1 00:00:05,420 --> 00:00:09,850 Hello and welcome you live from NRF to the Special Retail 2 00:00:09,860 --> 00:00:16,120 Podcast and E Tab Day One recap. I'm joined by Simon, Head of 3 00:00:16,129 --> 00:00:20,520 Sales for the UK. Yep, Mr Head of Marketing for 4 00:00:20,600 --> 00:00:25,260 etab Global, ETAP Central. Then what do you call it? 5 00:00:25,310 --> 00:00:26,380 Ethan Brick. That's it. 6 00:00:26,450 --> 00:00:27,540 And I and. You and. 7 00:00:27,550 --> 00:00:28,280 I'm. I'm. 8 00:00:28,290 --> 00:00:31,010 Looking for? Ohh. 9 00:00:31,450 --> 00:00:34,090 Yeah, perfect. So what we're gonna do, we're 10 00:00:34,100 --> 00:00:37,920 gonna spend the next 15 minutes going through what we took away 11 00:00:37,930 --> 00:00:40,320 today. What was the sort of highlights 12 00:00:40,330 --> 00:00:42,440 for us? We, I know we had, Simon, I 13 00:00:42,450 --> 00:00:44,060 think you were looking at innovation, right? 14 00:00:44,070 --> 00:00:47,160 You were looking for key innovations and what you saw. 15 00:00:47,230 --> 00:00:48,960 Yeah, I was. I was looking for innovation, 16 00:00:48,970 --> 00:00:52,020 but also looking around what I thought the key trends were and 17 00:00:52,030 --> 00:00:54,920 how things would translate into the needs of retailers. 18 00:00:54,990 --> 00:00:56,970 Fantastic. And Emma, what was just, I'm 19 00:00:56,980 --> 00:00:59,760 interest, what was your focus? Was there anything that you were 20 00:00:59,820 --> 00:01:02,200 sort of keeping an eye on as you were going through the talks? 21 00:01:02,290 --> 00:01:06,730 Yeah, I were focusing on the innovation and grocery mainly, 22 00:01:06,800 --> 00:01:09,020 OK. And the AI parts of all of it 23 00:01:09,030 --> 00:01:12,430 that the personalization and of course very interesting for me 24 00:01:12,440 --> 00:01:15,930 as a marketeer is the marketing is very much in focus, Yeah, now 25 00:01:15,940 --> 00:01:18,610 so. Yeah, I mean it it it was 26 00:01:18,620 --> 00:01:21,070 incredible. I think the scale you can see 27 00:01:21,080 --> 00:01:26,570 behind me, we're on level 1 mezzanine, basically the, the, 28 00:01:26,640 --> 00:01:28,670 the. To give you some context of the 29 00:01:28,680 --> 00:01:33,420 depth of of how big this event is, the building behind the 30 00:01:33,430 --> 00:01:36,400 camera is where the main. Talks are. 31 00:01:36,510 --> 00:01:40,420 Behind me there are three to five ex rivals, depending on how 32 00:01:40,430 --> 00:01:43,520 you split it on three different levels, again depending on how 33 00:01:43,530 --> 00:01:47,800 you split it And innovation and food innovation, which is new 34 00:01:47,810 --> 00:01:50,660 for this year so let's get straight into assignment. 35 00:01:50,870 --> 00:01:54,540 I'd love to know. You know, innovation trends. 36 00:01:54,690 --> 00:01:56,880 What what did you? Come away with like, I guess 37 00:01:56,890 --> 00:01:59,760 just mirroring what you say, The scale of the scale of the show 38 00:01:59,770 --> 00:02:02,880 is incredible. There's what, 6000 booths to 39 00:02:02,890 --> 00:02:05,280 look out. So finding innovation is easy 40 00:02:05,290 --> 00:02:07,180 and really difficult of finding that gold. 41 00:02:07,190 --> 00:02:11,250 But I think for me, if you take the Innovation zone, other than 42 00:02:11,260 --> 00:02:15,550 a a 3D mannequin and a robot, everything else was AI. 43 00:02:15,600 --> 00:02:18,330 Every single stand has the word AI in. 44 00:02:18,640 --> 00:02:21,830 And and also one of the trends that I see here is that there's 45 00:02:21,840 --> 00:02:24,450 lots of startups that have something really interesting, 46 00:02:24,560 --> 00:02:26,550 but can't quite explain what that is. 47 00:02:26,560 --> 00:02:28,860 Yeah. So when they, when they describe 48 00:02:28,870 --> 00:02:31,430 it on their stand versus the conversation that you have 49 00:02:31,440 --> 00:02:34,540 versus how I would describe it for the needs of retailers is 50 00:02:34,550 --> 00:02:38,300 quite different. So I've found that AI is a 51 00:02:38,310 --> 00:02:39,660 theme. I've learned some new words. 52 00:02:39,670 --> 00:02:42,070 I've learned about composable AI. 53 00:02:42,130 --> 00:02:47,140 That's the thing, apparently. And also deep, you mean you 54 00:02:47,150 --> 00:02:50,910 don't know. So composable AI is about how 55 00:02:50,920 --> 00:02:53,530 the connectivity of different things together, so connecting 56 00:02:53,540 --> 00:02:56,710 different parts of AI together into a single thing. 57 00:02:56,800 --> 00:02:59,060 And generative AI is mentioned quite a lot. 58 00:02:59,070 --> 00:03:02,810 And again I had to ask what do you mean by that and and that's 59 00:03:02,820 --> 00:03:06,330 about AI that can generative. Yeah. 60 00:03:06,520 --> 00:03:10,970 And it's about being able to then create images or text as as 61 00:03:10,980 --> 00:03:12,630 a base of AI which is quite interesting. 62 00:03:12,640 --> 00:03:16,390 So I think that I've found lots and lots of stands that have 63 00:03:16,400 --> 00:03:19,400 tried to elevate was talking about AI to try and add a few 64 00:03:19,410 --> 00:03:22,780 more words to to to add a little bit more value to it. 65 00:03:22,970 --> 00:03:27,570 However I think well I have found is that the use of AI is 66 00:03:27,580 --> 00:03:29,650 covering so many different things. 67 00:03:29,900 --> 00:03:32,700 It's not all capturing consumer behaviour, but whether it's 68 00:03:32,710 --> 00:03:37,290 stock forecasting, replenishment behaviour in store, footfall, 69 00:03:37,300 --> 00:03:41,870 tracking, all about data. Everything I've seen today has a 70 00:03:41,880 --> 00:03:45,110 dashboard and there's dashboard for everything and I think that 71 00:03:45,200 --> 00:03:48,480 the clever thing is being able to take the use of that data but 72 00:03:48,490 --> 00:03:50,930 being able to take it back into something that's actionable. 73 00:03:50,940 --> 00:03:54,130 Insight, which I think will be quite tricky, but but definitely 74 00:03:54,140 --> 00:03:56,370 a I is the theme of for the day for sure. 75 00:03:56,380 --> 00:04:00,560 Yeah, I I 100% it's interesting. Is it, is it do you think is it 76 00:04:00,570 --> 00:04:03,340 because there's a lot of technology startups who think 77 00:04:03,350 --> 00:04:06,050 ohh, I'm gonna go and start selling to retailers and that's 78 00:04:06,060 --> 00:04:08,470 why when you sort of say give me a use case then they're like ohh 79 00:04:08,480 --> 00:04:10,270 well you know we can do stuff with pledge. 80 00:04:10,320 --> 00:04:12,130 Tell me about that. And they're like it's all. 81 00:04:12,700 --> 00:04:13,590 It's that. It's a fact. 82 00:04:13,600 --> 00:04:16,130 I found it a lot. People explain something really 83 00:04:16,140 --> 00:04:17,709 well. And you ask, how does that 84 00:04:17,720 --> 00:04:19,470 change consumer behaviour? Yeah. 85 00:04:19,519 --> 00:04:22,060 And that's when it starts to crumble a little bit, because 86 00:04:22,070 --> 00:04:23,100 they're not quite yet. Sure. 87 00:04:23,110 --> 00:04:25,690 And and I think there's a whole lot of people that have invented 88 00:04:25,790 --> 00:04:27,290 something really cool. Yeah. 89 00:04:27,350 --> 00:04:30,250 And whether that really cool is something that translates into 90 00:04:30,720 --> 00:04:33,250 something that a retailer can use or something that just 91 00:04:33,260 --> 00:04:36,060 becomes a flagship that's really quite interesting. 92 00:04:36,070 --> 00:04:39,000 I'll probably do one. It is, there's a fine balance 93 00:04:39,010 --> 00:04:40,170 between those things at the moment. 94 00:04:40,180 --> 00:04:45,410 But yeah, it's AI recurring theme, but not necessarily. 95 00:04:45,640 --> 00:04:51,260 It's not necessarily all about AI changing the world, but how 96 00:04:51,270 --> 00:04:53,560 AI can complement some of the things that already happened. 97 00:04:53,710 --> 00:04:55,980 Understood, everyone. How about for you, what was like 98 00:04:55,990 --> 00:05:00,820 the the main part from a I, you know but I guess the AI themes 99 00:05:00,830 --> 00:05:03,640 we can't say apart from me because people watching this. 100 00:05:03,690 --> 00:05:05,380 Yeah. I'll probably thinking about how 101 00:05:05,390 --> 00:05:07,050 do I use these Yeah. So what? 102 00:05:07,060 --> 00:05:10,360 What was it for you? For me it was like you need to 103 00:05:10,370 --> 00:05:13,660 have the base first. You need to have the digital 104 00:05:13,810 --> 00:05:17,920 ground pillars like the CRM system, your data warehouse, 105 00:05:17,930 --> 00:05:20,190 your data management. You need to have everything in 106 00:05:20,200 --> 00:05:24,740 place first and then you can go further and have the customer 107 00:05:24,750 --> 00:05:27,310 experience in the centre of all of it. 108 00:05:27,380 --> 00:05:31,070 Yeah, yeah, you need to think through, OK, where can I do 109 00:05:31,140 --> 00:05:36,890 efficiency with a where can I do stuff less dependent on the 110 00:05:36,900 --> 00:05:41,530 staffing itself, Yeah. So you can focus on the customer 111 00:05:41,540 --> 00:05:45,110 experience instead of doing this repetitive task that we can use 112 00:05:45,120 --> 00:05:47,690 AI4. So that was very interesting. 113 00:05:47,700 --> 00:05:51,680 A lot of talks were focusing about how can we improve the 114 00:05:51,730 --> 00:05:56,060 customer experience and how can we automate with AI so we can 115 00:05:56,070 --> 00:05:59,320 have time to do the stuff that we are good at as humans. 116 00:05:59,330 --> 00:06:01,100 Not that a I do. Yeah. 117 00:06:01,170 --> 00:06:04,540 So that was very interesting. I think efficiency driven out of 118 00:06:04,550 --> 00:06:09,960 tasks being automated is 100%. But the the key thing is, and 119 00:06:10,080 --> 00:06:13,000 this is depending on who you speak, you need to have a base 120 00:06:13,010 --> 00:06:16,050 to build on, right? You need your data to be there. 121 00:06:16,060 --> 00:06:18,390 You need to have had the, I don't know, your supply chain 122 00:06:18,400 --> 00:06:21,020 needs to be in some shape of water or your front of house 123 00:06:21,090 --> 00:06:23,310 loyalty programme needs to have that data. 124 00:06:23,380 --> 00:06:24,710 Yeah. So I'm. 125 00:06:24,720 --> 00:06:27,050 I'm curious Emma, did you have any talks on loss today? 126 00:06:27,060 --> 00:06:29,470 Did you see anything about loss? Yeah, I did it. 127 00:06:29,480 --> 00:06:33,010 There are of course still a big trend with a loss prevention or 128 00:06:33,020 --> 00:06:37,090 trend maybe a threat to all retailers that we have this loss 129 00:06:37,100 --> 00:06:40,320 prevention issues. We yeah, but and they are also 130 00:06:40,330 --> 00:06:44,210 new names for it. So they say terms. 131 00:06:44,440 --> 00:06:46,320 So it's now that. Actor. 132 00:06:46,560 --> 00:06:48,250 Yeah, Bad actor. Yeah, yeah, Yeah. 133 00:06:49,740 --> 00:06:51,370 Remember first I said, well, what are you saying about it 134 00:06:52,540 --> 00:06:53,730 anyway? Yeah. 135 00:06:53,940 --> 00:06:56,640 Yeah, there's so many buzzwords right now about loss 136 00:06:56,650 --> 00:06:58,660 preventions. You need to collect all of these 137 00:06:58,670 --> 00:07:02,760 and write them down to be on top of mind of these loss prevention 138 00:07:02,770 --> 00:07:04,500 solutions. Is there anything as a market 139 00:07:04,510 --> 00:07:07,480 here that you're thinking when I get back home, there's something 140 00:07:07,490 --> 00:07:10,200 I want to experiment with? Is there something that I've 141 00:07:10,210 --> 00:07:13,140 inspired you? From the whole show, yeah. 142 00:07:13,150 --> 00:07:16,000 From from today because there was an inspiration from today. 143 00:07:16,090 --> 00:07:20,100 Yeah, actually it was that the retail media part, OK, Like a 144 00:07:20,110 --> 00:07:21,130 lot. Of the big trend? 145 00:07:21,140 --> 00:07:22,100 No. Retail media? 146 00:07:22,110 --> 00:07:23,470 Yes. Yeah, Yeah. 147 00:07:23,540 --> 00:07:28,480 And that the marketeers lead the way based on their analysis and 148 00:07:28,490 --> 00:07:33,230 their data-driven campaigns, data-driven work through like 149 00:07:33,240 --> 00:07:35,170 Google Analytics. We haven't done that for a 150 00:07:35,180 --> 00:07:37,290 while. We've been marketing and now 151 00:07:37,300 --> 00:07:41,010 it's time for retail to step into that because of all these 152 00:07:41,900 --> 00:07:45,280 AI possibilities. Now you can be, we have sensors, 153 00:07:45,290 --> 00:07:48,430 we have the smart way of measure things. 154 00:07:48,440 --> 00:07:52,690 We can measure things based on all these AI smartness that we 155 00:07:52,700 --> 00:07:53,250 have. Now. 156 00:07:53,300 --> 00:07:55,450 Yeah, that I've been doing for a while. 157 00:07:55,460 --> 00:07:59,270 So now I think that OK, what I know based on my work, I can 158 00:07:59,280 --> 00:08:01,740 apply on this retail thing. Yeah. 159 00:08:01,800 --> 00:08:05,910 And we can do basically think that the store could be like a 160 00:08:05,920 --> 00:08:08,070 website. Yeah, so. 161 00:08:08,150 --> 00:08:10,510 Take, which has been the the the thing that I've been saying for 162 00:08:10,520 --> 00:08:12,450 years. Make the invisible visible, 163 00:08:12,520 --> 00:08:15,720 right, And that's how you make your store operations and 164 00:08:15,730 --> 00:08:17,440 everything that you can't see become always. 165 00:08:17,600 --> 00:08:21,080 I think Marc Benioff in the Walmart final keynote sort of 166 00:08:21,090 --> 00:08:23,980 summarised there when he sort of asked the audience, does anyone 167 00:08:23,990 --> 00:08:27,360 remember Minority Report right in terms at the moment when he 168 00:08:27,370 --> 00:08:30,580 goes into the Gap and, you know, he's recognised. 169 00:08:30,630 --> 00:08:32,640 He's. I I think for me, the one thing 170 00:08:32,650 --> 00:08:35,980 that I noticed on a few of the analysis, trends, panelling, 171 00:08:36,870 --> 00:08:40,220 trend talks that I went to is the fact that people who are 172 00:08:40,230 --> 00:08:44,300 already in your customer base want more and a bigger 173 00:08:44,310 --> 00:08:49,020 acceleration of customisation, that threat to my privacy. 174 00:08:49,310 --> 00:08:51,660 I'm already there. I'm already bought into you as a 175 00:08:51,670 --> 00:08:54,060 retailer. Yeah, I want you to know me. 176 00:08:54,070 --> 00:08:56,460 I want you to offer that service to me. 177 00:08:56,530 --> 00:08:59,710 Yeah, I think that was one of the big sort of stats for the 178 00:08:59,720 --> 00:09:03,160 day that that's coming up. OK, final thoughts, Final 179 00:09:03,170 --> 00:09:05,860 thoughts on. As much as today's been great, I 180 00:09:05,870 --> 00:09:08,570 think the thing that I was expecting see more of that 181 00:09:08,580 --> 00:09:13,150 happen is around sustainability. Yes, I I thought he would be one 182 00:09:13,160 --> 00:09:15,130 of the big themes that I would see today. 183 00:09:15,230 --> 00:09:18,130 And there's a there's a sustainability corner, yeah. 184 00:09:18,180 --> 00:09:21,750 But there isn't really the level of messaging that I would say 185 00:09:21,760 --> 00:09:23,730 about helping retailers be more sustainable. 186 00:09:23,740 --> 00:09:25,690 I hope that's that's been something that's somewhat of a 187 00:09:25,700 --> 00:09:28,180 surprise to me saying OK. And that. 188 00:09:28,790 --> 00:09:31,390 And I will bring the personalisation. 189 00:09:31,400 --> 00:09:35,730 I think, yeah, that we in the future will be so well known by 190 00:09:35,740 --> 00:09:39,050 the stores that when I walk in they will already know what I 191 00:09:39,060 --> 00:09:40,250 will order. Yeah. 192 00:09:40,320 --> 00:09:44,090 So that's a really cool thing that I'm looking forward to. 193 00:09:44,100 --> 00:09:48,090 OK Can they read my mind? Kind of with AI when I walk in 194 00:09:48,160 --> 00:09:53,340 and they already have picked out the really nice theme of clothes 195 00:09:53,350 --> 00:09:56,280 and I can just choose and walk out that would. 196 00:09:56,350 --> 00:10:00,480 Be very cool, Yeah, I think. I think retailers are are 197 00:10:00,490 --> 00:10:03,160 definitely challenged with understanding all of these 198 00:10:03,170 --> 00:10:05,600 themes. Let's look at what day two 199 00:10:05,610 --> 00:10:07,840 brings. We'll be back again tomorrow. 200 00:10:08,710 --> 00:10:12,800 Yes, tomorrow to to provide. So thank you so much for tuning 201 00:10:12,810 --> 00:10:16,160 into this LinkedIn live. Look forward to meeting with you 202 00:10:16,170 --> 00:10:18,340 tomorrow if you have any questions. 203 00:10:18,410 --> 00:10:20,960 If you if there's something on top of mind, reach out to your 204 00:10:20,970 --> 00:10:25,110 local I tab or TAB team Ohh, message us directly. 205 00:10:25,120 --> 00:10:27,410 We're here to answer your questions, so if there's 206 00:10:27,420 --> 00:10:29,690 anything else that you need to know, just let us know and we'll 207 00:10:29,700 --> 00:10:32,350 do our best to go hunt and bring it to you. 208 00:10:32,440 --> 00:10:33,380 Thank you so much.