WEBVTT 61a60597-dfeb-4676-a097-fe8bb5548733-0 00:00:00.040 --> 00:00:02.745 Aimee and Mark, thank you so much for being here at this 61a60597-dfeb-4676-a097-fe8bb5548733-1 00:00:02.745 --> 00:00:03.600 year's Dreamforce. 22f6e789-5873-49b9-bcb9-0374666d90bc-0 00:00:03.640 --> 00:00:05.400 And this is a question for both of you. f9a857a9-2dac-4900-9c41-07666f689d22-0 00:00:05.400 --> 00:00:08.360 Knowing how hard it can be to deliver these personalized f9a857a9-2dac-4900-9c41-07666f689d22-1 00:00:08.360 --> 00:00:11.320 experiences that customers really enjoy, what would your f9a857a9-2dac-4900-9c41-07666f689d22-2 00:00:11.320 --> 00:00:11.840 advice be? 76ffa7c1-2e2c-4216-b65c-47abae3c680a-0 00:00:12.360 --> 00:00:13.120 Keep it simple. c90ec114-a820-46ba-a477-e7c91fa18487-0 00:00:14.720 --> 00:00:18.019 Keep it centered around what really drives the customer's c90ec114-a820-46ba-a477-e7c91fa18487-1 00:00:18.019 --> 00:00:19.840 behavior that you want to drive. cfd8dacc-509e-461b-973c-d718f7670511-0 00:00:21.720 --> 00:00:23.240 Be cool, not creepy. 7401d141-bdf8-4199-b04f-8641b0f2e7cc-0 00:00:23.880 --> 00:00:27.784 Like, if you're going to ask a question, do something with the 7401d141-bdf8-4199-b04f-8641b0f2e7cc-1 00:00:27.784 --> 00:00:30.760 answer and have it be expected, not unexpected. 553e2d38-f950-413f-905e-52384cb7ab19-0 00:00:31.840 --> 00:00:33.080 Those are really good tenants. 7337ac02-107a-44d5-b3a1-08e608d1a726-0 00:00:33.080 --> 00:00:35.200 I think the other piece is just get started. d1de7102-8a3e-4c05-8195-e8291d38f22a-0 00:00:36.200 --> 00:00:37.720 People sometimes. 551fc064-14bf-4171-a507-78154b532fcb-0 00:00:37.880 --> 00:00:40.823 I don't think any organization lacks an idea for how to make 551fc064-14bf-4171-a507-78154b532fcb-1 00:00:40.823 --> 00:00:42.560 their experience more personalized. b0519d9a-aa22-4105-8aa4-f3f897da394b-0 00:00:42.560 --> 00:00:46.014 If you get people in a room, they'll come up with five ideas b0519d9a-aa22-4105-8aa4-f3f897da394b-1 00:00:46.014 --> 00:00:48.280 off the bat of what they could do next. d3d3f8c5-7bbe-4426-9c0a-21c62deb92ca-0 00:00:48.280 --> 00:00:51.893 But then there's paralysis around bringing the people in d3d3f8c5-7bbe-4426-9c0a-21c62deb92ca-1 00:00:51.893 --> 00:00:55.000 the room together to actually get anything done. 84295997-6976-4cb1-8117-1fa9ebe13be5-0 00:00:55.520 --> 00:00:57.520 So I think a lot of it goes back to that. 866e27ba-cc2b-48fa-8b37-f77881f31d8f-0 00:00:59.000 --> 00:01:02.620 I also, in my book layout five promises you've got to deliver 866e27ba-cc2b-48fa-8b37-f77881f31d8f-1 00:01:02.620 --> 00:01:04.840 to the customer when you personalize. f90ef67a-df6c-4cc7-9853-1a87054ab46a-0 00:01:04.840 --> 00:01:06.880 And I think the last one is the most important. 52f2dbfb-a040-49a4-ad40-5991417eb4d8-0 00:01:06.880 --> 00:01:10.616 So I'll hit on that. Delight Me, which is about just making my 52f2dbfb-a040-49a4-ad40-5991417eb4d8-1 00:01:10.616 --> 00:01:14.293 experience a little bit better each time you connect with me, 52f2dbfb-a040-49a4-ad40-5991417eb4d8-2 00:01:14.293 --> 00:01:18.089 which comes back to testing and learning, shrinking the time it 52f2dbfb-a040-49a4-ad40-5991417eb4d8-3 00:01:18.089 --> 00:01:20.640 takes for you to implement those insights. 08327f65-8ec2-4223-9c3e-297eac7b5075-0 00:01:20.640 --> 00:01:25.050 So I find most organizations are still taking 12 to 16 weeks to 08327f65-8ec2-4223-9c3e-297eac7b5075-1 00:01:25.050 --> 00:01:28.910 turn around and make a campaign better or making make a 08327f65-8ec2-4223-9c3e-297eac7b5075-2 00:01:28.910 --> 00:01:30.840 marketing experience better. 43423161-4a0e-49d7-a464-83aaf8ce0fd7-0 00:01:31.040 --> 00:01:32.360 And that's just way too long. 720da1bd-756c-4e3b-aec3-25c2f762bbfb-0 00:01:32.360 --> 00:01:35.883 How do you make it better every single week, which means 720da1bd-756c-4e3b-aec3-25c2f762bbfb-1 00:01:35.883 --> 00:01:39.716 reengineering your processes, measuring things in a much more 720da1bd-756c-4e3b-aec3-25c2f762bbfb-2 00:01:39.716 --> 00:01:43.363 automated fast fashion, and equipping the teams with those 720da1bd-756c-4e3b-aec3-25c2f762bbfb-3 00:01:43.363 --> 00:01:43.920 insights. 04a82d03-e2bd-4055-8ba9-beebd5f8bf40-0 00:01:44.520 --> 00:01:46.560 What have you been seeing lately, Aimee? 194bc3ae-88a3-4a9b-8e4a-8ea0c3e605f2-0 00:01:47.480 --> 00:01:50.720 I guess I would add to that the surprise and delight factor. 1624cad8-3d04-49ca-9096-78c0614e1f6e-0 00:01:50.720 --> 00:01:53.920 I think it's hard to measure, but it makes a difference. b118d7f0-958b-4b53-9697-20e667b653de-0 00:01:53.920 --> 00:01:57.249 If you find that one reason why they want to come to your store b118d7f0-958b-4b53-9697-20e667b653de-1 00:01:57.249 --> 00:02:00.578 or your retail or interact with you or your employees, that one b118d7f0-958b-4b53-9697-20e667b653de-2 00:02:00.578 --> 00:02:02.920 unique thing is going to bring them back in. 3e7dc173-99f5-4d5b-a87b-e07753e84916-0 00:02:03.240 --> 00:02:03.480 Yes. 2b616c1e-5e6a-4474-92c7-2bdfb813edf4-0 00:02:03.480 --> 00:02:06.080 So how do you also unlock what that could be? c0112aa9-1ea6-4fe0-97f4-61750095e858-0 00:02:06.080 --> 00:02:10.170 Not just points, because points is kind of interesting and these c0112aa9-1ea6-4fe0-97f4-61750095e858-1 00:02:10.170 --> 00:02:14.010 go beyond and what's that one unique thing for your brand in c0112aa9-1ea6-4fe0-97f4-61750095e858-2 00:02:14.010 --> 00:02:17.786 your category that actually ties to your brand promise, why c0112aa9-1ea6-4fe0-97f4-61750095e858-3 00:02:17.786 --> 00:02:19.360 people choose your brand? f5adf3c9-a60c-469b-8ec7-bb6121965207-0 00:02:19.880 --> 00:02:23.360 I think I'd also add how do you engage the entire organization? c63f0b9d-de7f-4e1d-9e79-1cb5e8979ba8-0 00:02:23.600 --> 00:02:26.339 So if the entire organization understands what makes the c63f0b9d-de7f-4e1d-9e79-1cb5e8979ba8-1 00:02:26.339 --> 00:02:28.982 customer tick, they're all interacting the customer at c63f0b9d-de7f-4e1d-9e79-1cb5e8979ba8-2 00:02:28.982 --> 00:02:29.800 different places. 0de16246-2c02-42ec-a9f7-d18cc939fc68-0 00:02:30.000 --> 00:02:32.358 Your finance team might be setting pricing and they might 0de16246-2c02-42ec-a9f7-d18cc939fc68-1 00:02:32.358 --> 00:02:34.717 have to understand why a customer does or doesn't come to 0de16246-2c02-42ec-a9f7-d18cc939fc68-2 00:02:34.717 --> 00:02:34.880 you. 0c69d7b5-da57-445d-a22a-d1907dcf1bb0-0 00:02:35.040 --> 00:02:37.081 The operations team is interacting with your customer 0c69d7b5-da57-445d-a22a-d1907dcf1bb0-1 00:02:37.081 --> 00:02:37.800 in a different way. 6b169d71-52a4-42d9-a4b5-a7a69e28ed9f-0 00:02:37.960 --> 00:02:40.920 If you engage all of these different people, you have so 6b169d71-52a4-42d9-a4b5-a7a69e28ed9f-1 00:02:40.920 --> 00:02:43.985 many different ideas that could come out solving different 6b169d71-52a4-42d9-a4b5-a7a69e28ed9f-2 00:02:43.985 --> 00:02:44.920 customer problems. 1b274a20-bc95-49f6-a675-8bdba6ba5ac8-0 00:02:44.920 --> 00:02:47.844 And to your point, how you operationalize those then to 1b274a20-bc95-49f6-a675-8bdba6ba5ac8-1 00:02:47.844 --> 00:02:50.978 create a unique ecosystem where you could take advantage of 1b274a20-bc95-49f6-a675-8bdba6ba5ac8-2 00:02:50.978 --> 00:02:51.240 that. 27114cc2-7d9e-4321-94d5-fbd6563c9bd1-0 00:02:51.440 --> 00:02:54.421 I remember when you drew the customer flywheel on your 27114cc2-7d9e-4321-94d5-fbd6563c9bd1-1 00:02:54.421 --> 00:02:57.348 whiteboard when you were launching personalization at 27114cc2-7d9e-4321-94d5-fbd6563c9bd1-2 00:02:57.348 --> 00:03:00.872 Starbucks that you had everyone in your office and, and engaging 27114cc2-7d9e-4321-94d5-fbd6563c9bd1-3 00:03:00.872 --> 00:03:03.799 the CEO, the CIO, the various stakeholders around it. 27ae72d7-f9f5-4330-bd04-4ca83da020df-0 00:03:03.800 --> 00:03:06.962 And I think that visual connection of, ok, this is the 27ae72d7-f9f5-4330-bd04-4ca83da020df-1 00:03:06.962 --> 00:03:08.400 big dream we're building. 527d38e6-87d2-47b4-9535-a3f71234c9ea-0 00:03:08.760 --> 00:03:11.358 And yes, it's going to be a hard road and it's going to take 527d38e6-87d2-47b4-9535-a3f71234c9ea-1 00:03:11.358 --> 00:03:14.000 dollars and it's going to be a phased approach really helped. 48cf21a9-88b6-48df-bbd2-82ac92ee5278-0 00:03:14.440 --> 00:03:17.667 It was a hard journey, but that alignment at the front was 48cf21a9-88b6-48df-bbd2-82ac92ee5278-1 00:03:17.667 --> 00:03:18.160 critical. becedefb-35e4-4cf5-aedd-33182c8640af-0 00:03:18.160 --> 00:03:19.960 Mark, Aimee, thank you so much for being here. 34742c77-e13b-440e-b1e5-6f8ab1454adc-0 00:03:20.400 --> 00:03:21.360 Thank you for having us.