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Google Marketing Live: Highlights + Takeaways
paid media, privacy + more with Fathom’s Claire Abraham + Stephen Epple
Earlier this summer, senior marketing leaders and Google’s premier partners came together in San Francisco for Google Marketing Live to engage directly with product managers, learn new best practices, and get an inside look at how the company’s latest products are developed.
Fathom’s paid media manager, Claire Abraham, and executive vice president of digital strategy, Stephen Epple, were in attendance so you didn’t have to be. Once they were back in Cleveland, we sat down for a conversation to discuss what stood out. Over the course of 48 minutes, we discussed the intersection of privacy and paid media, updates to Google’s product roadmap, and how marketing leaders should balance machine learning and human optimization across channels.
You can listen to or read any portion of the three-part conversation below.
part 1: privacy + paid media
part 2: Google’s product roadmap
part 3: paid media bidding + machine learning
part 1 transcript: privacy + paid media
Joe Adams: Let’s talk about Google Marketing Live. Who can tell me what that is and why we were there?
Claire Abraham: So there were 5,000 people there gathered in San Francisco, premier partners only, agencies and brands and special guest, Katy Perry. As premier partners, we were offered three seats at the Google Marketing Live event and we went to learn about what new products they are offering, what innovations are coming up in the next year, and where they’re going with an eye to privacy.
Joe Adams: Did you know that going into the event? Did you know that privacy would be at the forefront of the event or is that something that came up over the course of the two days?
Stephen Epple: Yeah, I think everything that’s happening with Facebook, with Google privacy, had to be a topic.
Joe Adams: Sure.
Stephen Epple: And so probably important to talk about, how did they address privacy over the course of two days?
Claire Abraham: Yup. So privacy came up in just about every session that I went to. It was in the keynote, it was in the future of search, and then it was a part of a lot of the more technical, smaller group sessions that I went to as well. A big theme that they talked to privacy under was our innovations and our reporting capabilities significantly surpassed where we are at with privacy. So we want to give you the insight that you crave and we want to give you that data to be able to react to, and we have the ability, but we are not there when it comes to privacy capabilities and how to report on that responsibly.
Joe Adams: So essentially, Google has the information. These platforms have the information, but they’re grappling with whether or not morally or ethically they can share the information with advertisers.
Claire Abraham: Correct. And technically, how to share it with advertisers.
Joe Adams: Sure. And so one of the notes I saw from your recap was transparency. So Google’s advertisers, platforms in general are collecting more and more information. And as consumers, we understand that. At what point does Google share that information with advertisers? Is it after they’re transparent with the consumer and let them make the decision?
Claire Abraham: I think that’s what they’re trying to work through today. So Facebook, you’re automatically opting in under all these terms and conditions to give your data, and so now Google, with their Google Chrome and other entities, is saying, “At what point do we ask for consent?” So that was another conversation that they talked about, too, is not only collecting, how do they ask for consent when they’re collecting data, but how are you asking for that consent when you’re asking for data, so using their first party tools like Google Tag Manager and Google Analytics to collect first party data, not using third party data, to not purchasing lists, not collecting data on your website without acknowledgement, so adhering to GDPR as much as possible, although it’s not being enforced in America.
Joe Adams: It’s only a matter of time.
Claire Abraham: Exactly. Right. So their thought there is going towards GDPR standards, but what does that look like for the US?
Joe Adams: And so based on that thought, what actions are they taking?
Claire Abraham: So in the Google Chrome app, they’re letting users opt out of third party cookie tracking or just cookies being tracked after they leave a website in general. And they had stats about how many people who are visiting, that section of settings, but then they later say stats about how many people use their apps a day and it would be a very small fraction. So I think they have a ways to go when it comes to being upfront about your options when it comes to privacy. So the setting is there to say, “I don’t want cookies to track me after I leave a website,” but it is the default setting to be turned off.
Joe Adams: So essentially, customers have to opt out.
Claire Abraham: Right. And I think that we’ll be moving away from an opt out model, or I think users will expect something better than an opt out model in the very near future.
Joe Adams: So I guess as someone who manages accounts for brands, what sort of challenges does that pose in your day to day, getting the most for clients in paid search advertising, display advertising?
Claire Abraham: Yeah. I think about advertising from such a good place and altruistic place because that’s what we do here at Fathom, but I have to kind of sometimes step out of that and recognize that all this personal data is not always being leveraged for good.
Joe Adams: Sure.
Claire Abraham: So as an advertiser, I want as much audience data as possible because I am coming from a good place and I just want to show you what I think you’re a good fit for for my client, an ad that is right for you and makes sense for you at the right time. So from an audience perspective and an advertiser, I crave that audience insight and that data. But as a user and from a personal perspective, you kind of get into a different space and think about, “Okay, well, what would I want my data to be used for?” So there’s definitely a conflict as an advertiser from what you want versus what you want as a consumer.
Joe Adams: Sure. That’s a really good point. There’s two ways to think about sort of digital advertising, advertising in general. The altruistic sense is that your experience online is being personalized, right? And there’s questions that you can ask as you go further down the rabbit hole. The other side is, is information, are people being manipulated for nefarious purposes, which can happen, which is maybe expediting some of the transparency, some of the opt in versus opt out conversation. What can marketing leaders do to ensure sort of they’re using clean data and not sort of crossing the nefarious line?
Claire Abraham: Yup. So Fathom’s advice to our clients with regards to privacy is setting yourself and holding yourself to GDPR standards and making sure that you are getting opt in data and you’re collecting your own first party data through tools like Google Tag Manager and Google Analytics and making sure that there is, clarity throughout that whole process on what the data’s being used for and why you’re collecting their data.
Joe Adams: Honesty is the best policy sometimes.
Claire Abraham: Honesty is the best policy.
Stephen Epple: I think it’s around user expectation. So one of the quotes that they said that I really liked was that the responsibility is to use as little of the data as possible to meet the user expectation. And with that in mind, they talked about advertising has to work for everyone, users, publishers, marketers. And I think there’s times where a marketing decision or business decision cannot be what’s best for the consumer, right? So as a marketer you could think, “Hey, I could give such better information to this ad, more personalized if I use this data.” But you can’t use that mindset anymore. You have to understand that privacy is a concern and make sure it meets that user’s expectation and that the value exchange is fair.
Stephen Epple: So there’s a lot of perspective that says users are now more open to data as long as they’re getting something back out of it, right? And at the value exchanges, we might have your data and you buy more stuff from us. That’s not a fair value exchange, right? But if you’re providing something back to the end consumer, a more personalized experience, better shopping experience, whatever that may be, and that value exchange is equal for the amount of data that you’re taking, users have been more apt to that type of relationship.
Joe Adams: Can you share an example of sort of meeting those expectations in a positive way?
Stephen Epple: Yeah, so if I tell ESPN that I’m a fan of the Cleveland Browns, they’ll give me ads and they’ll give me news articles and ads for the Cleveland Browns, right? So I get a more personalized experience. I get the Browns articles and updates and then they can serve me more relevant ads hoping that I’m more likely to buy.
Joe Adams: Sure. How, if at all, is that information available to advertisers? Is it in a black box and you tell Google who you’d like to reach or do you have the ability to pick and choose from a set of criteria?
Stephen Epple: Yeah, so one of the things Google did a few years back was combine all their data on the backend from all of their platforms. And what they tout is that they have seven platforms that each have over a billion users, so you look at everything from the Google Play store to Google search and they’ve brought all that data together. So the fact that you have a TrueCar app on your phone that you downloaded in the Google Play store and then you go and search on Google for something related, what you’ll find is that you’re now tracked as in market to buy a car. And as an advertiser, I can spend additional dollars against you because I know that you’re likely to buy a car.
Claire Abraham: So another way that we have visibility into kind of that affinity that Stephen’s describing, like I like the Browns, versus someone who is in market for season tickets for the Browns. We have the difference in data to be able to target those two people differently through audience segments, one called affinity and one called in-market. So you can speak to people differently based on what they’re interested, their likes more of their personality makeup. You can also target people based on their historical and future buying behaviors. So an affinity audience targeting would be at a higher level. Maybe you’re just trying to make this person aware of what Browns gear you have for the season. Maybe this person never goes to a game, but they always spend Sunday on West 6th enjoying the other people who enjoy the Browns versus someone who’s a season ticket holder every year.
Joe Adams: And so how do you approach sort of, it’s not quite media mix, but mixing those affinity versus in market audiences to nurture audiences towards business outcomes when we have to balance sort of the user expectation that we were talking about before?
Claire Abraham: Yep. So those are such small pieces of a person.
Joe Adams: Sure.
Claire Abraham: Humans are complex and that makes up a very narrow percentage of who someone is. So we try both, right? Not one or the other is going to get you the result that is definitively what you wanted, but it’s about testing and understanding what performance gets you what you want, so testing the affinity targeting versus the in-market targeting and layering on demographic data with that and layering on location data. So to try and come up with that whole person, you might use a couple of different targeting tactics at once.
Joe Adams: This conversation sort of leads into one of the takeaways from the Google Marketing Live event, which was the the user journey reporting functionality. It seems like that’s something that’s on its way but not quite available. So that information is available to Google, tracking an individual across their entire digital journey and even offline habits on pathways purchased. How close is that sort of to market and its availability to marketers and sort of what does the functionality, like what will it allow us?
Claire Abraham: Right. So I think that this comes back to privacy again. They are probably ready with user journey reporting data. I think that we do have predictive intent and we’re at that stage, and you see it in advertising. People always think or theorize that, “Oh, my phone’s listening to me because I said something and then I saw an ad for it.” But what that really is is that predictive modeling. Your behavior implies that you would be interested in this thing, and it just so happened to be timed up that you realize you’re interested in this at the same time that the algorithm did.
Joe Adams: I’m squinting at you Claire, because I don’t believe what you’re saying is true.
Claire Abraham: This is Google’s formal response to, “Is my phone listening to me?”
Joe Adams: So if Google’s not listening, others are.
Claire Abraham: Quite possibly.
Joe Adams: So we have partners that you can buy inventory with for showing an ad if your phone hears a certain commercial.
Claire Abraham: Right. Definitely
Joe Adams: We’ve seen everything from Alexa and all the breaches they’ve had there and things like that. So Alexa just even announced more ad buying services, which again, allows a business decision to creep in on like, “Hey, this is good for the business, but is it good for the consumer?” And they’re not always making the best decision on both. Should advertisers be in the consumer’s living room with them on Sunday evening during family time?
Claire Abraham: With fair exchange of value.
Joe Adams: What is a fair exchange of value in that situation? What can an advertiser do to essentially have a seat on the couch?
Stephen Epple: Pay for my Netflix.
Joe Adams: So in exchange for $10-
Stephen Epple: $14.99.
Joe Adams: The family plan. Is it coming to that, though?
Stephen Epple: I think, I mean, if you saw a Facebook’s fine that just came out, right, $5 billion-
Joe Adams: That’s a lot of money.
Stephen Epple: You put that on top of the $2 billion they paid in legal fees, and that’s a big message on privacy from people.
Joe Adams: Sort of from the highest voices be responsible or there will be-
Stephen Epple: There’s sort of a claim of ignorance, right, of, “Hey, we’re providing a service. People know what they’re getting,” but it’s not enough just to put it in terms and services and say, “Yeah, everybody agreed to it, so we should be good here.” You have to go above and beyond and make sure that you’re taking care of these consumers. Facebook, Google, they’ve gotten so big, they have more of a responsibility in 2019 than than they ever had before.
Joe Adams: Sure. And kind of to go back to the expectations, advertisers have the opportunity to take advantage, sort of, of the opportunities to reach people based on the information collected in those ways that maybe consumers have opted into but really haven’t truly opted into, they’re unaware of. What can advertisers do to make sure they’re ahead of the curve and are caught sort of behind the eight ball when it comes to privacy?
Stephen Epple: I think you need to consider privacy as its own entity. So thinking about not just for your marketing efforts, are you using the right level of privacy concerns and challenges. You need to think of privacy as an entry point into your marketing program and how you interact with their consumer every level and through that door, and for us, right, we’re working with risk management and having that be a consideration. You need to have a separate view on privacy and have a thought on privacy. Have a plan for touch points, have a plan for the data you’re collecting and how you use it, an overall governing on privacy, because again, we’ve seen with Facebook, with others, it’s not enough just to be legally compliant. You can be legally compliant, and you can still not do what’s right for your consumer. I think you have to have both.
part 2 transcript: Google’s product roadmap
Joe Adams: So back on the topic of Google Marketing Live and sort of the takeaways from the event. So what innovation that you learned about, well, two part question, has you most excited? Second part question. What innovation had the audience sort of most excited about? So first we’ll start with you, what are you most excited about on Google’s product roadmap?
Stephen Epple: So for me, I’m a bit of a tech geek, so when you look at what Google is doing to … Google’s goal has always been to connect users to what they’re looking for, and do it better than anybody else. If you’re finding what you’re looking for more often, then you’re going to use their services. So I think when they talk about some of the word matching that they’re doing, so the comment that they made was, overall, Google can only understand language at the level of a four year old. So they’re still not as sophisticated as we might give them credit for. So when they talked about some of the technical things they’re doing to connect the dots, it’s really exciting.
Stephen Epple: So three of the things they talked about was around word matching. One is around synonyms, so they talked about expert language versus novice language. So if you’re an expert in the airline industry, right, and you’re talking about airfares, you’re like, “Hey, let’s put our information out there on airfare so people can find it.” People are actually searching for how to find the best prices on flights, so they’re connecting people that put out information on airfares to how to find the best information on flights, or best price on flights. Same thing for insurance. When you talk about best prices on insurance versus premiums, people don’t use the term premiums, they use the term, how do I find best prices on insurance? So they’re making a better user experience there.
Stephen Epple: They talked about the knowledge graph, which is really exciting. So the example they gave was somebody that searches, and I think we’ve all done this, you search something and you’re like, “There’s no way Google can connect me to what I’m actually looking for.” But then they do, right? And it’s things like the knowledge graph. So it’s, “Why does my TV look strange?” And what they’re doing is using neural embedding to connect queries for documents for anything that might be out there and say, “Hey, actually you’re looking for this underlining concept of-
Claire Abraham: The soap opera effect.
Stephen Epple: … the soap opera effect. And it’s why TVs look strange. And then they connect you to an article and a document on how to fix it. So things like that are really cool.
Stephen Epple: The last one was the neural matching. So they gave an example, and even a voice example, because they talked a lot about voice searches. You don’t want a voice response, sometimes you want a picture response, right? So they said, “Hey, what does Ironman look like?” You don’t want Google Home to tell you-
Joe Adams: A hundred-word description.
Stephen Epple: Yeah, exactly. You want to see a picture of it. My kids do this a hundred times a day. But the example they gave for enabling conversation was, “So which villain snaps his finger and destroys half the world?” That’s a pretty vague search, yet if you-
Joe Adams: It could be anything.
Stephen Epple: Exactly. But if you did that, they would show you who it was. I won’t try to ruin it. Thanos. Have you seen it?
Joe Adams: You just ruined it.
Stephen Epple: I haven’t seen it.
Joe Adams: I probably, I’m so far behind. I think these are Marvel movies that-
Claire Abraham: Avengers.
Joe Adams: When do I start?
Stephen Epple: Yeah.
Joe Adams: Oh, forget it.
Stephen Epple: I think those things are really cool in terms of the technical pieces they are enabling, and again, like this, I think we give Google a lot of credit, but they’ve said things like they only use two searches. They only use your most recent search to personalize your next search. So it’s not like they’re personalizing your entire database of searches. So if you say, what’s Claire’s example? If you say “Who is a bachelor, who’s a bachelorette?” And they tell you the name of whoever it is.
Claire Abraham: Hannah B.
Stephen Epple: Hannah B. And you say, and then you search, what is her birthday? If you searched, what does her birthday alone, Google wouldn’t know. But what they do is they use the previous context, but what they’ve reported it is they only use one search.
Joe Adams: But based on what we’ve talked about, they have the ability to use multiple searches and so are they thinking through-
Stephen Epple: So that’s where they talk about, so the stats they gave are that two of three queries are part of a multi-day task and one in eight queries in a month are repeats. So what they’re doing is connecting. So they used a camping as an example in their neural matching and they said everything that they break down everything that has to do with camping and they help you connect those dots. They know that if you search something around camping that the other things you might want are about a campsite, about camp equipment, about how to set up a tent. These different things are all related to this concept of camping.
Joe Adams: So camping and say, trying to understand, you searched for campsites in Ohio, you’re not the first person to search for that. Five times out of 10, after searching for camping in Ohio, people search for new tent or something next. And so they began to connect those dots to personalize your experience.
Stephen Epple: Yeah. And that’s what Claire was saying earlier of Google not that listening to your phone necessarily. They just can connect the dots for you based on what you’ve done in the past and try to give you something that you didn’t know you’re looking for.
Joe Adams: Hmm. Yet.
Stephen Epple: Yet.
Joe Adams: And so I think the common theme through all of that is the user expectation. It all puts the user at the forefront as long as that’s the case, I think advertisers win.
Claire Abraham: Yep. Yeah. And I think one thing that I’m excited about is very much user-centric and plays on the success that is social media and social media as a platform where people engage with ads maybe even more organically than they do on search. So one of the biggest innovations they talked about was bringing visualization to search and search ads.
Claire Abraham: So right now, search results, organic and paid, are very text-based, which is not the way that we experience the world in a lot of ways. We are on Instagram and Facebook and these very visual mediums and those social platforms have that advantage of taking in the way that we enjoy experiencing content and bringing that into advertising. So that was one of the pieces that I was excited about as an advertiser in search and display is bringing that visual medium to search and being able to bring to life a campus I’m advertising or bring to life a sales, a SaaS product that you know has a really beautiful interface that might not come across in a search text ad.
Claire Abraham: So that came across in a couple of their product announcements. So they announced gallery ads, which if you are a Facebook advertiser, you know as carousel ads. If you are a Facebook user, you know as the ads that have multiple pictures and you can swipe through. So bringing gallery ads to search is one of the products that they announced. So that’s in beta now, really exciting. Obviously maybe you’re thinking, well that doesn’t make any sense on desktop. It would be a mobile only feature. Discovery ads. So this is one of the places on, if you have a Google phone, that was not monetized. So Stephen has a Google phone and when they announced gallery or discovery ads, he was like, okay, that was the one place left on my phone that wasn’t monetized. But it’s a place where they aggregate things that you like. The news he normally reads, the articles he’s normally interested in, content that matches his interests and now there will be ads there as well.
Joe Adams: The direct pull from it seems very similar to the Instagram discovery tab.
Claire Abraham: Yes, it’s a lot like that. The discovery tab already existed, but what’s new is putting image ads in there.
Stephen Epple: It’s much easier to sort of inventory your interests and you’ll see pictures of them versus a bulleted list of the things you’ve searched recently.
Joe Adams: Yeah. So I’m not familiar with sort of what that looks like on a Google phone. What is it? Is it a tab in Chrome, is it-
Stephen Epple: Yeah, so it’s on the Google search page and it’s discover and it shows articles related to topics that I’ve shown interest in. So for me it’s worm farming.
Joe Adams: Of course.
Stephen Epple: It’s Chipotle and it’s-
Joe Adams: Not at the same time.
Stephen Epple: And it’s a soccer.
Joe Adams: Then, so based on that-
Stephen Epple: Now advertisers can buy against my interests.
Joe Adams: And so within those articles that are suggested based on relevance, there’ll be ads that are also relevant but paid for.
Stephen Epple: Yes.
Claire Abraham: Have you seen and did you start getting ads in that tab?
Stephen Epple: I’ve seen a couple of them.
Claire Abraham: Okay.
Stephen Epple: I mean it’s mixed in so like, “Hey, there’s a thunderstorm right now.” Right mixed in here. Here’s an ad for why I should refinance my home loan. I’m not going to do that.
Joe Adams: Was that based on the worm farming or the Chipotle?
Claire Abraham: But all of these things together make up kind of a picture of what Google is trying to be, which is more social. And they’ve definitely tried to be social in the past with, I’m blanking on that social network that they had that is lost.
Stephen Epple: Google Plus.
Claire Abraham: Google Plus. So they’ve had their hand in the game before and now they’re trying to learn from their competitors in social about the way that people interact with that native ad content and how it looks so much like the organic content and bring that to life in their platform.
Joe Adams: So instead of reinventing social platforms altogether, bringing elements of social into their core product.
Claire Abraham: Right.
Joe Adams: And so does the sort of the discover tab on your Google phone feel like a beta they might expand to sort of Google search across devices, or is it sort of native and-
Stephen Epple: Yeah, Google search is, I’m out there searching for something. Discover is them bringing me content before I might want it.
Joe Adams: Based on your search history though. So like they live together.
Stephen Epple: Yeah.
Joe Adams: At some level.
Stephen Epple: Yeah, definitely.
part 3 transcript: paid media bidding + machine learning
Stephen Epple: I think something else we should talk about, Claire, is the new bidding strategies.
Claire Abraham: Yep.
Stephen Epple: And not necessarily for the technical reason, but I think what they illustrate. So when Angela put the piece out a month or so ago around human versus algorithm.
Claire Abraham: Machine learning.
Joe Adams: Human optimization versus machine learning [read the perspective here].
Stephen Epple: Exactly. When Angela put that piece out, one of the things she talked about was why you need humans to understand the business and connect the dots to the machine and the new bidding strategies illustrate that. So one of the things they’re rolling out was seasonality adjustments. So that didn’t exist before. So if you just gave the machine all the power and let them run, they would optimize incorrectly because of your seasonality and they weren’t able to understand that ahead of time.
Stephen Epple: So now you can go in and you know your business, partners like them know your business and we can go in and make adjustments on your seasonality ahead of time. So we’re not optimizing the wrong way.
Joe Adams: So for instance, say a certain business every year, July is an incredibly strong month, but demand drops off for whatever reason in August. The machine may have optimized at a July level through August in the past, but now we can set ahead of time that we should scale back proactively heading into August.
Stephen Epple: Yeah, it’s really where any occasion where recent historical data doesn’t predict future. So if you run a sale, that’s going to skew everything and the machine’s not going to necessarily be able to pick that up the same way that you will. So now you can go in and make your adjustments and everything will be smooth.
Claire Abraham: Yep. I think that lives underneath this umbrella of machine learning and automation, which has been one of Google’s pillars for the last three years. So adopting automation within the Google platform, what does that mean? Their biggest push on automation came two years ago when they brought enhanced cost per click to the forefront of their bidding strategies.
Claire Abraham: So previously bidding was a hundred percent manual. With recommended bids, you could bid down and up with bid modifiers on locations and audiences, and then they rolled out enhanced cost per click. So you can still set your max cost per click, but when the time is right to bid up or down, we’ll be there for you and we’ll optimize for that right audience. But it was still 50% manual, 50% automation.
Claire Abraham: Since then, they’ve rolled out a few other automated bidding strategies. So an automated bidding strategy to maximize for clicks, an automated bidding strategy to maximize for conversions, one for impression share, target ROAS, target cost per acquisition.
Claire Abraham: So target cost per acquisition and target ROAS, you’re going to need to give it some data to be able to feed its algorithm for clicks and conversions. You hadn’t had to give it any data historically. So what Stephen’s talking about is that first iteration of automated bidding, it didn’t account for nuances of businesses. Like in a lot of our advertisers or in a lot of our clients platforms, we have 10 different conversion types because we want to track the entire user journey and we want to understand, what is the real value of this cost per click? What did they do on the site? Did they download something, did they engage with the video? Did they take our lowest funnel conversion action or did they take a medium one?
Claire Abraham: So we’re tracking all these different conversion types and the way that maximized conversions would have worked historically is it would have optimized for the easiest conversion. So you try it on a client and you see calls spike, but your lowest funnel conversion drops because it’s optimizing for what it can do most easily, which is drive more calls. Which is potentially not the actual business result that you were looking for from that campaign. So along with seasonality adjustments in bidding strategies, we now have the ability to set priorities of conversion types within those automated bidding strategies for conversions. So it’s definitely a next generation of automation in Google bidding strategies.
Joe Adams: What do you wish that Google would automate that they haven’t already?
Claire Abraham: They’re willing to automate quite a lot.
Joe Adams: They have stated a goal to put machine learning and automation in the hands of every advertiser. That’s their mission.
Claire Abraham: That’s their mission. Yeah. So you know that article that Angela put out is what does that balance between machine learning, automation and human optimization. And it’s things like them pushing maximize conversions and us viewing an influx in the wrong conversion types. The algorithms not going to catch that without human monitoring. So there’s definitely a marriage between adoption, I absolutely advocate for adoption of automation because it’s integral to the way that advertisers move forward and stay ahead of the curve with regards to where Google’s going. But it’s important that someone who understands the business goals is monitoring what that automation does for your business.
Joe Adams: How can marketing leaders have this conversation with their team because it’s not CMOs who are in the platform, right? They’re relying on us or relying on paid media specialists at their organization. What questions should those CMOs be asking? What sort of, what level of insights should they dive into to make sure that their teams, their agency partners, are taking advantage of what’s available and staying ahead of that curve that you mentioned, Claire?
Claire Abraham: I think that they should be asking whether or not their business goal is being met. So if at the end of the day, you’re receiving your top outcome and it’s meeting your expectations and the goal that you set, I think that’s largely where CMOs oversight lives. And then it’s up to your agency, your partners, your marketing directors to live in the granularity of what’s going to get us there. And sometimes that comes down to testing automation and testing the different levels of automation. Is it 50% automation for this campaign and this campaign at a very high level where we’re just trying to fill the top of the funnel with an audience of a demographic and a location? Maybe that makes sense to buy into automated bidding, automated audiences and automated creative. Maybe that’s a good use of time or not a good use of time to invest in that manual optimization.
Stephen Epple: Yeah. Yeah. For me. It’s about your audience and are you learning something about them and doing something different with that every day. So Google makes, I mean you have people like Claire spends and her team spend eight hours a day in the platform. They go to events like this. We learn what’s out there. There’s a lot that changes in this world as Google reduces the barrier to spending with them and better connecting you to results. Right? So Google’s, a lot of things they’ve done have been around helping you drive better results, right? That’s why there’s big barriers to spending dollars. They want to reduce those barriers.
Stephen Epple: We probably shouldn’t talk about bumper machines, but that’s my favorite.
Claire Abraham: That was your favorite innovation. But we won’t tell you about it.
Stephen Epple: We’re not going to.
Joe Adams: What is a bumper machine?
Stephen Epple: The bumper machine takes your video and it cuts it down to six second bumper ad automatically through machine learning.
Joe Adams: How does the machine understand which six seconds to cut?
Stephen Epple: It knows.
Claire Abraham: Good question.
Stephen Epple: It uses machine learning and algorithms to understand what’s the product placement key moments. Then it gives you control over the final cut.
Claire Abraham: It’s looking for logos and then it’s looking for people and then it’s looking for product use in that six seconds.
Joe Adams: Yeah, efficiency delivered.
Stephen Epple: Because who has a team to create videos? Nobody. So you don’t do bumper ads, but hey, if Google can do bumper ads for you, yeah, I’d spend the money.
Joe Adams: Sure.
Stephen Epple: Why not? And so reducing the barrier to spending more money. I mean that’s everything they’re doing, right. Bidding is complicated and you don’t get the best results. So hey, you use eCPC.
Claire Abraham: Yep.
Joe Adams: So you’d mentioned CMOs should seek to understand their audience better through the platform.
Stephen Epple: Yeah.
Joe Adams: How can they do that? What’s available to them to leverage and then glean from the information?
Stephen Epple: Yeah, so I think paid search is right and paid search through Google is right for a portion of your audience and a portion of their journey and understanding where you’re being effective and where you’re not is important. So they’ve taken affinity, this kind of confusing affinity in the audiences. And what’s the other term?
Claire Abraham: Custom intent audiences.
Stephen Epple: And custom intent audiences. Affinity audiences and intent audiences and they’ve merged them into just custom audiences. And this custom audiences bucket allowed you to go in and build very complex lists where you’re looking for the right person and serve them that right message. So you should be able to use that data to learn something about your audience.
Stephen Epple: And if you’re coming at it just from, and you’re only talking about bidding strategies and you’re talking about keyword targeting and you’re talking about like they opened up a lot of new ways and places to spend money. So they opened up local ads. So now you can place ads in the local search results. So they’ve opened up all these ways and places to spend money. But you need to be learning about your audience at the core and not keywords and bidding strategies and the technical aspects are critical, but that shouldn’t be at the core. It should be about your audience and what you can learn about your audience and what they’re reacting to.
Joe Adams: What message, what information, what images should you place, sort of in the inventory to meet those user expectations?
Stephen Epple: Yes. Yep. And then to Claire’s point, is that audience then driving to, are you then driving that audience towards your business goal?
If you’re interested in conversations with digital marketing experts like this one, I encourage you to check out our Q+A with Brittany Trafis on her experience at Eduventures Summit 2019, a conference for 500 of the most influential leaders in higher ed recruitment marketing and admissions.
