WEBVTT 9e1f345e-226a-449b-936a-8213f9d03fc9-0 00:00:00.040 --> 00:00:01.960 Pasquale, thank you so much for joining us. a4256102-c7e5-463c-b092-574bd7e16999-0 00:00:01.960 --> 00:00:04.502 What are you noticing about customer experience at this a4256102-c7e5-463c-b092-574bd7e16999-1 00:00:04.502 --> 00:00:05.320 year's Dreamforce? d5049ba9-0cb2-4ae6-ad3a-f799a4a5d1f1-0 00:00:05.560 --> 00:00:08.357 What we're seeing is that the end customer's expectation for d5049ba9-0cb2-4ae6-ad3a-f799a4a5d1f1-1 00:00:08.357 --> 00:00:11.109 customer service just keeps increasing and getting more and d5049ba9-0cb2-4ae6-ad3a-f799a4a5d1f1-2 00:00:11.109 --> 00:00:12.440 more demanding, as it should. e55475ef-718a-4647-8948-0fe29a21a9ed-0 00:00:12.720 --> 00:00:15.207 And what we're seeing is the customers now need to adapt to e55475ef-718a-4647-8948-0fe29a21a9ed-1 00:00:15.207 --> 00:00:17.280 that and move quickly, especially as they look to e55475ef-718a-4647-8948-0fe29a21a9ed-2 00:00:17.280 --> 00:00:19.560 leverage things like artificial intelligence and GenAI 0708eaac-0562-4a96-b103-98e195f7288f-0 00:00:19.560 --> 00:00:22.400 to deliver outcomes for their customers that are both better, 0708eaac-0562-4a96-b103-98e195f7288f-1 00:00:22.400 --> 00:00:24.920 faster, and cheaper than anything they've done before. 76ce94aa-4b1b-478c-b653-a00cf112c62a-0 00:00:25.400 --> 00:00:28.389 And what is Amazon Connect and how is it problem-solving for 76ce94aa-4b1b-478c-b653-a00cf112c62a-1 00:00:28.389 --> 00:00:28.880 customers? a16446a0-05e5-4df4-b617-db189d2c657e-0 00:00:29.320 --> 00:00:32.375 Amazon Connect is AWS's Contact Center and so it allows a16446a0-05e5-4df4-b617-db189d2c657e-1 00:00:32.375 --> 00:00:35.485 customers to be able to interact directly with their end a16446a0-05e5-4df4-b617-db189d2c657e-2 00:00:35.485 --> 00:00:38.541 customers through whatever channel they want to deliver a16446a0-05e5-4df4-b617-db189d2c657e-3 00:00:38.541 --> 00:00:39.360 great outcomes. 0d785757-e865-4850-935a-d0371b98eaec-0 00:00:39.360 --> 00:00:42.525 And so if you look at something like wanting to be able to, say, 0d785757-e865-4850-935a-d0371b98eaec-1 00:00:42.525 --> 00:00:45.594 solve a problem or even solve a problem before a customer even 0d785757-e865-4850-935a-d0371b98eaec-2 00:00:45.594 --> 00:00:48.565 knows they're having it, this allows them to engage directly 0d785757-e865-4850-935a-d0371b98eaec-3 00:00:48.565 --> 00:00:51.146 with them proactively, deliver often AI and or agent 0d785757-e865-4850-935a-d0371b98eaec-4 00:00:51.146 --> 00:00:54.264 experiences, and then alleviate that issue for them before they 0d785757-e865-4850-935a-d0371b98eaec-5 00:00:54.264 --> 00:00:55.920 even know something's gone wrong. ebf77618-86f8-463b-b77b-2ef6cd68d753-0 00:00:56.400 --> 00:00:59.562 How do you see a strategic partner like BCG helping with ebf77618-86f8-463b-b77b-2ef6cd68d753-1 00:00:59.562 --> 00:00:59.840 this? 6809b834-116f-4921-bdde-b777d87ca779-0 00:01:00.360 --> 00:01:00.560 Yeah. ccbf8aa2-6c54-467a-bb7d-287d45e3bbd6-0 00:01:00.800 --> 00:01:03.444 The key thing with a partner like BCG is that you really go ccbf8aa2-6c54-467a-bb7d-287d45e3bbd6-1 00:01:03.444 --> 00:01:06.045 deep with the customer and understand their business needs ccbf8aa2-6c54-467a-bb7d-287d45e3bbd6-2 00:01:06.045 --> 00:01:08.690 and help them leverage the innovation that we deliver to be ccbf8aa2-6c54-467a-bb7d-287d45e3bbd6-3 00:01:08.690 --> 00:01:11.423 able to let them move quickly and to experiment and learn and ccbf8aa2-6c54-467a-bb7d-287d45e3bbd6-4 00:01:11.423 --> 00:01:14.288 then deliver great outcomes for their end customers in ways they ccbf8aa2-6c54-467a-bb7d-287d45e3bbd6-5 00:01:14.288 --> 00:01:15.920 wouldn't be able to do on their own. 28be9056-d151-4f79-a4b3-82e48c060549-0 00:01:16.120 --> 00:01:18.623 That expertise has been invaluable for so many customers 28be9056-d151-4f79-a4b3-82e48c060549-1 00:01:18.623 --> 00:01:20.600 to be able to really outsize their outcomes. 65db5ae0-68a6-4ca7-af63-ce2885886296-0 00:01:21.120 --> 00:01:21.960 Thank you so much. 162225e7-590f-4c71-ab42-2c7ff0e673d0-0 00:01:22.200 --> 00:01:22.600 Thank you.