WEBVTT 1aac9cd4-0ab7-4e8d-8d2a-084393f461c9-0 00:00:00.590 --> 00:00:03.468 I'm here at the Cannes creativity festival, and I'm 1aac9cd4-0ab7-4e8d-8d2a-084393f461c9-1 00:00:03.468 --> 00:00:06.845 accompanied by Dinesh. Dinesh, thanks so much for joining us 1aac9cd4-0ab7-4e8d-8d2a-084393f461c9-2 00:00:06.845 --> 00:00:10.387 today. Can you tell us a little bit more about your role at the 1aac9cd4-0ab7-4e8d-8d2a-084393f461c9-3 00:00:10.387 --> 00:00:12.270 Zalando Marketing Services? Sure. ffcf379e-3a67-4768-ae21-f7a3752d48ad-0 00:00:13.120 --> 00:00:17.342 I lead the tech team at Zalando Marketing Services, and we ffcf379e-3a67-4768-ae21-f7a3752d48ad-1 00:00:17.342 --> 00:00:21.780 enable brands to connect with consumers, to inspire them with ffcf379e-3a67-4768-ae21-f7a3752d48ad-2 00:00:21.780 --> 00:00:24.930 storytelling experiences and build loyalty. 6b0a1711-4773-41eb-ae33-e624b152b409-0 00:00:26.370 --> 00:00:29.526 What do we know from the fashion industry is that the customer 6b0a1711-4773-41eb-ae33-e624b152b409-1 00:00:29.526 --> 00:00:32.632 journeys have complexified a lot. So there are a lot of touch 6b0a1711-4773-41eb-ae33-e624b152b409-2 00:00:32.632 --> 00:00:35.889 points. Can you tell us a little bit how you stitch it together? 6b0a1711-4773-41eb-ae33-e624b152b409-3 00:00:35.889 --> 00:00:36.140 Sure. 307c2e49-69ab-473e-a596-f21094890da8-0 00:00:37.470 --> 00:00:41.330 When we when we talk to our consumers, we see 0fe818d8-8e0b-4879-a517-7a73e53c7ef2-0 00:00:42.030 --> 00:00:44.930 consumers are looking for inspiration in their shopping 0fe818d8-8e0b-4879-a517-7a73e53c7ef2-1 00:00:44.930 --> 00:00:45.500 journey. So fe513b8b-522d-433f-aaaa-31f27f5591e9-0 00:00:46.270 --> 00:00:51.438 what we do is we use data and insights about how consumers fe513b8b-522d-433f-aaaa-31f27f5591e9-1 00:00:51.438 --> 00:00:53.190 interact on Zalando. 5b038c6d-4fe0-48f8-80e6-7fba12f1b229-0 00:00:54.310 --> 00:00:59.694 To be able to expand, you build on that and say, OK, who are the 5b038c6d-4fe0-48f8-80e6-7fba12f1b229-1 00:00:59.694 --> 00:01:01.600 users brands can reach? 9755dc8d-05c4-47a3-9215-3eed863f1e96-0 00:01:02.930 --> 00:01:06.939 And that can mean through the various social media channels 9755dc8d-05c4-47a3-9215-3eed863f1e96-1 00:01:06.939 --> 00:01:11.150 and one, brands can tell their stories themselves, but also we 9755dc8d-05c4-47a3-9215-3eed863f1e96-2 00:01:11.150 --> 00:01:15.160 enable who which influences brands can actually engage with 9755dc8d-05c4-47a3-9215-3eed863f1e96-3 00:01:15.160 --> 00:01:19.437 so that they can actually make their stories more authentic and 9755dc8d-05c4-47a3-9215-3eed863f1e96-4 00:01:19.437 --> 00:01:23.514 so they can authenticate their brands as well. And one build 9755dc8d-05c4-47a3-9215-3eed863f1e96-5 00:01:23.514 --> 00:01:27.658 their brand awareness in those social media channels, but not 9755dc8d-05c4-47a3-9215-3eed863f1e96-6 00:01:27.658 --> 00:01:31.935 in there, but actually drive the customers back into Zalando to 9755dc8d-05c4-47a3-9215-3eed863f1e96-7 00:01:31.935 --> 00:01:33.740 re-engage them and to drive af78003f-99a9-413d-b102-2ee403261aee-0 00:01:33.810 --> 00:01:37.593 purchase as well. And again, that's a loop of you learn af78003f-99a9-413d-b102-2ee403261aee-1 00:01:37.593 --> 00:01:41.040 insights, you do it. And when brands do this well, 0a5f0f4d-ef91-4e89-b57c-ca5685108e44-0 00:01:42.120 --> 00:01:44.822 we've actually seen brands who achieved what we call as 0a5f0f4d-ef91-4e89-b57c-ca5685108e44-1 00:01:44.822 --> 00:01:45.740 cultural relevance, 25e32495-62ab-48dd-a3b2-65a57781579e-0 00:01:46.420 --> 00:01:49.979 where when they do achieve cultural relevance, where the 25e32495-62ab-48dd-a3b2-65a57781579e-1 00:01:49.979 --> 00:01:51.790 right kind of users purchase, f9d28d78-0a5e-4536-8e4e-560af4e8a114-0 00:01:52.630 --> 00:01:55.980 they've achieved price leadership. What this means is f9d28d78-0a5e-4536-8e4e-560af4e8a114-1 00:01:55.980 --> 00:01:59.826 they break through the glass ceiling where they are no longer f9d28d78-0a5e-4536-8e4e-560af4e8a114-2 00:01:59.826 --> 00:02:02.060 compared with their peers on price. c7c940a2-600f-4164-bb08-603aa2e8660f-0 00:02:03.490 --> 00:02:07.454 You're one of the most advanced fashion players in the industry. c7c940a2-600f-4164-bb08-603aa2e8660f-1 00:02:07.454 --> 00:02:11.296 You're also a pure player. You are sitting on a lot of data, a c7c940a2-600f-4164-bb08-603aa2e8660f-2 00:02:11.296 --> 00:02:14.894 lot of insights. How do you curate those data to make them c7c940a2-600f-4164-bb08-603aa2e8660f-3 00:02:14.894 --> 00:02:16.480 actionable for the brands? b5427916-4b74-4ae0-ab3b-a089faa7321f-0 00:02:18.020 --> 00:02:21.860 It's a good question because our brands are asking the same b5427916-4b74-4ae0-ab3b-a089faa7321f-1 00:02:21.860 --> 00:02:25.380 question on, hey, how am I performing on the platform? 021c5b7b-37c7-46cc-b490-7d7a2edbc857-0 00:02:26.930 --> 00:02:29.680 And I'm investing into marketing, how does it 021c5b7b-37c7-46cc-b490-7d7a2edbc857-1 00:02:29.680 --> 00:02:33.147 contribute to my growth of the brand? And you know, we're 021c5b7b-37c7-46cc-b490-7d7a2edbc857-2 00:02:33.147 --> 00:02:36.615 analyzing all this data and we built a product called the 021c5b7b-37c7-46cc-b490-7d7a2edbc857-3 00:02:36.615 --> 00:02:38.110 customer journey compass. 43fde03d-f528-4c49-9945-091eef2070a5-0 00:02:39.370 --> 00:02:43.341 The customer journey compass does three things. One, it 43fde03d-f528-4c49-9945-091eef2070a5-1 00:02:43.341 --> 00:02:47.454 provides data on how many customers are engaging or aware 43fde03d-f528-4c49-9945-091eef2070a5-2 00:02:47.454 --> 00:02:51.851 of the brand or engaging with the brand and who have actually 43fde03d-f528-4c49-9945-091eef2070a5-3 00:02:51.851 --> 00:02:52.490 purchased 0ee9f250-91f5-4bb9-b237-2d7142f27e63-0 00:02:53.400 --> 00:02:57.330 along with the audience penetration of other brands 91672d2b-fa36-4bd2-a579-9fa6ae329d23-0 00:02:58.200 --> 00:03:00.680 overall in the platform as well as in the categories. 96dee18b-7f9f-4d04-b3d5-d6f95f0d2ae2-0 00:03:01.540 --> 00:03:05.312 Now two, it also helps compare against their peers. How, how 96dee18b-7f9f-4d04-b3d5-d6f95f0d2ae2-1 00:03:05.312 --> 00:03:09.269 does that, the penetration and their scores, compare with their 96dee18b-7f9f-4d04-b3d5-d6f95f0d2ae2-2 00:03:09.269 --> 00:03:10.630 peers and what doing. f4912490-c2d0-450d-901d-f986f2be1c0c-0 00:03:11.280 --> 00:03:12.110 And third, 2c413c2d-0e41-4215-80c4-7d0a085b94fb-0 00:03:12.940 --> 00:03:15.930 in addition to doing that, it gives specific audience 2c413c2d-0e41-4215-80c4-7d0a085b94fb-1 00:03:15.930 --> 00:03:19.529 segments, which says, OK, now if you want to increase engagement 2c413c2d-0e41-4215-80c4-7d0a085b94fb-2 00:03:19.529 --> 00:03:22.686 or you want to increase purchase or you want to increase 2c413c2d-0e41-4215-80c4-7d0a085b94fb-3 00:03:22.686 --> 00:03:23.240 awareness, e4afcd9b-5466-4fa8-b03c-6d9a8f3c1f74-0 00:03:24.670 --> 00:03:28.185 Based on the goal, the audience that will most likely engage and e4afcd9b-5466-4fa8-b03c-6d9a8f3c1f74-1 00:03:28.185 --> 00:03:31.647 it will drive the highest value for the brand. And we give that e4afcd9b-5466-4fa8-b03c-6d9a8f3c1f74-2 00:03:31.647 --> 00:03:35.055 to the brand as well. So these are three things that you know, e4afcd9b-5466-4fa8-b03c-6d9a8f3c1f74-3 00:03:35.055 --> 00:03:38.301 the customer journey compass provides and we've seen brands e4afcd9b-5466-4fa8-b03c-6d9a8f3c1f74-4 00:03:38.301 --> 00:03:41.763 really engaging with this and it changes our approach from, or e4afcd9b-5466-4fa8-b03c-6d9a8f3c1f74-5 00:03:41.763 --> 00:03:45.333 our whole marketing. It puts the customer the front and center of e4afcd9b-5466-4fa8-b03c-6d9a8f3c1f74-6 00:03:45.333 --> 00:03:48.200 marketing and we call it customer centric marketing, 95b5142e-bbfd-43b7-a316-cec8bf1b2eb9-0 00:03:49.430 --> 00:03:53.709 Super exciting. Dinesh, you've been in the AdTech industry for 95b5142e-bbfd-43b7-a316-cec8bf1b2eb9-1 00:03:53.709 --> 00:03:57.717 very many years. Can you tell us, what do you think AI has 95b5142e-bbfd-43b7-a316-cec8bf1b2eb9-2 00:03:57.717 --> 00:04:01.724 changed and what are you using at the moment at Zalando in 95b5142e-bbfd-43b7-a316-cec8bf1b2eb9-3 00:04:01.724 --> 00:04:02.540 terms of AI? b4e93692-923c-48a5-a4ce-ba3abea35493-0 00:04:03.520 --> 00:04:07.671 Now, we really believe AI is going to change the marketing b4e93692-923c-48a5-a4ce-ba3abea35493-1 00:04:07.671 --> 00:04:12.103 landscape. It's already doing and we know it is already making b4e93692-923c-48a5-a4ce-ba3abea35493-2 00:04:12.103 --> 00:04:16.536 the creative production a lot more efficient. And we've seen a b4e93692-923c-48a5-a4ce-ba3abea35493-3 00:04:16.536 --> 00:04:19.210 lot of examples here today at Cannes. d08144fa-60a3-42ed-ad36-d10e97518940-0 00:04:19.990 --> 00:04:24.223 And where we see in the whole marketing journey, because d08144fa-60a3-42ed-ad36-d10e97518940-1 00:04:24.223 --> 00:04:27.120 brands have a lot of engaging content. bd994fda-c08e-416f-a065-d5ef6f0d1015-0 00:04:28.160 --> 00:04:30.576 We are visualizing an experience where brands bring their bd994fda-c08e-416f-a065-d5ef6f0d1015-1 00:04:30.576 --> 00:04:30.910 content, 8f9c1cb3-94d5-4616-af1a-99d6dbc235ea-0 00:04:31.810 --> 00:04:38.594 And our platform is able to create unique ad experiences at 8f9c1cb3-94d5-4616-af1a-99d6dbc235ea-1 00:04:38.594 --> 00:04:39.160 scale 5b3eaf11-8454-4390-8ef6-dd00a7e30031-0 00:04:39.960 --> 00:04:43.497 Based on the users or how they would engage. So earlier it used 5b3eaf11-8454-4390-8ef6-dd00a7e30031-1 00:04:43.497 --> 00:04:46.870 to take a long time for these brands to create one creative. d9ebb248-a324-4df3-8a17-a7b97362cc81-0 00:04:47.560 --> 00:04:50.320 Now at scale, you're saying, OK, we can create 10 different d9ebb248-a324-4df3-8a17-a7b97362cc81-1 00:04:50.320 --> 00:04:53.035 creatives. Because we know audiences engage with different d9ebb248-a324-4df3-8a17-a7b97362cc81-2 00:04:53.035 --> 00:04:55.290 kinds of creatives, they can actually create it. 90a4b925-4e24-439c-91c6-46550cbbafb0-0 00:04:55.930 --> 00:04:59.732 And then, we will build it on top of our personalization 90a4b925-4e24-439c-91c6-46550cbbafb0-1 00:04:59.732 --> 00:05:03.802 stack, where we already match the right content to the right 90a4b925-4e24-439c-91c6-46550cbbafb0-2 00:05:03.802 --> 00:05:08.138 users thereby driving a lot more engagement. So we see marketing 90a4b925-4e24-439c-91c6-46550cbbafb0-3 00:05:08.138 --> 00:05:12.274 our investments into marketing driving a lot more efficiency. 90a4b925-4e24-439c-91c6-46550cbbafb0-4 00:05:12.274 --> 00:05:15.210 Thanks so much Dinesh for joining us today. ffe1d77b-9c72-49be-b3ba-b2151df3f1d5-0 00:05:15.880 --> 00:05:17.220 Thank you. Pleasure. 317b0609-a8c8-42e6-af35-8be5cf7c4f67-0 00:05:18.200 --> 00:05:21.730