WEBVTT 031b2b67-45cf-42ef-8955-33626bf3b159-0 00:00:00.200 --> 00:00:03.778 In many ways, products are dead, and customized experience are the future 031b2b67-45cf-42ef-8955-33626bf3b159-1 00:00:03.778 --> 00:00:04.600 of all companies. fe68ac1c-fa21-4677-a274-29e517527578-0 00:00:05.360 --> 00:00:09.280 We're joined by Stephanie from Microsoft and Jean- Manuel from BCG, 25284a28-4cbd-46de-b832-936a366b9f46-0 00:00:09.320 --> 00:00:10.960 welcome. Stephanie, 59b93455-5a2c-4f99-b615-b80f69115117-0 00:00:10.960 --> 00:00:15.960 tell us how is AI already changing the customer experience with Microsoft? 3bbecd79-01ae-4a55-99ef-dcb2b1db3fc1-0 00:00:15.960 --> 00:00:18.160 How is it changing the way you deal with customers? a39c27d7-312e-4ab7-809c-b22f8bd725a1-0 00:00:18.760 --> 00:00:22.880 It is letting us personalize things so much more than ever before. ac566e71-f19e-4177-b3c9-8ed86b0a09d6-0 00:00:23.160 --> 00:00:27.468 When I think about a company like Microsoft, just consider customers, ac566e71-f19e-4177-b3c9-8ed86b0a09d6-1 00:00:27.468 --> 00:00:31.223 they range from consumers to businesses for us, and with AI, ac566e71-f19e-4177-b3c9-8ed86b0a09d6-2 00:00:31.223 --> 00:00:35.040 we can bring all of their data together to serve them better. 064eda30-210b-4781-9225-9431acd41203-0 00:00:35.400 --> 00:00:37.360 So give us a few examples of how you're doing it. 6c6159a4-a7c4-498a-8412-b0b65934425c-0 00:00:37.600 --> 00:00:37.920 Yeah, 9d7e49a4-1325-4973-8b19-a8cb4e91f7d3-0 00:00:37.920 --> 00:00:43.145 so everything ranging from how do we think about the segments of our customers, 9d7e49a4-1325-4973-8b19-a8cb4e91f7d3-1 00:00:43.145 --> 00:00:48.240 and how do we use AI to help us get smarter and more intelligent there to how 9d7e49a4-1325-4973-8b19-a8cb4e91f7d3-2 00:00:48.240 --> 00:00:53.400 we treat them on a website when they arrive and start to look for information. 7daa3110-6dce-498f-b712-c5b46978fb65-0 00:00:54.200 --> 00:00:56.564 Jean-Manuel, just give us a sense of the potential for 7daa3110-6dce-498f-b712-c5b46978fb65-1 00:00:56.564 --> 00:00:58.800 this and the sort of efficiencies it might lead to. 50263b6f-4d13-48b1-9723-def261de8fdc-0 00:00:59.000 --> 00:00:59.480 That's right. db900701-03b3-4ab5-bb70-ff3a8911b447-0 00:00:59.480 --> 00:01:01.400 The potential is enormous at this stage. e72e1aeb-c961-4b33-9407-24acd7673931-0 00:01:02.040 --> 00:01:07.681 Imagine that now we're going to have the ability to have conversations with e72e1aeb-c961-4b33-9407-24acd7673931-1 00:01:07.681 --> 00:01:09.760 clients with virtual agents. 607e7283-cc33-4834-93f9-0b03467b47d2-0 00:01:10.200 --> 00:01:14.363 That means if clients want to, they can share their whole story for an 607e7283-cc33-4834-93f9-0b03467b47d2-1 00:01:14.363 --> 00:01:15.360 hour or even two, 044e31d1-619e-4d62-9e6b-be9847514c52-0 00:01:15.360 --> 00:01:17.480 where virtual agents will record that. f45d9218-bd53-4b87-9648-e631e388fcaa-0 00:01:17.720 --> 00:01:20.040 That means the company can know so much more. 2aee558b-2345-4a53-a6a4-ebc236686c13-0 00:01:20.360 --> 00:01:23.890 And while it was anonymized and data issues were there, here, 2aee558b-2345-4a53-a6a4-ebc236686c13-1 00:01:23.890 --> 00:01:26.681 the customer chooses to share his stories. Then, 2aee558b-2345-4a53-a6a4-ebc236686c13-2 00:01:26.681 --> 00:01:31.179 it's the role of the company to take that information and be able to customize 2aee558b-2345-4a53-a6a4-ebc236686c13-3 00:01:31.179 --> 00:01:35.280 completely the experience that they will have with their own customers. ae30ab70-849c-4dd2-8a5a-014c4cf89065-0 00:01:35.440 --> 00:01:39.050 In many ways, products are dead, and customized experience are the future ae30ab70-849c-4dd2-8a5a-014c4cf89065-1 00:01:39.050 --> 00:01:39.880 of all companies. f56b0ecb-d938-4bfc-804e-09d9a2c1a433-0 00:01:40.040 --> 00:01:41.000 I mean, it's really interesting. 1d787c67-2abc-4246-9f1a-980c07a12bdd-0 00:01:41.000 --> 00:01:43.462 as you say, there's a transparency there that hasn't 1d787c67-2abc-4246-9f1a-980c07a12bdd-1 00:01:43.462 --> 00:01:44.160 existed before. 995883be-e0c8-4450-bad3-ff1c89e25621-0 00:01:44.160 --> 00:01:47.202 Companies have worried about clients worrying about the data that is held on 995883be-e0c8-4450-bad3-ff1c89e25621-1 00:01:47.202 --> 00:01:47.400 them. a2858126-c0f8-4a94-be98-99f8da5a76d7-0 00:01:47.480 --> 00:01:49.440 This is much more transparent. e42a80ba-b08c-4096-8ade-6a4ea08f76de-0 00:01:49.680 --> 00:01:56.372 I love this for a B2B company, especially. Think about it: B2B companies really try e42a80ba-b08c-4096-8ade-6a4ea08f76de-1 00:01:56.372 --> 00:01:59.400 hard to build solutions for customers. 41ae0eec-6fd5-4671-aed9-0a2523ca4942-0 00:01:59.680 --> 00:02:04.120 If we do what we're talking about here, they don't have to build solutions. ce249f23-b28d-4e6a-a1fd-e739ebfda39f-0 00:02:04.320 --> 00:02:08.080 They ultimately end up at the solution by knowing the customer better. 230f7298-4be0-4282-937c-5fc4460b3f38-0 00:02:08.880 --> 00:02:10.440 So it's a very specialized experience. 0e3d1cc1-47e9-40a8-befc-f054360f1e1e-0 00:02:10.440 --> 00:02:13.160 It could be very specialized, and I think we . . . 0e3d1cc1-47e9-40a8-befc-f054360f1e1e-1 00:02:13.160 --> 00:02:15.400 AI will enhance the relationships we have. b7451a26-865d-4467-930b-c3a802f0656b-0 00:02:15.560 --> 00:02:19.195 So think about a salesperson, plays a really important role in the b7451a26-865d-4467-930b-c3a802f0656b-1 00:02:19.195 --> 00:02:22.126 relationship, but you can never have a discussion for b7451a26-865d-4467-930b-c3a802f0656b-2 00:02:22.126 --> 00:02:24.080 two hours with a salesperson, right? 75b8a30f-ecad-4425-ba02-b0b47fe0a09b-0 00:02:24.240 --> 00:02:24.840 Or more. b25754fa-2347-4697-87c8-0e7632451b62-0 00:02:25.440 --> 00:02:28.536 Now with an AI, client can have a conversation asking b25754fa-2347-4697-87c8-0e7632451b62-1 00:02:28.536 --> 00:02:32.320 technical questions to an AI for an hour, two hours, three hours. a05a7883-05df-47d1-8cba-12f49ed28e0b-0 00:02:32.680 --> 00:02:36.678 And if the company can guarantee that the AI never hallucinates, a05a7883-05df-47d1-8cba-12f49ed28e0b-1 00:02:36.678 --> 00:02:41.477 suddenly it's a source of info that will both share with the company what the a05a7883-05df-47d1-8cba-12f49ed28e0b-2 00:02:41.477 --> 00:02:45.414 customers really needs, but also help the client trust that the a05a7883-05df-47d1-8cba-12f49ed28e0b-3 00:02:45.414 --> 00:02:49.105 answers to their questions are very genuine and, therefore, a05a7883-05df-47d1-8cba-12f49ed28e0b-4 00:02:49.105 --> 00:02:51.320 will make it easier for them to buy. 194bc39a-5c19-4930-a32e-adddccb4b367-0 00:02:51.960 --> 00:02:52.200 Yeah. c0b59f3a-874a-4ae7-9a14-033a2d62c3cc-0 00:02:52.200 --> 00:02:56.092 And as a concrete example of that for Microsoft Azure, c0b59f3a-874a-4ae7-9a14-033a2d62c3cc-1 00:02:56.092 --> 00:03:00.196 which is our cloud service, we find that we've, you know, c0b59f3a-874a-4ae7-9a14-033a2d62c3cc-2 00:03:00.196 --> 00:03:04.160 we've put an AI agent on the website to help customers. 4318caaf-606b-4d19-9387-b238a5a8f596-0 00:03:04.160 --> 00:03:07.480 And initially we thought it was just going to help them with information. dfe0b030-fba2-4fee-a794-26100120afd8-0 00:03:07.880 --> 00:03:12.389 And now what we see is the customers who engaged with that agent, dfe0b030-fba2-4fee-a794-26100120afd8-1 00:03:12.389 --> 00:03:17.240 they are more likely to buy Microsoft Azure than other customers, yes. e65c60d4-3349-4ba0-96ea-a0c6f34573b2-0 00:03:17.240 --> 00:03:20.344 And is that because of trust or the amount of time they're spending talking e65c60d4-3349-4ba0-96ea-a0c6f34573b2-1 00:03:20.344 --> 00:03:21.120 through the detail? 78427614-08d6-49d1-b4fe-3525007df3ee-0 00:03:21.240 --> 00:03:24.875 I think they trust Microsoft more, and they've gotten the information that 78427614-08d6-49d1-b4fe-3525007df3ee-1 00:03:24.875 --> 00:03:25.360 they need, d064a430-4eff-4b57-8f83-6a96469070fc-0 00:03:25.360 --> 00:03:27.560 so they are deliberate in their desire to buy it. b2a88533-0056-4c94-acbd-4259279c8702-0 00:03:27.560 --> 00:03:30.560 Well, having seen that success, where does this go? 687ffaaf-a15c-4ca5-927d-95a587a60395-0 00:03:30.560 --> 00:03:32.240 How much more do you think we're going . . . 0c5721c7-3172-4a4a-867b-fdbd1045fab4-0 00:03:32.240 --> 00:03:34.591 you know, if we come back here, three years' time, 0c5721c7-3172-4a4a-867b-fdbd1045fab4-1 00:03:34.591 --> 00:03:37.588 how much will have changed in terms of how much you're using AI? 0c5721c7-3172-4a4a-867b-fdbd1045fab4-2 00:03:37.588 --> 00:03:38.880 From a marketing standpoint, 681dc394-3578-4304-99d6-5f7982a200eb-0 00:03:38.960 --> 00:03:42.010 I would love to as a customer comes on to, you know, 681dc394-3578-4304-99d6-5f7982a200eb-1 00:03:42.010 --> 00:03:46.845 any kind of an engagement with Microsoft, be able to pull up all of the information 681dc394-3578-4304-99d6-5f7982a200eb-2 00:03:46.845 --> 00:03:50.989 that I know about them and make a very personalized experience for that 681dc394-3578-4304-99d6-5f7982a200eb-3 00:03:50.989 --> 00:03:55.594 customer--whether they're exploring new things or they come and they, you know, 681dc394-3578-4304-99d6-5f7982a200eb-4 00:03:55.594 --> 00:03:58.760 really want to buy and bring them right over to sales. 9f78e1f4-5584-4169-818a-4f26ac1fbd76-0 00:03:58.760 --> 00:04:03.880 I just think the potential there to give the customer what they want is amazing. 5779f18f-a47f-457b-9ad4-739becfd6405-0 00:04:04.400 --> 00:04:08.130 And I believe on the sales side, you're going to have both channels, 5779f18f-a47f-457b-9ad4-739becfd6405-1 00:04:08.130 --> 00:04:12.401 the human channel and the virtual channel are going to be working in parallel, 5779f18f-a47f-457b-9ad4-739becfd6405-2 00:04:12.401 --> 00:04:16.294 and clients will have these discussions in parallel that will help them 5779f18f-a47f-457b-9ad4-739becfd6405-3 00:04:16.294 --> 00:04:20.727 understand better the potential solution they have and therefore buy with shorter 5779f18f-a47f-457b-9ad4-739becfd6405-4 00:04:20.727 --> 00:04:24.080 product- selling cycle actually, so. Probably transformative. 499e8c81-edf7-4c59-8848-900b681df47b-0 00:04:24.240 --> 00:04:26.560 It will be. Stephanie, dcd09c19-31c2-41e8-ad1a-e5e9359c30e7-0 00:04:26.600 --> 00:04:28.840 Jean-Manuel, thanks very much for joining us. 6657c400-b3ea-4371-bba1-9258cb7c7fda-0 00:04:28.960 --> 00:04:29.520 Thank you very much. a8eea84a-9d01-4ed9-a843-a550e122a1d5-0 00:04:29.520 --> 00:04:30.120 Thank you very much.