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00:00Williams-Sonoma is, across all your brands, this is like one of the most canonically human experiences.
00:07You go into one of the stores, it's very personal.
00:09How did you think about recreating that experience using agents?
00:15Yeah, it's a great question, Madhav.
00:18Like you mentioned, let me just tell you a little bit about Olive first, just for context.
00:23So Olive is our Williams-Sonoma agent, and of course she can help with customer service issues,
00:28you know, simple ones, complex ones.
00:31But what's really exciting is that, you know, we've been able to sort of capture a lot of the essence
00:35of what the brand's about,
00:37which is helping with life moments, helping with entertaining, helping with planning, helping with cooking,
00:42helping with a lot of these, you know, like kind of life moments that center around what the brand is
00:47great at.
00:48And, you know, as we started to think about what does agentic AI look like for the Williams-Sonoma brand,
00:55you know, what we found and what was effective for us is that, you know,
00:59even though we were talking about AI, we didn't start with the AI.
01:03We actually didn't even start with the data.
01:05We started with the humans.
01:06We asked ourselves, what does the optimal human experience look like for these different scenarios?
01:14And I'm blessed to work at a company where I'm surrounded by experts in their space.
01:18We've got, you know, test kitchen chefs, we have merchants that understand entertaining.
01:24We've got interior designers with our furniture brands.
01:27We've got all these different experts.
01:29And before we even got into the AI, before we even got into the data, you know,
01:33I and my team just sort of sat down and just picked their brain.
01:36How do you do this?
01:37When a customer asks this question, how do you think about this?
01:40How do you think about different types of customers and personas?
01:44And that was just a data goldmine.
01:47And that's where a lot of the sort of light bulbs popped about, okay, this is what we can do,
01:52is try to figure out how do we sort of encapsulate these amazing experts and leverage the AI.
01:57And then we moved to the data, right?
01:59We took some of these kind of concepts and ideas and we mined and mined and mined our data.
02:03We've got years and years of years of great first-party data, you know,
02:08customer service engagements, store engagements, transactional data, recipe data, expert data,
02:14test kitchen data, all these different sort of sources of great data.
02:19And then we moved to the AI.
02:21And then we started to sort of take this and iterate and test into these experiences.
02:26We sort of socialized it internally.
02:28We shared it back with those experts.
02:30We said, pretend this is a customer.
02:32Let's see how this agent does.
02:33And we iterated and fine-tuned and ultimately what was born was all of which was something that we were
02:38very proud of
02:39and we've continued to build on her capabilities.
02:42But we found that if you start with the human and not with the AI and not even the data,
02:46you can end up really creating some pretty compelling experiences that are grounded in the way that people like to
02:52engage with people.
02:53Yeah.
02:55It's an incredible experience.
02:57And, you know, we talk a lot about AI use cases, right?
03:00There's, we're seeing an incredible explosion of coding use cases, engineering use cases.
03:05We see customers using these agents internally to drive productivity for their employees.
03:09We see process optimization.
03:11There's a lot of very impactful use cases that are out there today.
03:16But this one, this one is facing your end customer.
03:21Yep.
03:21Like that is a high bar.
03:22Yep.
03:22It's got to be an agent that you really trust to be out there to have these interactions.
03:26So putting something like that out there, you lined out the steps, drive the outcome, figure out the data.
03:33But what did you learn along the way?
03:34Like what's worked, what's not worked?
03:36What's been something that you've really taken from this journey?
03:40Yeah, I think we've had to break some of the conventional thinking in, you know, e-commerce and digital experiences.
03:48I think historically e-commerce has been built for transactional efficiency, right?
03:56You think about search, shop, cart, checkout, you know, the metrics are all about how do I drive conversion and
04:03how do I do it as quickly as possible, right?
04:05Amazon has built a massive business on this concept.
04:10And even when you look at the LLMs sometimes, like they're very quick to try to give you an answer.
04:16And I think what we found is that there's a lot of, especially when you talk about discovery, there's a
04:22lot of value in the experience, in the back and forth, in the exploration.
04:28And if you drive that engagement and you're not so quick to jump to, well, here's some products, here's something
04:35to go buy, but let's explore this, right?
04:37And, again, this sort of started with the human piece, which is, okay, we sort of probed some of our,
04:41you know, best sales associates and customer service agents and folks and said, like, sometimes the best response to a
04:47question is another question.
04:49And what we found is that if you can kind of engage people and drive engagement in the exploration, in
04:55the discovery, it can drive a tremendous amount of value, right?
05:00So, you know, the engagement is the conversion in some cases.
05:04And we've seen with sort of embracing this approach and guiding customers and letting them explore whether it's product, again,
05:12or entertaining or some of the things that Olive can do or some of the things that we do with,
05:15you know, our other brands in Williams-Sonoma, Inc., you know, Pottery Barn, West Elm, around helping customers with, you
05:21know, interior design and some of these other areas.
05:24We've just seen the conversion results follow extremely strongly, like multiples, multiples from a conversion value when you can engage
05:32customers in that experience.
05:33Yeah, and in some ways, that is replicating what you do in the store, which is a deeply engaging experience
05:38versus a transaction.
05:39Yeah, that's fascinating.
05:41So last question.
05:42We have a couple of minutes here.
05:45There's been things that work, things that don't work.
05:47You are kind of at the forefront of these agentic systems.
05:51You've done everything from building them, testing them, scaling them, operating them.
05:54You're doing all of these things.
05:55So I would love, I think everyone here would appreciate, where do you think the state of the art is?
06:01What's working?
06:01What's not working?
06:02And what are you really excited about going forward?
06:06Yeah, I'll start with the sort of the positive side, the things that are working.
06:12And again, to kind of pick up on the theme that I shared earlier, you know, historically, e-commerce is
06:17built around sort of transactional efficiency.
06:19And even if you think about the previous generations of AI and machine learning, it's things like product recommendations.
06:25It's things like algorithmic scoring.
06:28It's things like fraud protection.
06:29It's things like customer segmentation, right?
06:31So even when you're talking about personalization, you're talking about segment-based personalization.
06:36It's like putting people into buckets and then building experience around those buckets.
06:39And what's really exciting about this latest generation of agentic tech is that it's, when you say personalization, it's true
06:47personalization.
06:49It's true, like one-to-one, like let me understand your exact scenario, your exact issue.
06:54And let me sort of be able to package up all the expertise that we have, all the data that
07:00we have, all the capabilities that we have to create this excellent experience.
07:03I don't think the industry has really delivered on that yet.
07:07I think we're still, as much as I think we're very proud of what we built and what we've done,
07:13I think we're in the early innings.
07:15I think the best is yet to come.
07:16So I'm very excited about the potential of us in the industry and certainly with Williamson, the way that we're
07:22thinking about it is almost reinventing digital commerce and bringing the human back into shopping and bringing the discovery back
07:30into shopping.
07:31And I'll sort of segue to the second part of your question, which is, you know, what's not working and
07:38what we've learned is chat is great for a lot of things.
07:42It can be pretty good for customer service.
07:45It can be pretty good for Q&A and quick questions.
07:47It's pretty god-awful for shopping.
07:50I don't know if you've ever actually tried to follow the entire shopping experience to try to chat your way
07:53to a purchase, unless you're buying something that's highly commoditized.
07:59And, you know, many of us have sort of started and the industry has started in this sort of chat
08:03modal, but I think the future and where everyone's going and where we're going certainly is where we're focused is
08:08really thinking about these multimodal experiences and thinking about where agents start to break the bounding box of chat windows
08:14and start to think about immersive visual experiences, thinking about the intersection of voice.
08:20And I think that's really where we're focused, right?
08:23So when you think about, you know, I'll segue from the Williams-Sonoma brand, you know, to another one of
08:28our brands is Pottery Barn or West Elm, which really focus primarily with interior decorating and furniture.
08:34You know, if you're decorating, it's inherently this very visual medium, right?
08:39Like you can't text your way, like, what do you want to, I don't know, I want a nice looking
08:43thing, right?
08:44Like I need to see it, right?
08:48And agents can do this, right?
08:50Like you talk about this intersection of large language models, large image models built on top of proprietary data with
08:56these guided experiences.
08:57Like you can really help people guide and visualize their way into these very complex things.
09:02And what's really exciting, I think, about how we're positioned and where I'm very bullish about it is, you know,
09:08we all have access to the same models.
09:11But, you know, what really differentiates and what we're seeing where we're able to unlock value is our massive amounts
09:20of sort of first party data, right?
09:22And being able to sort of activate that.
09:24So everything from we talked about Olive, like our test kitchen data, to the transactional data, to, you know, all
09:31this data that we have around that fuel a lot of the content that we build and even the training
09:36content internally and all that, massively impactful.
09:40You know, second is, you know, our multi-channel nature of our business.
09:46We've got, you know, digital and e-commerce, but we've also got stores, we've got, you know, customer service agents,
09:52but we also have an in-home business, right?
09:54So, you know, little known, you know, fact about Williams-Sonoma is, you know, half of our retail sales from
09:58a revenue perspective comes from going into customers' homes and helping them with their interior design.
10:06And by the way, it's free.
10:07So if you ever want to take us up on it, if you're moving or redecorating, just sign up, but
10:11we'll help you for free.
10:12You don't have to pay an expensive interior designer.
10:14A designer will do it for free.
10:16I mean, you'll buy some stuff, but the service is free.
10:23But you sort of start to think about where all these things intersect and how you can activate these experiences.
10:28And it's not just about digital.
10:30It's about, you know, putting this tech in the hands of an interior designer.
10:33It's about getting into, helping get into customers' homes.
10:36It's about understanding kind of their sort of space and being able to help them visualize it.
10:40And you start to think about the sort of, you know, multi-channel connection.
10:45And you've got sort of this proprietary data.
10:47You've got this internal expertise I talked about.
10:48You talk about this sort of channel excellence.
10:50And then for us, you know, we're also very highly vertically integrated.
10:53So, you know, the vast majority of what we sell is designed, built in-house.
10:58We source it.
10:59We manufacture it.
11:00We transport it all over the world.
11:04We handle the delivery.
11:06We handle the merchandising and marketing.
11:07Every single part of that experience, right?
11:09So, AI can start to touch and really connect the dots across all of it because we've got a line
11:13of sight into the entire experience.
11:15So, I'm very bullish about how all this is going to come together for us.
11:19I'm very excited.
11:19I think, you know, what we've been able to do in partnership with Model View and your team at Salesforce
11:25and what we've been with all of on the kind of consumer-facing side, what we've seen internally in terms
11:30of Agenda tech, how you kind of connect it with data and other types of both technology capabilities and experience.
11:37It's super exciting.
11:38I think we're very early.
11:39And I think the best is yet to come.
11:41Awesome.
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