WEBVTT 1 00:00:00.155 --> 00:00:02.245 When we have a client with a certain product, 2 00:00:02.335 --> 00:00:04.965 which is sold in retail spaces, we want 3 00:00:04.965 --> 00:00:08.525 to find users which have a proper interest in buying 4 00:00:08.805 --> 00:00:11.725 products of this category in the shop themselves. 5 00:00:16.905 --> 00:00:19.925 We can activate those direct segments and we can find 6 00:00:19.985 --> 00:00:23.525 and identify users which have previously shown interest in 7 00:00:23.525 --> 00:00:24.685 buying this product, and 8 00:00:24.685 --> 00:00:27.045 therefore offer an immediate value to the client. 9 00:00:27.465 --> 00:00:31.365 For clients, uh, which don't sell a product in retail shops, 10 00:00:31.705 --> 00:00:34.765 we usually take a more abstract route to find a, um, 11 00:00:34.915 --> 00:00:36.645 fitting target group for their campaign. 12 00:00:36.985 --> 00:00:40.085 We, um, evaluate the clients or the brands 13 00:00:40.145 --> 00:00:42.925 and the campaign's target, and then we, um, try 14 00:00:42.925 --> 00:00:45.005 and find retail data segments 15 00:00:45.035 --> 00:00:48.885 that fit this target group in a more abstract way. 16 00:00:49.185 --> 00:00:51.405 One recent example from, uh, my work is 17 00:00:51.405 --> 00:00:54.645 that a client offering a sustainability offering, 18 00:00:54.815 --> 00:00:57.165 which is not sold in a retail shop, 19 00:00:57.265 --> 00:01:00.765 and one way of reaching the target for us was to activate, 20 00:01:00.825 --> 00:01:03.765 um, retail data segments for users 21 00:01:04.225 --> 00:01:06.885 who have an actual interest in buying sustainability 22 00:01:07.045 --> 00:01:08.525 products in retail shops. 23 00:01:08.555 --> 00:01:12.205 That allows us to still reach a relevant, uh, audience, 24 00:01:12.745 --> 00:01:16.565 but just being able to execute a broader budget throughout 25 00:01:16.565 --> 00:01:17.725 the campaign's runtime.