David’s Bridal CEO Kelly Cook on Betting Big and Knowing When Not To

1 00:00:06,320 - > 00:00:10,000 Narrator: This is Monday Conversation, a PYMNTS podcast. 2 00:00:10,000 - > 00:00:13,039 Karen Webster sits down with the visionaries behind the 3 00:00:13,039 - > 00:00:16,239 trends for the story of shaping what's next in payments and 4 00:00:16,239 - > 00:00:17,120 commerce. 5 00:00:17,120 - > 00:00:22,559 In this episode, PYMNTS CEO Karen Webster sits down with 6 00:00:22,559 - > 00:00:26,640 David's Bridal CEO, Kelly Cook, to talk about the push to 7 00:00:26,640 - > 00:00:28,800 reinvent David's Bridal. 8 00:00:37,679 - > 00:00:40,240 Karen Webster: Over the years, I've had the opportunity to 9 00:00:40,240 - > 00:00:43,759 speak with Kelly Cook, the CEO of David's Bridal, otherwise 10 00:00:43,759 - > 00:00:46,799 known as David's Today, about the many moves that she's made 11 00:00:46,799 - > 00:00:51,520 in the space, her devotion to AI with her IELT to algorithm 12 00:00:51,520 - > 00:00:55,200 initiative across the business, and some of the bold strokes 13 00:00:55,200 - > 00:01:01,280 that she has acted on to expand beyond the bride to all occasion 14 00:01:01,280 - > 00:01:06,079 dressing, to expand beyond her virtual and physical storefronts 15 00:01:06,079 - > 00:01:10,560 to the Amazon marketplace, to go wholesale and to really 16 00:01:10,560 - > 00:01:15,439 reinvigorate the brand as well as the women and the families 17 00:01:15,439 - > 00:01:16,239 that she touches. 18 00:01:16,239 - > 00:01:20,319 So today I'm here to talk about her philosophy for making those 19 00:01:20,319 - > 00:01:22,000 big bets and bold moves. 20 00:01:22,000 - > 00:01:26,159 And I look forward to hearing all about what inspires her, the 21 00:01:26,159 - > 00:01:29,200 results of some of these big bets and bold moves in the 22 00:01:29,200 - > 00:01:33,200 market, and how she gets her inspiration for the things that 23 00:01:33,200 - > 00:01:34,000 she does every day. 24 00:01:34,000 - > 00:01:36,239 Hey Kelly, it's so great to see you again. 25 00:01:36,239 - > 00:01:40,319 And I'm looking forward to this conversation, very different 26 00:01:40,319 - > 00:01:42,480 conversation than the ones we've had in the past. 27 00:01:42,480 - > 00:01:47,760 It's really all about how you drive strategy getting inside 28 00:01:47,760 - > 00:01:51,280 your head around the big bets and the bold moves that you've 29 00:01:51,280 - > 00:01:52,959 made at David's. 30 00:01:52,959 - > 00:01:54,640 So I'm excited to have that conversation. 31 00:01:54,719 - > 00:01:55,680 Kelly Cook: I hope you are too. 32 00:01:55,680 - > 00:01:56,480 I am. 33 00:01:56,480 - > 00:01:58,000 I'm looking forward to it, Karen. 34 00:01:58,000 - > 00:01:59,359 Thank you so much. 35 00:01:59,760 - > 00:02:02,879 Karen Webster: So let's start with sort of the basic brass 36 00:02:02,879 - > 00:02:03,439 tacks. 37 00:02:03,439 - > 00:02:06,319 You have done so many things, which we'll talk about in 38 00:02:06,319 - > 00:02:06,959 detail. 39 00:02:06,959 - > 00:02:13,039 Is the big bets philosophy a strategy of yours, or is that 40 00:02:13,039 - > 00:02:16,240 just who you are as a person and an executive? 41 00:02:16,719 - > 00:02:19,199 Kelly Cook: I think it's more the latter. 42 00:02:19,199 - > 00:02:26,400 I think my entire career I have been drawn to taking the 43 00:02:26,400 - > 00:02:28,319 ordinary and making it extraordinary. 44 00:02:28,319 - > 00:02:33,759 And I think embedded in that, you know, requires some some big 45 00:02:33,759 - > 00:02:35,439 bets, some leaps of faith. 46 00:02:35,439 - > 00:02:39,520 You know, it it we take big bets because playing it safe is 47 00:02:39,520 - > 00:02:41,280 just procrastination in a suit. 48 00:02:41,280 - > 00:02:43,840 You know, and if it feels uncomfortable, it probably 49 00:02:43,840 - > 00:02:46,159 belongs on a couch and not on a strategy deck. 50 00:02:46,159 - > 00:02:49,439 You know, and so I think it's part of a little bit who I'm 51 00:02:49,439 - > 00:02:50,319 wired, you know. 52 00:02:50,319 - > 00:02:54,080 I I think I'm drawn to that because I'm I'm drawn to 53 00:02:54,080 - > 00:02:55,520 large-scale transformation. 54 00:02:55,520 - > 00:02:58,960 And I think embedded in that, you have to take big bets. 55 00:02:59,280 - > 00:03:01,599 Karen Webster: Well, it also suggests that you have a lot of 56 00:03:01,599 - > 00:03:04,800 conviction and confidence in moving forward. 57 00:03:04,800 - > 00:03:09,039 And I know that those things are driven by data and not just 58 00:03:09,039 - > 00:03:12,240 sort of what you decide to wake up on one morning and do. 59 00:03:12,240 - > 00:03:16,400 Although instincts probably play a big part in how you 60 00:03:16,400 - > 00:03:20,560 decide to execute some of the big bets and bold moves that 61 00:03:20,560 - > 00:03:21,280 you've made. 62 00:03:22,080 - > 00:03:23,199 Kelly Cook: Yeah, I mean, it's true. 63 00:03:23,199 - > 00:03:26,479 So if you I mean, if you think about David's just in general, 64 00:03:26,479 - > 00:03:31,360 you know, we it was the burning platform when I took over CEO is 65 00:03:31,360 - > 00:03:34,080 that the company had filed for restructuring in 19 and it had 66 00:03:34,080 - > 00:03:35,039 filed in 23. 67 00:03:35,039 - > 00:03:37,039 I mean, that's two times in four years. 68 00:03:37,039 - > 00:03:41,199 So something transformative needed to happen to be able to 69 00:03:41,199 - > 00:03:44,560 create a you know a thriving brand, not just a surviving one. 70 00:03:44,560 - > 00:03:48,960 And, you know, when we sat down to build out IELTA algorithm, 71 00:03:48,960 - > 00:03:52,080 you know, the I think the team was feeling like they were in a 72 00:03:52,080 - > 00:03:52,800 pretty dark place. 73 00:03:52,800 - > 00:03:55,680 And I, you know, I told them, I said, look, sometimes when 74 00:03:55,680 - > 00:03:58,080 you're in a dark place, you think you've been buried, but 75 00:03:58,080 - > 00:04:01,360 you've actually been planted, you know, and it's the it's the 76 00:04:01,360 - > 00:04:06,240 it's it's a mindset shift that the art of the possible is that 77 00:04:06,240 - > 00:04:10,560 exactly possible, you know, and so it was a it was a really 78 00:04:10,560 - > 00:04:15,840 thrilling time to sit down with the management team and build 79 00:04:15,840 - > 00:04:19,360 out out to algorithm and come out uh on the other side going, 80 00:04:19,360 - > 00:04:22,000 wow, this is extraordinary. 81 00:04:22,000 - > 00:04:25,040 This is and we knew we needed revolutionary change and not 82 00:04:25,040 - > 00:04:26,319 evolutionary, right? 83 00:04:26,399 - > 00:04:26,560 Karen Webster: Right. 84 00:04:26,560 - > 00:04:29,759 So so planting is a it's actually a really good um 85 00:04:29,759 - > 00:04:30,480 philosophy. 86 00:04:30,480 - > 00:04:33,519 That's a good you should make that into a cup or something, 87 00:04:33,519 - > 00:04:34,319 like a plant. 88 00:04:35,199 - > 00:04:38,240 Kelly Cook: You need to do that into a cup and send it to you. 89 00:04:40,079 - > 00:04:41,759 Karen Webster: Okay, that's a deal. 90 00:04:41,759 - > 00:04:42,639 That's a deal. 91 00:04:42,639 - > 00:04:45,439 So let me let's unpack some of these big bets. 92 00:04:45,439 - > 00:04:50,079 So David's, most people may be familiar with David's bridal, 93 00:04:50,079 - > 00:04:52,480 has gone definitely beyond the bride. 94 00:04:52,480 - > 00:04:58,079 So what's interesting about that is 90% of all brides make 95 00:04:58,079 - > 00:05:01,040 their first stop your store or site. 96 00:05:01,040 - > 00:05:04,879 I mean, so you've got the market of the brides who are 97 00:05:04,879 - > 00:05:09,839 interested in getting their big day organized with you. 98 00:05:09,839 - > 00:05:14,560 But you decided to go beyond the bride to all occasion 99 00:05:14,560 - > 00:05:15,439 dressing. 100 00:05:15,439 - > 00:05:19,040 And that's a different audience, potentially. 101 00:05:19,040 - > 00:05:22,800 It's a very different strategy, it's different merchandising, 102 00:05:22,800 - > 00:05:24,160 all of the above. 103 00:05:24,160 - > 00:05:27,519 Some people may say, why didn't you just stick with the niche? 104 00:05:27,519 - > 00:05:29,920 Because you can build out from the niche, go deep in the 105 00:05:29,920 - > 00:05:31,199 vertical you have. 106 00:05:31,199 - > 00:05:32,480 Why expand? 107 00:05:32,480 - > 00:05:35,839 What did you see that others didn't and gave you the 108 00:05:35,839 - > 00:05:37,680 conviction to making that big move? 109 00:05:38,000 - > 00:05:39,120 Kelly Cook: Oh, love that. 110 00:05:39,120 - > 00:05:41,519 It's really quite simple, Karen. 111 00:05:41,519 - > 00:05:44,480 The the conviction came from data. 112 00:05:44,480 - > 00:05:49,920 And it really surfaced when we when we got into the wedding 113 00:05:49,920 - > 00:05:53,920 planning process, and we really, really went deep into that. 114 00:05:53,920 - > 00:05:57,360 It it, you know, the planning when a girl gets proposed to, 115 00:05:57,360 - > 00:06:01,040 she's happy for about 15 minutes and crying, hugging everybody, 116 00:06:01,040 - > 00:06:04,639 and then after 15 minutes, panic sets in because she's got to 117 00:06:04,639 - > 00:06:06,000 plan this massive wedding. 118 00:06:06,000 - > 00:06:10,959 And it takes literally over her life for 18 months, and there's 119 00:06:10,959 - > 00:06:15,199 300 tasks associated with the wedding planning journey, but it 120 00:06:15,199 - > 00:06:15,839 wasn't just that. 121 00:06:15,839 - > 00:06:20,720 When we drill down, she's buying 18 outfits. 122 00:06:20,959 - > 00:06:21,839 Karen Webster: That's incredible. 123 00:06:22,079 - > 00:06:22,959 Kelly Cook: Yeah, 18. 124 00:06:22,959 - > 00:06:25,600 And I remember when I got married, I was like, oh my, we 125 00:06:25,600 - > 00:06:26,480 were so poor back then. 126 00:06:26,480 - > 00:06:30,079 I think my dress cost $19 on a clearance rack seats, you know. 127 00:06:30,079 - > 00:06:33,839 But it's it's not like that now, and it's magnificent. 128 00:06:33,839 - > 00:06:38,079 Like it's it's absolutely magnificent to see um the 129 00:06:38,079 - > 00:06:41,199 evolution of the of the wedding experience for brides. 130 00:06:41,199 - > 00:06:44,560 But that there were 18 outfits, and we're like, we've only been 131 00:06:44,560 - > 00:06:45,519 focusing on a gown. 132 00:06:45,519 - > 00:06:48,399 And then we found out there's you know, a bachelorette party 133 00:06:48,399 - > 00:06:48,720 outfit. 134 00:06:48,720 - > 00:06:51,360 There's an outfit she wears the day of the wedding that she's 135 00:06:51,360 - > 00:06:52,480 getting dressed in. 136 00:06:52,480 - > 00:06:57,439 Most brides now are changing out of the ceremony gown into a 137 00:06:57,439 - > 00:06:58,480 reception gown. 138 00:06:58,480 - > 00:07:04,079 And so we needed to serve her in all of those different areas, 139 00:07:04,079 - > 00:07:07,920 and it wasn't just the bride, her bridesmaids, her bride's 140 00:07:07,920 - > 00:07:10,480 bride also have seven outfits. 141 00:07:10,480 - > 00:07:14,560 So we needed to really expand our offering and ensure that we 142 00:07:14,560 - > 00:07:18,639 were serving all of their apparel, footwear, and product 143 00:07:18,639 - > 00:07:20,000 needs for the whole journey. 144 00:07:20,319 - > 00:07:23,600 Karen Webster: Well, it also extends beyond that because 145 00:07:23,600 - > 00:07:25,279 that's the bridal experience. 146 00:07:25,279 - > 00:07:29,040 But then there's the, you know, now we're into graduation 147 00:07:29,040 - > 00:07:34,480 season, and there are bridal showers, there are baby showers, 148 00:07:34,480 - > 00:07:38,480 there's like the whole lifestyle around getting dressed 149 00:07:38,480 - > 00:07:39,759 for special occasions. 150 00:07:39,759 - > 00:07:43,600 And one of the things that you said the last time we spoke was 151 00:07:43,600 - > 00:07:46,800 that the woman who buys her bridesmaid's dress at David's 152 00:07:46,800 - > 00:07:51,120 will come back and buy more things from us, presumably maybe 153 00:07:51,120 - > 00:07:54,000 her bridal gown, but these other occasions as well. 154 00:07:54,000 - > 00:07:55,519 Is that what you're seeing? 155 00:07:55,839 - > 00:07:56,879 Kelly Cook: It is, Karen. 156 00:07:56,879 - > 00:07:58,800 We absolutely are seeing that. 157 00:07:58,800 - > 00:08:02,720 And it's not just it's not just bridesmaids, you know. 158 00:08:02,720 - > 00:08:06,480 You brought up prom, I believe, and you know, it was the same 159 00:08:06,480 - > 00:08:07,680 thing there as well. 160 00:08:07,680 - > 00:08:10,879 So what what was interesting, let me just tell you how we 161 00:08:10,879 - > 00:08:12,160 started to expand in prom. 162 00:08:12,160 - > 00:08:15,199 It actually, it actually came from moms. 163 00:08:15,199 - > 00:08:20,160 Um, moms knew about David's mom moms had the the brand 164 00:08:20,160 - > 00:08:25,360 recognition of us being sort of an all-in sort of occasion uh 165 00:08:25,360 - > 00:08:28,720 destination as related to mother, the bridegowns and 166 00:08:28,720 - > 00:08:32,559 flower girl and all of the wedding-oriented uh brand uh 167 00:08:32,559 - > 00:08:33,440 activities. 168 00:08:33,440 - > 00:08:39,840 But what was interesting is that moms, the range of mom is 169 00:08:39,840 - > 00:08:41,279 very, very wide. 170 00:08:41,279 - > 00:08:45,440 You know, a mom can be, you know, sort of in the ages of you 171 00:08:45,440 - > 00:08:48,879 know 38-ish, you know, up to 58, 60. 172 00:08:48,879 - > 00:08:54,320 And what we realized is is that mom is an attitude and not an 173 00:08:54,320 - > 00:08:54,720 age. 174 00:08:54,720 - > 00:09:00,559 And so there is a wide range of silhouettes and styles from 175 00:09:00,559 - > 00:09:04,399 lots of coverage to fitted to not fitted to sequence to 176 00:09:04,399 - > 00:09:05,600 elegant to modern. 177 00:09:05,600 - > 00:09:10,799 And what we realized is that we were missing, we were missing a 178 00:09:10,799 - > 00:09:16,399 sort of youngish attitude mom that wanted something a little 179 00:09:16,399 - > 00:09:18,480 bit sexier and a little bit more fit. 180 00:09:18,480 - > 00:09:22,240 And what we realized is that sort of silhouette started to 181 00:09:22,240 - > 00:09:25,679 shape itself into proms, formals, winter formals, you 182 00:09:25,679 - > 00:09:28,960 know, college against sorority events, debutante balls. 183 00:09:28,960 - > 00:09:31,200 And then it just it began from there. 184 00:09:31,200 - > 00:09:35,120 So it sort of started with the dress, and then it sort of sort 185 00:09:35,120 - > 00:09:39,600 of uh anchored there out to other uses, such as prom and and 186 00:09:39,600 - > 00:09:40,799 all those other events. 187 00:09:41,120 - > 00:09:44,480 Karen Webster: So I would imagine that that so much of 188 00:09:44,480 - > 00:09:49,600 your base becomes sort of a referral network inside their 189 00:09:49,600 - > 00:09:51,919 network, but then other people say, Where did you get that 190 00:09:51,919 - > 00:09:52,320 dress? 191 00:09:52,320 - > 00:09:54,879 Oh, David's, oh, I can get that dress at David's. 192 00:09:54,879 - > 00:09:58,320 I mean, so it's also maybe they're the ambassador, but 193 00:09:58,320 - > 00:10:02,000 they're also educating people in their network that you are an 194 00:10:02,000 - > 00:10:05,919 alternative to where they might think about going to get those 195 00:10:05,919 - > 00:10:07,279 those dresses for those occasions. 196 00:10:07,600 - > 00:10:09,039 Kelly Cook: 100% right, Karen. 197 00:10:09,039 - > 00:10:13,679 I mean, I will tell you that I think that's one of my favorite 198 00:10:13,679 - > 00:10:19,679 parts about this job is that it doesn't matter where I am, uh, 199 00:10:19,679 - > 00:10:24,159 the grocery store, church, an event, standing, you know, 200 00:10:24,159 - > 00:10:24,960 walking a dog. 201 00:10:24,960 - > 00:10:26,080 It doesn't matter. 202 00:10:26,080 - > 00:10:29,440 As soon as I say I work at David's bridle, they're like, 203 00:10:29,440 - > 00:10:31,679 oh, my cousin got her dress and taste. 204 00:10:31,679 - > 00:10:34,480 Oh, my daughter got her dress and things, my grandma. 205 00:10:34,480 - > 00:10:39,919 I mean, it is the best job ever because you're making them feel 206 00:10:39,919 - > 00:10:42,320 so good about a memory. 207 00:10:42,320 - > 00:10:45,200 I mean, I've I I I feel bad for like a dentist. 208 00:10:45,200 - > 00:10:46,879 Oh, I got my root canal down here. 209 00:10:46,879 - > 00:10:51,679 You know, I don't, I don't, it's like such an addictive 210 00:10:51,679 - > 00:10:55,919 business, you know, and so happy, and all the memories are 211 00:10:55,919 - > 00:10:58,480 happy and all the memories are joyful. 212 00:10:58,480 - > 00:11:01,840 And it that like that feeds our business. 213 00:11:01,840 - > 00:11:04,879 It feeds who we are, it feeds how we come to work every day. 214 00:11:04,879 - > 00:11:07,679 It's just it's a it's absolutely incredible. 215 00:11:08,000 - > 00:11:08,639 Karen Webster: Right, you're right. 216 00:11:08,639 - > 00:11:10,399 It's a happy, it's a happy occasion. 217 00:11:10,399 - > 00:11:12,720 It's can be a stressful occasion, but it's a happy 218 00:11:12,720 - > 00:11:13,039 occasion. 219 00:11:13,039 - > 00:11:15,840 It's memories, people taking pictures, and the pictures that 220 00:11:15,840 - > 00:11:16,399 go everywhere. 221 00:11:16,399 - > 00:11:20,559 Last forever, they last forever, they last forever. 222 00:11:20,559 - > 00:11:22,879 Let's talk about so we talked about Beyond the Bride. 223 00:11:22,879 - > 00:11:24,720 Let's talk about beyond the store. 224 00:11:24,720 - > 00:11:28,879 So you've recently set up a storefront on Amazon. 225 00:11:28,879 - > 00:11:33,840 Some may say, okay, that's little fox in the hen house kind 226 00:11:33,840 - > 00:11:34,399 of thesis. 227 00:11:34,399 - > 00:11:36,240 Not sure it's good for us. 228 00:11:36,240 - > 00:11:37,919 Why is it good for David's? 229 00:11:38,639 - > 00:11:42,080 Kelly Cook: So I I love this question, Karen. 230 00:11:42,080 - > 00:11:44,080 And there's a reason why. 231 00:11:44,080 - > 00:11:50,399 One of the major shifts of where David's was basically for 232 00:11:50,399 - > 00:11:55,679 75 years, um, to the shift we made with IELTA algorithm, is 233 00:11:55,679 - > 00:11:58,080 that we no longer have competition. 234 00:11:58,080 - > 00:12:02,240 That right there is a fundamental shift. 235 00:12:02,240 - > 00:12:04,639 And let me explain why. 236 00:12:04,639 - > 00:12:08,320 We own our own joint venture. 237 00:12:08,320 - > 00:12:12,399 So we have 46 design and production centers all over the 238 00:12:12,399 - > 00:12:18,000 world, and they allow us to bring any type of dress, any 239 00:12:18,000 - > 00:12:22,799 type of gown to the market, whether it is a uh price point 240 00:12:22,799 - > 00:12:26,799 at $99 or $10,000 to $20,000. 241 00:12:26,799 - > 00:12:29,919 We have gowns right now that we produce that are in the price 242 00:12:29,919 - > 00:12:31,759 range of $10,000 to $15,000. 243 00:12:31,759 - > 00:12:36,799 What that, what having that in our portfolio that we owned 244 00:12:36,799 - > 00:12:41,600 enables us to change our product architecture to say, wait a 245 00:12:41,600 - > 00:12:45,840 minute, we don't have to just sell gowns at David's. 246 00:12:45,840 - > 00:12:51,919 We can produce and sell gowns and dresses for anyone at any 247 00:12:51,919 - > 00:12:55,440 point in her journey where she's buying, it doesn't have to be 248 00:12:55,440 - > 00:12:55,759 us. 249 00:12:55,759 - > 00:13:00,159 And when we changed our mindset to that, to say, if you take 250 00:13:00,159 - > 00:13:06,559 just bridal, we want to serve and sell to every bride in the 251 00:13:06,559 - > 00:13:10,480 world, regardless of whether she buys it directly from us or 252 00:13:10,480 - > 00:13:10,720 not. 253 00:13:10,720 - > 00:13:12,159 That was the shift. 254 00:13:12,159 - > 00:13:16,240 And when you take those, when you change your mindset like 255 00:13:16,240 - > 00:13:20,559 that, then everybody that is selling a dress to a bride 256 00:13:20,559 - > 00:13:21,919 becomes a partner. 257 00:13:21,919 - > 00:13:26,240 So we built our strategy around, we launched DoorDash. 258 00:13:26,240 - > 00:13:29,519 By the way, Vegas is the number one city for DoorDash wedding 259 00:13:29,519 - > 00:13:29,840 dresses. 260 00:13:29,840 - > 00:13:32,159 You probably wouldn't figure that out, you know. 261 00:13:32,159 - > 00:13:36,960 Uh, but then we sold on Amazon, we launched on Walmart. 262 00:13:36,960 - > 00:13:41,039 We are launching three more marketplaces within the next 60 263 00:13:41,039 - > 00:13:42,080 to 90 days. 264 00:13:42,080 - > 00:13:47,120 We have a David's bridal store inside Liverpool in Mexico City. 265 00:13:47,120 - > 00:13:50,799 You know, we we our our job was to sell, you know, we're 266 00:13:50,799 - > 00:13:52,720 selling boutiques now with wholesale. 267 00:13:53,039 - > 00:13:54,799 Karen Webster: Yeah, I was gonna ask you about that next. 268 00:13:54,799 - > 00:13:55,039 Yeah. 269 00:13:55,039 - > 00:14:00,240 So you're basically where the customer is buying a bridal gown 270 00:14:00,240 - > 00:14:02,960 or an all occasion, a dress for any occasion. 271 00:14:03,279 - > 00:14:05,759 Kelly Cook: Yes, ma'am, that is exactly right. 272 00:14:05,759 - > 00:14:10,960 And that has enabled us to grow in an asset-light way, and that 273 00:14:10,960 - > 00:14:13,919 was one of the tenets of the IELTA algorithm. 274 00:14:13,919 - > 00:14:16,879 Grow in an asset-light way, period. 275 00:14:16,879 - > 00:14:19,919 And so that's what the transformation is doing to our 276 00:14:19,919 - > 00:14:24,000 company, and that's why when we look out to our profit targets 277 00:14:24,000 - > 00:14:26,799 and our plans for this year, I mean, it's such a dramatic shift 278 00:14:26,799 - > 00:14:29,759 from where the company has been because it's growing in an 279 00:14:29,759 - > 00:14:30,879 asset-light way. 280 00:14:30,879 - > 00:14:34,639 So we're I'm so proud of the team and the progress. 281 00:14:34,960 - > 00:14:37,519 Karen Webster: It's about it's about distribution at this point 282 00:14:37,519 - > 00:14:40,320 because you have the product, it's getting it into those 283 00:14:40,320 - > 00:14:40,639 channels. 284 00:14:40,639 - > 00:14:43,759 And and and what did the so through the wholesale 285 00:14:43,759 - > 00:14:47,360 relationship and all the what 7,000 or so boutiques that sell 286 00:14:47,360 - > 00:14:50,480 bridal dresses, what did they think when you knocked on their 287 00:14:50,480 - > 00:14:50,639 door? 288 00:14:50,639 - > 00:14:53,200 Were they were they like, oh, where have you been? 289 00:14:53,200 - > 00:14:57,759 I can't believe that it's taken us so long to do a deal, or was 290 00:14:57,759 - > 00:15:00,480 there more of a sales process that needed to happen? 291 00:15:00,799 - > 00:15:02,080 Kelly Cook: Yeah, good question. 292 00:15:02,080 - > 00:15:04,720 So, I mean, obviously the reason why we went into 293 00:15:04,720 - > 00:15:07,840 wholesale is because we want to be the engine in everybody's 294 00:15:07,840 - > 00:15:10,000 car, not just be a car driving down the road, right? 295 00:15:10,000 - > 00:15:11,919 And that's what the JV allowed us to do. 296 00:15:11,919 - > 00:15:15,360 And I would say honestly, the reception has been, you know, a 297 00:15:15,360 - > 00:15:16,639 little all over the place, I think. 298 00:15:16,639 - > 00:15:17,919 Yeah, you know, with wholesale. 299 00:15:17,919 - > 00:15:22,320 We already were signing wholesale deals, Karen, to be 300 00:15:22,320 - > 00:15:23,919 honest, before we announced it. 301 00:15:23,919 - > 00:15:27,360 Um, we wanted to understand if there was a market need and 302 00:15:27,360 - > 00:15:29,200 there was a market response. 303 00:15:29,200 - > 00:15:34,320 And you know, the what's amazing and extraordinary, um, 304 00:15:34,320 - > 00:15:36,399 and I I love this stat. 305 00:15:36,399 - > 00:15:40,320 Our wholesale partners are telling us right now, on 306 00:15:40,320 - > 00:15:44,320 average, we're saving them around 20 points of margin. 307 00:15:44,320 - > 00:15:45,360 You're kidding. 308 00:15:45,360 - > 00:15:50,080 No, no, and the reason if you here's the reason why that is 309 00:15:50,080 - > 00:15:50,960 happening. 310 00:15:50,960 - > 00:15:53,919 David's is is massive. 311 00:15:53,919 - > 00:15:58,240 You know, we have a massive share, and we sell millions of 312 00:15:58,240 - > 00:16:01,759 units a year from all our different categories, right? 313 00:16:01,759 - > 00:16:07,840 And our joint venture is producing all of those goods for 314 00:16:07,840 - > 00:16:10,960 us and designing them and producing them with all this 315 00:16:10,960 - > 00:16:16,639 luxury and and exclusivity and craftsmanship and all of that, 316 00:16:16,639 - > 00:16:19,039 and that gives us scale. 317 00:16:19,039 - > 00:16:25,360 And because we have the scale, it keeps cost efficient, and we 318 00:16:25,360 - > 00:16:28,240 are passing all of that efficiency on to our wholesale 319 00:16:28,240 - > 00:16:31,440 partners, we're just passing it right on to them, and that's 320 00:16:31,440 - > 00:16:32,799 where they're like, oh my gosh. 321 00:16:32,799 - > 00:16:36,399 And then when you take it a step further, that we go from 322 00:16:36,399 - > 00:16:40,720 size double zero to size 30, which is a challenge in some 323 00:16:40,720 - > 00:16:42,879 areas of luxury. 324 00:16:42,879 - > 00:16:46,320 And you say, Oh, and by the way, we can get it to you 325 00:16:46,320 - > 00:16:49,919 quickly in nine weeks, which most people wait six months. 326 00:16:49,919 - > 00:16:53,600 Like, it's just everything our wholesale partners are telling 327 00:16:53,600 - > 00:16:56,960 us they need that's what we're that's what we're delivering. 328 00:16:56,960 - > 00:17:00,639 And we have our first wholesale show in New York next week for 329 00:17:00,639 - > 00:17:02,559 bridal fashion week at one fine day. 330 00:17:02,559 - > 00:17:04,640 And we're we're you know, we're already booked up with 331 00:17:04,640 - > 00:17:05,119 appointments. 332 00:17:05,119 - > 00:17:08,480 So we're so excited to bring this. 333 00:17:08,480 - > 00:17:12,640 And I think the I think the hurdle to your point, 334 00:17:12,640 - > 00:17:16,880 transparently, Karen, was them understanding we're not the 335 00:17:16,880 - > 00:17:20,400 enemy, you know, we're the partner, you know, and we win. 336 00:17:20,400 - > 00:17:23,440 If you sell a bridal gown, you take her, you know, we'll give 337 00:17:23,440 - > 00:17:25,599 you the gown, we're all good, you know. 338 00:17:25,599 - > 00:17:28,960 And it it's a little bit of a, you know, it's a mindset shift, 339 00:17:28,960 - > 00:17:30,000 but it is working. 340 00:17:30,240 - > 00:17:30,640 Karen Webster: Yeah. 341 00:17:30,640 - > 00:17:33,599 Well, I mean, scale is the is the is the word, right? 342 00:17:33,599 - > 00:17:34,640 I mean, you have the scale. 343 00:17:34,640 - > 00:17:37,200 You're buying sequins by the by the pound. 344 00:17:37,200 - > 00:17:39,359 You're buying feathers by the pound. 345 00:17:39,359 - > 00:17:40,799 I mean, so so you've got these. 346 00:17:40,799 - > 00:17:48,079 I mean, you're I was gonna wear feathers today, actually, but 347 00:17:48,079 - > 00:17:50,640 it's not quite feather weather in Boston yet. 348 00:17:50,640 - > 00:17:53,599 But um, but I I mean that is the point. 349 00:17:53,599 - > 00:17:57,519 And I think you know, your stat about the margin uh lift is 350 00:17:57,519 - > 00:18:01,599 incredible because it's very tough in any retail environment 351 00:18:01,599 - > 00:18:03,759 to kind of get that kind of margin improvement. 352 00:18:03,759 - > 00:18:06,960 And and that's uh that that that's that's wonderful. 353 00:18:06,960 - > 00:18:11,680 I I want to go to the alda algorithm thesis because that is 354 00:18:11,680 - > 00:18:13,440 fundamental to your strategy. 355 00:18:13,440 - > 00:18:16,640 And you've been talking about AI reshaping the customer 356 00:18:16,640 - > 00:18:20,000 experience long before AI has been kind of a part of the 357 00:18:20,000 - > 00:18:24,079 everyday narrative around AI as being so transformative. 358 00:18:24,079 - > 00:18:29,200 But but with AI, what was the outcome you were trying to 359 00:18:29,200 - > 00:18:29,680 deliver? 360 00:18:29,680 - > 00:18:34,079 And and I want to qualify that by saying, you know, there's AI 361 00:18:34,079 - > 00:18:37,839 that seems generic, and then there's AI that really is 362 00:18:37,839 - > 00:18:40,799 contextualized to the individual. 363 00:18:40,799 - > 00:18:45,359 How are you getting the latter and not the former with your 364 00:18:45,359 - > 00:18:45,920 strategy? 365 00:18:46,319 - > 00:18:48,400 Kelly Cook: So that is such an awesome question. 366 00:18:48,400 - > 00:18:51,599 You're the first person that's ever presented AI, an AI 367 00:18:51,599 - > 00:18:52,079 question like that. 368 00:18:52,079 - > 00:18:53,599 So I commend you for that. 369 00:18:53,599 - > 00:18:57,200 We we had four problem statements as it related to AI 370 00:18:57,200 - > 00:18:59,279 that we were trying to leverage AI for. 371 00:18:59,279 - > 00:19:01,920 One was for the bride. 372 00:19:01,920 - > 00:19:05,759 Um, this 300-task planning system is a nightmare for her. 373 00:19:05,759 - > 00:19:09,839 So we needed to de-stress that, and we needed to provide an 374 00:19:09,839 - > 00:19:13,920 agentic AI sort of concierge, if you will, that is available to 375 00:19:13,920 - > 00:19:18,319 her at all times of the day, 24/7, that she can manipulate 376 00:19:18,319 - > 00:19:22,160 and change wedding tasks based on whatever's changing in her 377 00:19:22,160 - > 00:19:22,559 environment. 378 00:19:22,559 - > 00:19:24,960 So we we needed to de-stress planning. 379 00:19:24,960 - > 00:19:28,880 The second problem statement was you know, to be able to do 380 00:19:28,880 - > 00:19:32,240 the transformation that we're doing at David's, we have a 381 00:19:32,240 - > 00:19:35,359 substantial amount of work that's going on, you know, 382 00:19:35,359 - > 00:19:40,640 process changing, uh, teams are changing, KPIs are changing, uh, 383 00:19:40,640 - > 00:19:43,599 projects are, you know, really very tightly managed. 384 00:19:43,599 - > 00:19:46,160 We needed a better sort of internal tool to do that. 385 00:19:46,160 - > 00:19:50,160 The third thing we needed to look at AI for is we just had to 386 00:19:50,160 - > 00:19:57,039 analyze data differently and quickly turning it, turn it into 387 00:19:57,039 - > 00:20:00,240 an insight and then quickly turn it into an action and then 388 00:20:00,240 - > 00:20:00,960 read the result. 389 00:20:00,960 - > 00:20:05,359 That process was taking way too long, and it was sort of in a 390 00:20:05,359 - > 00:20:07,039 legacy environment, if you will, Karen. 391 00:20:07,039 - > 00:20:11,039 So we needed to, it needed to keep up with the progress that 392 00:20:11,039 - > 00:20:13,119 we had with ILTA algorithm. 393 00:20:13,119 - > 00:20:15,680 And the fourth problem statement was we just needed 394 00:20:15,680 - > 00:20:17,519 100x content. 395 00:20:17,519 - > 00:20:21,119 Like we needed a lot of content in the market. 396 00:20:21,119 - > 00:20:24,960 And so what we've done is we've taken an AI approach to each 397 00:20:24,960 - > 00:20:25,359 one of those. 398 00:20:25,359 - > 00:20:29,440 You know, obviously we launched a Gentec AI Perl Planner in the 399 00:20:29,440 - > 00:20:29,839 summer. 400 00:20:29,839 - > 00:20:33,839 Our users on that platform are exceeding our expectations. 401 00:20:33,839 - > 00:20:36,799 Uh, so we feel awesome about that. 402 00:20:36,799 - > 00:20:41,599 Um, we are we are we've got AI tools that are managing our 403 00:20:41,599 - > 00:20:42,160 content now. 404 00:20:42,160 - > 00:20:46,000 We use AI for subject line and copy and digital media. 405 00:20:46,000 - > 00:20:50,000 Uh, we've got AI and product pages for videos, but I will 406 00:20:50,000 - > 00:20:54,000 tell you a very, very funny story about that going poorly. 407 00:20:54,000 - > 00:20:57,680 You know, you know, if you go too fast with AI, you gotta whoa 408 00:20:57,680 - > 00:21:00,000 back up a little bit. 409 00:21:00,000 - > 00:21:04,240 So uh I told this story recently somebody else, but I 410 00:21:04,240 - > 00:21:09,039 was uh it was like a year ago, and I was uh on my couch on a 411 00:21:09,039 - > 00:21:09,759 Friday night. 412 00:21:09,759 - > 00:21:10,880 It was like eight o'clock. 413 00:21:10,880 - > 00:21:14,079 I turned on my, you know, turned off my laptop and I was 414 00:21:14,079 - > 00:21:16,000 having a glass of wine and opened up my phone. 415 00:21:16,000 - > 00:21:19,359 I was on TikTok and I came across this beautiful video. 416 00:21:19,359 - > 00:21:22,640 I knew it was our product and our our voice and everything. 417 00:21:22,640 - > 00:21:26,480 I was like, oh man, look at team go to you go. 418 00:21:26,480 - > 00:21:28,079 So beautiful. 419 00:21:28,079 - > 00:21:32,720 And then at the end of the video, Karen, it said David's 420 00:21:32,720 - > 00:21:35,519 bridal, B-R-I-D-L-E. 421 00:21:35,519 - > 00:21:48,319 After I lost 10 years of my life, you know, I called the CMO 422 00:21:48,319 - > 00:21:48,880 at the time. 423 00:21:48,880 - > 00:21:52,480 And look in their defense, though, but this is how this is 424 00:21:52,480 - > 00:21:55,279 how it sort of plays out in real life. 425 00:21:55,279 - > 00:21:58,799 They were going down the AI path, they were trying, they had 426 00:21:58,799 - > 00:21:59,599 put something in the test. 427 00:21:59,599 - > 00:22:06,240 It worked, but because it was 100% AI, it had bypassed the QA 428 00:22:06,240 - > 00:22:08,960 process that we usually do before the market. 429 00:22:08,960 - > 00:22:10,559 They didn't catch it, you know. 430 00:22:10,559 - > 00:22:12,960 And I'm like, okay, no problem. 431 00:22:12,960 - > 00:22:15,119 But it was the company's name. 432 00:22:15,119 - > 00:22:16,880 You know, could it have been anything else? 433 00:22:16,880 - > 00:22:22,880 But but that but look, you from my perspective, I was thrilled. 434 00:22:22,880 - > 00:22:26,160 I was thrilled that they were pushing it, they were taking a 435 00:22:26,160 - > 00:22:28,799 bet, they were taking a chance, they were moving quickly. 436 00:22:28,799 - > 00:22:32,319 Sometimes we're gonna fall forward uh on our face, but I'd 437 00:22:32,319 - > 00:22:35,359 rather fall forward going fast than fall backwards on our tushy 438 00:22:35,359 - > 00:22:36,079 going slow. 439 00:22:36,079 - > 00:22:39,119 So I I think that I I was proud of the team. 440 00:22:39,359 - > 00:22:43,680 Karen Webster: So Kelly, when you think about the planner, and 441 00:22:43,680 - > 00:22:47,839 you think about that almost as a platform for other third 442 00:22:47,839 - > 00:22:51,039 parties to participate and to monetize your reach. 443 00:22:51,039 - > 00:22:53,359 I mean, is that part of a strategy as well that you're 444 00:22:53,359 - > 00:22:54,160 contemplating? 445 00:22:54,640 - > 00:22:56,400 Kelly Cook: It it absolutely is. 446 00:22:56,400 - > 00:23:00,720 So we are actually in discussions right now to white 447 00:23:00,720 - > 00:23:05,039 label agentic prolay planner for another industry. 448 00:23:05,039 - > 00:23:09,039 And that's because the the the the LLMs that are the 449 00:23:09,039 - > 00:23:12,480 underpinning of how the knowledge base works relative to 450 00:23:12,480 - > 00:23:18,319 the agentic AI is is repeatable, meaning if the data 451 00:23:18,319 - > 00:23:20,559 are there, then you can translate that to another 452 00:23:20,559 - > 00:23:21,119 industry. 453 00:23:21,119 - > 00:23:23,759 And we're very, very excited about it. 454 00:23:23,759 - > 00:23:28,079 You know, on our radar, we have Cincinnata planned for the end 455 00:23:28,079 - > 00:23:28,720 of this year. 456 00:23:28,720 - > 00:23:31,920 And, you know, that is a $27 billion business. 457 00:23:31,920 - > 00:23:36,319 We love to celebrate with our our Hispanic 15-year-old 458 00:23:36,319 - > 00:23:40,160 beautiful women, girls, I guess rather, ladies, let me say it 459 00:23:40,160 - > 00:23:40,640 that way. 460 00:23:40,640 - > 00:23:44,240 And so that is that is as big as an event as a wedding. 461 00:23:44,240 - > 00:23:48,079 I mean, they are if you've never been, they are absolutely 462 00:23:48,079 - > 00:23:51,119 incredible, so full of joy and excitement. 463 00:23:51,119 - > 00:23:53,519 So that's a whole nother way. 464 00:23:53,519 - > 00:23:57,680 But yes, the the um the white label opportunity for the Pearl 465 00:23:57,680 - > 00:24:01,279 ecosystem is 100% on our radar right now. 466 00:24:01,599 - > 00:24:04,000 Karen Webster: Well, Kelly, always a pleasure talking to 467 00:24:04,000 - > 00:24:04,160 you. 468 00:24:04,160 - > 00:24:06,799 It's really great to get an understanding of how you make 469 00:24:06,799 - > 00:24:11,039 decisions and a little bit more under the hood of how you've 470 00:24:11,039 - > 00:24:15,359 navigated David's transformation in such a significant way and 471 00:24:15,359 - > 00:24:19,200 obviously have delivered so much success as a result of your 472 00:24:19,200 - > 00:24:19,680 focus. 473 00:24:19,680 - > 00:24:22,400 I love the fact that there aren't any rules. 474 00:24:22,400 - > 00:24:24,480 I mean, the only rule is that there isn't any. 475 00:24:24,480 - > 00:24:29,680 And I think that's um not always easy to say as the CEO, 476 00:24:29,680 - > 00:24:33,200 but it does inspire the best of people, and then you can 477 00:24:33,200 - > 00:24:36,880 obviously um put the parameters around what's necessary to get 478 00:24:36,880 - > 00:24:37,519 things to market. 479 00:24:37,519 - > 00:24:38,240 Always a pleasure. 480 00:24:38,240 - > 00:24:38,960 Thanks so much for your time. 481 00:24:39,279 - > 00:24:40,079 Kelly Cook: Thank you so much, Karen. 482 00:24:40,079 - > 00:24:40,799 Always a pleasure. 483 00:24:40,799 - > 00:24:42,160 Can't wait to see you soon. 484 00:24:42,480 - > 00:24:44,160 Karen Webster: See you soon, but by now. 485 00:24:48,400 - > 00:24:51,680 Narrator: That's it for this episode of the PYMNTS Podcast: 486 00:24:51,680 - > 00:24:53,519 the thinking behind the doing. 487 00:24:53,519 - > 00:24:57,279 Conversations with the leaders transforming payments, commerce, 488 00:24:57,279 - > 00:24:58,720 and the digital economy. 489 00:24:58,720 - > 00:25:02,160 Be sure to follow us on Spotify and Apple Podcasts. 490 00:25:02,160 - > 00:25:05,680 You can also catch every episode PYMNTS .com/ podcasts. 491 00:25:07,759 - > 00:25:09,440 Thanks for listening.