, for our SEO, for our email campaigns, really everything that an organization might do.

That's what will be important because when we give the data to the stakeholders, we need to make sure that it's interpretable and broadly correct as well. Then finally, data security. This is how we ensure that we're following industry best practices, which most people would historically refer to as data governance.

We have IT security in place. We have data sovereignty. We're storing it in the correct regions. We have all of our GDPR and CCPA boxes covered. This is the data security piece.

Now, we talked about how this works for large brands. At large agencies, this corresponds very similarly, where you might be thinking about data access in terms of, well, I need to make sure that I have access to my client's data. Still, I don't want everybody in my agency to also have access to that data. How can I adequately provision my dashboards and reporting tools to ensure that data access is shared?

Same thing if we're talking about data quality. We need to ensure that the quality on behalf of the client is aligned with their objective, and, if possible, broadly aligned with the client's organizational data governance structure. That way, the activities that you as an agency are doing can feed into the global consolidated data access for the leaders in that vein.

Then, finally, data security. You need to ask yourself, if you're in the agency side of things, should I be storing this data on behalf of my customer or should I be storing the data on my customer systems? If I'm working with transaction or CRM data, data that's identifiable, who's the owner? Who's responsible for the security of that data? Who's responsible for the GDPR compliance aspect of that data?

These are all things that translate to the agency side of things. So, whether you're on the brand side or whether you're on the agency side, this is a really valuable framework for assessing what marketing data governance looks like here. Buki, you mentioned earlier data culture as well.

One of the things we see is that their marketing data governance reflects an organization's data culture. Do you have any insights you can share where you've seen this be successful or where you've seen this fail as well?

Buki Froelke:
Absolutely. So, I wanted to touch on a couple of things you said that were so critical, that idea of data access. It's that ease of connectivity and shareability. Being able to empower all users across marketing and business organizations with the data that they need to make great decisions. So, a data culture incorporating marketing data governance allows marketers to thrive in this space. That ability to easily connect to and share access to your marketing data comes alive when incorporated into your data culture.

Evan Kaeding:
Awesome. Yeah, and that's an important element of the piece, is making sure that when you share access to the right people, they feel empowered to use that data to drive decisions. As marketing leaders, you don't need to feel encumbered by asking or receiving questions from individual contributors about, "Can I trust this data? What should I do next?" The answer usually lies in the data. But if it's not trustworthy, that will make it very challenging for you and your team to effectively scale decision-making, which will be necessary to drive marketing effectiveness across the different channels you're working with.

This is usually what we talk about marketing data governance. There's a variety of different tools and mechanisms you can use to ensure that this is the case.

We're working on this here at Supermetrics in the context of what we call Hub. Hub is a tool that can ensure that data access is provisioned to the right people, with the right clients, and with the right data. Ensuring that you have tools for managing data quality, that meets the certain compliance standards you've set as the organization, and of course, following data security practices.

So, without diving too deeply into the product side of things, these are some of the things that we've been investing in as a company, as Supermetrics, to ensure that we can also adhere to a sound marketing data governance strategy.

But when it comes to data access, which is the first box here, we touched on a few different users and mechanisms for ensuring that the right users have access to the right data to make the necessary decisions.

This is a concept that we've been kicking around, and I think Buki. I have been nerding out maybe a bit on the sidelines as well, which is around what we're referring to as, call them, data access models or different kinds of data access solutions. I think Google's done a great job positioning a few products here. I'll let Buki discuss those and how they fit into this mechanism here. But when we talk about the difference between a centralized reporting structure and a decentralized reporting structure for data access, what exactly are we talking about here?

Centralized is where we talk about moving all of that marketing data into what you'd call an enterprise data warehouse or a marketing data warehouse in some cases. Historically, this might've been an on-prem data warehouse. Still, more and more, we're seeing this be in the cloud on something like Google BigQuery, and this tends to be secure, it's governed, it's owned by a data team or a BI team, and all of the data coming out of this ends up being very clean, very robust, and scalable as well.

I don't think we need to sell anybody at this point on the idea that a centralized solution is a good idea, but for those who are skeptical, of course, centralized is one thing that we strongly recommend to ensure that you do have a strong data culture, that you're sharing that centralized data and the governed data with those who need to make big decisions.

These are decisions that are made weekly, quarterly, and annually as well. These are the things where a centralized data solution works out well. But what is decentralized data access? We can define it in the context of a few products here. Decentralized data access is a different model where we empower on-the-ground stakeholders to get access to the data they need in the fastest and most efficient way possible.

So, in the context of Supermetrics, I'll describe it where you might have a media planner who needs to get access to their Google Ads campaigns, and they need to do that for a variety of different accounts because they're running campaigns across a couple of different countries or brands. That planner could then use the decentralized solution, something like Supermetrics for Google Sheets, bring that data down, analyze it very quickly, and really can make that decision in minutes without ever having to rely on or potentially create an additional set of workloads for the centralized BI team.
So, that's an example of how quick and decentralized data access can end up actually augmenting your ability to ensure that the right data is being put into the right hands of the people who need to make decisions.

Buki, Google has a great couple of products that map to these different centralized and decentralized models. Could you explain what those are?

Buki Froelke:
Sure. So, as Evan mentioned, we've been nerding out on the centralized versus decentralized concept because it speaks strongly to how you can leverage tools and applications.

When you think about centralized data in the context of Google Cloud, you're thinking of BigQuery as your data warehouse or unified data platform. Looker BI that speaks the language of your organization. Those are the tools, products, and applications that you can think of when you think of centralized data if you're familiar with essentially Google Cloud products and Google products.

So, when you think about decentralized data, as Evan mentioned, you think of Looker Studio. The ability to have control of building the dashboard that speaks best to your analytics and findings. So, this concept of centralized and decentralized is becoming increasingly important to your data strategy.

Evan Kaeding:
Excellently put. What we advocate for both brands and agencies isn't one of the other. It really is both, where centralized solutions end up being able to use a variety of large volumes of historical data to make things like trend analysis or MMM or potentially MTA much more feasible. Things that you just couldn't do in a decentralized environment. That's a very important invalid use case.

However, there's a separate and distinct need within organizations for a decentralized reporting model, putting the data in the hands of the individual decision-makers where they can get access to the data quickly, securely, reliably without creating another workload for the centralized data team, who ultimately needs to move necessarily through the different mechanisms to ensure that that data can be governed.

We often see that this ends up resulting in marketing data fast and slow. We don't want BI teams to be overburdened by ad hoc requests.
We've seen time and time again that BI teams say, "Well, hey. We're doing a lot of this work. We're centralizing this data, we're governing it, we're putting it in dashboards," but oftentimes they end up drowning in ad hoc requests that could be answered with something fairly simple as well.

Putting decentralized tools in the hands of individual users isn't something that flouts your data strategy or circumvents it in any way. It's something that enhances it, and we're encouraging our customers who want to move fast while still retaining the power of decentralized solutions to enable their organizations, both on the agency side and on the brand side here as well today.

So, these are the two different access models that we talk about. These are how they fit in the context of our different marketing data collection strategies and our marketing data governance process. What does the actual process look like if you want to start with these different mechanisms? First, what's most important is getting executive buy-in, and I think Buki here can coach us through some good strategies here for getting executives bought in and ensuring that the data culture is overall aligned with the organization.

Buki Froelke:
Definitely Evan. To speak to that, how do you get that executive buy-in as you explore marketing data governance within your organization? What becomes increasingly critical again is data culture. It's that ability to say, "Hey, the perspectives across the business matter to our governance." That ability to make sure that everyone has access to the data they need in a safe and secure way.

So, as you continue to engage with your leadership, go to your data leadership and make sure that data leadership and marketing leadership are aligned. Marketing data governance is a collaborative approach, not just a silo. Just as we talk about data silos, it's that communication silo. Being able to step away from that and have a collaborative approach to marketing data governance between your leadership from data along with marketing as well.

Evan Kaeding:
I couldn't agree more. Coming from the Supermetrics side, I can't tell you the number of times I've been on calls with customers for whom it's the first time that the marketing team is meeting the data team and vice versa. We are all joined today to discuss your marketing data plans for your organization. It's great that eventually, we get these things and the holy matrimony of marketing and data in the same room.

But in many cases, it's too little too late. The campaign is run, the data's dirty, and we are still determining what's going to be our best next dollar to be spending. So, ensuring you can get that executive buy-in from both the marketing and data leaders is going to be increasingly important for any success here. The other thing I mentioned on executive buy-in is going back to that data collection strategy.

Why are you collecting that data? What is the ROI associated with your campaign monitoring and reporting, performance insights, and data activation? Do a proof of concept and try to explain how exactly it's going to save you time. It's going to save you money, or it's going to make you more money. That's going to be how you can get executive buy-in for a project like this. Once you've got the executive buy-in, it's time to build the data collection strategy. If you're an agency, I hope you're working with the brands you work with to inform what you recommend and what you see in the space as a good data collection strategy.

This will include everything from building out your alignment on what kind of data are we capturing, why are we capturing it, and what that data will be used for?

Because then that's going to align your marketing data governance strategy. You've decided exactly what kind of data you're capturing, how it should be captured, and then what standards should you put in place for ensuring that that data stays within a tolerable consistency?

Because again, it's great if you have executive buy-in. It's great if you have the strategy. Still, if you're not aligned on what the marketing data governance looks like, well, you're going to end up with data in a bunch of different prices. It's not necessarily going to be high enough quality for you to start using either way.

Then, lastly, starting small and building feedback loops. So, ensuring that feedback loops are in place ensures that you're maintaining the data access that you need for the right people, and you're putting it straight into their workflows. It's ensuring the data quality is baked into every process that you have for media execution, for SEO, for analytics, whatever that happens to be. If those feedback loops are in place, you can essentially have your own marketing data governance dashboard that can be reviewed by your team every week, ensure that the campaigns are tagged correctly, ensure that the leads that are coming in are tagged correctly with the right UTMs, and ensure that by the time that customer purchase data hits your CRM, it's ready to be segmented out and used in your activation strategy here.

So, we've worked with a number of different companies who have worked with marketing data governance on the Supermetrics side. I think these are really the four main steps that we see as being successful. This can be led by an agency but typically is going to be serving the brand's overall strategy when it comes to customer acquisition.

Whether you're doing this at a global scale, at a regional scale, or just for a smaller side of your business, this is going to be a great way to ensure that the data you're collecting is actually delivering business results by putting the data in the hands of the people who actually need to use it. Buki, anything else that you want to add on getting started or different ways that you've seen companies be successful in getting marketing data governance off the ground?

Buki Froelke:
Absolutely. So, I think what's important as you start to have these conversations about how to get marketing data governance off the ground for your organizations is to remember that at the most basic level, data governance is the practice of enhancing your organization's data so that it's discoverable, understood, protected, trusted across the organization.

So, if you start at that most basic level of, this is what data governance is, what does it mean to us as marketers, it's increasingly important regarding the landscape, the impending signal loss. You can start to build that data culture and empower your leadership to understand how important it is to have that collaboration and communication when it comes to data governance.

Evan Kaeding:
Absolutely. Yeah. When you mentioned the impending signal loss as well, there's a lingering fear that things may not necessarily be as good as they are today in the near future, as well, with regard to things like cookie deprecation. We saw news from Apple's developer conference last week that things like link trimming will be coming in, potentially impacting the ability of conversion APIs to function properly. Even things like UTM parameters are in jeopardy in Safari as well. Things that we don't necessarily know what the impacts are today, but we see the direction that things are going.

So, if you want to understand historically how you can capture that data, make sure that it's clean, especially when it comes to downloading that data from the different APIs, from the different performance marketing platforms that you might be using, building that, storing that, getting that on your cloud as soon as possible is one of the things that we see as being important for getting started today. So, that's about the end of our regularly scheduled content. Azure, I'm happy to welcome you back if you want to help kick us off with the Q&A. I think Buki and I'd be happy to start answering some questions here.

Azure Alladin:
Perfect, perfect. Thanks, Evan and Buki. Yeah, I don't have too much to add here. Let's hop into the chat, and Evan and Buki I will leave it up to you what questions make the most sense for you guys to answer.

Evan Kaeding:
So, let's go ahead and answer this one here. So, does the marketing data governance follow the principles of governance into activation? Example transparency, consensus-oriented, et cetera. I'd say for this one, it ends up being the fact that marketing data governance ultimately is what you define it to be within your organization. So, if we talk about things like consent, we talk about things like transparency and what your contract is, your data contract is with your customers and your users, that certainly falls into data governance as well, and is something that you're going to have to work with with regard to what your obligations are to your customers in the industry in which you work as well.

So, a couple of things need to be considered, depending on the industry you work in. If you're talking about transparency and the right to be forgotten in the context of your geographic location or the industry that you work in, maybe it's healthcare, maybe it's financial services, something like that, you've got a couple of different things to consider within marketing data governance as well. Let's see what we've got here.

Buki Froelke:
I see one from an anonymous attendee. At what point should I invest in a marketing data governance strategy? Does it make sense to start even if your ad spend isn't that big yet? So, that is a great question. It really touches on that data culture piece that we've been talking about throughout the conversation.

It's that idea that when you think about marketing data governance strategy, it's really an extension of the data culture of your company. So you really can start much earlier than you think. It's not necessarily dependent on your ad spend. It is more infused into how your company thinks about data culture. Evan, I'll let you touch a little bit more on that, but the data culture piece is critical there.

Evan Kaeding:
Yeah, I think so, for sure. Having worked on both the startup SMB side and the enterprise side, I see that it's never too early to begin. Usually, when you begin with very little ad spend, it is easier to implement something straightforward. If you're talking too large CPG brands with campaigns running across five continents and hundreds of different countries, that's a pretty big project.

But if you're a small company, maybe operating in one market, spending somewhere between five and 10K a month, then chances are it's going to be a little bit less of a lift for you to actually have an effective data governance plan. Hopefully, it's something that you can stay for the future as well so that when you do reach those larger ad spend levels, you actually have a historical set of performance and trend data that you can look at.

That historical seasonality and trend data can be super valuable depending on the industry that you're in. So, if you're in something like hospitality or something seasonal, something like retail, for example, if you have spikes on Black Friday, that can help you estimate a capacity plan for the different upcoming cycles. So, good investment ends up being rewarded in time as well. Buki, I've got another good one you'd be perfect for here. Who should own the marketing data governance project? Maybe I'll add as well, Does it depend on the data culture within the organization?

Buki Froelke:
Great question. So, I think at the beginning of our conversation, we talked about data governance and the focus on security and, oh, that's an IT thing.

So, I think that we want to break down those layers. Who should own the marketing data governance approach? We believe in communication and collaboration there. It's an ongoing approach and conversation that requires all parties. It's not just segmented to IT, it's not just a data challenge.

It's really the collaboration between marketing and data and leadership infused in culture, that's really going to show the ownership there that's shared.

Evan Kaeding:
Yeah, couldn't agree more. That collaborative culture is increasingly important. The best thing we see is when companies are very clear on their strategic priorities because the strategic priorities are ultimately set by people usually either at the very top of the data teams or the very top of the marketing teams.

As long as those are aligned, then it becomes very easy. If the marketing team is working toward those companies' strategic goals and the data team is also working toward those companies' strategic goals. It becomes very easy to work in harmony toward that strategic goal set by the company as well.

Another great question here on how to make sure you can sustain new... So, the question is, how to make sure you can sustain new governance habits versus slipping back into old ways?

This is the piece of the puzzle that I think many are struggling to crack. I've seen this time and time again. You introduce a new framework. Everyone says, "Great, we're going to tag our campaigns exactly this way. We're going to store data in this place and only this place, and we're pretty much ready to go." It lasts for about two months, I'd say, that's usually about what I've seen. Depending on the size of the organization, I'd say two months is about the half-life of most data governance projects.

That's going to be the case if you don't follow the fourth step of getting started. The fourth step that we had was building feedback loops. As part of your weekly campaign review cycle, if you're in an agency, you're probably preparing weekly reports for clients. If you're in a brand, maybe you're doing this weekly or monthly. Add a slide to your Looker studio report or your Looker report that reports on marketing data governance. How compliant are we across the ad spend channels we support with our governance? Are we 50% compliant? Are we 80% compliant?

How happy are we if we are 95% compliant? 95 is good enough, and you say, "Hey, we're good. We're trending positively." If you're at 50%, I have some questions about what tools and processes were in place for implementing that data governance and ensuring that people responsible for generating that data are held to account.

So, I guarantee that when you add that data governance reporting to the same cadences that you use for maintaining that campaign budgeting and those different campaigns that you're putting out, you're going to see some much better data governance habits built into your organization.

Buki Froelke:
I could not agree more, Evan, on just the idea of those feedback loops and how critical it becomes to those ongoing and collaborative conversations that you'll continue to have regarding your marketing data governance, that data ownership, data policies, and standards, being able to continue that conversation and keep it fresh for folks.

Evan Kaeding:
Definitely, definitely. One question from Taylor Robinson here that I found interesting as well. How can agencies help and guide partners or help guide slash partners with clients on marketing data governance? Taylor adds connecting the dots of poor data governance, and the impact of it on performance is still a struggle. What I would say is that if you can work to try to quantify the effect that bad marketing data governance is having on the business, that's going to be very powerful.

When we work with some organizations on determining what their most effective campaigns are, oftentimes we come back and we might say, "Well, unfortunately, we don't actually have the data necessary to answer that question." In other words, not we don't know the answer, it's that the answer is unknowable.

That's not a good position to be in, because if you're not able to determine what your best campaigns are, what your best audiences are, how you segment that data, then you're going to end up in a situation where the maximum effectiveness that you're going to get from those campaigns is essentially driven by increasing budgets.

If you're not able to increase budgets in order to increase effectiveness, well, then you need to start being more efficient. So, doing everything you can with the budget as it is and basically keeping that budget static and implementing data governance is a great way to ensure that you can drive the investment of that media and talk about that efficiency, too. We sometimes see on average, that if you're taking even five to 10% of that media spend, you can make that significantly more efficient by driving more clients or reducing the amount that needs to be spent in order to deliver the same results. Anything to add there Buki?

Buki Froelke:
Sure. Just to touch on that cohesive view of how impactful marketing data governance is, it's that idea of data collection that we talked about, to data hygiene, being able to get those insights for campaign monitoring and reporting the analysis where the data is going into those campaigns to show the effectiveness. Being able to build those audience segments that enable and reach customers more efficiently. So, as you start to unpeel how you can partner in those spaces, those are some critical focus areas that lean into our discussion.

Evan Kaeding:
Yeah, great point. I think I would also add that when you're an agency, you have a pretty unique view of many different clients. When you can find a client that has successfully implemented data governance, you can turn around and say, "Hey, I've got this client over here," even if it's in a different industry, different vertical altogether, you can say, "Hey, I'm working with this client. They implemented data governance," and demonstrate why that's a success story. Were they able to save money on their campaigns? Were they able to make them more effective and more efficient? When you're an agency, you benefit from working with multiple clients and seeing their different problems. Suppose you're a specialized agency in that same vertical.

In that case, you can start to acquire a variety of different data sets from your customers as well and potentially use those as benchmarks.

Of course, if your customers consent to those kinds of things where you can start to say, "Hey," when I work with agencies in the fashion and beauty industry with ecommerce platform with an average order size of 50 euros, then you can start to say, "Well, these are about what I tend to see for top of funnel campaigns for awareness. This is about what I tend to see for bottom of funnel campaigns."

If you can align that across your clients, you can actually build a data set that is strategically differentiated for you as an agency, where you then become the expert in the space and people come to you not only for help with their marketing data governance, but also for benchmarks on how they're doing relative to their peers in the industry.

Buki Froelke:
Evan, I could not agree more on empowering agencies on how to lean into what we discussed regarding marketing data governance. Those stories are so important to your clients, and being able to connect their journey to a client that you've worked with before becomes critical.

Evan Kaeding:
Yeah, definitely. I for sure am very grateful for the background and time that I had in my agency days. I certainly learned from a fire hose in that sense. The last question we have here is from an anonymous attendee. What's the ideal cadence for marketing and data team collaboration? I think this one's tricky because when we talk to global organizations, it doesn't make sense to get everybody from the central data team and everybody from the distributed marketing teams on the phone every week.

But if you're smaller, you're regional, then you can certainly have discussions and certainly have meetings every week, for example. So, I think it probably depends most on the size of the organization, but maybe a few other factors. Buki, do you have a strong opinion on this one?

Buki Froelke:
I'm leaning exactly where you are, Evan. Just to add there, consistency is key. Consistency and commitment are more critical than even cadence.

Evan Kaeding:
Yeah. I would echo that as well. Yeah, it depends on the business situation, yeah. It's for sure the case that you're going to see that the commitment there is going to be more important than the actual cadence itself. Great question and great response, Buki. Awesome.

I think that's just about everything that we wanted to show. Thank you, everybody, for the questions you've answered, and thank you, of course, Buki and Azure, for participating in the webinar today. I've enjoyed discussing marketing and data governance with you two.