Predictive Brand Intelligence with Grant McDougall, BlueOcean
The following was transcribed from a recent interview on The Agile Brand with Greg Kihlström podcast.
Today we’re going to talk about using AI and Machine learning to achieve predictive brand intelligence, and what this means for marketers in a shift to a world of first-party data strategies. To help me discuss this topic, I’d like to welcome Grant McDougall, Co-Founder & CEO of BlueOcean.
[Greg Kihlström] Why don't we start by you giving a little background on yourself and what you're currently doing at BlueOcean?
[Grant McDougall, Co-Founder and CEO, BlueOcean] Yeah, absolutely. I'm Australian; I live in San Francisco. My background started in the Internet back in the late ‘90s. I really got excited about the notion of technology and experiences coming together. I started my career at a company called Spike, which is Australia's first digital company, and I fell in love with the notion that you could create meaningful experiences for brands and people. I then spent some time at Motor Media, which was based out here in the U.S., you know, working on companies like General Motors and Hewlett Packard, and then went to Digitas, which was led by a really inspired leader, David Kenny, and then into the holding companies. And I continue to just really build on this notion that you could use data, experiences and creative to build meaningful experiences in real time.
About seven years ago I met my business partner, Liza Nebel, and we just saw eye to eye on the notion that you could bring this machine-based intelligence to the creative product. And we started a company to do that, and we discovered BlueOcean as part of that. And so, you know, what we've been doing over the last three years is using the very assets that brands use to drive demand, to measure them relative to their competitors, and to make that human-readable and understandable, so, you know, you're not talking about lifetime value or you're not talking about data sets; you're talking about recommendations and things that marketers can use to drive performance.
Well, let's start by talking about consumer sentiment and other ways that brands can learn more about where they should focus their marketing effort. So with BlueOcean, you've defined the category of predictive brand intelligence. For those listening, what does that mean for marketers, and what are some of the tools and methods that this either augments or replaces?
Yeah, so when we think about it, it's really the notion of decision intelligence, and so using brand as the lens. And for us, everything starts with the brand. It's the commercial strategy of a company, and it includes, you know, what are they doing from a marketing and advertising perspective? What's the content strategy of the company? How do they actually go to market? And what's the relative performance? Does it actually increase market share? Does the brand grow as a consequence? And then, ultimately, it is all of the emotional values. So what are your customers saying? What are your employees saying? And what's the news saying about you?
Once you can do that, you have the ability to see the whole playing field. And I think that's an important component of decision intelligence through the lens of brand. And what that allows companies to do is to understand where to start and where's the answer, so they can actually do what they're fantastic at, which is ultimately using the human creativity inside the marketing organization to take action on the thing that really matters to them, in line with their strategy.
And so, to follow on to that, some of what you're talking about is really finding ways to prioritize, right? So can you give an example of how would an organization use some of these insights to reprioritize strategies?
Yeah, I mean, we've got a really large client in Microsoft. We're across 17 lines of their business on the commercial side. And so when we think about how do you do that; how do you make those decisions as the CMO, you know, we’ve printed a framework which has five areas in it. It's called, Familiarity; Uniqueness – uniqueness is all about, are you different in the category from a differentiation perspective; Consistency – what's the shape of your marketing and do people recognize it; is it timely; is it driving to the necessary commercial results? And then, ultimately, on the last side, it's about Reverence and, you know, is there a loyalty component?
What we do is we bring the brand or the product and six of its competitors into an environment so you can see them. And often what we see is, you know, is there a relative under-investment on the media side? Are you attracting the right sort of consideration to the brand? And ultimately are people sharing it? That gives us a good understanding of share of voice. So what happens in large portfolios, that allows the CMO to say, “Well, great, actually, we are under-invested in this brand and, you know, we need to increase spend.” Often, that's a really subjective conversation between the CFO and the CMO. You know, and now we're providing the necessary data for those kind of spend-related elements.
The other component is, in the case of someone at Microsoft, that they've got really high brand reverence, but, you know, they really need to build an understanding of the developer community, for instance. And so what they're doing is they're using the reverence score as a means to establish an OKR in the business and then use that to really measure performance against it.
We've had some other examples, Greg, you know, our friends at Juniper Networks, working directly with the CMO. He tooled BlueOcean into his environment last year, and the brand team, as a consequence of being able to demonstrate that they had a gap in their their advertising and marketing, was able to, sort of, 4x their budget because they could actually have the conversation at the board level, and they were using brand metrics to drive that. And so our market index or scorecard allows CMOs to not only have a unified language but to be able to communicate with quant data at CFO and at the board level, for the first time, which is really exciting.
How does an agile approach help make this even more effective? I mean, so, you know, you're talking about using AIML, humans and machines working together. But is there an agile component to this, whether it's formal agile or just an agile mindset?
Yeah, it's definitely – you know, we as a business, you know, subscribe to agile. That's how we build our software. And I've always thought that marketing needed to have a refocus. And so examples where – you know, we were going into COVID. And a lot of the companies that we were working with were trying to respond in real time. And so they used BlueOcean to understand what were the themes that were being driven; what were their competitors doing, both on, you know, the content that they were producing and the brand?
And so they got to this point where they could actually understand the starting point more quickly. And ultimately that allowed them to launch campaigns at a more rapid pace; iterate on the messaging; see if it was resonating with audiences; and continue to develop, you know, work against that. And so the ability to see that information – so, having clarity of information is the first point. Being able to iterate and not have to spend 12 weeks doing traditional market research or, you know, basically just be determined only on social listening really is changing behavior.
And so marketers are now at a point of saying, “Oh, great, I have a confidence in the data, and what that's allowing me to do is get to the starting point more quickly and to actually put more content, more activities, spend more in the right places and increase media working dollars. And, ultimately, I think we're seeing more efficiency as a consequence, all through the agile mindset.
And I would imagine that, I mean, that's also feeding better data back into the funnel in the first place, right? You know, so in other words, you're not just running the same thing for 12 weeks and then checking back in, but because you're iterating, you’re actually getting better information and more accurate, you know, back into the system. Do you see that as well?
I do, Greg. I think there's a couple things that we see. You know, as marketers, digital as a whole has had such a heavy bias in our communications mix because it could prove performance. And what's happened is we've forgotten that you actually have to continually introduce your brand to consumers, and that ultimately – and Byron Sharp talks about mental availability. I fundamentally believe, because you can iterate and you can take learnings, what it does is it widens the funnel. It allows you to experiment in new ways.
And I like to describe it as, you know, the digital marketers of the past, we had these diminishing returns, and it was like panning for gold. You know, we were really keen about that. What we hadn't done is put water in the pan, and so, you know, for us, it's about, you have to have brand investment. Otherwise you get these diminishing returns on your digital investment and you lose the share of, kind of, understanding within your audience.
And so I think we're about to go back into an era of brand reinvention, where the quality of content, the way that we produce information all is going to be redefined. Because we're seeing, you know, the changes in privacy where it's not about 1-to-1 targeting. It's going to be all about how do I establish context and audiences to keep people engaged with my brand?
Yeah, and that's actually a perfect segue. I wanted to switch gears to exactly that topic. And, you know, it's something that is certainly top of mind for marketers these days, is deprecation of third-party cookies by Google and others, as well as a lot of other changes as far as device ID tracking, and everything like that. You touch on this a little bit already, but, you know, for those a little less familiar with these issues, can you summarize, kind of, where these issues coincide with what you're working on?
Yeah, so I think there's two things to think about. You know, digital of the past – so think about what's powered Google's business has been last-click attribution. So you go and you do a search. You take an action. The marketer sees that action and ultimately gets rewarded. And so you can actually see a relationship between what you're doing and the outcome. And so that's been the fundamental premise of digital, be it a display ad or through programmatic media or any experience.
How the – how you get tracked through that process is through those cookies. You know, it basically gets placed, a unique ID, on your action. And marketers use that to do many other things, like target you in media to personalize experiences, to really get it to a 1-to-1 basis. I think what's happening now is, you know, people have realized that they are being marketed to, that their data is being sold, that their information is being used to to almost profile them. And so you saw what Apple did with device IDs and and locking that down using privacy as a means to differentiate their products. People like DuckDuckGo have come into the market.
What that has done is meant that marketers have had to change the way that they market. So the old digital techniques – which I I think is really funny, right? We're talking about digital, as a whole, is almost a legacy product, means we have – which is weird. We have to change the way that we think about it. You know, we have to go back and say, OK, great, well, how were brands built in the ‘50s?
Brands were built by, you know, producing great content, which happened to be advertising, so we could get audiences to coalesce around them. And then we marketed to them. We didn't know who they were. We just knew that people loved high-quality content that mattered to them. So I think we're going back, more back to that kind of mindset, where brands are going to increase the value of the content they're producing. They're going to ultimately spend more time fascinating on the context of what they're producing for their audience, and then beginning to drive, you know, using brand as the means to collect that audience in a meaningful way.
And so where does AI and ML fit into this mix as well?
Look, I think, if you think about how do you understand context, you have to ultimately be able to understand the whole playing field. You need to know what ads are being produced, what's being consumed. What are your competitors doing on a relative basis? How are they shaping their marketing. What's their performance on a revenue perspective? And then, how do people feel about that?
You can't do that just by being a human and observing it. It's just too slow. We live in a digital context which is changing rapidly. So you need to – you need to have tools and techniques that can observe that content, learn from what's being said, how it's being placed in a media perspective. And so we use machine learning to not only ingest that content but to learn from it, you know, what's effective advertising? You know, what are competitors saying? Where's the white space? And we do that at scale across hundreds of thousands of brands.
Talking a little bit more about this, you know, just understanding the customer, I feel like the North Star, so to speak, is 1-to-1 personalization – 1-to-1 omni-channel personalization, you know, true multi-touch attribution. How close are we to that? Is that science fiction still, or is that – you know, how close are we to living in that world?
I think we are living in a hyper-personalized world. So when I think about – think about your Nikes, if you bought a pair of Nikes and you personalized them, right? That exists today. Think about recommendations on Netflix – you know, what you like. You're living in that environment. I think – so we definitely have gotten to the point where machines and marketers understand their users and can target them based on how they feel, what they think and, more importantly, how they behave. And so the component that's difficult is actually getting into attribution, so your action and, you know, what happened, when it's in a completely closed digital environment. That's live. That's real. We can do that and we can see it.
The challenge is for marketers that use nontraditional digital media. They've got market mix models. So people like the Nielsens and the Comscores of the world have spent a lot of time building brand equity models, which are often slow. And there's not a linkage between action and sales. And so it ends up being very, very expensive. It's going to get harder to do that. And you're going to need context-aware applications as inputs to drive those because you're going to lose a lot of your digital signal.
From your perspective, what advice would you have to, let's say, the marketer there that maybe isn't quite as advanced as some of the things that we're talking about here but understands this stuff enough to know that definitely there needs to be a move to first-party marketing. Listening and understanding the customer has always been key, but, with the tools available, certainly more and more possible, as well as more and more important. What should they be paying attention to that maybe is either slipping under the radar or, you know, what should be top of mind for them right now?
Yeah, so for me, the first thing I would do is I would take a market-driven approach to understanding what competitors are doing, have the ability to see that transparently and be able to act.
The second thing I'd be doing is I'd be saying, look, first-party data is really important. And the tools that you've used to acquire first-party data from your field and from your channel partners and from your direct sales environments, that's great, but you have to keep fueling that data. And the only way that we're going to be able to fuel that data in the future is by doing brand- led activities, so continually re-imagining, re-introducing, creating compelling content to bring to customers, to give them a reason to come and spend time with your brand. Because, if you don't do that, the value of your first-party data is going to decline, and you're not going to be able to continue to add new users, new behaviors, all of the things that really start to make that data set valuable. And it's largely going to decay.
So you're going to have to take a brand-first approach and understand that you're probably going to need to give up some of the classic demand-generation activities to make space for it in your communications mix. They need to get comfortable with being uncomfortable because you can't quantify all that investment. But it's going to be an absolute necessity if you're a B2B marketer or a B2C marketer.
You know, I sit with a lot of CMOs today, talking about how can we put more heart, more empathy into our, in our brands, so we can attract, acquire and retain customers through what we're saying and doing as a brand in content, and then using that as a means, through the value exchange with them, to drive outcomes that you can remarket to.
Yeah, I love what you said, as far as being comfortable with being uncomfortable, because, I do think that many things that have happened recently have caused us to have to rethink assumptions, as well as just the way the world's moving. I think things are moving in a direction, as far as data being so important, as well as just needing to understand the customer. I think that might be uncomfortable for some people, as – you know, as that phrase would suggest, but it is a matter, to take it back to agile thinking here is, you know, you don't have to be a scrum master to appreciate the need to be agile and adapt and be comfortable with change, right?
Exactly. You know, one thing I've got to say about COVID, be it – for all its negatives, it’s had some really positive things, and I – you know, it's really made CEOs become the chief brand officer. And so if you look at Satya, at Microsoft, the way he led the company through that crisis was he used empathy to make sure that, you know, he was putting people back to work.
If you went and looked at ServiceNow, the way that they responded was in an agile way, but it was through their customers, telling the story of the customers helping people. And then, ultimately, all of the tools and technologies that were deployed as a consequence were, obviously, software, were meaningful, but they came through this lens of emotion, being authentic, and really trying to be helpful. And so I was really pleased to see the shift in the mental mindset in CEOs. It was less about market performance and it became, “Well, what are we doing within the communities we operate? How are we actually responding to this in real time? And how are we making a material difference to people's lives? And then, on top of that, it's forced us all to be digital at the core, even if you're a grandmother.
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About the Guest
Grant McDougall is the CEO and Co-Founder of BlueOcean, the AI-powered first predictive brand intelligence platform. Grant has spent more than 25 years leading the development of digital products for brands like Toyota, Samsung, Apple, Visa, HP, IBM, NerdWallet, AT&T, VMWare, and others. He founded BlueOcean on the premise that by harnessing algorithms, we can speed up the time it takes to get brand insight and strategy recommendations that drive business outcomes at a fraction of the cost. As a former agency insider, Grant is leading the charge to provide accountability and accessibility to actionable brand insights. He also serves as a board member for Blackbelt.ai, an AI marketing company. Grant is based in San Francisco but is originally from Australia.
About the Host, Greg Kihlström
Greg Kihlstrom is a best selling author, speaker, and entrepreneur and host of The Agile Brand podcast. He has worked with some of the world’s leading organizations on customer experience, employee experience, and digital transformation initiatives, both before and after selling his award-winning digital experience agency, Carousel30, in 2017. Currently, he is Principal and Chief Strategist at GK5A. He has worked with some of the world’s top brands, including AOL, Choice Hotels, Coca-Cola, Dell, FedEx, GEICO, Marriott, MTV, Starbucks, Toyota and VMware. He currently serves on the University of Richmond’s Customer Experience Advisory Board, was the founding Chair of the American Advertising Federation’s National Innovation Committee, and served on the Virginia Tech Pamplin College of Business Marketing Mentorship Advisory Board. Greg is Lean Six Sigma Black Belt certified, and holds a certification in Business Agility from ICP-BAF.