1 00:00:03,800 --> 00:00:06,400 Speaker 1: Rocket Lab founder Sir Peter Beck was the guest of 2 00:00:06,480 --> 00:00:09,520 Speaker 1: honor at an event at Parliament last week to celebrate 3 00:00:09,640 --> 00:00:14,400 Speaker 1: rocket labs success. The government loves the space industry and 4 00:00:14,440 --> 00:00:17,880 Speaker 1: it's easy to see why. It's growing very quickly, now 5 00:00:18,040 --> 00:00:21,840 Speaker 1: worth two point five billion dollars and supports around seventeen 6 00:00:21,960 --> 00:00:25,639 Speaker 1: thousand full time jobs according to a Deloitte report that 7 00:00:25,800 --> 00:00:29,000 Speaker 1: came out last month, not bad for an industry that 8 00:00:29,040 --> 00:00:32,600 Speaker 1: didn't even exist a decade ago. But from the stage 9 00:00:32,600 --> 00:00:35,680 Speaker 1: of the banquet hall at Parliament, So Peter issued a 10 00:00:35,800 --> 00:00:39,120 Speaker 1: challenge to the leaders of our companies, not just space companies, 11 00:00:39,360 --> 00:00:42,839 Speaker 1: any sort of company, think bigger, whatever industry you're in, 12 00:00:43,240 --> 00:00:44,600 Speaker 1: be more ambitious. 13 00:00:45,280 --> 00:00:49,080 Speaker 2: So the space industry is predicted in about a decade 14 00:00:49,240 --> 00:00:51,960 Speaker 2: or slightly less, to be worth two point three trillion dollars. 15 00:00:52,720 --> 00:00:56,600 Speaker 2: That's a pretty big opportunity, and you know there's nothing 16 00:00:56,640 --> 00:00:59,360 Speaker 2: stopping New Zealand from getting a decent chunk of that. 17 00:01:00,680 --> 00:01:02,400 Speaker 2: I've written the little texts at the bottom. It probably 18 00:01:02,400 --> 00:01:04,760 Speaker 2: should have been bigger texts. But I reckon that we 19 00:01:04,880 --> 00:01:07,520 Speaker 2: just set a ten percent target. I reckon that it's 20 00:01:07,600 --> 00:01:10,679 Speaker 2: perfectly reasonable that we build an industry in New Zealand 21 00:01:10,680 --> 00:01:12,520 Speaker 2: where two hundred and thirty billion. That sounds about the 22 00:01:12,560 --> 00:01:16,280 Speaker 2: right size number to meet. So that should be our goal. 23 00:01:16,400 --> 00:01:19,640 Speaker 2: Let's make I appreciate your Prime Minister wanting to double it, 24 00:01:19,680 --> 00:01:22,160 Speaker 2: but I think we can. We can take turnred and 25 00:01:22,160 --> 00:01:23,319 Speaker 2: thirty billion dollars of it. 26 00:01:24,440 --> 00:01:24,640 Speaker 1: Yeah. 27 00:01:26,600 --> 00:01:28,520 Speaker 2: The interesting thing is that I knew that when I 28 00:01:28,520 --> 00:01:30,120 Speaker 2: would say that, there'd be a couple of sniggers in 29 00:01:30,160 --> 00:01:33,200 Speaker 2: the room. And that's the reality. And this is the 30 00:01:33,240 --> 00:01:37,520 Speaker 2: thing that holds back New Zealand. New Zealand are great executioners, 31 00:01:37,680 --> 00:01:39,840 Speaker 2: Like we can build stuff that works, We're really really 32 00:01:39,840 --> 00:01:42,360 Speaker 2: good at it, but we're just a bit shy in aspiration. 33 00:01:42,840 --> 00:01:45,480 Speaker 2: And you know, if I was talking in the same 34 00:01:45,560 --> 00:01:47,760 Speaker 2: room in America, nobody would giggle that we wanted to 35 00:01:47,800 --> 00:01:51,600 Speaker 2: make take ten percent of the space industry. So one 36 00:01:51,600 --> 00:01:54,240 Speaker 2: thing that I would recommend here is, like, you know, 37 00:01:54,280 --> 00:01:56,440 Speaker 2: whoever the business owners we ever since I sit on 38 00:01:56,480 --> 00:01:59,560 Speaker 2: the boards of the companies in New Zealand, the one 39 00:01:59,640 --> 00:02:01,880 Speaker 2: question that every New Zealand the company and every New 40 00:02:01,960 --> 00:02:04,760 Speaker 2: Zealand board member should ask is show me a part 41 00:02:04,800 --> 00:02:06,880 Speaker 2: to a billion. Show me a part to a billion. 42 00:02:07,360 --> 00:02:10,600 Speaker 2: And if every single person said in a running a company, said, 43 00:02:10,600 --> 00:02:12,120 Speaker 2: show me a part of a billion. Sure, you're not 44 00:02:12,160 --> 00:02:13,840 Speaker 2: going to have a whole bunch of companies, but you'll 45 00:02:13,840 --> 00:02:15,720 Speaker 2: get enough enough to have a difference. 46 00:02:16,080 --> 00:02:18,280 Speaker 1: So you can see why the Prime Minister and Space 47 00:02:18,360 --> 00:02:22,320 Speaker 1: Minister Judith Collins love the space industry so much. It 48 00:02:22,320 --> 00:02:26,280 Speaker 1: epitomizes they're going for growth mantra. If we hope to 49 00:02:26,280 --> 00:02:30,840 Speaker 1: grow GDP and productivity, building companies like rocket Lab is 50 00:02:30,880 --> 00:02:34,200 Speaker 1: a very effective way to do it. But how realistic 51 00:02:34,360 --> 00:02:37,320 Speaker 1: is Sir Peter's target ten percent of the space industry 52 00:02:37,360 --> 00:02:41,600 Speaker 1: two hundred and thirty billion dollars. What would it involve? Well, 53 00:02:41,800 --> 00:02:45,320 Speaker 1: as Peter has told me many times, launching rockets is 54 00:02:45,320 --> 00:02:48,240 Speaker 1: the smallest piece of the pie in the space industry. 55 00:02:48,680 --> 00:02:53,239 Speaker 1: That's followed by building satellites, spacecraft and payloads. That's quite 56 00:02:53,240 --> 00:02:56,680 Speaker 1: a big chunk. But the biggest chunk increasingly is the 57 00:02:56,720 --> 00:03:03,079 Speaker 1: revenue derived from delivering services in space. Think about satellite broadband. SpaceX, 58 00:03:03,120 --> 00:03:07,160 Speaker 1: for instance, is expected to generate around twelve billion dollars 59 00:03:07,320 --> 00:03:11,359 Speaker 1: US and service revenue this year, offering Internet connections all 60 00:03:11,360 --> 00:03:14,960 Speaker 1: over the world, Supplying satellite to mobile services like one 61 00:03:15,040 --> 00:03:17,760 Speaker 1: end z is currently doing in New Zealand in collaboration 62 00:03:17,880 --> 00:03:23,480 Speaker 1: with SpaceX things like global positioning, remote sensing, and Earth observation. 63 00:03:23,760 --> 00:03:25,960 Speaker 1: That's where the money would really start to add up 64 00:03:26,240 --> 00:03:29,800 Speaker 1: in service revenue. We don't play in that space yet, 65 00:03:30,200 --> 00:03:33,360 Speaker 1: but rocket Lab is gearing up to launch Neutron later 66 00:03:33,400 --> 00:03:36,960 Speaker 1: this year, which allows for launching more satellites at once 67 00:03:37,080 --> 00:03:40,880 Speaker 1: and larger payloads. It's a much bigger rocket than Electron, 68 00:03:40,960 --> 00:03:45,160 Speaker 1: its existing rocket. It has also announced the Flatlite, a 69 00:03:45,200 --> 00:03:48,160 Speaker 1: new type of satellite that allows it to efficiently pack 70 00:03:48,240 --> 00:03:51,920 Speaker 1: in a larger number of satellites to launch on Neutron 71 00:03:51,960 --> 00:03:56,000 Speaker 1: to build constellations of satellites in low Earth orbit. Now, 72 00:03:56,000 --> 00:03:59,520 Speaker 1: given it can build the satellites launch them itself from 73 00:03:59,560 --> 00:04:02,440 Speaker 1: New Zealand or the US, the next step is to 74 00:04:02,480 --> 00:04:06,760 Speaker 1: go into delivering services just like SpaceX does, in which 75 00:04:06,800 --> 00:04:10,600 Speaker 1: Amazon is about to do with its Kuyper rawband satellite 76 00:04:10,600 --> 00:04:12,720 Speaker 1: service as well. Then you throw in the likes of 77 00:04:12,760 --> 00:04:15,960 Speaker 1: the Golden Dome project, this thing the US is pursuing 78 00:04:16,040 --> 00:04:18,880 Speaker 1: to try and protect the country from cruise missiles and 79 00:04:18,920 --> 00:04:23,839 Speaker 1: spaceborne threats, the equivalent of Israel's Iron Dome, and you 80 00:04:23,880 --> 00:04:27,560 Speaker 1: have a potentially lucrative ongoing revenue stream of commercial and 81 00:04:27,839 --> 00:04:31,760 Speaker 1: national security services. So then that two hundred and thirty 82 00:04:31,880 --> 00:04:36,359 Speaker 1: billion dollar target starts to look a bit more doable. Now, technically, 83 00:04:36,800 --> 00:04:39,120 Speaker 1: rocket Lab is a US company, so a lot of 84 00:04:39,160 --> 00:04:40,839 Speaker 1: their revenue is sort of counted in the US, but 85 00:04:40,880 --> 00:04:43,000 Speaker 1: I think we can claim that given that they still 86 00:04:43,000 --> 00:04:45,640 Speaker 1: have a huge presence in New Zealand. But what I'd 87 00:04:45,680 --> 00:04:48,960 Speaker 1: love to see is New Zealand startups partner with rocket 88 00:04:49,000 --> 00:04:52,800 Speaker 1: Lab to innovate on that incredible infrastructure platform that rocket 89 00:04:52,839 --> 00:04:56,159 Speaker 1: Lab is building and has built. That's definitely one of 90 00:04:56,160 --> 00:04:59,480 Speaker 1: the biggest opportunities we have as a country to grow 91 00:05:00,120 --> 00:05:04,120 Speaker 1: revenue and GDP quickly and definitely not a goal to 92 00:05:04,160 --> 00:05:06,560 Speaker 1: be sniggered at. I'm Peter Griffin and on the business 93 00:05:06,560 --> 00:05:09,159 Speaker 1: of tech powered by two degrees business. We're going from 94 00:05:09,200 --> 00:05:13,880 Speaker 1: space to the rapidly changing advertising market. Maurice Riley stands 95 00:05:13,920 --> 00:05:18,640 Speaker 1: at the intersection of data technology and advertising strategy as 96 00:05:18,680 --> 00:05:22,200 Speaker 1: the Chief Data Officer for New Zealand and Australia at 97 00:05:22,320 --> 00:05:26,919 Speaker 1: Publicist Group, the French multinational advertising and public relations company 98 00:05:27,000 --> 00:05:30,920 Speaker 1: that's one of the largest agencies in the world. Advertising 99 00:05:30,960 --> 00:05:34,359 Speaker 1: has become one hundred percent data driven. It started with 100 00:05:34,520 --> 00:05:39,159 Speaker 1: using things like census data to target advertising online and 101 00:05:39,240 --> 00:05:43,800 Speaker 1: creating direct mail lists. It's evolved into social media platforms 102 00:05:43,880 --> 00:05:48,400 Speaker 1: using sophisticated digital signals to tailor adverts to users, and 103 00:05:48,440 --> 00:05:51,000 Speaker 1: it's more important than ever now to have a direct 104 00:05:51,520 --> 00:05:55,680 Speaker 1: digital relationship with your customers. Morris argues that you need 105 00:05:55,760 --> 00:05:58,919 Speaker 1: to control your own data destiny to an extent. We 106 00:05:59,040 --> 00:06:02,280 Speaker 1: haven't seen every book for He introduces a concept that's 107 00:06:02,520 --> 00:06:06,159 Speaker 1: new to me, the middle verse of the customer journey 108 00:06:06,560 --> 00:06:08,880 Speaker 1: when they are buying something. I guess you could describe 109 00:06:08,880 --> 00:06:12,440 Speaker 1: it as the middle of the funnel that advertising people 110 00:06:12,680 --> 00:06:15,960 Speaker 1: talk about. This is the most commonplace where things start 111 00:06:16,000 --> 00:06:19,720 Speaker 1: to fall apart, where a customer loses interest, gets distracted, 112 00:06:19,839 --> 00:06:23,920 Speaker 1: and doesn't end up completing a purchase. Publicist is using 113 00:06:24,040 --> 00:06:27,120 Speaker 1: data to tackle that problem in the middle verse, and 114 00:06:27,160 --> 00:06:30,360 Speaker 1: it's just undertaken. A major acquisition that Morris recons will 115 00:06:30,360 --> 00:06:33,440 Speaker 1: really allow the agency to better help its customers in 116 00:06:33,480 --> 00:06:36,360 Speaker 1: this part of the world take more money off the table. 117 00:06:36,640 --> 00:06:52,920 Speaker 1: So here's my interview with Publicist Groups Maurice Riley Marris. 118 00:06:53,000 --> 00:06:55,320 Speaker 1: Welcome to the Business of Tech. Thanks so much for 119 00:06:55,440 --> 00:06:56,400 Speaker 1: coming on. How are you doing. 120 00:06:56,920 --> 00:06:59,000 Speaker 3: I'm doing great. Peter it's great to be here. Thanks 121 00:06:59,040 --> 00:06:59,760 Speaker 3: for having me on. 122 00:07:00,640 --> 00:07:03,400 Speaker 1: So, Marris, you have quite a long history in the 123 00:07:04,120 --> 00:07:09,240 Speaker 1: advertising industry, including extints to other companies, but publicists. You know, 124 00:07:09,240 --> 00:07:11,320 Speaker 1: a few years ago you were there, you're back now 125 00:07:11,400 --> 00:07:14,960 Speaker 1: you're the publicist data guru. I guess they'd call you 126 00:07:15,000 --> 00:07:18,360 Speaker 1: for New Zealand and Australia. What does that entail your 127 00:07:18,440 --> 00:07:20,360 Speaker 1: job with publishers this time around. 128 00:07:20,760 --> 00:07:25,520 Speaker 3: Yeah, So being the data guru, or the daddy of data, 129 00:07:25,800 --> 00:07:30,640 Speaker 3: as I sometimes am referred to, means I am ensuring 130 00:07:30,760 --> 00:07:36,600 Speaker 3: that not only the group's data assets and technology, but 131 00:07:36,680 --> 00:07:41,440 Speaker 3: also our clients data assets technology are future proof and 132 00:07:41,480 --> 00:07:46,120 Speaker 3: fit for purpose, fit for purpose for delivering the growth 133 00:07:46,160 --> 00:07:50,320 Speaker 3: outcomes that we need today, but also future proof to 134 00:07:50,440 --> 00:07:55,440 Speaker 3: make sure, particularly in this era of uncertainty, that they 135 00:07:55,480 --> 00:08:00,480 Speaker 3: are ready and resilient for the data landscape as it 136 00:08:00,520 --> 00:08:01,200 Speaker 3: is coming at us. 137 00:08:01,560 --> 00:08:03,400 Speaker 1: You know, Publicist is one of one of the biggest 138 00:08:03,560 --> 00:08:09,000 Speaker 1: advertising and marketing agencies in the world, and it has, 139 00:08:09,360 --> 00:08:11,360 Speaker 1: particularly in the last ten years, has become such a 140 00:08:11,440 --> 00:08:13,240 Speaker 1: data driven industry, hasn't. 141 00:08:12,960 --> 00:08:15,920 Speaker 3: It one hundred percent? And and you know, I we 142 00:08:16,080 --> 00:08:18,480 Speaker 3: it's an old cliche, but we like to say data 143 00:08:18,560 --> 00:08:23,160 Speaker 3: is just people in disguise, so using information and data 144 00:08:23,200 --> 00:08:25,320 Speaker 3: points not in the form that we know it today, 145 00:08:25,600 --> 00:08:30,760 Speaker 3: but has been influencing marketing for years and influencing strategy 146 00:08:30,840 --> 00:08:35,120 Speaker 3: every you know, you mentioned my my tenure in advertising. 147 00:08:35,240 --> 00:08:37,600 Speaker 3: You know, back in the United States, we were using 148 00:08:37,840 --> 00:08:41,720 Speaker 3: you know, pano and direct mail lists and census data 149 00:08:41,760 --> 00:08:44,400 Speaker 3: to inform our strategies. Now we just have that in 150 00:08:44,440 --> 00:08:49,280 Speaker 3: a different form, with a whole bunch more signals at 151 00:08:49,320 --> 00:08:52,280 Speaker 3: our disposal to will together to get to that that 152 00:08:52,280 --> 00:08:55,640 Speaker 3: that unlock that insight that unlocks a great creative idea 153 00:08:56,000 --> 00:08:58,680 Speaker 3: or make sure that we're getting to the prospects and 154 00:08:58,720 --> 00:08:59,920 Speaker 3: the humans that we want to. 155 00:09:00,600 --> 00:09:03,720 Speaker 1: You know, that is the operative thing at the moment. 156 00:09:04,480 --> 00:09:06,720 Speaker 1: In our current economic climate the same and you're you're 157 00:09:06,760 --> 00:09:09,800 Speaker 1: based in Australia is a little bit behind us, I think, 158 00:09:09,800 --> 00:09:12,800 Speaker 1: but starting to feel the sort of the chill winds 159 00:09:12,840 --> 00:09:16,200 Speaker 1: we've got, the uncertainty around tarifs and things like that. 160 00:09:16,600 --> 00:09:18,480 Speaker 1: What's your sort of takeaway when you know you're in 161 00:09:18,480 --> 00:09:21,800 Speaker 1: New Zealand at the moment visiting your clients and your 162 00:09:21,800 --> 00:09:25,120 Speaker 1: colleagues at publicists, what's the sense you get about what 163 00:09:25,160 --> 00:09:27,559 Speaker 1: the priorities are for your customers? Here at the moment. 164 00:09:28,120 --> 00:09:30,079 Speaker 3: Yeah, look in this market, I think your your your 165 00:09:30,120 --> 00:09:33,920 Speaker 3: treasury is tipping growth to start to return the second 166 00:09:34,000 --> 00:09:38,080 Speaker 3: half of the year. But you know that doesn't mean 167 00:09:38,080 --> 00:09:40,920 Speaker 3: consumers aren't still feeling it every day in the in 168 00:09:40,920 --> 00:09:45,160 Speaker 3: in in the aisle. So our customers and our clients 169 00:09:45,200 --> 00:09:51,959 Speaker 3: are you know, being a bit more uh cautious of 170 00:09:52,000 --> 00:09:56,560 Speaker 3: how what they're spending, looking how the ties are turning. 171 00:09:56,840 --> 00:09:59,280 Speaker 3: But I think that the key is that I look 172 00:09:59,320 --> 00:10:02,400 Speaker 3: at for our cus resus not what they're spending, but 173 00:10:03,080 --> 00:10:06,640 Speaker 3: how they're spending it. So we're seeing a lot more 174 00:10:07,000 --> 00:10:10,080 Speaker 3: and having a lot more conversations with clients around you know, 175 00:10:10,120 --> 00:10:12,520 Speaker 3: how can I get more with our half? And that's 176 00:10:12,640 --> 00:10:18,000 Speaker 3: leading to, uh, can we drive more efficiency around every 177 00:10:18,040 --> 00:10:22,480 Speaker 3: dollar that's that's that we're spending. That's leading to conversations 178 00:10:22,480 --> 00:10:25,840 Speaker 3: around how we can have more integrated service models. So 179 00:10:26,080 --> 00:10:30,200 Speaker 3: creative and media and digital and CRM and commerce agencies 180 00:10:30,200 --> 00:10:36,400 Speaker 3: are working together and sharing similar tech infrastructure as well 181 00:10:36,440 --> 00:10:39,920 Speaker 3: as workflows to you know, get more out of the 182 00:10:39,960 --> 00:10:42,400 Speaker 3: dollars they're spending. So those are the leading indicators that 183 00:10:42,440 --> 00:10:46,120 Speaker 3: I'm looking at of what clients are doing to have 184 00:10:46,240 --> 00:10:49,960 Speaker 3: that lower for longer, but also prepare themselves for when 185 00:10:50,360 --> 00:10:52,880 Speaker 3: growth comes back and they're they're they're spending more company. 186 00:10:52,920 --> 00:10:59,280 Speaker 1: What's your impression of how sophisticated advertising and marketing market 187 00:10:59,400 --> 00:11:02,080 Speaker 1: we are here in New Zealand. You know, we've seen 188 00:11:02,080 --> 00:11:05,160 Speaker 1: the likes of Salesforce and that really trying to educate 189 00:11:05,160 --> 00:11:09,520 Speaker 1: their customers about integrating you know, direct marketing and customer 190 00:11:09,559 --> 00:11:14,079 Speaker 1: relations management, advertising campaigns, sort of controlling it all in 191 00:11:14,600 --> 00:11:19,120 Speaker 1: one central place. I think that's improving the efficiency you 192 00:11:19,160 --> 00:11:21,760 Speaker 1: were talking about and the impact that they're having. But 193 00:11:21,840 --> 00:11:24,240 Speaker 1: then I guess a lot of our campaigns here sort 194 00:11:24,280 --> 00:11:27,520 Speaker 1: of go directly out onto you know, social media. That's 195 00:11:27,520 --> 00:11:30,959 Speaker 1: been the big transition in most places, but particularly in 196 00:11:30,960 --> 00:11:34,240 Speaker 1: New Zealand, we've we've felt it where media outlets have 197 00:11:34,320 --> 00:11:38,199 Speaker 1: decreased in relevance in terms of advertising. Social media is 198 00:11:38,200 --> 00:11:42,239 Speaker 1: where it's at increasingly, TikTok and those sorts of platforms. 199 00:11:42,280 --> 00:11:46,040 Speaker 1: How good are our businesses here at sort of leveraging 200 00:11:46,600 --> 00:11:50,160 Speaker 1: you know, those big platforms that they don't necessarily have 201 00:11:50,240 --> 00:11:53,320 Speaker 1: control of the data themselves, but they they have a 202 00:11:53,360 --> 00:11:56,360 Speaker 1: pathway to really reaching the audience that they're looking for. 203 00:11:57,120 --> 00:11:59,320 Speaker 3: Yeah, there's there's there's so much to unpack in that 204 00:11:59,400 --> 00:12:01,040 Speaker 3: question that I get excited about, and I know we 205 00:12:01,080 --> 00:12:02,680 Speaker 3: only have a limited time, so I'm going to try 206 00:12:02,760 --> 00:12:06,600 Speaker 3: to break it down and also also reserve my excitement 207 00:12:06,640 --> 00:12:08,319 Speaker 3: a bit. But we can talk about this longer over 208 00:12:08,400 --> 00:12:12,640 Speaker 3: cocktails sometimes. First I want to add to your question 209 00:12:12,679 --> 00:12:15,840 Speaker 3: and say, sophistication is not just on the paid media side, 210 00:12:15,840 --> 00:12:18,920 Speaker 3: but let's also consider it on the owned side, you know, 211 00:12:19,160 --> 00:12:23,120 Speaker 3: so email and website. And when I first came to 212 00:12:23,160 --> 00:12:27,679 Speaker 3: this market some ten years ago, I was really excited 213 00:12:27,679 --> 00:12:31,520 Speaker 3: about some of the work Publicis was doing and had 214 00:12:31,640 --> 00:12:37,760 Speaker 3: done with the likes of Countdown, where they had done 215 00:12:37,800 --> 00:12:43,160 Speaker 3: the whole marketing architecture martech that enabled them to deliver 216 00:12:43,960 --> 00:12:46,920 Speaker 3: eight hundred unique emails a week. Eight hundred thousand unique 217 00:12:46,920 --> 00:12:49,640 Speaker 3: emails a week. You know, that's personalization at scale that 218 00:12:50,160 --> 00:12:54,680 Speaker 3: consistently that few people can legitimately say that they've achieved. 219 00:12:54,960 --> 00:12:57,280 Speaker 3: So on the own side, there is great sophistication here. 220 00:12:57,360 --> 00:12:59,640 Speaker 3: Now I take your point, though, we got to do 221 00:12:59,679 --> 00:13:01,880 Speaker 3: better and can do better, and on the road to 222 00:13:01,880 --> 00:13:06,079 Speaker 3: do better on the paid side, and that's going to 223 00:13:06,120 --> 00:13:08,000 Speaker 3: be of two for us. That's going to be when 224 00:13:08,000 --> 00:13:10,920 Speaker 3: it comes to client and agency maturity of the capability 225 00:13:10,960 --> 00:13:13,000 Speaker 3: they have not only in terms of the platforms with 226 00:13:13,040 --> 00:13:16,479 Speaker 3: the tech, but also the product that the media platforms 227 00:13:16,520 --> 00:13:19,400 Speaker 3: are providing in order to drive that sophistication. And you 228 00:13:19,559 --> 00:13:22,880 Speaker 3: see both of those things growing on the paid paid 229 00:13:22,920 --> 00:13:28,880 Speaker 3: media side. To give you any example, in my experience 230 00:13:28,920 --> 00:13:32,079 Speaker 3: in the United States, I had long had the experience 231 00:13:32,200 --> 00:13:34,760 Speaker 3: of being able to target at the head end and 232 00:13:35,640 --> 00:13:40,600 Speaker 3: household level ads because pay TV cable TV was so 233 00:13:40,640 --> 00:13:47,120 Speaker 3: prevalent here. We now have streaming and CTV driving. We 234 00:13:47,240 --> 00:13:50,640 Speaker 3: already have the data pipes to allow that to be addressable. 235 00:13:50,640 --> 00:13:53,640 Speaker 3: Our recent acquisition of Lodo may allows us to look 236 00:13:53,640 --> 00:13:58,839 Speaker 3: at behaviors associated with different ctvs and target ads through 237 00:13:59,480 --> 00:14:02,840 Speaker 3: those ct TV channels, that adjustable TV channels. But the 238 00:14:02,880 --> 00:14:05,800 Speaker 3: product is also developing. How that experience shows up what 239 00:14:05,840 --> 00:14:09,240 Speaker 3: we can do in terms of dynamic content is improving 240 00:14:09,280 --> 00:14:12,400 Speaker 3: here and we'll get there and I think New Zealand 241 00:14:12,440 --> 00:14:13,560 Speaker 3: as well, and its way to get there. 242 00:14:13,800 --> 00:14:17,439 Speaker 1: Yeah, that's a really interesting category that you've been looking at, 243 00:14:17,960 --> 00:14:20,680 Speaker 1: so called connected TV. So we have here TV and 244 00:14:20,760 --> 00:14:26,640 Speaker 1: ZED plus on demand streaming service three now or three 245 00:14:26,680 --> 00:14:29,440 Speaker 1: plus as they call it now. So those are two 246 00:14:29,520 --> 00:14:33,280 Speaker 1: big ones. But you know, when you interact with those services, 247 00:14:33,320 --> 00:14:36,360 Speaker 1: it's still sort of like linear TV. You get to 248 00:14:36,400 --> 00:14:38,960 Speaker 1: watch a show when you want to watch it, but 249 00:14:39,040 --> 00:14:42,880 Speaker 1: you're presented with some ads embedded every so often in 250 00:14:42,920 --> 00:14:46,720 Speaker 1: that show. You don't really have the opportunity to skip 251 00:14:46,760 --> 00:14:49,360 Speaker 1: through the ads. So you're sitting there watching these ads 252 00:14:49,400 --> 00:14:51,320 Speaker 1: and they are just basically the same ads that they're 253 00:14:51,360 --> 00:14:55,560 Speaker 1: serving up on free to air or pay TV channels, 254 00:14:56,000 --> 00:14:58,960 Speaker 1: and they're not relevant to me. They're not customized for me. 255 00:14:59,120 --> 00:15:01,720 Speaker 1: So it's a very an experience to when I'm scrolling 256 00:15:01,760 --> 00:15:06,160 Speaker 1: through Facebook or Instagram where I'm getting highly targeted adverts, 257 00:15:06,160 --> 00:15:08,440 Speaker 1: and that seems to be a disconnect that has lingered 258 00:15:08,480 --> 00:15:11,560 Speaker 1: for quite a while. But obviously this is just an 259 00:15:11,640 --> 00:15:16,200 Speaker 1: internet feed. They know exactly who is longed in watching 260 00:15:16,240 --> 00:15:18,480 Speaker 1: that show. So are we getting to a point now 261 00:15:18,640 --> 00:15:21,600 Speaker 1: where we are really going to see, you know, a 262 00:15:21,640 --> 00:15:25,520 Speaker 1: real shift in TV advertising where it is highly targeted 263 00:15:25,760 --> 00:15:26,600 Speaker 1: to the individual. 264 00:15:27,600 --> 00:15:31,600 Speaker 3: Yeah, I mean, there we have the pipes. You know, 265 00:15:31,720 --> 00:15:34,120 Speaker 3: let's think of CTV as the muscle car of TV. 266 00:15:34,440 --> 00:15:37,160 Speaker 3: You know, I saw a stat that's still sixty percent 267 00:15:37,360 --> 00:15:42,840 Speaker 3: of kiwis are engaging with TV, and each day and 268 00:15:44,160 --> 00:15:49,720 Speaker 3: CTV is increasingly taking more and more share, So we're there. 269 00:15:49,840 --> 00:15:52,680 Speaker 3: We already have the pipes and the ability and the 270 00:15:52,800 --> 00:15:58,440 Speaker 3: data for that CTV and those ads to be addressable. Again, 271 00:15:58,640 --> 00:16:03,520 Speaker 3: our Lord of my acquisition gives us thousands of behaviors, 272 00:16:03,680 --> 00:16:09,760 Speaker 3: demographic purchase behaviors, category behaviors that is already linked to 273 00:16:10,600 --> 00:16:15,760 Speaker 3: those CTV providers. So once we identify your target, we 274 00:16:15,880 --> 00:16:20,760 Speaker 3: can deliver that add to the most relevant audience on CTV. 275 00:16:21,320 --> 00:16:23,080 Speaker 3: That's what I'm really excited about for this market. And 276 00:16:23,080 --> 00:16:25,760 Speaker 3: if I'm doing my JOBE correctly, I'm going to get 277 00:16:25,800 --> 00:16:28,680 Speaker 3: more clients excited to go on that journey with me, 278 00:16:29,440 --> 00:16:32,240 Speaker 3: to target in that way and to experiment on these 279 00:16:32,280 --> 00:16:33,760 Speaker 3: platforms with that type of data. 280 00:16:34,360 --> 00:16:38,640 Speaker 1: Yeah, and that goes for podcasts as well, for even 281 00:16:38,640 --> 00:16:43,280 Speaker 1: for internet radio obviously not over broadcast radio. At this point, 282 00:16:43,320 --> 00:16:46,560 Speaker 1: we don't really have digital audio to any degree in 283 00:16:46,640 --> 00:16:49,880 Speaker 1: New Zealand. So the most you'll see is the name 284 00:16:49,920 --> 00:16:53,640 Speaker 1: of the of the if in frequency you know that 285 00:16:53,680 --> 00:16:55,680 Speaker 1: will come up in your car. But a lot of 286 00:16:55,680 --> 00:16:59,320 Speaker 1: people now are listening via streaming devices. iHeartRadio is big 287 00:16:59,320 --> 00:17:02,400 Speaker 1: in New Zealand's true in died me So again, you've 288 00:17:02,400 --> 00:17:05,720 Speaker 1: got that ability to you know exactly who's listening, what 289 00:17:05,760 --> 00:17:08,119 Speaker 1: they've listened to in the in the past, what podcasts 290 00:17:08,200 --> 00:17:11,920 Speaker 1: they have subscribed to, so that all that sort of 291 00:17:11,960 --> 00:17:15,000 Speaker 1: stuff is going to influence what they want to consume. 292 00:17:15,080 --> 00:17:18,679 Speaker 3: That's that's exactly right, and that that uh, there's an 293 00:17:18,720 --> 00:17:21,800 Speaker 3: idea that that that that that I'm positing that I 294 00:17:21,960 --> 00:17:25,840 Speaker 3: call the middle verse when it comes to the data strategy, 295 00:17:25,880 --> 00:17:29,400 Speaker 3: that that UH drives that and the middle verse. Look, 296 00:17:29,440 --> 00:17:33,560 Speaker 3: I don't often use uh a rugby metaphors, but in 297 00:17:33,560 --> 00:17:35,439 Speaker 3: New Zealand, I feel like I have to. So I'm 298 00:17:35,440 --> 00:17:36,920 Speaker 3: gonna I'm going to try it and don't judge me 299 00:17:36,960 --> 00:17:38,720 Speaker 3: if I get it wrong. But if you think of 300 00:17:38,760 --> 00:17:41,360 Speaker 3: the customer journey, you know, like a rugby game, right, 301 00:17:41,440 --> 00:17:45,160 Speaker 3: the kickoff is the awareness and getting over the try 302 00:17:45,200 --> 00:17:48,040 Speaker 3: line is conversion. But we all know the real game 303 00:17:48,200 --> 00:17:52,280 Speaker 3: happens in the rock in midfield, right, in the playing 304 00:17:52,280 --> 00:17:55,640 Speaker 3: of midfield. Think of that as your purchase journey. Right. 305 00:17:56,119 --> 00:17:59,760 Speaker 3: How it's so easy in media to identify those people 306 00:18:00,160 --> 00:18:03,080 Speaker 3: at the try line, those in market audiences. But the 307 00:18:03,119 --> 00:18:07,760 Speaker 3: middle verse is that muck and messy middle where magic 308 00:18:07,800 --> 00:18:10,840 Speaker 3: can really happen. How are we identifying those behaviors that 309 00:18:11,080 --> 00:18:16,520 Speaker 3: are predictive that you can be nudged into the category? 310 00:18:16,680 --> 00:18:20,320 Speaker 3: How are though identifying those behaviors that are those category 311 00:18:20,480 --> 00:18:24,280 Speaker 3: entry points where we can tell emotional stories around and 312 00:18:24,359 --> 00:18:26,800 Speaker 3: have created moments around and still target it to the 313 00:18:26,800 --> 00:18:30,560 Speaker 3: precise individual that would be relevant for. That's the power 314 00:18:30,560 --> 00:18:33,040 Speaker 3: of the middle verse, and that's the power of behavioral 315 00:18:33,160 --> 00:18:38,120 Speaker 3: data when it's linked to CTV and those more mid 316 00:18:38,160 --> 00:18:40,680 Speaker 3: and upper funnel channels, that we can start to plan 317 00:18:40,880 --> 00:18:46,399 Speaker 3: to start to grow demand, create demand, not just target 318 00:18:46,600 --> 00:18:49,919 Speaker 3: people in market that are already close to the try line. 319 00:18:50,160 --> 00:18:52,840 Speaker 1: Right, Yeah, that's the crucial But you see, you know 320 00:18:52,920 --> 00:18:55,840 Speaker 1: lots of campaigns that are aimed at filling the funnel, 321 00:18:55,960 --> 00:18:58,200 Speaker 1: but then actually when you get down into that funnel, 322 00:18:58,920 --> 00:19:01,800 Speaker 1: it becomes a little bit more complicated. And it's all 323 00:19:01,840 --> 00:19:05,159 Speaker 1: about behavioral signals, isn't it. What are some of the 324 00:19:05,560 --> 00:19:09,000 Speaker 1: ones that we tend to overlook that you're helping your 325 00:19:09,040 --> 00:19:10,160 Speaker 1: customers identify? 326 00:19:10,720 --> 00:19:14,440 Speaker 3: Yeah, so a couple examples come to mind, but I'll 327 00:19:14,840 --> 00:19:17,760 Speaker 3: I'll give you one that's more of a mindset one 328 00:19:17,800 --> 00:19:20,520 Speaker 3: that's a behavior that leads to a mindset. One that 329 00:19:20,520 --> 00:19:28,040 Speaker 3: I think is interesting in a a healthcare client that 330 00:19:28,119 --> 00:19:33,680 Speaker 3: I'm working with was trying to obviously change healthy behaviors 331 00:19:34,000 --> 00:19:40,080 Speaker 3: and get people to intentionally search for treatment around a 332 00:19:40,119 --> 00:19:46,879 Speaker 3: certain a certain uh chronic condition. And you could just 333 00:19:46,920 --> 00:19:49,600 Speaker 3: go to market and and and and and start to 334 00:19:49,600 --> 00:19:53,040 Speaker 3: target demographically, which is what we've typically done. And in 335 00:19:54,920 --> 00:19:59,520 Speaker 3: oftentimes data around healthcare is a bit sensitive, right It's 336 00:19:59,560 --> 00:20:03,320 Speaker 3: it's it's protected protect the class, and it's not readily available. 337 00:20:04,240 --> 00:20:08,840 Speaker 3: But behaviors around people who are proactive about their healthcare, 338 00:20:09,359 --> 00:20:16,000 Speaker 3: who are into wellness content is readily available. Behavior Signals 339 00:20:16,040 --> 00:20:20,240 Speaker 3: around people who are careers for loved one who are 340 00:20:20,560 --> 00:20:23,760 Speaker 3: there and therefore their influential in people's health care decisions 341 00:20:23,920 --> 00:20:27,480 Speaker 3: are readily available. Those are behavioral signals we can look 342 00:20:27,520 --> 00:20:30,240 Speaker 3: at to say, these are the people we should be 343 00:20:30,320 --> 00:20:33,639 Speaker 3: talking to to nudge them into the healthy behaviors that 344 00:20:33,680 --> 00:20:36,520 Speaker 3: we want them we want to actually see and get 345 00:20:36,680 --> 00:20:39,320 Speaker 3: to our business outcomes. That's what I'm meaning around the 346 00:20:39,640 --> 00:20:42,239 Speaker 3: power of that behavioral data, where we can use that 347 00:20:42,400 --> 00:20:45,960 Speaker 3: to understand what's most relevant in this person's life today 348 00:20:46,320 --> 00:20:48,879 Speaker 3: and then nudge them into our category. If we have 349 00:20:49,040 --> 00:20:51,480 Speaker 3: a product or service that is relevant to. 350 00:20:51,440 --> 00:20:55,000 Speaker 1: Them and what sort of form does the nudge take. 351 00:20:55,080 --> 00:20:57,760 Speaker 1: They might have seen an advert of something to get 352 00:20:57,760 --> 00:21:00,560 Speaker 1: them into the funnel, but I guess there's a mirrored 353 00:21:01,080 --> 00:21:04,000 Speaker 1: collection of things that you you advise or can help 354 00:21:04,080 --> 00:21:06,520 Speaker 1: customers do to actually get them over the line as well. 355 00:21:07,320 --> 00:21:11,359 Speaker 3: Yeah, so this is where the uh, the connectivity that 356 00:21:11,400 --> 00:21:14,280 Speaker 3: I mentioned earlier that clients are asking for, where their 357 00:21:15,200 --> 00:21:19,400 Speaker 3: agencies are cooperating, collaborating with one another, and coming from 358 00:21:19,400 --> 00:21:24,480 Speaker 3: shared strategies and shared data architecture and technology architecture. So 359 00:21:24,520 --> 00:21:27,719 Speaker 3: we can power the campaigns that are driven through this insight. 360 00:21:28,080 --> 00:21:33,280 Speaker 3: So when an AD is served on on CTV, for 361 00:21:33,320 --> 00:21:37,119 Speaker 3: ex instance, it's already targeted that same data and insight 362 00:21:37,240 --> 00:21:40,120 Speaker 3: that is talking to that personal CTV is carrying over 363 00:21:40,200 --> 00:21:42,040 Speaker 3: to when they land on the website, we know who 364 00:21:42,040 --> 00:21:44,879 Speaker 3: they are or carrying over to our life cycle comms 365 00:21:44,880 --> 00:21:49,119 Speaker 3: in CRM and email. Those are all places we can 366 00:21:49,240 --> 00:21:53,440 Speaker 3: we can nudge people to the outcomes that we want. Now, 367 00:21:53,720 --> 00:21:55,920 Speaker 3: I am not going to sit and pretend like it's 368 00:21:56,000 --> 00:22:01,080 Speaker 3: it's it's it's easy. We so often talk about the funnel, 369 00:22:01,320 --> 00:22:04,159 Speaker 3: but we all can admit, as marketers and people in 370 00:22:04,200 --> 00:22:06,280 Speaker 3: tech that the funnel is more like le's like a 371 00:22:06,280 --> 00:22:10,639 Speaker 3: funnel these days and more like a pinball machine where 372 00:22:10,680 --> 00:22:14,240 Speaker 3: we're bouncing around from channel to channel. But that's why 373 00:22:14,600 --> 00:22:17,800 Speaker 3: brands being clear about not only what they're good at 374 00:22:17,840 --> 00:22:22,080 Speaker 3: producing from a channel and content perspective, but also what 375 00:22:22,160 --> 00:22:27,639 Speaker 3: their brand architecture, data architecture, technology architecture can help orchestrate. 376 00:22:28,040 --> 00:22:30,680 Speaker 3: And then having that connected team working through all those things, 377 00:22:30,720 --> 00:22:33,119 Speaker 3: that's where it really becomes really important for everyone to 378 00:22:33,119 --> 00:22:36,080 Speaker 3: be aligned. What are we going after, what experiences are 379 00:22:36,119 --> 00:22:38,840 Speaker 3: we going to invest in, and how is our connected 380 00:22:38,880 --> 00:22:41,840 Speaker 3: strategy that nuts just people to that conversion point. 381 00:22:42,000 --> 00:22:45,760 Speaker 1: You talked about this US based company, Lodo May, which 382 00:22:46,080 --> 00:22:49,600 Speaker 1: Publicist Group has just bought, Yes, which is all about 383 00:22:49,680 --> 00:22:52,160 Speaker 1: data and AI, and I want to talk a bit 384 00:22:52,400 --> 00:22:56,199 Speaker 1: about AI. But yeah, tell us what the capability this 385 00:22:56,520 --> 00:22:57,920 Speaker 1: acquisition brings to the group. 386 00:22:58,800 --> 00:23:02,800 Speaker 3: Yeah, So with this quisition, I'll go back a bit. 387 00:23:03,160 --> 00:23:08,120 Speaker 3: Publicis Group about five six years ago purchased Epsilon, which 388 00:23:08,320 --> 00:23:12,760 Speaker 3: gave us a really big identity graph data asset that 389 00:23:13,160 --> 00:23:17,000 Speaker 3: was really powerful in the US and in Europe. This 390 00:23:17,160 --> 00:23:19,400 Speaker 3: data asset, for those of you who are not familiar 391 00:23:19,440 --> 00:23:23,399 Speaker 3: with the term identity graph, is basically the collection of 392 00:23:23,640 --> 00:23:26,560 Speaker 3: behavioral signals that all of us drop each day as 393 00:23:26,560 --> 00:23:32,400 Speaker 3: we're into engaging with different digital platforms and different data 394 00:23:32,440 --> 00:23:37,560 Speaker 3: partnerships that we exclusively have to round out a more 395 00:23:37,880 --> 00:23:41,159 Speaker 3: whole picture, a wider aperture of who an individual is. 396 00:23:41,200 --> 00:23:44,159 Speaker 3: We don't know who that particular person is, but we 397 00:23:44,320 --> 00:23:46,600 Speaker 3: know the device that you're on at different signals that 398 00:23:46,680 --> 00:23:52,320 Speaker 3: you're giving us to indicate certain behaviors. So with this acquisition, 399 00:23:52,440 --> 00:23:57,960 Speaker 3: we now have an identity graph at scale in all 400 00:23:58,040 --> 00:24:01,840 Speaker 3: of our key markets around the world world. That equates 401 00:24:02,119 --> 00:24:08,160 Speaker 3: to an understanding of around ninety one percent of Internet 402 00:24:08,200 --> 00:24:13,480 Speaker 3: adults in our key markets. That's that census level level 403 00:24:13,480 --> 00:24:17,040 Speaker 3: of understanding of individuals. In New Zealand in particular, we 404 00:24:17,240 --> 00:24:22,080 Speaker 3: have about two million, just over two million unique IDs, 405 00:24:22,240 --> 00:24:25,040 Speaker 3: active unique ideas, which is so important. Doesn't mean they're 406 00:24:25,080 --> 00:24:27,439 Speaker 3: just sitting on a database somewhere, not that these are 407 00:24:27,480 --> 00:24:30,080 Speaker 3: active as the people we can see today. So that 408 00:24:30,960 --> 00:24:33,800 Speaker 3: is the power that this acquisition gives to us, not 409 00:24:33,840 --> 00:24:36,320 Speaker 3: only around the globe but specifically in New Zealand. 410 00:24:36,560 --> 00:24:40,920 Speaker 1: Wow, And I guess in the last ten to twenty 411 00:24:41,000 --> 00:24:44,320 Speaker 1: years the real masters of the identity graph have been 412 00:24:44,400 --> 00:24:47,720 Speaker 1: the social media companies. You know the likes of you know, 413 00:24:47,800 --> 00:24:52,720 Speaker 1: LinkedIn has its own identity graph for me as a user, 414 00:24:52,760 --> 00:24:55,720 Speaker 1: which is incredibly detailed, who my colleagues are, who I'm 415 00:24:55,720 --> 00:25:00,600 Speaker 1: interacting with for the vast number of kiwis on Facebook 416 00:25:00,600 --> 00:25:04,639 Speaker 1: and Instagram and those platforms as well, so they've been 417 00:25:04,680 --> 00:25:07,520 Speaker 1: building that. You've got these exclusive relationships to get these 418 00:25:07,600 --> 00:25:11,880 Speaker 1: insights into that, but potentially huge change coming to that industry. 419 00:25:11,920 --> 00:25:16,720 Speaker 1: We've got the antitrust cases against Google. You know, there's 420 00:25:16,720 --> 00:25:20,760 Speaker 1: potential for spinning off of Chrome. There's the one against Meta. 421 00:25:21,040 --> 00:25:23,920 Speaker 1: You know, they may have to divest WhatsApp and Instagram. 422 00:25:23,920 --> 00:25:26,680 Speaker 1: This is going on in court, you know as we speak, 423 00:25:26,800 --> 00:25:29,320 Speaker 1: so I guess you know, there's a long way to go. 424 00:25:29,359 --> 00:25:33,200 Speaker 1: There'll be appeals, no doubt. It's quite messy at the moment. 425 00:25:33,320 --> 00:25:36,359 Speaker 1: Donald Trump may intervene at the last minute to save 426 00:25:36,440 --> 00:25:41,600 Speaker 1: them from the Department of Justice. But you know, what's 427 00:25:41,640 --> 00:25:44,479 Speaker 1: your advice really at the moment to advertisers who are 428 00:25:44,480 --> 00:25:46,959 Speaker 1: looking at what's coming and what's it going to mean 429 00:25:47,000 --> 00:25:50,439 Speaker 1: for the likes of a publicist group that you know 430 00:25:50,480 --> 00:25:53,439 Speaker 1: that values data so much and to get those really 431 00:25:53,960 --> 00:25:59,680 Speaker 1: quality IDs from millions of kiwis are working with these platforms. 432 00:25:59,720 --> 00:26:02,480 Speaker 1: What are you thinking as you say this potential change coming. 433 00:26:03,080 --> 00:26:07,320 Speaker 3: Yeah, So what I can't do is comment on ongoing litigation 434 00:26:07,440 --> 00:26:11,359 Speaker 3: and legal matters. That's above my pay grade. But what's 435 00:26:11,400 --> 00:26:16,520 Speaker 3: within my remit is to help clients be ready. It's 436 00:26:16,720 --> 00:26:22,720 Speaker 3: an certain era that we're coming in, but there are 437 00:26:22,760 --> 00:26:27,280 Speaker 3: are signals with how we can be ready and how 438 00:26:27,280 --> 00:26:31,640 Speaker 3: we can be resilient. And I think that's part of 439 00:26:31,680 --> 00:26:35,000 Speaker 3: our data strategy. With our acquisition of Lodo may we 440 00:26:35,240 --> 00:26:38,320 Speaker 3: are We've talked a lot about the data, but also 441 00:26:38,560 --> 00:26:43,040 Speaker 3: it gives us access to a privacy centric data collaboration 442 00:26:43,200 --> 00:26:48,760 Speaker 3: room for data sets to come together in a privacy 443 00:26:48,800 --> 00:26:52,120 Speaker 3: compliant way. So even if you're not using the the 444 00:26:52,119 --> 00:26:54,760 Speaker 3: the identity graph, we now have this piece of tech 445 00:26:54,840 --> 00:26:59,240 Speaker 3: through this acquisition where different data partnerships can be be 446 00:27:00,040 --> 00:27:03,199 Speaker 3: come together. Brands got different data partnerships with partners in 447 00:27:03,240 --> 00:27:06,720 Speaker 3: a privacy compliant way. My job is to make sure 448 00:27:07,160 --> 00:27:12,920 Speaker 3: we have a Swiss army knife of privacy enhancing technology, data, 449 00:27:12,960 --> 00:27:19,560 Speaker 3: clean room technology, durable identity data that is helping our 450 00:27:19,600 --> 00:27:23,840 Speaker 3: clients be ready and resilient for whatever the data landscape 451 00:27:23,880 --> 00:27:27,600 Speaker 3: and privacy landscape moves toward. 452 00:27:27,960 --> 00:27:30,920 Speaker 1: Yeah, and I guess you know. The mantra we've heard 453 00:27:30,960 --> 00:27:34,119 Speaker 1: I think in recent years is you sort of need 454 00:27:34,160 --> 00:27:38,159 Speaker 1: to own your audience to some degree on platforms that 455 00:27:38,240 --> 00:27:40,959 Speaker 1: you can control. So that's why I thinks like digital 456 00:27:41,000 --> 00:27:43,960 Speaker 1: newsletters and that have become so important. The more people 457 00:27:44,119 --> 00:27:47,879 Speaker 1: you have direct access to rather than through a third 458 00:27:47,880 --> 00:27:52,560 Speaker 1: party like a social media network, The more direct access 459 00:27:52,600 --> 00:27:55,280 Speaker 1: you have to that data, the richer the data is, 460 00:27:55,600 --> 00:27:57,720 Speaker 1: and you've got control over it and in a cost 461 00:27:57,760 --> 00:28:01,320 Speaker 1: effective way. So is that still something you're trying to 462 00:28:01,560 --> 00:28:03,440 Speaker 1: get your customers to really think about? 463 00:28:03,680 --> 00:28:05,760 Speaker 3: One hundred percent? You need to be controlled of your 464 00:28:05,800 --> 00:28:08,760 Speaker 3: own data destiny. So even though we have this data 465 00:28:08,760 --> 00:28:14,439 Speaker 3: asset that I've spoken about, it is not replaced my 466 00:28:14,560 --> 00:28:17,399 Speaker 3: push of helping clients get their first party data strategies 467 00:28:17,440 --> 00:28:21,600 Speaker 3: in order and where they can learn and they have 468 00:28:21,680 --> 00:28:25,880 Speaker 3: permission to with their customers learn about them more. I 469 00:28:26,040 --> 00:28:32,439 Speaker 3: hope for world where our brands have a trusted relationship 470 00:28:32,480 --> 00:28:36,840 Speaker 3: with their customers and customers want to willingly give them 471 00:28:37,000 --> 00:28:41,360 Speaker 3: their data. They trust that brand is going to use 472 00:28:41,520 --> 00:28:44,600 Speaker 3: that data within the permissions that customer has said they can, 473 00:28:44,920 --> 00:28:46,920 Speaker 3: and that that data is going to be secure, and 474 00:28:46,960 --> 00:28:49,720 Speaker 3: that is also part of my remit and my job. 475 00:28:50,080 --> 00:28:52,400 Speaker 3: And then once they have that data and that data 476 00:28:52,440 --> 00:28:56,080 Speaker 3: they have permission to use for marketing, my job is 477 00:28:56,120 --> 00:28:59,680 Speaker 3: then to help them use it in a compliant way 478 00:29:01,200 --> 00:29:04,720 Speaker 3: and at a scale that actually drives impact. And that's 479 00:29:04,760 --> 00:29:10,640 Speaker 3: not a binary choice. There are uh technologies, data assets, 480 00:29:11,760 --> 00:29:15,000 Speaker 3: some of which I've mentioned previously that allow us to 481 00:29:15,320 --> 00:29:18,720 Speaker 3: get that skill we need and still be compliant with 482 00:29:19,000 --> 00:29:21,320 Speaker 3: not only the letter of the law, but with the 483 00:29:21,360 --> 00:29:25,360 Speaker 3: social contracts we have with our customers and the markets 484 00:29:25,440 --> 00:29:26,240 Speaker 3: that we operate in. 485 00:29:26,920 --> 00:29:30,000 Speaker 1: Yeah, that's that's a really important point there because in 486 00:29:30,280 --> 00:29:33,080 Speaker 1: New Zealand we have a Privacy Act obviously, but you know, 487 00:29:33,120 --> 00:29:35,960 Speaker 1: the penalties compared to Australia are very low for things 488 00:29:36,000 --> 00:29:39,760 Speaker 1: like data breaches, you know, whereas in Australia after the 489 00:29:40,280 --> 00:29:42,720 Speaker 1: Optist data breach and that they really ramped up the 490 00:29:43,320 --> 00:29:46,920 Speaker 1: maximum finds if you are negligent and and a data 491 00:29:46,960 --> 00:29:50,640 Speaker 1: breach results from that. But there is a social contract 492 00:29:50,840 --> 00:29:53,760 Speaker 1: as well, and we've seen New Zealand companies punished for 493 00:29:54,520 --> 00:30:00,280 Speaker 1: privacy breaches. For instance, there's emerging technologies like CCTV that 494 00:30:00,560 --> 00:30:03,600 Speaker 1: is linked to AI, where you can identify someone's face 495 00:30:03,640 --> 00:30:05,880 Speaker 1: when they walk into a store, some of them are 496 00:30:05,920 --> 00:30:09,040 Speaker 1: being tagged as shoplifters or offenders. And then later on 497 00:30:09,120 --> 00:30:11,280 Speaker 1: if they try to come into a store, even in 498 00:30:11,320 --> 00:30:14,360 Speaker 1: a different part of the country, that company can say, hey, 499 00:30:14,360 --> 00:30:18,440 Speaker 1: we don't want you shopping here. So what are some 500 00:30:18,480 --> 00:30:21,280 Speaker 1: of the issues on the radar for you that are 501 00:30:21,320 --> 00:30:25,200 Speaker 1: really sort of centered around that privacy and data security 502 00:30:25,280 --> 00:30:27,560 Speaker 1: area that is becoming a lot more complicated. 503 00:30:28,400 --> 00:30:32,720 Speaker 3: Yeah, I think the core tenets are important, even that 504 00:30:32,800 --> 00:30:35,600 Speaker 3: the privacy lot of New Zealand past in twenty twenty 505 00:30:35,640 --> 00:30:39,280 Speaker 3: and then the update that's coming that twenty twenty was 506 00:30:39,480 --> 00:30:44,360 Speaker 3: technology agnostic, right, and the core tenants remain that transparency 507 00:30:44,640 --> 00:30:47,920 Speaker 3: of what's being collected and how it's being used, that consent, 508 00:30:48,480 --> 00:30:50,880 Speaker 3: all of these things are still core. And as you 509 00:30:50,920 --> 00:30:53,680 Speaker 3: look at the laws around the world and where they're going, 510 00:30:53,840 --> 00:30:56,800 Speaker 3: there's still some core tenants that are It's just true 511 00:30:57,840 --> 00:31:03,200 Speaker 3: even as you get to the various executions of the law. 512 00:31:03,680 --> 00:31:07,760 Speaker 3: So that's what we try to help our clients with, 513 00:31:07,920 --> 00:31:12,320 Speaker 3: and we're advising them on understanding what the requirements are 514 00:31:12,360 --> 00:31:16,240 Speaker 3: in their marketing, but more importantly take that legal ease 515 00:31:17,640 --> 00:31:19,240 Speaker 3: and look at it through the lens of a consumer 516 00:31:19,360 --> 00:31:23,440 Speaker 3: and create a great customer experience through it, because more 517 00:31:23,480 --> 00:31:31,560 Speaker 3: and more privacy compliance is actually a brand is infecting 518 00:31:31,560 --> 00:31:35,160 Speaker 3: your brand hygiene and your brand trust measures. Clients are 519 00:31:35,480 --> 00:31:41,120 Speaker 3: not just choosing where they spend based off of a 520 00:31:41,160 --> 00:31:45,920 Speaker 3: shopping experience. They're increasingly becoming more aware and choosing where 521 00:31:45,920 --> 00:31:48,880 Speaker 3: they're spend based off of the data experience. So if 522 00:31:48,880 --> 00:31:53,080 Speaker 3: you have a good, strong policy privacy policy, talk about it, 523 00:31:53,160 --> 00:31:54,880 Speaker 3: make sure it's showing up at different points in the 524 00:31:54,920 --> 00:31:58,400 Speaker 3: purchase journey to remind people of your policy, but also 525 00:31:58,480 --> 00:32:02,800 Speaker 3: your commitment to protecting and using their data in responsible, 526 00:32:02,840 --> 00:32:06,080 Speaker 3: reasonable and responsible ways. Consumers want to hear that. We 527 00:32:06,200 --> 00:32:08,960 Speaker 3: know they're not shy to share their data willingly when 528 00:32:08,960 --> 00:32:12,360 Speaker 3: there's a value exchange, but what they are crying out 529 00:32:12,440 --> 00:32:16,200 Speaker 3: for is more transparency around what's being collected, how it's 530 00:32:16,240 --> 00:32:20,080 Speaker 3: being used, and clear pathways to opt out or end 531 00:32:20,920 --> 00:32:23,680 Speaker 3: at any given time should they choose. 532 00:32:24,440 --> 00:32:26,640 Speaker 1: Yeah, and this is the theme that's really coming up 533 00:32:26,680 --> 00:32:29,560 Speaker 1: in a lot of surveys of consumers here in New 534 00:32:29,640 --> 00:32:31,880 Speaker 1: Zealand at the moment. One end Z, the big mobile 535 00:32:31,920 --> 00:32:35,280 Speaker 1: network operator, just did one I was involved in helping 536 00:32:35,560 --> 00:32:37,760 Speaker 1: write up the results of it, which really showed that 537 00:32:37,760 --> 00:32:40,400 Speaker 1: when it comes to artificial intelligence, there's a lot of 538 00:32:40,480 --> 00:32:46,840 Speaker 1: distrust there because consumers, their initial interactions with AI in 539 00:32:46,880 --> 00:32:52,680 Speaker 1: the customer space has really been through chatbots, customer service chatbots, 540 00:32:52,720 --> 00:32:57,320 Speaker 1: and it's been an unsatisfactory experience. They're also worried about 541 00:32:57,360 --> 00:32:59,800 Speaker 1: what happens to their data, how their data is going 542 00:32:59,840 --> 00:33:03,480 Speaker 1: to be used in the AI context. I guess you know, 543 00:33:03,600 --> 00:33:07,280 Speaker 1: artificial intelligence is changing the game when it comes to advertising. 544 00:33:07,760 --> 00:33:10,640 Speaker 1: I mean, in one sense, when you interact with Google, 545 00:33:10,680 --> 00:33:14,640 Speaker 1: now you're seeing AI overviews. So that's that's turning the 546 00:33:14,960 --> 00:33:17,000 Speaker 1: ad market upside down in terms of how do you 547 00:33:17,040 --> 00:33:20,440 Speaker 1: get into those overviews? How do you get into AI 548 00:33:20,680 --> 00:33:24,960 Speaker 1: chatbots in a compelling way? But behind the scenes, the 549 00:33:25,080 --> 00:33:29,480 Speaker 1: data that you're looking at, the identity graph, all of 550 00:33:29,520 --> 00:33:33,280 Speaker 1: that information, how is AI changing how all of that 551 00:33:33,320 --> 00:33:37,080 Speaker 1: works as well? It's got to be huge consequences of 552 00:33:37,280 --> 00:33:40,920 Speaker 1: the generative AI revolution for advertising behind the scenes. 553 00:33:41,640 --> 00:33:45,120 Speaker 3: Yeah, it put us as we believe that impactful AI 554 00:33:45,200 --> 00:33:49,160 Speaker 3: for marketing use cases, you know, needs to be trained 555 00:33:49,440 --> 00:33:53,800 Speaker 3: off the best data. AI is nothing without good data 556 00:33:53,960 --> 00:33:57,960 Speaker 3: to be trained on, which is why some of the 557 00:33:58,400 --> 00:34:01,800 Speaker 3: scarier stories around AI is you know, propelling those things. 558 00:34:01,800 --> 00:34:04,719 Speaker 3: With the data set going into training the AI was 559 00:34:04,960 --> 00:34:08,640 Speaker 3: just not inclusive enough or broad enough. So part of 560 00:34:08,640 --> 00:34:11,359 Speaker 3: our acquisition of Avloda May was to round out some 561 00:34:11,480 --> 00:34:15,480 Speaker 3: of that our identity graph around the world so we 562 00:34:15,480 --> 00:34:17,919 Speaker 3: can have the best data to train to train our AI. 563 00:34:18,600 --> 00:34:23,800 Speaker 3: Same applies to our brands and customers who are building 564 00:34:23,840 --> 00:34:27,720 Speaker 3: out their AI apps and and and any and agents. 565 00:34:27,960 --> 00:34:31,120 Speaker 3: You know what data are you training it on. We 566 00:34:31,200 --> 00:34:34,919 Speaker 3: have to remember, Peter, though, that AI has been influencing 567 00:34:35,480 --> 00:34:40,839 Speaker 3: marketing for years, you know, you know, everything from recommendation 568 00:34:40,960 --> 00:34:46,440 Speaker 3: engines to look like modeling. Now we have the chatbots 569 00:34:46,480 --> 00:34:49,320 Speaker 3: and and so forth, so we're used to it as 570 00:34:49,440 --> 00:34:53,439 Speaker 3: as as an industry and consumers, their awareness is growing 571 00:34:53,440 --> 00:34:57,200 Speaker 3: to AI has been influencing their life for years, their 572 00:34:57,280 --> 00:35:00,080 Speaker 3: social media news feed. You know what I watch on 573 00:35:00,120 --> 00:35:05,279 Speaker 3: a Saturday night on Netflix's that's our AI. Going back 574 00:35:05,320 --> 00:35:09,000 Speaker 3: to our job of building trust, drive that awareness. It 575 00:35:09,040 --> 00:35:11,920 Speaker 3: is now our responsibility not only to have a compliant 576 00:35:12,080 --> 00:35:15,000 Speaker 3: data privacy, but to drive that awareness of how we're 577 00:35:15,120 --> 00:35:18,879 Speaker 3: using the data and how it adds value to consumers 578 00:35:19,160 --> 00:35:22,200 Speaker 3: is the job that we have to increasingly do. I 579 00:35:22,320 --> 00:35:25,800 Speaker 3: don't care that Netflix is looking at all my viewership 580 00:35:25,840 --> 00:35:28,080 Speaker 3: data to serve me up a really good thing to 581 00:35:28,120 --> 00:35:31,000 Speaker 3: watch on Saturday night, because there's a value exchange there. 582 00:35:31,719 --> 00:35:33,200 Speaker 3: We need to do the same thing and get on 583 00:35:33,200 --> 00:35:36,640 Speaker 3: the front foot of doing that across multiple industries. 584 00:35:37,320 --> 00:35:41,000 Speaker 1: Yeah, and look, we've just seen the launch of Meta AI, 585 00:35:41,120 --> 00:35:45,840 Speaker 1: the standalone sort of fully duplex app that Meta release Twitch. 586 00:35:45,960 --> 00:35:49,080 Speaker 1: You know, I've been experimenting with and you know Grock 587 00:35:49,120 --> 00:35:51,720 Speaker 1: has done this as well, Open AI, where you actually 588 00:35:51,719 --> 00:35:55,000 Speaker 1: start to have more of a naturalistic conversation with an 589 00:35:55,040 --> 00:35:58,280 Speaker 1: AI bot and you know, the likes of the Lix 590 00:35:58,600 --> 00:36:01,440 Speaker 1: and Siri. It's taking bit longer than they wanted, but 591 00:36:02,360 --> 00:36:05,239 Speaker 1: generative AI being introduced to those platforms. So we are 592 00:36:05,280 --> 00:36:10,080 Speaker 1: sort of entering the era off having a truly useful 593 00:36:10,560 --> 00:36:14,240 Speaker 1: conversational digital assistant. And I guess you know the business 594 00:36:14,239 --> 00:36:18,120 Speaker 1: model independing that is the supercharged alixis and series are 595 00:36:18,160 --> 00:36:21,160 Speaker 1: going to be recommending you things based on all the 596 00:36:21,239 --> 00:36:22,279 Speaker 1: data they have about you. 597 00:36:22,640 --> 00:36:27,279 Speaker 3: Yeah, and recommending things, but also then interacting with other 598 00:36:27,320 --> 00:36:29,920 Speaker 3: agents on your behalf. You know, there's a stat I 599 00:36:29,920 --> 00:36:32,920 Speaker 3: think from a Salesforce research that I saw at a 600 00:36:32,920 --> 00:36:36,560 Speaker 3: conference last week that one in four consumers have used 601 00:36:36,600 --> 00:36:42,280 Speaker 3: AI in a shopping journey so far, so far. Yeah, 602 00:36:42,360 --> 00:36:45,680 Speaker 3: So people are getting more comfortable with it, obviously, the 603 00:36:45,760 --> 00:36:48,759 Speaker 3: use cases of chat GPT and it being helpful to 604 00:36:48,840 --> 00:36:53,600 Speaker 3: them and that that regard everything from helping them work 605 00:36:53,680 --> 00:36:57,400 Speaker 3: to providing them therapy. Yes, that is a real that 606 00:36:57,640 --> 00:37:02,759 Speaker 3: actually using chat SHEP too to supplant therapists is an 607 00:37:02,760 --> 00:37:07,880 Speaker 3: increasing use case. We're getting more comfortable with all of 608 00:37:07,880 --> 00:37:11,640 Speaker 3: the ways AI is now at the forefront of helping 609 00:37:11,719 --> 00:37:15,480 Speaker 3: us in many aspects of our life personally, but also 610 00:37:15,600 --> 00:37:18,320 Speaker 3: obviously on the business side. 611 00:37:18,600 --> 00:37:21,640 Speaker 1: Just finally, Mars, as you sort of survey the landscape 612 00:37:21,640 --> 00:37:24,800 Speaker 1: in this part of the world, any one particular trend 613 00:37:24,960 --> 00:37:28,319 Speaker 1: that you're concerned about or think is going to really 614 00:37:28,320 --> 00:37:32,400 Speaker 1: figure largely as we look through twenty twenty five, hopefully 615 00:37:32,440 --> 00:37:34,200 Speaker 1: to a bitter economic climate. 616 00:37:34,640 --> 00:37:38,320 Speaker 3: Yeah, I'm going to take this as a very narrow 617 00:37:39,239 --> 00:37:41,640 Speaker 3: trend in marketing that I see a lot of my 618 00:37:41,680 --> 00:37:49,000 Speaker 3: colleagues do this trend of constantly debating this what is 619 00:37:49,040 --> 00:37:51,960 Speaker 3: believed to be a binary choice of brand marketing and 620 00:37:52,000 --> 00:37:57,640 Speaker 3: performance marketing and the two sho never intertwine. No, they do. 621 00:37:57,840 --> 00:38:01,240 Speaker 3: And there's been heaps of studies that suggests that both 622 00:38:01,239 --> 00:38:06,960 Speaker 3: are important to get that multiplier effect across both, so 623 00:38:07,560 --> 00:38:10,640 Speaker 3: brand and performance and vice versa. That leads back to 624 00:38:10,840 --> 00:38:13,000 Speaker 3: understanding you know those consumers that are in the middle 625 00:38:13,520 --> 00:38:16,400 Speaker 3: and being exposed to brand before they get to in 626 00:38:16,520 --> 00:38:20,160 Speaker 3: market as we talked earlier, and that middle verse. But yeah, 627 00:38:20,200 --> 00:38:24,720 Speaker 3: it seems like it's a trend of it being constantly debated, 628 00:38:24,800 --> 00:38:27,480 Speaker 3: debated year over year, and I think we should just 629 00:38:27,520 --> 00:38:28,160 Speaker 3: get on with it. 630 00:38:28,560 --> 00:38:31,240 Speaker 1: So just to explain that, Mars, you've got brand marketing 631 00:38:31,280 --> 00:38:35,600 Speaker 1: people understand, we've got iconic New Zealand and international brands 632 00:38:35,600 --> 00:38:39,160 Speaker 1: were exposed to and they're great advertising campaigns and that 633 00:38:39,200 --> 00:38:44,400 Speaker 1: are designed to promote those brands. What's the performance element 634 00:38:44,480 --> 00:38:44,839 Speaker 1: of it? 635 00:38:44,840 --> 00:38:47,799 Speaker 3: The performance tends to be once you've done the brand job, 636 00:38:47,840 --> 00:38:51,200 Speaker 3: you've gotten someone's attention somewhere through the journey, you didn't 637 00:38:51,200 --> 00:38:52,960 Speaker 3: see it pop up a whole bunch of signals who 638 00:38:53,000 --> 00:38:57,080 Speaker 3: are in market for your service, all right, And oftentimes 639 00:38:57,320 --> 00:39:00,480 Speaker 3: the planning of those two campaigns or the actually are 640 00:39:00,480 --> 00:39:05,080 Speaker 3: planned differently or connected or going back to how we 641 00:39:05,160 --> 00:39:09,360 Speaker 3: nudge people through the channel, we don't think of it holistically. 642 00:39:09,360 --> 00:39:13,239 Speaker 3: And there's a brand planned and an in market plan 643 00:39:13,360 --> 00:39:17,160 Speaker 3: or a performance plan those in market audiences, and there's 644 00:39:17,200 --> 00:39:19,359 Speaker 3: a debate of how much should brand be invested in 645 00:39:19,360 --> 00:39:21,480 Speaker 3: and how much should performance be invested in? And what 646 00:39:21,600 --> 00:39:23,239 Speaker 3: data are we using for brand and what date are 647 00:39:23,239 --> 00:39:27,080 Speaker 3: we using for performance. They aren't binary choices. They work together. 648 00:39:27,239 --> 00:39:30,560 Speaker 3: They and when they're harmonized. There's a recent study from 649 00:39:30,600 --> 00:39:35,280 Speaker 3: the WRC that says if you shift to a mixed plan, 650 00:39:35,840 --> 00:39:40,760 Speaker 3: it can lift median revenue ROI by ninety percent. Obviously 651 00:39:40,840 --> 00:39:44,120 Speaker 3: that's varies by category of what your entry point is, 652 00:39:44,400 --> 00:39:46,440 Speaker 3: but the evidence is there, and there's been heaps of 653 00:39:46,480 --> 00:39:49,200 Speaker 3: other studies and evidence out there that proves the same. 654 00:39:49,560 --> 00:39:52,480 Speaker 1: So that's really powerful. So it's and I think, you 655 00:39:52,520 --> 00:39:55,080 Speaker 1: know we're guilty of that here in New Zealand's and 656 00:39:55,200 --> 00:39:57,719 Speaker 1: you know my interactions with people in advertising is there 657 00:39:58,080 --> 00:40:00,440 Speaker 1: some of them are really hung up. They're focused passion 658 00:40:00,560 --> 00:40:04,880 Speaker 1: is the brand? What advertising and marketing can we do 659 00:40:04,960 --> 00:40:08,480 Speaker 1: to uphold this great brand like Whitaker's chocolate or something 660 00:40:08,480 --> 00:40:11,359 Speaker 1: in iconic New Zealand brand. It's a whole different set 661 00:40:11,400 --> 00:40:14,040 Speaker 1: of people who actually do the stuff. Further down the funnel, 662 00:40:14,080 --> 00:40:19,000 Speaker 1: it's more nuts and bolts and performance based. As you say, 663 00:40:19,040 --> 00:40:22,360 Speaker 1: But what you're saying is unless you jell those things 664 00:40:22,400 --> 00:40:24,680 Speaker 1: really well, you're leaving a lot of money on the table. 665 00:40:25,280 --> 00:40:28,160 Speaker 3: Correct And with some of our clients here in New Zealand. 666 00:40:28,239 --> 00:40:31,040 Speaker 3: That's why we have the Connected platform where our creative 667 00:40:31,200 --> 00:40:34,120 Speaker 3: agencies are working hand in hand with our media agencies 668 00:40:34,239 --> 00:40:38,440 Speaker 3: and to make sure that brand and media plans and 669 00:40:38,440 --> 00:40:41,120 Speaker 3: our serium agencies all of their connected, so we can 670 00:40:41,239 --> 00:40:44,400 Speaker 3: talk about when we get someone's attention, we drive that curiosity, 671 00:40:44,760 --> 00:40:48,200 Speaker 3: where are all the points along that journey where we're 672 00:40:48,840 --> 00:40:51,480 Speaker 3: driving that conversion, driving them to kart? You know that 673 00:40:51,560 --> 00:40:54,600 Speaker 3: has to be harmonizing together and that is key to 674 00:40:54,680 --> 00:40:57,600 Speaker 3: our proposition and service that we offer to our clients 675 00:40:57,719 --> 00:40:59,760 Speaker 3: here in New Zealand and around the world. 676 00:41:00,640 --> 00:41:03,080 Speaker 1: Well Maris, thanks so much for your insights. Great to 677 00:41:03,080 --> 00:41:05,880 Speaker 1: see you in New Zealand. Hopefully the message is getting 678 00:41:05,920 --> 00:41:10,080 Speaker 1: through here and we will see better times ahead. But 679 00:41:10,160 --> 00:41:12,120 Speaker 1: thanks so much for coming on the Business of Tech. 680 00:41:12,440 --> 00:41:15,840 Speaker 3: No, thanks for having me and next time let me 681 00:41:15,920 --> 00:41:18,160 Speaker 3: come down to Wellington and we can do this over 682 00:41:18,200 --> 00:41:18,560 Speaker 3: a beer. 683 00:41:24,600 --> 00:41:27,359 Speaker 1: Thanks so much to Morris Riley for coming on our 684 00:41:27,440 --> 00:41:31,600 Speaker 1: data guru and advertising expert. Show notes are in the 685 00:41:31,640 --> 00:41:35,319 Speaker 1: podcast section at Businessdesk dot co dot en zed and 686 00:41:35,360 --> 00:41:38,400 Speaker 1: the podcast, of course is streaming on iHeartRadio or in 687 00:41:38,440 --> 00:41:42,040 Speaker 1: your favorite podcast app. Would love your feedback and topic 688 00:41:42,160 --> 00:41:45,080 Speaker 1: and guest suggestions. Get in touch with me via email 689 00:41:45,280 --> 00:41:48,120 Speaker 1: Peter at Peter Griffin dot co dot en zed, and 690 00:41:48,120 --> 00:41:50,360 Speaker 1: of course you'll find me on LinkedIn. Would love to 691 00:41:50,400 --> 00:41:53,239 Speaker 1: hear from you next week. An Ozzie business coach who 692 00:41:53,280 --> 00:41:56,400 Speaker 1: has written a very practical book, Cutting through the BS 693 00:41:56,520 --> 00:41:59,520 Speaker 1: Around AI, with the aim of giving businesses of any 694 00:41:59,600 --> 00:42:03,279 Speaker 1: size some tips on how to integrate artificial intelligence in 695 00:42:03,320 --> 00:42:06,360 Speaker 1: a useful way. That's dropping next Thursday. I'll catch you 696 00:42:06,440 --> 00:42:06,560 Speaker 1: then