A strong marketing data strategy is the foundation of any digital media plan, but most marketers miss the mark when developing an effective one for their brand. In this episode of The Loop Marketing Podcast, you’ll hear from Coegi’s Executive Vice President of Operations and Analytics, Katie Kluba, and Director of Digital Operations, Julia Wold, as they discuss data strategy, and why most marketers get it wrong.
You’ll learn:
- How to apply upfront data-driven work to inform marketing strategies
- The importance of data restraint and why “more” is not better and
- The keys to giving the client the data story they need to hear
The following is an edited transcript of the podcast. Click here to listen to the full episode on your favorite streaming platform.
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Q: What are some things that marketers should be doing in the upfront work to make their marketing strategy have stronger buy-in and have a better opportunity to truly be successful?
Katie: Yes, for sure. This is such a good topic to be discussing. I want to start at the beginning. So, first and foremost, it is really important to find a true digital partner. A true digital partner is a partner who’s going to tell you what you need to hear, not what you want to hear, and then you need to find a digital partner that is also comprehensive.
What I mean by that is they need to have a proven track record of success, but they also need to possess the technical prowess, if you will, to support data collection methodologies and the media tracking requirements that will be needed to create data decisioning. So once you call Coegi – we do all of that – so once you find your digital partner, what marketers should do to set themselves up for success is first and foremost, be crystal clear on what they are trying to accomplish with the campaign initiatives.
From there, you can start creating a measurement plan or framework, if you will, and the objective here is to tie the digital media performance back to what the marketer is trying to accomplish. I’m going to give you just a few tips about this measurement plan. Keep it simple and straightforward. Over complicating measurement is not a recipe for success.
And then I would say, remember that the power of data decisioning is based on the reliability of the data. So junk in, junk out, meaning make it meaningful.
And I would say lastly, and this is very important, you should separate the media optimizations or performance from any larger picture media effectiveness that you’re trying to measure. Measurement is not a one size fits all approach and campaign performance should be separated from the measuring the impact of the media to the brand objectives, business objectives that may be offline.
Q: Can you talk about what it takes to define campaign performance and where the waters sometimes get muddied for marketers in evaluating success?
Katie: Absolutely. You will see that a brand will be running an awareness campaign to drive awareness of potentially a new product or service that they have brought to market. And what ends up happening is the brand marketer and the digital partner will often come up with some media performance metric. So something that’s attainable in the platform, a click-through rate, an impression, a reach, a cost per click, and they will use that as a proxy, if you will, to the brand loyalty, the brand effectiveness.
Was the media that was put in the market, did it hit the mark? Did the audience resonate with that brand?
Do they remember or recall what the brand message was all about?
Those two things are very different. So your media effectiveness should be a separate study. You can do branding surveys, there are many, many things that you can do, market research and other things. But you should not confuse performance based metrics to business initiatives. All can be measured, but that doesn’t necessarily mean it has to happen in one study.
Q: What are some ways that you have gone about figuring out the right methodology to evaluate campaign performance and business objectives for our brands, especially when there are so many measurement partners to consider?
Julia: Yeah, so going off of what Katie said, it’s first imperative to identify what you’re trying to achieve, identify the best methodology that’s going to get you there. So if you are trying to have an impact on perception, thinking through that, likely a survey based perception. A panel-based study is going to be your best bet in terms of proving out performance beyond media metrics with reach, completion rate, all that. Once you can identify the methodology that best fits your client’s end goals, then you can align to a provider that’s going to meet those goals. Like we said, there are so many providers out there that tout similar capabilities. So it’s really important to compare vendors and get a holistic view of the entire ecosystem because some vendors could be piggybacking off of other vendors’ data to improve and fuel their own methodology.
So getting a holistic view of the ecosystem is important. And then when you are pitching that solution to your client and you’ve come up with your provider that you’re looking to leverage, you have more of a talk track to show the work behind your recommendation. Also, forging meaningful relationships with these different partners, it really helps to solidify your approach and show the client that your recommendation carries some weight.
And then lastly, like Katie said, too, success of a campaign is a multifactor approach. You’re looking at success from a media perspective, looking at its success from a business perspective, and then also making sure that you and the client really align all the way down from initial planning to a final readout that this was the plan that we chose all along the way. There are instances where sometimes clients can say, well, I wish we were measuring that. Unfortunately, switching measurement mid campaign is very difficult. And then you’re never going to be able to prove your success because you’re constantly chasing another lead and not focusing on what your core set was. So having a solidified approach early on is really going to help you prove out your value.
Q: What are some ways that marketers can avoid confirmation bias and use truly data-driven processes to ensure they’re collectively moving toward the brand’s goals?
Julia: So, there’s a couple things that you can do. It really starts with the strategy upfront. I know once media is up and running, you are going to get more of those media-based metrics in terms of performance. But you can also leverage tools along the way. So, perhaps prior to setting up your campaign, you launched a study to understand, “okay, this is who we think we’re going to target. What are they saying from a respondent perspective? And is the focus of how we approach targeting going to measure up?” There’s also ways that you could think to tag your media to get a readout from an audience perspective. So we have tools like The Trade Desk where we can put in an audience profile and then see other audiences that index highly with that. And so that can confirm or deny what you’re looking at. But like you said, bias exists everywhere and it can be really challenging. So as a marketer, you really need to put yourself in the shoes of all of these different individuals and of who you’re trying to reach and think holistically, but then also you as a test and learn approach to say, “okay, I thought it was going to go this way, maybe it didn’t.” And you know, being wrong isn’t bad either. it’s just now you understand what you’re not gonna do in the future and how to pivot.
Katie: Julia, you’re spot on. Test and learn is the way to go. Test and learn is the way to go, whether you’re pivoting mid-flight or you’re creating a test design for measurement pre-campaign launch. But what you want to be careful of is when you set up any test that you are not putting your thumb on the read or the test design to support what you think the test is going to read out. So I would say bias is really easy to avoid, but it is often not avoided. I have found that the most successful marketers are the ones that listen to the experts, which is their digital partner and put some faith that the digital partner has the expertise in the measurement of the ecosystem, that a well thought out test design will tease out without any bias, without any type one or type two errors, whether or not your hypothesis proves true or false.
Julia: That’s a really good point, Katie. I just want to interject too, when you do work with a smaller independent agency like Coegi, we are a little bit more agile and more flexible in the relationship standing and you know, we’re not held to the silos of some of the holding companies that they put in place just for their job function. So what we’re really looking to do is to give you the best approach rather than what’s the easiest approach or what’s the approach that fits into the job function that I’m currently doing.
Q: A large number of marketers have that tendency to overcomplicate data, especially when we’re translating that into reporting for brands. What steps should we be taking as marketers to get the most out of our data and truly and intelligently inform marketing strategies in business goals at large?
Julia: I feel like maybe a broken record at this point because I’m always like, “think about it up front, think about it upfront,” but it definitely needs to be thought of upfront. So the way that we approach setting up campaigns is really thinking through what is the end goal that you have in mind and then working backwards. So, establishing that groundwork. If you know, for instance, your client is really interested in understanding how different geographies within their media buy are performing, then let’s focus on that and really drive that in. And focus less on – who cares about device type, who cares about you know, time of day? Those are all important and those all happen in the background, but you don’t need to pull out every single insight in the hopes that something sticks.
So, really focus on the one element that you know your client bought into and that you know you can set up a campaign where it flows from the DSP or the platform directly into analytics and then ties to maybe your advanced measurement goals. Something that I was just working on for a client recently and we were really focused as an agency on the audience. It was for a client that sold a product and we thought that the audience was so important to say this audience engaged more than this audience, but at the end of the day, all the end client cared about was like, what product of my product lines should I promote more of? Where do I need the people in store to start pushing more of based on what the consumer demand is? So if we had maybe just listened a little bit more to our client we could have helped to really craft our reporting insights to be based on what product is really driving and all of that audience stuff that we find so important is still important. But we’re just trying to complement what they’re looking for versus trying to recreate the wheel.
Katie: We, as marketers, have a lot of information about advanced measurement that includes bridging the gap between the online and offline point of sale world. There are measurement providers out there that are very powerful. The point Julia was making about listening to our clients is critical because you might have someone saying “well, what about that clickthrough rate? What about that time on site? Or what about the cost per acquisition in this particular case?” It may have been some sort of online event, right? So all of that is interesting when you’re trying to maximize and squeeze every penny out of your online marketing dollar to get your brand in front of the relevant audience, consumer base that you’re trying to reach. Very important. But at the end of the day, what the client wanted to understand is, of all of the products that I have, what are the ones that the offline world should be pushing, right? The display should be set up such that, that’s the product that is eye level. So that is a perfect example of how bias comes into a measurement framework. What you’re saying versus what you really need are two different things. So it is important to continue to have conversations, to tease all these things out. Open mind, come to it with an open mind, blank slate.
Julia: Yeah, and I don’t think many clients are going to be super black and white on what they’re looking for. So it is an evolution of like really listening intently to off the cuff comments that they might make when you’re doing reporting. And then that’s where you have the opportunity to pivot. And maybe it’s not even a pivot of your strategy, it’s just a pivot of the way that you’re going to read out your strategy and speak to the client.
Q: What are some steps that we should be taking to ensure that the data that we are translating back to the client is truly speaking the same language and helping the brand be empowered, not just causing greater confusion or going down a rabbit hole leading to nowhere?
Katie: You recall I said at the top of this podcast to keep it simple, be clear and keep it simple. That resonates with measurement, period. If you do nothing else but do that, you’ll be miles ahead of what is too often just checking the box scenario. In our industry, if you were good at Excel, you became an analyst. But that doesn’t mean that you can tie business objectives back to media optimizations and media buying. So I would say first and foremost, do not overcomplicate your performance story.
Remember, more is not better necessarily, it’s just more.
Secondly, observations are observations. You should be able to read, interpret, the data in front of you. Then, based off of what you’re looking at, your recommendation should be what you’re going to do or what you have done, so the result of what you have done or what you’re going to do based on what you’re looking at to get the media buy – the performance – which is different than the media impact, but to get the performance to where it needs to be. So we’re effective and efficient driving every penny, nickel, squeezing that out, driving the KPI for the client. It sounds redundant, it’s literally foundational to any measurement strategies. Do not overcomplicate it, keep it simple. That’s what I would say.
Q: What predictions do you all have in terms of what changes are going to be needed to keep measurement as informative as it is today, going into two or three or even 10 years down the line?
Katie: So first of all, everyone’s in the same boat. No one should panic. We’re all in the same boat, so we will not really know the true impact until the deprecation of the cookie occurs. We can project what we think is going to happen, and what we think is going to happen is that there’s going to be less focused targeting. Right now the industry is such, we collect so much information about users who engage with the media and also engage on brands’ websites that we can create segments of how they consume that media and actions they take thereof. So there will be less ability to create those segments. However, as I said, we’re all in the same boat, so there will not be really one advantage for one marketer versus another. Outside of a few things that are going on that I think marketers should be doing immediately – and if they’re not, they need to start – there are a few identity grids that have been developed when the news came out that the cookie was going to be deleted. These identity grids are going to allow the marketers to continue to target and create segments of audiences just as they do today. So, they need to speak with their digital partner and make sure they’re opting into these identity grids.
Julia: Yeah, and I’ll just kind of piggyback off of that. Something that we’ve done as an operations department here at Coegi to help prepare these marketers for this is just to get a better understanding of the fact there are a ton of data providers out there in the ecosystem, and while we’re not talking about the marketer’s first party data they do likely want to tap into somebody else’s third party data because as we know, first-party data and zero-party data is finite. In order to scale you’re going to need other opportunities, so it’s really important for us to know who our data providers are, what their collection methodology is, how they are planning for a cookie list future, how they’re already overcoming the privacy laws of GDPR, CCPA the Pepitas of Canada.
And just getting that foundational knowledge – I feel like foundation is another key word for this podcast – but getting that knowledge of how things are being collected there. It’ll give you a lot more peace of mind in understanding that you’re reaching people with ethical third-party data sources. Additionally from our approach too is to think about using your first-party data as it is now, you have the opportunity still with cookies to layer on and see where your audience indexes with other third-party sources so you can start to create a persona of who your current customer is and make sure that you just start to collect that stuff now so that it’s useful for the future. So for instance, say you don’t have a first-party list, but now you know, I can create a persona based on people and maybe they like to engage on this type of content, including a contextual element to your next media buy is going to be a great way to test out how it performs. That way you can still have what a cookie is able to give you today and you have that comparative tool.
Additionally, a lot of what I’m seeing in the marketplace and where I’m seeing a lot of people are leaning, are toward more of those PMP and even programmatic guaranteed buys. And I almost feel like we as marketers are slightly going back to what things looked like 10 years ago from a buying standpoint because we know that we can trust that certain publisher and it’s all about kind of that relationship building again, whereas we got a little loosey goosey taking whatever was available to us. Now we’re just becoming more intentional with the way that we’re building our campaigns and really focusing on quality.
I will say that ever since I’ve been here at Coegi for six years, quality has always been something that we’ve focused on and it’s just being more and more elevated as we continue to evolve. So I feel like our company has been really set up well for navigating this new landscape.
Katie: Yeah, that’s a really good point, Julia. Extending your first-party and zero-party audiences leveraging third-party data providers is going to be key. The direct deals are going to be key. Contextually relevant buys are going to be key. I do want to add that we’re really talking more about the programmatic ecosystem and the impact is going to be felt primarily there. We still have a lot of user profile information within the social sphere, so your addressability there will still be pretty focused.
Q: Lastly, what do you feel is the most common mistake that marketers are making today in their use of data and how it is informing marketing strategies?
Katie: Well, I’m going to be honest, number one. The most common mistake I see is marketers just don’t use data. So there’s a couple reasons why they don’t, even if they think they’re using data, they’re probably not using it correctly. I’m not trying to upset my brand friends, but interpreting the data correctly is important to make data decisions, right? Data informed decisions. And I would say the other area or reason why most marketers do not use data, is they don’t know where to get the data. And so that’s where I would say the two areas are probably the biggest components of why we have bias. Can we go back to that question? Why do we have bias in our measurement and which leaks into our strategy? The digital ecosystem is so measurable and if there is some trust given to the integrity of the data, which has to be pur purposeful and the measurement plan that is tied to the strategy, if there’s some trust given there in connectivity, what you’re going to get out of that is a really solid circular feedback loop of data decisioning. And I think your campaigns are going to do very, very well for your brand.
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To improve your measurement and data strategies, check out Coegi’s 5 Step Guide to Successful Marketing Measurement.
