Latest / ContraMinds Podcast - Unlocking Personal Growth and Professional Excellence / The Super CMO Show - Amita Mehra (#012)

Transcript

The Super CMO Show - Amita Mehra (#012) · ContraMinds Podcast - Unlocking Personal Growth and Professional Excellence

• 0:00
  SPEAKER_02: I can talk about Mondelee's example.
• 0:03
  SPEAKER_02: So they basically um so you probably are familiar, Mondelee's is has brands like Oreo, Cadbury, Belder.
• 0:11
  SPEAKER_02: So what they were seeing was was how e-commerce and these digital channels had actually transformed the CPG market um and also pretty much uh fragmented it, if you will.
• 0:26
  SPEAKER_02: Uh so they pivoted into uh personalized advertising.
• 0:30
  SPEAKER_02: Um they actually partnered with Google Cloud to unify all their silo data.
• 0:38
  SPEAKER_02: Um, so it could be actually easily analyzed and unlocked.
• 0:43
  SPEAKER_02: So that was basically their first party strategy because originally they were basically picking up data from all different sources, they unified it with Google Cloud, and then they coupled it with delivering custom uh content to the consumers.
• 1:00
  SPEAKER_02: So they're using the capability of um you know mm generating multiple creatives uh at scale, uh customized to the specific audience.
• 1:10
  SPEAKER_02: So they basically coupled the two things, uh unified their data, used AI to actually generate um creatives at scale for personalization, and then they actually saw ROI um increase by about 10%.
• 1:27
  SPEAKER_02: Um and this not only actually was a one-single campaign, it was actually a great example of how they established a framework for long-term strategic marketing initiatives.
• 1:39
  SPEAKER_02: So now every time they go into it, their their first focus is data, and then the second focus is uh personalization at scale.
• 1:48
  SPEAKER_00: Hello everyone.
• 1:49
  SPEAKER_00: Welcome to another edition of the Super CMO show.
• 1:53
  SPEAKER_00: In this episode, I'm talking to Amita Mehera.
• 1:56
  SPEAKER_00: Amita Mehera is the head of agency business at Google.
• 2:01
  SPEAKER_00: Amita comes with over 20 years of experience, and for a decade and a half, she's been evangelizing the digital advertising business at Google across the AIPAC region.
• 2:12
  SPEAKER_00: I spoke to Amita about how the world of digital advertising is changing with the advent of AI, the new AI-driven Google ad platform, the skills needed for the marketers and the media professionals of the future, and some of the digital ad campaigns that serve as a benchmark for the best-in-class digital ad campaigns in her view.
• 2:34
  SPEAKER_00: Over to my conversation with Amita Mehera.
• 2:39
  SPEAKER_00: This episode of the Super CMO show was made possible by the great folks at Moving Walls.
• 2:47
  SPEAKER_00: Moving Walls provides a global technology platform built by out-of-home advertising experts automating the process of planning, buying, executing, and measuring out-of-home campaigns.
• 3:01
  SPEAKER_00: Moving walls helps leading brands and agencies to move to audience-based planning, improve turnaround times with automated proposals and implement programmatic digital out-of-home and verified campaign performances.
• 3:18
  SPEAKER_00: Moving Walls helps measure, reach and influence moving audiences across the world.
• 3:24
  SPEAKER_00: For more information, log on to www.movingwalls.com.
• 3:54
  SPEAKER_02: That's a great question, and thank you for deeply reading through my profile.
• 3:59
  SPEAKER_02: So my job in Google is to manage media partnerships for Singapore, media agency partnerships for Singapore.
• 4:07
  SPEAKER_02: What it means is that the way our platforms, our products work, they actually are to deliver for the advertisers.
• 4:14
  SPEAKER_02: The results are for the advertisers, but media agencies are key partners to actually use these products to drive those results for the advertisers.
• 4:24
  SPEAKER_02: So my real job is to make sure that the agencies can navigate our products, our org structures as well as our ecosystem very well.
• 4:34
  SPEAKER_02: So it's actually beneficial for them when they use our products for the advertisers.
• 4:40
  SPEAKER_00: Okay.
• 4:40
  SPEAKER_00: So what does that mean?
• 4:42
  SPEAKER_00: So if I were a say a media agency and if I had a set of advertisers, uh how do you think advertisers should leverage Google?
• 4:52
  SPEAKER_00: And how should advertisers bring in the media agencies to get the best value for the investments that they do with the Google ad platform?
• 5:02
  SPEAKER_00: So how do you how do you see that?
• 5:04
  SPEAKER_00: And give me some examples of what you've seen work.
• 5:08
  SPEAKER_02: Okay, uh, you're literally asking me to concise my 14 years into this conversation.
• 5:15
  SPEAKER_04: Yeah.
• 5:16
  SPEAKER_02: So uh our products are really uh for the advertisers to drive their business outcomes through their marketing.
• 5:24
  SPEAKER_02: So the idea is to make marketing their profit centers with our uh Google, Google's AI-powered products.
• 5:32
  SPEAKER_02: The role that media agencies play in this is very fundamental.
• 5:37
  SPEAKER_02: It's to ensure the marketers can actually navigate the ever-evolving landscape of what's all is happening, whether it's consumer behavior, media consumption, channel proliferation, regulatory environment, or a new technology.
• 5:54
  SPEAKER_02: For instance, now the AI is actually all around us.
• 5:58
  SPEAKER_02: So it's their job to stay on top of all of this while optimizing the business outcomes for the advertisers.
• 6:05
  SPEAKER_02: So the way my role uh translates is to make sure that the agencies that I work with they stand out, they're able to talk the advertisers through all the complexities and unknowns with all the insights, understanding of our products, and have a really good track record of driving results uh for the advertisers.
• 6:29
  SPEAKER_00: Okay.
• 6:30
  SPEAKER_00: And uh so one of the things that I uh that I read in many of the uh you know articles that were shared and you know did a bit of uh digging around in many of the stuff that uh you've done.
• 6:44
  SPEAKER_00: Uh one thing that you talk about uh very passionately and what you go with with media agencies and this partnership that you talk about is you talk about in digital marketing uh the need for brands to embrace experimentation, right?
• 7:02
  SPEAKER_00: Uh so why do you think uh this is so critical?
• 7:06
  SPEAKER_00: And uh, if I were a marketer and if I were a uh you know a media head, uh this whole thing around experimentation uh is something which is a big idea that you talk about.
• 7:19
  SPEAKER_00: So, uh, how do you really uh you know look at embracing experimentation and uh what does it include?
• 7:28
  SPEAKER_00: And how do you really think about this whole framework of embracing experimentation?
• 7:36
  SPEAKER_02: First of all, I personally think that we all are experimenting at all times, and that's exactly how we develop, learn, grow in any aspect of life.
• 7:49
  SPEAKER_02: So experimentation as a philosophy is a critical part of our life.
• 7:54
  SPEAKER_02: When we talk about marketing, now, as I touched upon a little bit, marketing environment is constantly evolving, not just by how consumers are shifting, also by the technology that's shifting.
• 8:09
  SPEAKER_02: In fact, if you look at it last couple of few years, most of the business leaders are actually pressured toward profitability.
• 8:18
  SPEAKER_02: They are making ruthless prioritization of their budgets, where to put the budgets in.
• 8:23
  SPEAKER_02: And somewhere marketing has a key role to make sure that you know we are constantly experimenting what works, what does not work, what delivers better financial ROI, how do we make better connections with our consumers, and also to some degree, how do we make our lives as marketers easier so that uh we can make sure that we are delivering those results uh for the business.
• 8:50
  SPEAKER_02: So that's why experimentation is super critical.
• 8:54
  SPEAKER_02: In terms of after you've gone the first step of having the mindset to experiment, if I talk from Google perspective, we have a lot of frameworks, uh, whether it's a controlled framework where you can actually test out a new product versus a legacy structure that you may have in our um ad campaigns.
• 9:16
  SPEAKER_02: That's one way to look at experimentation.
• 9:19
  SPEAKER_02: How do you basically ensure that you're actually setting up the right um structure for the experimentation?
• 9:27
  SPEAKER_02: It's a key part of the framework.
• 9:30
  SPEAKER_02: The next is actually let the experiment run.
• 9:35
  SPEAKER_02: Most of the marketers I feel they struggle through the experimentation period because they're impatient, they're actually testing out, but they're like, oh, what's happening?
• 9:45
  SPEAKER_02: So I think that patience is a very important part of the framework where you, whatever the predetermined, um uh pre-stipulated or pre-predicted timeline that you've set for the experimentation, make sure you have the patience to actually let the experimentation run.
• 10:00
  SPEAKER_02: And then the third, obviously, the most critical part is to actually analyze gains because there's never going to be a scenario where there is a clear winner.
• 10:10
  SPEAKER_02: So, what are the trade-offs?
• 10:11
  SPEAKER_02: What works, what is more scalable, do you want scale versus cost efficiency?
• 10:16
  SPEAKER_02: Or, I mean, in an ideal scenario, you would get it all with the experimentation, but analyzing that experimentation is a super critical part of the framework, it will vary by the business, by the needs, um, on what exactly is the that analysis that needs to be done.
• 10:32
  SPEAKER_02: But effectively, you need to have a clear roadmap of what you're experimenting with, have patience during the experimentation period, don't get too nervous about the spikes or ups and downs, or every experiment is not gonna succeed.
• 10:50
  SPEAKER_02: That's super critical to keep in mind, and then toward the end, how do you analyze?
• 10:55
  SPEAKER_02: And if I can actually draw some um experience from my conversations with the media agencies that I work with, they're very well capable of running um these experiment frameworks for the marketers.
• 11:07
  SPEAKER_02: So if I actually look at just from a Google standpoint, I see a high degree of proficiencies within the agencies to actually be able to do a head-to-head uh test within our ecosystem as well as with other channels because media agencies are pretty much 360, they have view across all.
• 11:27
  SPEAKER_02: So they have the right KPIs, they have the right frameworks to actually make sure that uh they can show the marketers what is the right path and what is the right roadmap.
• 11:37
  SPEAKER_00: Okay.
• 11:38
  SPEAKER_00: So you talked about some frameworks, right?
• 11:40
  SPEAKER_00: So uh the experimentation frameworks.
• 11:43
  SPEAKER_00: So can you elaborate a bit on that?
• 11:46
  SPEAKER_00: Uh say, for example, uh, you know, there is a new category launch that I'm doing for a CPG versus uh I'm launching a new uh you know uh say financial services credit card that I'm looking at.
• 12:01
  SPEAKER_00: Uh so uh if I were to really think about experimentation, uh as an advertiser or as a marketer, uh I want certainty okay in my strategy, uh, but uh the way the Google platforms work is uh you're building hypothesis through your marketing strategy, right?
• 12:21
  SPEAKER_00: Which is very different from how probably it was done uh you know many decades ago, right?
• 12:29
  SPEAKER_00: So, therefore, uh if I were a marketer, uh how do I think of the various levers of experimentation?
• 12:38
  SPEAKER_00: And uh how do I as a media agency help you uh navigate through this mindset?
• 12:44
  SPEAKER_00: I think uh if you can give me with a real life example of uh, you know, you don't you don't need to name the brand, you don't need need yeah, you know, need to name the category, but how did they approach experimentation and what is really the consultative approach that you would recommend as somebody who's seen both sides?
• 13:03
  SPEAKER_02: Uh you actually draw uh a very good um insight that uh traditionally traditionally marketers have been looking for certainty, uh which is pretty much the opposite of the spectrum when we look at experimentation.
• 13:19
  SPEAKER_02: Uh, there is gonna be no guarantee of results.
• 13:23
  SPEAKER_02: So I want to basically start from there.
• 13:26
  SPEAKER_02: However, where media agencies actually play a very critical role because they are not working with a single advertiser, even within the same category.
• 13:35
  SPEAKER_02: Yeah, drawing examples, case studies of other brands is actually super critical because not every experiment which is new to an advertiser is new to the world.
• 13:47
  SPEAKER_02: So I think the confidence can come from other brands' experiments.
• 13:53
  SPEAKER_02: We actually also, as Google, uh, we invest a lot in actually publishing some of these um articles even uh publicly to make sure that people can actually learn from each other because otherwise you're actually uh in isolation trying to figure out what works for you and reinvent the wheel every time.
• 14:13
  SPEAKER_02: So there are there are enough ways that media agencies and we try to actually support the industry to see what has worked in the category or in the particular set of uh brands so that you can actually have some level of confidence before you're getting into the uh experiment.
• 14:31
  SPEAKER_02: So that's obviously one uh one part to the one answer uh to the question.
• 14:37
  SPEAKER_02: The second part I'll address the levers specifically.
• 14:40
  SPEAKER_02: So um in the marketing scheme, we are obviously looking at the consumers, so audience is one lever.
• 14:47
  SPEAKER_02: So, what has been your traditional audience?
• 14:50
  SPEAKER_02: What exactly do you want to actually try and test in this experiment?
• 14:53
  SPEAKER_02: That's one lever.
• 14:55
  SPEAKER_02: Your actual uh channel, uh, which channel or format or creative?
• 15:00
  SPEAKER_02: So there are these are the multiple levers, even budget.
• 15:04
  SPEAKER_02: Uh, what exactly is the budget that you want to experiment with?
• 15:08
  SPEAKER_02: Sometimes you also experiment with the outcomes.
• 15:10
  SPEAKER_02: So let's say a brand is traditionally looking for um engagement as a metric.
• 15:16
  SPEAKER_02: What does engagement mean or has meant uh with the channels they have worked with uh traditionally?
• 15:22
  SPEAKER_02: And what does engagement mean?
• 15:24
  SPEAKER_02: How does it have to be redefined with the channel that we are actually talking about?
• 15:29
  SPEAKER_02: So once you have all of this laid out, uh, which are all the levers that you experiment with, in fact, I'll actually suggest that not going for more than one or two uh levers in a single experiment because then you you're actually creating a very uh a lot of noise in the experiment.
• 15:46
  SPEAKER_02: So if it is audience, be it audience, if it is actually the channel, be channel.
• 15:51
  SPEAKER_02: So I can actually um uh you asked for an example.
• 15:54
  SPEAKER_02: So I'm gonna give you an anonymous example.
• 15:57
  SPEAKER_02: We were we were working with a um ride hailing company, and um they basically were looking for some uh mid-funnel consideration uh for the clients, uh for the customers.
• 16:10
  SPEAKER_02: Um, so the agency actually set up a head-to-head between two channels.
• 16:15
  SPEAKER_02: So the constant was the creative, constant was the budget, uh, the variable was actually the platform.
• 16:24
  SPEAKER_02: Um, in fact, actually, they also kept the audience constant.
• 16:28
  SPEAKER_02: So they kept three levers constant, the platform was um uh the basically the main variable because they were trying to choose between the two platforms, and that's how they approached the experiment.
• 16:39
  SPEAKER_02: So, which of your levers you're gonna keep constant, which are of them you're actually gonna change so that you get a very clear set of understanding.
• 16:48
  SPEAKER_02: The other thing that they tweaked in this example uh example was also how what does engagement mean?
• 16:54
  SPEAKER_02: Because the two platforms actually delivered a very different set of results as a report.
• 16:59
  SPEAKER_02: So, what was that uh understanding of how to translate or how to actually bring parity to what engagement actually means?
• 17:09
  SPEAKER_02: So because it's a consideration um um play, so engagement was actually super critical.
• 17:16
  SPEAKER_02: So defining that upfront that on this platform this is the metric, on this platform, this is the metric, so that there was a uh clear understanding of when the tests or experiment finishes, what exactly are we saying is success?
• 17:30
  SPEAKER_02: So this is uh a live example, uh, I would say, where um the agency actually played a critical role in identifying.
• 17:38
  SPEAKER_00: Okay.
• 17:38
  SPEAKER_00: So so clearly the variable that you're talking about is uh uh you know creative is a key variable.
• 17:44
  SPEAKER_00: Yes.
• 17:45
  SPEAKER_00: Uh the platform was uh something that was there.
• 17:48
  SPEAKER_00: You're uh you know, you're comparing a couple of platforms, you're comparing a couple of uh you know channels, you are comparing a couple of uh maybe uh uh you know middle of the funnel uh kind of approaches that you are looking at.
• 18:01
  SPEAKER_00: So, therefore, one of the most important things do you believe that today's marketer uh needs to have is this ability to uh have uh a very analytical mindset.
• 18:15
  SPEAKER_00: Is that very important for today's marketers?
• 18:17
  SPEAKER_00: And if I were to uh prepare myself to be a more and more from an ideas first marketer to an analytics first marketer, how should I change my mindset and how should I prepare myself?
• 18:31
  SPEAKER_02: You asked me the question that I don't think I can answer without saying AI.
• 18:37
  SPEAKER_02: Um, as we all know, um with the with the actual AI being in most of our ad products, this has become even more critical.
• 18:51
  SPEAKER_02: Because the thing that at the moment Air can't do is actually look at the bigger picture for your organization and create some of these hypotheses or create some of these analytics.
• 19:03
  SPEAKER_02: So it's actually super critical as all of us marketers to to shift or to learn or to upscale or to evolve, depending on where you are, into a sort of a data-led, data-driven or analytics-led uh marketer, because that's obviously the backbone of marketing.
• 19:24
  SPEAKER_02: So the way we actually say powerful marketing is built on good data.
• 19:30
  SPEAKER_02: So, not just the advertisers, but even the media agencies, they should have a strong point of view on the data strategies and the capabilities to build brand.
• 19:39
  SPEAKER_02: And and you know, if you would have heard the even the term data spine, because that's super critical to actually reflect respective businesses' need.
• 19:50
  SPEAKER_02: Now, um, you obviously it starts with a mindset, you there is a need also uh in the whole uh cluttered marketing, fragmented channels, it's important to actually understand.
• 20:06
  SPEAKER_02: So, I would actually start with uh thinking about data from our first party uh data.
• 20:12
  SPEAKER_02: So it's important for brands and marketers to actually start investing.
• 20:17
  SPEAKER_02: It's a cost for sure, it's an infrastructure for some cases.
• 20:22
  SPEAKER_02: So, as an example, CPG is a hardest um category when we talk about first-party data.
• 20:27
  SPEAKER_02: Where do they get the first party data from?
• 20:29
  SPEAKER_02: Their products are uh sometimes really low ticket, uh, it's difficult to actually gather.
• 20:34
  SPEAKER_02: But it's important to actually invest in those infrastructures to then educate and inform your marketing strategies.
• 20:44
  SPEAKER_02: So it's it's starting from a mindset, but it actually ends up becoming an upskilling exercise for the uh marketers and also an investment from the business so that you have sufficient data to make some of these decisions.
• 20:59
  SPEAKER_00: Okay, so so clearly the first-party data thinking uh is waiting, I would say is waiting to take off with all the changes in AI and the new platforms that you are uh actually looking at, right?
• 21:13
  SPEAKER_00: Say, for example, uh your AI-driven new platform that you have, which is the Demand Gen and Perform Performance Max that you have.
• 21:23
  SPEAKER_00: Can you talk a little bit about how these platforms have been transformed and how does it help a media agency?
• 21:31
  SPEAKER_00: How does it help a marketer?
• 21:32
  SPEAKER_00: Can you talk about what is the transition that you're making in these platforms to become more and more AI embedded?
• 21:41
  SPEAKER_02: Um, actually, let me take a bit of a step back.
• 21:44
  SPEAKER_02: Um, we are obviously really out there with our AI powered products now.
• 21:48
  SPEAKER_02: Imagine Performance Mass are one of the two are two of the many products that we've launched recently.
• 21:54
  SPEAKER_02: But I want to actually talk about the fact that we've been using machine learning um in our products for A really long time now, it's been more than four or five years.
• 22:02
  SPEAKER_02: We've actually started with search.
• 22:05
  SPEAKER_02: Um, so as an example, broad match is a perfect example of how we actually use a lot of automation to understand what queries can be matched to your broad queries.
• 22:17
  SPEAKER_02: So it's not entirely new, but yes, now what we have are fully AI-powered solutions.
• 22:25
  SPEAKER_02: So, what these solutions allow marketers to do is to not actually worry about what keywords to target, which audience to look for, where to look for these audiences, how to set their budgets, what should be my right bidding?
• 22:45
  SPEAKER_02: Um, what exactly is the value that I'm getting from all of these different consumers that are coming to my website or if they are actually making a purchase?
• 22:55
  SPEAKER_02: AI takes away all this work, learns from within your campaign, can build images from your website, can actually also, we have a lot of generative AI in our products now, can also actually build creatives and takes away a lot of burden of identifying where exactly is the right ROI and uh decide the bidding, self-optimize to some degree, and ensure that you're getting the results.
• 23:29
  SPEAKER_02: So, you as a marketer, your job is to have that strategy of what is exactly your goal, what is exactly the cost that you're willing to pay for that goal, what is the messaging.
• 23:43
  SPEAKER_02: As long as you have very clear understanding of these three, you can actually pretty much let AI do the rest.
• 23:51
  SPEAKER_02: Of course, we also know some advertisers will be sensitive about what is the messaging that's going on.
• 23:57
  SPEAKER_02: So, we do have certain uh controls in play where um what level of flexibility you want uh the AI, I mean the machine to actually have.
• 24:08
  SPEAKER_02: So if you're a small advertiser with low brand um uh guidelines, then you can actually literally have just the budget, um, the goal and the cost per goal, and that should be pretty much it for you to get going.
• 24:24
  SPEAKER_02: But as you obviously are more sensitive, you we do have a lot of other filters that you can apply to make sure that we are also creating a safe for brands environment.
• 24:33
  SPEAKER_00: Okay, so so you uh so how is this whole uh you know pre-AI marketing and post-AI marketing uh differ, and therefore, how should I think about my marketing if I were a marketer and if I were a media agency?
• 24:52
  SPEAKER_00: So, uh, what are the changes that I need to really start thinking about?
• 24:58
  SPEAKER_02: So um with AI marketing is gonna continue to evolve actually.
• 25:03
  SPEAKER_02: To be honest, even we can't predict or we can't be certain exactly how far this is gonna go.
• 25:10
  SPEAKER_02: So the first thing as a marketing industry, I think we need to be used to or get used to is just embracing change and keep evolving.
• 25:20
  SPEAKER_02: That's very critical, and that's it may sound like a philosophy, but it is actually a critical part of uh embracing the new technology.
• 25:30
  SPEAKER_02: Um, in terms of the actual core competencies or capabilities, um I think we've talked about it.
• 25:37
  SPEAKER_02: I think data and measurement uh to guide marketing or media decision making is going to be super critical.
• 25:45
  SPEAKER_02: So, tactically, uh, what portion of your team should be make up made up with data scientists or analytics specialists versus um client servicing if you're talking about a media agency?
• 25:57
  SPEAKER_02: So that shift needs to change.
• 26:00
  SPEAKER_02: Um how what are the signals?
• 26:03
  SPEAKER_02: What are the uh systems that you're actually deploying to predict the probability of success, or how you're actually monitoring outcomes is going to be the critical part, and that's when you need these data scientists or analytics um specialists to do it.
• 26:20
  SPEAKER_02: So data would be my first or number one thing.
• 26:23
  SPEAKER_02: Um audience uh and how does it inform the brand strategy that will still remain um the core of marketing?
• 26:33
  SPEAKER_02: So I always call marketers our consumer chasers, so we will continue to chase them.
• 26:39
  SPEAKER_02: But of course, uh it's gonna be continually difficult for uh brands to actually stay tuned uh to the audience behavior because it's actually shifting so fast, it's so dynamic, it's so fragmented.
• 26:53
  SPEAKER_02: Um, so what exactly is uh their audience strategy?
• 26:58
  SPEAKER_02: Um again, got to back to data-driven, what has worked in the past, um, then accordingly figure out a communication strategy, um, planning, rely on AI to find your audience.
• 27:14
  SPEAKER_02: I don't need to define um, so let me give you an example.
• 27:18
  SPEAKER_02: Uh, you must have heard some advertisers say, Oh, I think Gen Z is gonna buy my product.
• 27:24
  SPEAKER_02: Um, but when you run your campaign, you actually realize you're getting the best possible uh sale from a different set of uh audiences.
• 27:32
  SPEAKER_04: Yeah.
• 27:33
  SPEAKER_02: So you you you're actually you need to educate or sometimes re-educate or revalidate your own um concepts of what works.
• 27:43
  SPEAKER_02: Uh, but then the trust in AI obviously is um super critical for that as well.
• 27:48
  SPEAKER_02: The third thing that I'll also uh touch upon is um privacy readiness.
• 27:53
  SPEAKER_02: Uh consumers are obviously demanding privacy, um, so we need to make sure that um, you know, this from not just regulatory standpoint, it's just good, you know, yeah, good practice because if consumers want uh privacy, then um you should have a solid strategy of how you can be privacy-centric and not just on your website, how you're advertising.
• 28:19
  SPEAKER_02: There's been a high reliance on third-party cookies uh to actually deliver results.
• 28:24
  SPEAKER_02: So when the cookies eventually will uh phase out, uh how do they how do the marketers actually stay ready for that uh moment?
• 28:32
  SPEAKER_02: Now, I here actually I'll probably call out one of uh the agencies that I work with, Omnicor Media Group in our region, has been at the forefront of innovating in light of third-party cookie deprecation.
• 28:44
  SPEAKER_02: They're actively going to market and talking about the importance of signals and solutions moving to privacy and AI first world, which is uh is important.
• 28:54
  SPEAKER_02: They've actually even created a resid uh readiness framework uh with in collaboration with Google to help advertisers assess the impact of their current media investments across data collection, targeting, activation tactics, and measurement.
• 29:09
  SPEAKER_02: So um I think these would be the core principles of uh marketing, and um back to my point, we'll all have to continuously learn.
• 29:20
  SPEAKER_02: Um it's no longer don't don't we we cannot look at marketing as a career for life, but it's gonna be a lifetime of careers, um, and obviously we need to evolve our roles.
• 29:35
  SPEAKER_00: Very nice.
• 29:36
  SPEAKER_00: Uh in our earlier uh you know uh part of the conversation, you talked about first-party data.
• 29:43
  SPEAKER_00: I think uh there's a lot of discussion today on uh you know marketers creating first-party data or uh you know taking the help of media agencies uh to start preparing the first-party data infrastructure which can then uh integrate with uh Google's marketing platform.
• 30:04
  SPEAKER_00: So, can you talk a little bit about some of the successful examples that you have seen of some brands taking uh steps in this direction and what would you identify as some of the steps that brands need to take to move to a first-party world which will then get integrated with the Google platform?
• 30:25
  SPEAKER_02: I'll probably talk about three categories of uh advertisers.
• 30:31
  SPEAKER_02: There is one category of advertiser that's actually ready with first-party data.
• 30:36
  SPEAKER_02: So any digital native um advertiser, marketplace, there is a ton of first-party data.
• 30:44
  SPEAKER_02: Their whole business is on first-party data.
• 30:48
  SPEAKER_02: So there is a section or segment of advertisers that you can say is ready with first party data.
• 30:56
  SPEAKER_02: So how do we basically make sure that they are ahead?
• 31:01
  SPEAKER_02: We are making sure that they they can actually you know bring the industry together.
• 31:07
  SPEAKER_02: So, how do we spot light on them and actually make sure that people can actually learn from that?
• 31:11
  SPEAKER_00: So I'm just interrupting you.
• 31:13
  SPEAKER_00: So for the audience, yes, uh, how does how do you define first party data?
• 31:19
  SPEAKER_00: Because there are many, many uh definitions of what is first party data.
• 31:24
  SPEAKER_00: So it's important that we have a common definition of what is defined by first party data, right?
• 31:29
  SPEAKER_00: Correct?
• 31:30
  SPEAKER_02: That is correct.
• 31:32
  SPEAKER_02: So I am not an expert of first-party data, but for the common denominator, let's call it the data that a user has provided uh themselves to an advertiser.
• 31:46
  SPEAKER_02: So it could be I either via um an app registration, a website registration, or sometimes you uh depending on advertisers, they also collect it at point of sale.
• 31:57
  SPEAKER_02: So any user, uh any data that user has actually uh provided themselves.
• 32:02
  SPEAKER_00: Fantastic.
• 32:03
  SPEAKER_00: Yeah.
• 32:04
  SPEAKER_02: Okay, so back to my segment.
• 32:05
  SPEAKER_02: So one segment that's ready, that's actually leveraging it, how do we spot light on them and use uh or inspire others?
• 32:14
  SPEAKER_02: The second segment, which I feel is a regulated segment, so I'll use finance industry as an example.
• 32:20
  SPEAKER_02: They they sit on first-party data, they have they know exactly everybody who's their current customer, but they have limitations on what they can share.
• 32:31
  SPEAKER_02: They obviously are under strict guidelines, regulations, as well as um to make sure that when they're sharing the data, uh, they're also doing it in a safe manner.
• 32:42
  SPEAKER_02: So that's a bit of a, I would say, the most challenging segment, and I'm sure there are others in that category too where there are more sensitivities.
• 32:51
  SPEAKER_02: So that's where I feel the struggle is, and I don't think it's truly answerable uh from a marketing standpoint.
• 32:58
  SPEAKER_02: It's basically a lot of legal and all other teams that actually can solve for that.
• 33:04
  SPEAKER_02: And then let me address the third segment, which is where it's not organically there, but the marketers need to start thinking about it.
• 33:12
  SPEAKER_02: So some of those um verticals or industries would be retail.
• 33:17
  SPEAKER_02: Um, are you every time a consumer buying, um, are you actually collecting that data?
• 33:23
  SPEAKER_02: Uh, so you'll see examples like HM, Uniqlo, IKEA, um at the checkout, they give you some sort of incentive to actually log in or they um you know create an app to make sure that you're actually using the app to check out so that they're constantly um getting the first-party data and uh so that they can actually work with this.
• 33:46
  SPEAKER_02: So a lot of um uh progress has actually been made, uh, particularly in the retail segment.
• 33:53
  SPEAKER_02: CPG uh is I think the most where the most struggle is because their ticket item is low and their distribution is actually pretty fragmented because uh sometimes their products are sold in departmental stores, supermarkets, or um even uh online on mom and pop shops.
• 34:11
  SPEAKER_02: So that's been the biggest struggle.
• 34:14
  SPEAKER_02: But um, I know some CPG companies are actually making uh progress there.
• 34:20
  SPEAKER_02: One example is Coca-Cola, Coca-Cola has actually really invested in their website to uh make sure when a consumer is actually looking at their ad, they actually come and come to their website, and if they choose to, they can actually register.
• 34:37
  SPEAKER_02: Similarly, Unilever, um, everybody is now investing in a little bit of a product page, even if they may not be selling there, but they actually use some of the incentives or sampling.
• 34:49
  SPEAKER_02: PNG does a lot of sampling, that's another way to actually collecting uh first-party data.
• 34:54
  SPEAKER_02: So every vertical is actually trying to tackle it differently based on the nuances uh of the consumers as well as their own distribution channel.
• 35:04
  SPEAKER_02: But I would actually say, in my experience, um, most of them are actively already thinking about it.
• 35:10
  SPEAKER_02: It's just making sure that they actually cross the line uh and um get it done and make it significantly uh statistically significant uh in terms of scale so that it's actually utilized for the analytics as well as for their marketing strategies.
• 35:30
  SPEAKER_00: Okay.
• 35:31
  SPEAKER_00: So so clearly what you uh said was uh you know building that infrastructure and investing in the first party data, infrastructure is critical.
• 35:39
  SPEAKER_00: And uh uh how uh how do you think uh if I was a say a new marketer or a traditional marketer coming into this kind of a first-party data world?
• 35:51
  SPEAKER_00: Uh, how does uh Google help me leverage and get value out of it?
• 35:56
  SPEAKER_00: So if I was a uh is there some examples that you can say uh you know how the uh you know broad matching happens and therefore you're able to then provide enough value to your marketing objectives.
• 36:07
  SPEAKER_00: So, how do you think uh you know agencies and marketers need to now take advantage of uh uh the first party infrastructure that gets created and then leveraging the uh you know the gold mine that uh you know uh Google has got in terms of achieving their marketing objectives?
• 36:27
  SPEAKER_02: Yeah, I think the first and the most obvious use case is to identify the value of the consumer because uh every consumer is not gonna uh be um spending the same.
• 36:39
  SPEAKER_02: So that is super critical, and then you can actually send these signals.
• 36:44
  SPEAKER_02: So um our automated bidding types actually can take these signals of which type of customer is the most valuable based off of your existing first party and actually find similar audiences.
• 37:00
  SPEAKER_02: So the way this actually works is that you can allow the system to mirror your high value uh customers uh and get most out of your ad spends.
• 37:12
  SPEAKER_02: So TROS basically is the targeting that we do, which is the bidding type, which is you're actually bidding for the value of the consumer.
• 37:24
  SPEAKER_02: That's obviously one and the most critical use case, but it can generally help you scale.
• 37:29
  SPEAKER_02: So let's say you're a uh you have a limited uh first-party data, well, but you want to actually reach more, your actual goal is to reach and expand and get more sales, brand new sales, people you haven't reached out to earlier.
• 37:45
  SPEAKER_02: So instead of using the traditional um targeting methods of your demographic or the specific set of audience, you can actually just uh let the system let AI actually find um new audiences based off of your first party data.
• 38:01
  SPEAKER_02: So getting more most results from your ad spends is obviously one thing that will resonate with most marketers, and the second is actually getting more scale.
• 38:12
  SPEAKER_02: These would be the top two use cases of how they can actually leverage first-party data, and there's a lot.
• 38:18
  SPEAKER_02: Um, so we do have support center help center, you can actually go out and uh search for it.
• 38:24
  SPEAKER_02: There are a lot of other use cases as well, but these would be, I would say, my top two, and this also pretty much um is what is on top of mine for every marketer's one or the other.
• 38:37
  SPEAKER_00: Okay, so uh, if I were talking about uh media agencies, uh many a times uh I saw this in one of the Google reports, uh uh and it's an interesting point that that you make, and a lot of skill building workshops that you run for them uh uh is about moving from being an idea generator to a solution facilitator, right?
• 39:03
  SPEAKER_00: Which is a very interesting terminology that I read in one of your uh uh you know resources and the research reports that you publish for uh the agencies and for the marketers.
• 39:14
  SPEAKER_00: So uh so when you really talk about this, it's a massive shift from just being an idea generator to a solution facilitator, right?
• 39:24
  SPEAKER_00: Because what you're really doing is then you're looking at the ecosystem, you're looking at channels, you're looking at creative types, you're looking at what kind of a problem that you have.
• 39:33
  SPEAKER_00: So your ability to kind of think solutions and not just ideas is that something that uh is a very important skill that you think uh you know uh marketers and the agency uh folks need to start uh you know preparing themselves for in the coming decade?
• 39:52
  SPEAKER_02: Absolutely, you're pretty much bang on.
• 39:54
  SPEAKER_02: But if you'd like, I can um talk a little bit more in detail of what that could mean and if other skills that I think 100%, 100%.
• 40:04
  SPEAKER_02: So um I think uh let's just establish uh the automation is going to change the nature of jobs um and employment.
• 40:13
  SPEAKER_02: Um so we need to think about also uh not just the jobs that might be displaced, um, which could be some of the repetitive tasks, yes, but then how the current jobs are gonna evolve and how the new jobs are gonna emerge.
• 40:31
  SPEAKER_02: So, I mean, this is probably cliche.
• 40:34
  SPEAKER_02: Uh, what I'm doing right now, 30 years ago, nobody was doing.
• 40:39
  SPEAKER_02: Um, so it is gonna create the jobs that did not exist uh pre-AI.
• 40:45
  SPEAKER_02: So, in context of marketing, we may not need as many campaign practitioners, for example, but uh data and analytics role would evolve into most critical uh part of the media teams.
• 40:59
  SPEAKER_02: Um I'm actually hypothetically saying imagine a role called AI custodian um or AI marketing specialist or AI content writer, um AI growth hacker.
• 41:13
  SPEAKER_02: That would be a great marketing role for future.
• 41:17
  SPEAKER_02: Um, and in order to actually understand what skills that would be, um so we we still need some technical skills.
• 41:24
  SPEAKER_02: So, as an example, what does omnichannel mean?
• 41:28
  SPEAKER_02: So each channel may have its own AI capability, but who's there trying to actually uh look at a holistic view of omnichannel?
• 41:36
  SPEAKER_02: The ability to understand all the solutions and their interplay, you still need that capability to make sure that your budget is obviously not getting wasted.
• 41:48
  SPEAKER_02: Um, basic programming skill is not a bad thing to learn, and I'm not asking everybody to become an engineer, but familiarity with uh some of the upcoming languages are I don't know it yet.
• 42:00
  SPEAKER_02: Um it can empower individuals to actually build some even solutions for themselves.
• 42:07
  SPEAKER_02: Um, and then also back to your uh solution facilitator storytelling, content curation, um you know, strategic thinking, planning, how do you use the data uh to make marketing strategy?
• 42:24
  SPEAKER_02: How do you identify trends?
• 42:26
  SPEAKER_02: Actually, why don't I give you an example?
• 42:28
  SPEAKER_02: Um so it's actually uh it's a global example.
• 42:34
  SPEAKER_02: Um so Bayer.
• 42:37
  SPEAKER_02: Um Bayer is a pharmaceutical brand.
• 42:41
  SPEAKER_02: They found a great business insight for its brand, uh, Claritin, it's an antihestamine.
• 42:49
  SPEAKER_02: That pollen levels are actually expected to be double by 2040.
• 42:54
  SPEAKER_02: The reason for this is actually male trees.
• 42:57
  SPEAKER_02: That insight inspired the creative minds at both Bayer and their agency, basically NRGB Do come up with Diversity Tree projects.
• 43:07
  SPEAKER_02: This was to ease allergen or allergy symptoms by planting pollen absorbing female trees.
• 43:15
  SPEAKER_04: Okay.
• 43:15
  SPEAKER_02: So Diversity Tree was uh uh basically a creative campaign, it was a messaging, um, and it was actually really successful.
• 43:24
  SPEAKER_02: They I think they won gold line at Cannes last year.
• 43:28
  SPEAKER_02: So again, AI can't use the insight at the moment, make it relevant to the business, and actually say how exactly that messaging needed to be done.
• 43:42
  SPEAKER_02: So you need to be that solution facilitator in between.
• 43:45
  SPEAKER_02: But AI can multiply this creativity.
• 43:49
  SPEAKER_02: So, in order to actually get plenty of eyes on this campaign, on the diversity message, Bear actually scaled it through YouTube.
• 43:58
  SPEAKER_02: They used our video reach campaigns.
• 44:00
  SPEAKER_02: It's an AI powered solution which targeted users across YouTube.
• 44:05
  SPEAKER_02: So, you know, we have in-feed ads, in-stream ads, shorts.
• 44:09
  SPEAKER_02: So the campaign was basically just scaling it across.
• 44:12
  SPEAKER_02: So you need a solution facilitator to build a solution from an insight relevant to the business, but you AI can help you multiply that creativity.
• 44:22
  SPEAKER_02: So I would say while we need solution facilitators, we definitely need more people who can leverage and who know how to use AI to then multiply all those solutions, to scale those solutions, to actually make them work and hopefully analyze and report.
• 44:43
  SPEAKER_02: So these would be the main roles and main skills that will be relevant to marketing.
• 44:49
  SPEAKER_00: Perfect, perfect.
• 44:52
  SPEAKER_00: So if I were to look at connected TVs, which is another area which is fairly in early stage, while there are many connected TV that are happening all over the world, if I were to look at one aspect that I think you speak about is integrated planning.
• 45:12
  SPEAKER_00: I think you started about this whole interplay, is what you use, and you know, we call it integrated planning.
• 45:19
  SPEAKER_00: So if I was a media uh planner and if I was a media orchestrator, if I were to call it, okay, so how do you see the connected TV uh you know being completely working closely with my mobile media, with my traditional uh you know, uh internet media?
• 45:39
  SPEAKER_00: So, how do you see the interplay and is there a need for an integrated planning thinking for media planners and for brands?
• 45:49
  SPEAKER_02: It absolutely is very critical.
• 45:53
  SPEAKER_02: Um consumers, we are chasing them, they are all over the place, sometimes on two devices.
• 46:02
  SPEAKER_02: One is playing YouTube, one is playing perhaps um N OTT.
• 46:08
  SPEAKER_02: So we need that integrated planning to make sure that we are capturing that user wherever they are.
• 46:16
  SPEAKER_02: Because at the end of the day, the users are no longer limited by a living room TV situation, which then we started imagining them just stuck to their desktops.
• 46:29
  SPEAKER_02: That changed with mobile, and now I think it's all over screens are unlimited.
• 46:34
  SPEAKER_02: I I would be surprised if next year I had a TV on my wrist too.
• 46:41
  SPEAKER_02: So it is very important, it's critical.
• 46:44
  SPEAKER_02: I can talk about our platform.
• 46:46
  SPEAKER_02: Uh so we have uh DB360, it's our uh DSP, where you can buy YouTube and all our integrated partners, OTT partners, and actually, what's the beauty of the platform is that you can actually frequency management across all in one shot.
• 47:07
  SPEAKER_02: So if you've said that a user should see my ad three times, so let's say one time they were on YouTube, one time they were on platform X and platform Y, it will actually count it as three and get you so much media efficiency.
• 47:22
  SPEAKER_02: So you can actually holistically see it as a connected TV.
• 47:27
  SPEAKER_02: Um, or sorry, they are watching the connected TV.
• 47:31
  SPEAKER_02: You can actually see it as an integrated strategy with real benefit of frequency management.
• 47:37
  SPEAKER_02: So our platform can actually make sure that irrespective of where the user is, you're not double dipping, you're not actually uh showing the same ad at the frequency of three across the three platforms to the same user while your intention of was to actually show them only three times.
• 47:54
  SPEAKER_02: So that's actually the perfect example of how the power of our platform can actually allow um media agencies or advertisers to gain efficiencies using um very, very, very fundamental um processes that we have.
• 48:12
  SPEAKER_00: So so therefore, uh at one end you've got the DB360, which is really the central core of how you can orchestrate uh campaigns across channels, and then you have the uh you know uh the storytelling and the creative that's sitting at the other end, and then you are uh saying uh you've got first-party data sitting at the other end, and therefore you are actually saying, hey, use your first party data in an interesting manner on our DB360 across channels, with uh you know, uh, say a whole range of creatives, and then that's really the way you should start thinking using AI-powered uh you know strategies, and that's really how it should move going forward.
• 48:58
  SPEAKER_00: I think that's the way uh you are recommending that uh marketers and media agencies start to think about brand building in the coming years, right?
• 49:07
  SPEAKER_02: My job is Dania.
• 49:11
  SPEAKER_02: Yes, uh absolutely.
• 49:12
  SPEAKER_02: Um, of course, uh, if you're actually looking at brand not just on a single platform, that would be uh the most recommended strategy where you can actually have an omni platform uh at a perfect media efficiency.
• 49:28
  SPEAKER_02: So, yes.
• 49:29
  SPEAKER_00: So uh give me a give me an example of uh a campaign or a brand that's used uh this kind of a strategy very uh in an effective manner, and uh you believe that they are on the path to thinking like this, uh a media agency, or a you don't need to name name the media agency, but a campaign that probably caught your attention because you see it from uh you know different markets, you see it from different brands, you see it from different categories.
• 49:56
  SPEAKER_00: Uh so give me some uh one or two interesting uh case studies which you thought was interesting, and there was some of these concepts that we spoke about for the last uh you know couple of minutes, who uh where you saw it work and the kind of results that they achieved.
• 50:14
  SPEAKER_02: I can talk about Mondelee's example.
• 50:17
  SPEAKER_02: Um, so they basically um so you probably are familiar, Mondelee's is has brands like Oreo, Cadbury, Banditab.
• 50:25
  SPEAKER_02: So what they were seeing was was how e-commerce and these digital channels had actually transformed the CPG market um and also pretty much uh fragmented it, if you will.
• 50:40
  SPEAKER_02: Uh so they pivoted into uh personalized advertising.
• 50:44
  SPEAKER_02: Um they actually partnered with Google Cloud to unify all their silo data, um, so it could be actually easily analyzed and unlocked.
• 50:57
  SPEAKER_02: So that was basically their first party strategy because originally they were basically picking up data from all different sources, they unified it with Google Cloud, and then they coupled it with delivering custom uh content to the consumers.
• 51:14
  SPEAKER_02: So they're using the capability of um you know mm generating multiple creatives uh at scale, uh customized to the specific audience.
• 51:24
  SPEAKER_02: So they basically coupled the two things, uh unified their data, used AI to actually generate um creatives at scale for personalization, and then they actually saw ROI um increase by about 10%.
• 51:41
  SPEAKER_02: Um and this not only actually um was a one-single campaign, it was actually a great example of how they established a framework for long-term strategic marketing initiatives.
• 51:53
  SPEAKER_02: So now every time they go into it, their their first focus is data, and then the second focus is uh personalization at scale.
• 52:02
  SPEAKER_00: Fantastic, fantastic.
• 52:04
  SPEAKER_00: Uh so that pretty much uh you know summarizes uh this example summarizes whatever we were talking about.
• 52:11
  SPEAKER_00: So I'm going to uh you know end this conversation with a couple of rapid-fire questions.
• 52:16
  SPEAKER_00: Uh so uh my first question is uh if I were a uh digital marketer uh planning for my career in the future, uh what would be your uh you know top three skills that you think uh I should be uh focused on?
• 52:37
  SPEAKER_02: I cannot stop speaking about data and analytics as number one.
• 52:44
  SPEAKER_02: Second, prompt engineering.
• 52:47
  SPEAKER_02: Learn how to actually feed AI or make AI work.
• 52:51
  SPEAKER_02: And the third, I'll take your cue on that one, which is be solution facilitator.
• 52:56
  SPEAKER_00: Okay, fantastic.
• 52:58
  SPEAKER_00: Uh the if I were an 18-year-old uh studying marketing in a university, uh what would you what would your advice be to them?
• 53:10
  SPEAKER_02: First of all, you're probably studying an old curriculum.
• 53:16
  unknown: Yeah.
• 53:17
  SPEAKER_02: Uh secondly, I think uh a lot of learning is actually gonna happen um on the job for them.
• 53:24
  SPEAKER_02: Um so my best advice would be to keep an open mind, embrace and adapt, don't be inundated with all that's going on, um, and just focus on the core skills.
• 53:35
  SPEAKER_00: Okay.
• 53:36
  SPEAKER_00: Um what is one piece of advice uh over your career that you received which you value even today?
• 53:45
  SPEAKER_00: And as you work, that keeps coming back at you every time when you do your job.
• 53:50
  SPEAKER_00: So one piece of advice.
• 53:52
  SPEAKER_02: Um risks, uh always be open to take risks.
• 53:57
  SPEAKER_02: Um there are obviously rules to taking risks.
• 54:01
  SPEAKER_02: Take an informed risk, communicate your risks, but do take risks and don't um don't hesitate from failing because risk, the word risk in itself has a high probability of failing.
• 54:17
  SPEAKER_02: Um so yeah, I would always say take risks.
• 54:21
  SPEAKER_02: Um if you're no matter where you are, which company, which team, as long as you have taken informed and you've communicated well, um, I'm sure your ideas will be welcome.
• 54:33
  SPEAKER_00: Uh if uh if uh I were looking at uh resources where I can learn some of the new technologies and the whole AI-driven marketing that you're talking about, uh where are the places that uh you know I need to go?
• 54:50
  SPEAKER_02: I'm glad you asked this question.
• 54:52
  SPEAKER_02: I am so ready for this.
• 54:53
  SPEAKER_02: Uh first of all, uh Google has actually recently launched uh a course called Google AI Essentials, it's uh in collaboration with Coursera.
• 55:02
  SPEAKER_02: So you from Gen I to prompt techniques, responsible AI, and even you know how to develop strategies to stay up to date in the emerging landscape of AI, it's got all.
• 55:15
  SPEAKER_02: So Google AI Essentials can be your starting point, but we also have other courses.
• 55:21
  SPEAKER_02: Um, we also have um Google Career Certificates, which is available at Grow with Google.
• 55:28
  SPEAKER_02: Um, so where we you know we help the industry to actually gain knowledge uh around um data, advanced data analytics, business intelligence, and finally the third stop you can visit is uh Google Cloud's website.
• 55:43
  SPEAKER_02: So we have a lot of machine learning and artificial intelligence courses there.
• 55:47
  SPEAKER_02: They these training programs actually uh include digital leader certification, uh professional data engineer certification, courses on training image classification models, courses on building and deploying AI solutions, vertex AI, gen i gen AI.
• 56:05
  SPEAKER_02: I mean, it's got a lot of uh information.
• 56:08
  SPEAKER_02: So if you're looking for a fundamental for all jobs, start with Google AI Essentials, go to Grow with Google, and then if you're looking for very specific, more advanced, you can also visit Google Cloud's website.
• 56:25
  SPEAKER_00: And uh the last question that I have is if I were a creative uh mind and a creative director, uh, where can I learn from Google the various campaigns and other repositories of campaigns that I can get inspired by?
• 56:42
  SPEAKER_00: Is there one place to go?
• 56:44
  SPEAKER_02: Absolutely, go to think with Google.
• 56:46
  SPEAKER_02: In fact, I would be um I would probably I'm half unsure, but maybe some of the examples that I use today would all already be there on the publication.
• 56:58
  SPEAKER_02: So think with Google is a one-stop shop for all marketing um experts or even the beginners to see what solutions work, you hear from largest companies, largest brands, their case studies, their leaders, how they're approaching AI.
• 57:15
  SPEAKER_02: So you'll get a lot of resources there.
• 57:18
  SPEAKER_00: Great.
• 57:18
  SPEAKER_00: So thanks, Amitha.
• 57:20
  SPEAKER_00: It was lovely talking to you.
• 57:21
  SPEAKER_00: Uh, I think uh your width and breadth of experience, uh, your point about having the data skills and the prompt engineering skills and uh getting this whole AI-driven thinking is something that came out very, very clearly.
• 57:36
  SPEAKER_00: And uh I can see Google at the forefront of uh transforming this uh marketing industry and how you are partnering with brands and media agencies.
• 57:49
  SPEAKER_00: Uh, it came out very well, and uh thanks a lot for sharing your thoughts and ideas with us, and thanks a thanks a ton for talking to me.
• 57:57
  SPEAKER_02: Thank you so much, uh Swamisar, and thank you, Contraminds, for having me.
• 58:02
  SPEAKER_00: Welcome.
• 58:03
  SPEAKER_00: Thanks for listening to this episode.
• 58:06
  SPEAKER_00: For selected links and detailed show notes, visit www.contraminds.com.
• 58:13
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• 58:36
  SPEAKER_00: Thanks for listening and stay safe.