1 00:00:41,700 --> 00:00:43,230 Elle: Let's be honest. 2 00:00:43,290 --> 00:00:45,600 Every PMM dreams about 3 00:00:45,600 --> 00:00:46,890 shaping the product roadmap. 4 00:00:47,610 --> 00:00:50,280 The truth is you can, but only 5 00:00:50,280 --> 00:00:52,110 if you've built real trust 6 00:00:52,110 --> 00:00:54,120 with your product partners. 7 00:00:54,510 --> 00:00:55,650 That trust comes when 8 00:00:55,650 --> 00:00:57,240 you show up with sharp 9 00:00:57,240 --> 00:00:58,320 customer insights. 10 00:00:58,500 --> 00:01:00,450 Share ownership over adoption 11 00:01:00,450 --> 00:01:02,640 metrics and make it clear 12 00:01:02,640 --> 00:01:04,260 that you're in this together. 13 00:01:04,800 --> 00:01:06,150 If you're looking to earn a 14 00:01:06,150 --> 00:01:07,875 seat at the Roadmap Table, 15 00:01:07,875 --> 00:01:09,735 today's episode is your 16 00:01:09,735 --> 00:01:11,625 step-by-step blueprint, 17 00:01:12,045 --> 00:01:13,845 and I have the perfect pm m 18 00:01:13,875 --> 00:01:15,465 expert to guide you through. 19 00:01:16,065 --> 00:01:17,355 With that, it is my 20 00:01:17,355 --> 00:01:19,345 pleasure to have Sheryl Li, 21 00:01:19,365 --> 00:01:20,565 product marketing leader at 22 00:01:20,565 --> 00:01:23,085 Confluence on the show today. 23 00:01:23,565 --> 00:01:25,275 Sheryl is one of the best pmms 24 00:01:25,275 --> 00:01:26,865 to help you lead the way in 25 00:01:26,865 --> 00:01:28,155 shaping the product roadmap. 26 00:01:28,530 --> 00:01:29,700 Let me tell you why. 27 00:01:30,290 --> 00:01:32,280 Sheryl has always had a 28 00:01:32,280 --> 00:01:34,500 scientific mindset, think 29 00:01:34,560 --> 00:01:36,240 intellectual curiosity, 30 00:01:36,270 --> 00:01:37,980 experimentation, and 31 00:01:38,010 --> 00:01:39,180 pattern recognition. 32 00:01:39,630 --> 00:01:41,790 That scientific mindset became 33 00:01:41,790 --> 00:01:43,560 her superpower in product 34 00:01:43,560 --> 00:01:45,270 marketing, especially when it 35 00:01:45,270 --> 00:01:47,070 comes to shaping the roadmap. 36 00:01:47,484 --> 00:01:48,882 She started out with a 37 00:01:48,882 --> 00:01:50,262 deep love for science, 38 00:01:50,592 --> 00:01:52,062 and I mean deep. 39 00:01:52,392 --> 00:01:53,952 Her science fair project 40 00:01:53,952 --> 00:01:55,812 on turning algae into 41 00:01:55,812 --> 00:01:58,062 biofuel, earned her an award 42 00:01:58,062 --> 00:02:00,282 and even got an asteroid 43 00:02:00,312 --> 00:02:02,142 named after her by MIT. 44 00:02:02,562 --> 00:02:03,102 Wow. 45 00:02:03,912 --> 00:02:05,706 But instead of life in a 46 00:02:05,706 --> 00:02:07,776 lab, she took her curiosity 47 00:02:07,776 --> 00:02:09,306 and problem solving skills. 48 00:02:09,566 --> 00:02:11,096 Into management consulting, 49 00:02:11,306 --> 00:02:12,146 advising some of the 50 00:02:12,146 --> 00:02:13,376 world's biggest brands. 51 00:02:13,886 --> 00:02:15,146 From there, she became 52 00:02:15,146 --> 00:02:16,436 a founding member of the 53 00:02:16,436 --> 00:02:17,696 pricing team at Twilio. 54 00:02:17,966 --> 00:02:18,896 Then went on to leave 55 00:02:18,896 --> 00:02:20,066 major product launches 56 00:02:20,066 --> 00:02:21,566 at Confluent Post IPO. 57 00:02:22,256 --> 00:02:23,816 Today she heads up product 58 00:02:23,816 --> 00:02:25,316 marketing for Confluence, 59 00:02:25,316 --> 00:02:26,756 fastest growing products, 60 00:02:27,236 --> 00:02:29,036 and brings a rare blend of 61 00:02:29,036 --> 00:02:30,691 technical curiosity, business 62 00:02:30,691 --> 00:02:31,971 savvy, and go to market 63 00:02:31,971 --> 00:02:34,075 magic to everything she does. 64 00:02:34,265 --> 00:02:35,455 Sheryl, it's so amazing 65 00:02:35,455 --> 00:02:36,415 to have you on the show. 66 00:02:36,809 --> 00:02:37,109 Sheryl: Hi 67 00:02:37,403 --> 00:02:37,523 Elle: I. 68 00:02:37,709 --> 00:02:38,219 Sheryl: Thank you so 69 00:02:38,219 --> 00:02:39,419 much for having me. 70 00:02:39,479 --> 00:02:40,769 Wow, what a throwback. 71 00:02:41,628 --> 00:02:42,558 Elle: Yeah, of course. 72 00:02:43,279 --> 00:02:44,884 okay, so let's dive right in. 73 00:02:44,884 --> 00:02:46,174 First, tell me and get 74 00:02:46,174 --> 00:02:47,494 our audience up to speed. 75 00:02:47,854 --> 00:02:49,084 What is confluent? 76 00:02:49,114 --> 00:02:50,842 So, we can clue in some 77 00:02:50,842 --> 00:02:51,562 of the members who may 78 00:02:51,562 --> 00:02:52,492 be new to the company. 79 00:02:53,227 --> 00:02:54,067 Sheryl: Absolutely. 80 00:02:54,487 --> 00:02:56,497 So Confluent is a data 81 00:02:56,497 --> 00:02:57,697 streaming platform that 82 00:02:57,697 --> 00:02:59,047 helps companies work 83 00:02:59,047 --> 00:03:00,217 with real time data. 84 00:03:00,517 --> 00:03:01,357 And so that's what we 85 00:03:01,357 --> 00:03:02,677 call data in motion. 86 00:03:03,007 --> 00:03:04,297 And you can think about this 87 00:03:04,297 --> 00:03:06,757 in contrast to storing data in 88 00:03:06,757 --> 00:03:08,617 a database or data warehouse 89 00:03:08,617 --> 00:03:09,967 and analyzing it later. 90 00:03:10,718 --> 00:03:11,872 It's built on top of 91 00:03:11,872 --> 00:03:13,402 Apache Kafka, an open 92 00:03:13,402 --> 00:03:14,482 source technology that 93 00:03:14,482 --> 00:03:15,592 our founders created. 94 00:03:16,042 --> 00:03:17,452 Kafka has become the standard 95 00:03:17,452 --> 00:03:18,982 for handling such large 96 00:03:18,982 --> 00:03:20,632 volumes of real-time data, 97 00:03:20,872 --> 00:03:22,522 and it's being used by 80% 98 00:03:22,522 --> 00:03:24,262 of the Fortune 100 companies 99 00:03:24,456 --> 00:03:26,115 So to bring this to life, 100 00:03:26,145 --> 00:03:28,275 uh, a good example is fraud 101 00:03:28,275 --> 00:03:29,445 detection and banking. 102 00:03:29,805 --> 00:03:30,495 So when you have a 103 00:03:30,495 --> 00:03:32,604 transaction, realtime data 104 00:03:32,604 --> 00:03:34,104 is actually being streamed, 105 00:03:34,448 --> 00:03:36,036 in the backend and analyzed 106 00:03:36,066 --> 00:03:37,446 instantly so that they can 107 00:03:37,446 --> 00:03:38,976 flag suspicious activity. 108 00:03:39,426 --> 00:03:41,166 And so for you that might mean 109 00:03:41,166 --> 00:03:42,636 getting a push notification 110 00:03:42,846 --> 00:03:44,226 from your bank on your phone, 111 00:03:44,647 --> 00:03:46,297 you verify if that transaction 112 00:03:46,297 --> 00:03:47,497 was actually made by you. 113 00:03:47,827 --> 00:03:49,327 And so preventing fraud 114 00:03:49,327 --> 00:03:50,767 before it actually happens. 115 00:03:50,992 --> 00:03:52,012 Elle: Oh wow. 116 00:03:52,012 --> 00:03:52,312 Yes. 117 00:03:52,312 --> 00:03:53,422 It's good to hear the 118 00:03:53,422 --> 00:03:54,862 technology that's actually 119 00:03:54,862 --> 00:03:56,242 powering some of that. 120 00:03:56,299 --> 00:03:57,308 I've always wondered, I'm 121 00:03:57,308 --> 00:03:58,178 like, how do they know 122 00:03:58,178 --> 00:03:59,108 and how do they get to me 123 00:03:59,108 --> 00:04:00,428 so quickly to validate? 124 00:04:00,438 --> 00:04:00,528 Right. 125 00:04:01,169 --> 00:04:02,075 very interesting. 126 00:04:02,135 --> 00:04:03,335 Thank you for that context. 127 00:04:03,515 --> 00:04:04,815 So, for the first segment 128 00:04:04,815 --> 00:04:06,075 of our show today, I want 129 00:04:06,075 --> 00:04:08,205 to start with a case study 130 00:04:08,415 --> 00:04:09,915 of how you and your team 131 00:04:09,945 --> 00:04:11,685 took customer insights, 132 00:04:11,986 --> 00:04:12,640 bringing some of your 133 00:04:12,640 --> 00:04:14,860 scientific magic and truly 134 00:04:14,860 --> 00:04:17,410 impacted the product roadmap. 135 00:04:17,560 --> 00:04:18,700 So tell me more about this. 136 00:04:18,700 --> 00:04:19,810 What was going on at 137 00:04:19,810 --> 00:04:21,550 Confluence when you realized 138 00:04:21,550 --> 00:04:23,080 you may need to bring in 139 00:04:23,080 --> 00:04:24,970 new elements to the roadmap? 140 00:04:25,190 --> 00:04:25,863 Sheryl: Yeah. 141 00:04:25,949 --> 00:04:27,659 so when I first joined 142 00:04:27,659 --> 00:04:29,189 Confluent, we had just 143 00:04:29,189 --> 00:04:30,749 launched our cloud connectors 144 00:04:30,749 --> 00:04:32,669 product and we were really 145 00:04:32,669 --> 00:04:34,199 trying to grow its adoption 146 00:04:34,259 --> 00:04:36,179 within our existing Confluent 147 00:04:36,179 --> 00:04:37,259 Cloud customer base. 148 00:04:38,069 --> 00:04:39,089 for those who are less 149 00:04:39,089 --> 00:04:41,129 familiar, connectors are 150 00:04:41,129 --> 00:04:42,809 prebuilt integrations that 151 00:04:42,809 --> 00:04:44,669 connect Kafka with popular 152 00:04:44,669 --> 00:04:46,589 data systems like your Oracle 153 00:04:46,589 --> 00:04:47,909 database, snowflake data 154 00:04:47,909 --> 00:04:49,769 warehouse, or your S3 buckets. 155 00:04:51,036 --> 00:04:53,136 Given its widespread adoption 156 00:04:53,286 --> 00:04:55,116 of, uh, with Kafka users in 157 00:04:55,116 --> 00:04:56,376 the open source community 158 00:04:56,616 --> 00:04:57,606 and just the critical 159 00:04:57,606 --> 00:04:59,196 role connectors play into 160 00:04:59,196 --> 00:05:00,936 bringing data on and off 161 00:05:00,936 --> 00:05:02,886 the platform, wanted to 162 00:05:02,886 --> 00:05:04,088 really un unan answer this 163 00:05:04,088 --> 00:05:05,738 question of why isn't the 164 00:05:05,738 --> 00:05:07,118 growth higher already? 165 00:05:07,568 --> 00:05:09,398 Was it an awareness problem? 166 00:05:09,398 --> 00:05:10,778 Were there product gaps? 167 00:05:11,084 --> 00:05:11,954 Was there a gap with 168 00:05:11,954 --> 00:05:13,244 sales and go to market. 169 00:05:13,723 --> 00:05:15,992 so to do that, I kicked off 170 00:05:15,992 --> 00:05:17,582 an investigation and decided 171 00:05:17,582 --> 00:05:19,442 to conduct interviews with 172 00:05:19,652 --> 00:05:21,422 the field folks and customers, 173 00:05:21,422 --> 00:05:23,582 as that's oftentimes you 174 00:05:23,582 --> 00:05:24,932 can get a lot of, uh, good 175 00:05:24,932 --> 00:05:26,552 insights and answers there. 176 00:05:27,242 --> 00:05:28,592 And as part of that process, 177 00:05:28,592 --> 00:05:30,572 I also partnered with the PM 178 00:05:30,812 --> 00:05:32,492 to drive those conversations 179 00:05:32,492 --> 00:05:34,352 so that we can both hear 180 00:05:34,352 --> 00:05:35,612 the feedback firsthand. 181 00:05:36,212 --> 00:05:36,542 Elle: Yes. 182 00:05:36,572 --> 00:05:36,782 Okay. 183 00:05:36,782 --> 00:05:37,502 So there's so much 184 00:05:37,502 --> 00:05:38,582 that you said there 185 00:05:38,582 --> 00:05:39,692 that I wanna unpack. 186 00:05:40,037 --> 00:05:41,237 first of all, what I love 187 00:05:41,237 --> 00:05:43,427 about how you described 188 00:05:43,427 --> 00:05:44,927 your process is that it's 189 00:05:44,927 --> 00:05:46,427 so true to who you are. 190 00:05:46,427 --> 00:05:47,447 It's scientific, it's 191 00:05:47,447 --> 00:05:48,947 methodical in terms 192 00:05:48,947 --> 00:05:50,147 of the investigation. 193 00:05:50,506 --> 00:05:52,207 really emulates that curiosity 194 00:05:52,207 --> 00:05:53,827 that you and most pmms. 195 00:05:54,099 --> 00:05:55,447 Have, okay. 196 00:05:55,447 --> 00:05:57,722 So let's say that, I'm 197 00:05:57,722 --> 00:06:00,302 inspired by this story and as 198 00:06:00,302 --> 00:06:02,312 a PMM in my own organization, 199 00:06:02,372 --> 00:06:03,932 I want to contribute to the 200 00:06:03,932 --> 00:06:05,432 product roadmap in my role 201 00:06:05,432 --> 00:06:06,902 today in the same, similar 202 00:06:06,902 --> 00:06:07,952 way that you and your 203 00:06:07,952 --> 00:06:09,572 team were able to impact 204 00:06:09,632 --> 00:06:10,862 your products roadmap. 205 00:06:11,162 --> 00:06:12,932 So let's outline the steps 206 00:06:12,932 --> 00:06:14,942 that A PMM would need to take. 207 00:06:15,572 --> 00:06:16,592 I guess what 208 00:06:16,652 --> 00:06:17,612 would step one be? 209 00:06:18,415 --> 00:06:18,830 Sheryl: So at Confluent 210 00:06:19,580 --> 00:06:21,050 pmms, we actually own 211 00:06:21,050 --> 00:06:22,550 the entire end-to-end, 212 00:06:22,550 --> 00:06:24,080 go to market motion from 213 00:06:24,080 --> 00:06:25,340 messaging to launches, 214 00:06:25,340 --> 00:06:26,450 and then also post-launch. 215 00:06:26,600 --> 00:06:27,110 Option. 216 00:06:28,520 --> 00:06:30,890 after a launch, we work 217 00:06:30,890 --> 00:06:32,630 together with PM to help 218 00:06:32,630 --> 00:06:33,920 drive product adoption 219 00:06:33,920 --> 00:06:35,210 and the revenue metrics. 220 00:06:35,930 --> 00:06:37,520 So I would say if you're 221 00:06:37,520 --> 00:06:39,230 not in a position where 222 00:06:39,230 --> 00:06:40,370 you officially own these 223 00:06:40,370 --> 00:06:41,990 metrics, I would still really 224 00:06:41,990 --> 00:06:43,730 encourage you to get curious 225 00:06:43,730 --> 00:06:45,530 about it and have regular 226 00:06:45,530 --> 00:06:47,300 syncs with your PM and data 227 00:06:47,300 --> 00:06:48,770 science teams to track them. 228 00:06:49,400 --> 00:06:50,450 And this is especially 229 00:06:50,450 --> 00:06:52,040 important if your company 230 00:06:52,040 --> 00:06:53,210 has consumption based 231 00:06:53,210 --> 00:06:54,980 pricing that's how you 232 00:06:54,980 --> 00:06:56,240 ultimately drive revenue. 233 00:06:56,865 --> 00:06:57,255 Elle: Yeah. 234 00:06:57,255 --> 00:06:58,005 Yes, of course. 235 00:06:58,035 --> 00:06:58,515 Okay, that makes 236 00:06:58,515 --> 00:06:59,205 a lot of sense. 237 00:06:59,462 --> 00:07:00,420 and it's, it's interesting 238 00:07:00,420 --> 00:07:01,899 that you said and brought 239 00:07:01,899 --> 00:07:04,419 up whether or not pmms own 240 00:07:04,419 --> 00:07:06,039 the metrics, because as 241 00:07:06,039 --> 00:07:07,779 you probably know, product 242 00:07:07,779 --> 00:07:08,769 marketing is so different 243 00:07:08,769 --> 00:07:10,839 in every organization, and 244 00:07:10,839 --> 00:07:12,459 sometimes product marketers 245 00:07:12,459 --> 00:07:13,689 and product managers, their 246 00:07:13,689 --> 00:07:14,769 roles and responsibilities 247 00:07:14,769 --> 00:07:16,449 blend with one another, 248 00:07:16,659 --> 00:07:17,409 which is why it's so 249 00:07:17,409 --> 00:07:18,939 important to be hand in hand. 250 00:07:19,179 --> 00:07:19,749 But from your 251 00:07:19,749 --> 00:07:21,309 perspective, why is it. 252 00:07:21,379 --> 00:07:23,029 Such a good best practice 253 00:07:23,029 --> 00:07:26,029 for pmms to monitor product 254 00:07:26,029 --> 00:07:27,414 adoption or similar metrics. 255 00:07:28,367 --> 00:07:29,807 Sheryl: Yeah, so when I'm 256 00:07:29,807 --> 00:07:31,067 thinking about the product 257 00:07:31,067 --> 00:07:32,477 marketing function, it's 258 00:07:32,477 --> 00:07:33,437 really the connective 259 00:07:33,437 --> 00:07:35,357 tissue between products, 260 00:07:35,357 --> 00:07:36,767 sales, and the customer. 261 00:07:37,017 --> 00:07:37,437 Elle: Mm-hmm. 262 00:07:37,457 --> 00:07:38,777 Sheryl: So when you do a 263 00:07:38,777 --> 00:07:40,757 launch beyond just the launch 264 00:07:40,757 --> 00:07:42,347 metrics, it's important 265 00:07:42,347 --> 00:07:43,847 that we aren't just sending 266 00:07:43,847 --> 00:07:45,017 out these products into the 267 00:07:45,017 --> 00:07:47,057 universe without knowing 268 00:07:47,117 --> 00:07:48,257 how it's being used. 269 00:07:48,257 --> 00:07:49,337 Who's using it? 270 00:07:49,752 --> 00:07:51,042 If it's being used at all. 271 00:07:51,372 --> 00:07:52,662 So I really encourage my 272 00:07:52,662 --> 00:07:54,132 team to feel a sense of 273 00:07:54,132 --> 00:07:56,442 ownership to what product 274 00:07:56,442 --> 00:07:57,702 and engineering are building 275 00:07:57,972 --> 00:07:58,932 and making sure that it 276 00:07:58,932 --> 00:08:00,372 actually resolves, uh, 277 00:08:00,372 --> 00:08:02,172 the customer pain and then 278 00:08:02,172 --> 00:08:03,642 channel that feedback back 279 00:08:03,642 --> 00:08:05,652 from the customers to the 280 00:08:05,652 --> 00:08:06,337 product and ENG teams. 281 00:08:06,993 --> 00:08:07,533 Elle: Yes. 282 00:08:07,533 --> 00:08:07,893 Yes. 283 00:08:07,893 --> 00:08:09,988 And just to double click 284 00:08:09,988 --> 00:08:11,608 on something you said, is 285 00:08:11,608 --> 00:08:12,568 that the feeling of the 286 00:08:12,568 --> 00:08:14,458 ownership and being able 287 00:08:14,458 --> 00:08:17,068 to look back and understand 288 00:08:17,068 --> 00:08:17,998 how the products that we're 289 00:08:17,998 --> 00:08:19,378 launching are influencing 290 00:08:19,378 --> 00:08:20,608 the rest of the world and 291 00:08:20,608 --> 00:08:21,958 influencing in particular our 292 00:08:21,958 --> 00:08:24,043 customers is so important. 293 00:08:24,043 --> 00:08:27,028 And as pmms, who should 294 00:08:27,028 --> 00:08:27,928 be wearing the customer 295 00:08:27,928 --> 00:08:29,848 shoes every day, looking 296 00:08:29,848 --> 00:08:31,918 at these insights, I 297 00:08:31,978 --> 00:08:33,268 think would just add 298 00:08:33,268 --> 00:08:34,828 additional color and value. 299 00:08:35,173 --> 00:08:37,393 To that overall analysis. 300 00:08:37,783 --> 00:08:38,083 okay. 301 00:08:38,083 --> 00:08:39,253 Very helpful, thank you. 302 00:08:39,283 --> 00:08:41,443 Okay, so first up is review 303 00:08:41,443 --> 00:08:42,943 that product data or adoption 304 00:08:42,943 --> 00:08:45,133 metrics, and then what's next? 305 00:08:45,163 --> 00:08:46,153 What's the next step? 306 00:08:46,614 --> 00:08:47,129 Sheryl: next step? 307 00:08:47,129 --> 00:08:48,104 is thinking about. 308 00:08:49,069 --> 00:08:50,689 How the product data and 309 00:08:50,689 --> 00:08:52,129 adoption metrics you've seen 310 00:08:52,279 --> 00:08:53,629 compare to where you need 311 00:08:53,629 --> 00:08:54,889 to be or where it should 312 00:08:54,889 --> 00:08:55,999 be or where you want to be. 313 00:08:56,989 --> 00:08:57,739 at Confluent, 314 00:08:57,739 --> 00:08:59,029 because we have this 315 00:08:59,168 --> 00:08:59,288 Elle: I. 316 00:08:59,389 --> 00:09:00,589 Sheryl: Source counterpart, 317 00:09:01,489 --> 00:09:02,989 we were able to compare 318 00:09:02,989 --> 00:09:05,119 and see like, hey, actually 319 00:09:05,119 --> 00:09:06,589 the open source connectors 320 00:09:06,589 --> 00:09:08,329 product has really good 321 00:09:08,329 --> 00:09:11,119 adoption with Kafka users, and 322 00:09:11,119 --> 00:09:12,379 that really needs to be our 323 00:09:12,379 --> 00:09:14,509 North Star for our own cloud 324 00:09:14,509 --> 00:09:15,859 connectors product as well. 325 00:09:16,669 --> 00:09:18,199 so to be able to answer that 326 00:09:18,199 --> 00:09:20,149 question, customers often 327 00:09:20,149 --> 00:09:21,829 have the answers to those, 328 00:09:22,341 --> 00:09:23,559 to those type of questions. 329 00:09:23,889 --> 00:09:25,209 And so that's why we decided 330 00:09:25,209 --> 00:09:27,173 to conduct interviews, and 331 00:09:27,173 --> 00:09:29,093 really get in deeper with 332 00:09:29,093 --> 00:09:30,503 the customers in terms of 333 00:09:30,953 --> 00:09:32,573 how and why and are they 334 00:09:32,573 --> 00:09:33,773 aware of this product. 335 00:09:34,439 --> 00:09:34,769 Elle: Yes. 336 00:09:34,799 --> 00:09:35,189 Okay. 337 00:09:35,189 --> 00:09:36,569 So you mentioned 338 00:09:36,629 --> 00:09:37,349 having some kind of 339 00:09:37,349 --> 00:09:38,639 benchmark for you guys. 340 00:09:38,639 --> 00:09:40,229 It was that, um, open 341 00:09:40,229 --> 00:09:42,659 source database, uh, but for 342 00:09:43,349 --> 00:09:45,004 potentially other pmms who. 343 00:09:46,020 --> 00:09:47,400 Don't have a similar 344 00:09:47,400 --> 00:09:48,120 benchmark, they'd have to 345 00:09:48,120 --> 00:09:49,740 create one of their own. 346 00:09:50,097 --> 00:09:51,507 so, but very good to note. 347 00:09:51,537 --> 00:09:54,027 Okay, so first is analyzing 348 00:09:54,027 --> 00:09:55,764 that data, the customer 349 00:09:55,820 --> 00:09:56,728 adoption, product, 350 00:09:56,728 --> 00:09:58,768 adoption, usage, et cetera. 351 00:09:59,368 --> 00:10:00,298 Measuring that 352 00:10:00,298 --> 00:10:01,528 against a benchmark. 353 00:10:01,798 --> 00:10:03,568 And once you identify some 354 00:10:03,568 --> 00:10:06,109 kind of, discrepancy or. 355 00:10:06,641 --> 00:10:08,512 maybe that your metrics are 356 00:10:08,512 --> 00:10:09,682 not where they should be. 357 00:10:10,012 --> 00:10:11,512 That's a signal that it's 358 00:10:11,512 --> 00:10:13,758 time to start discovering why 359 00:10:13,968 --> 00:10:15,438 that's hence the investigation 360 00:10:15,438 --> 00:10:16,458 aspect of that, right. 361 00:10:16,535 --> 00:10:17,375 where you started to do 362 00:10:17,375 --> 00:10:18,605 your customer interviews. 363 00:10:18,935 --> 00:10:21,845 So how did you conduct these 364 00:10:21,845 --> 00:10:23,045 interviews, I guess, like 365 00:10:23,190 --> 00:10:25,775 how did you determine who you 366 00:10:25,775 --> 00:10:28,072 needed to interview and, talk 367 00:10:28,072 --> 00:10:29,602 through that process with us? 368 00:10:30,137 --> 00:10:30,647 Sheryl: Yeah, that's 369 00:10:30,647 --> 00:10:31,457 a good question. 370 00:10:31,457 --> 00:10:32,777 So when you're determining 371 00:10:32,777 --> 00:10:34,487 who to interview, you 372 00:10:34,487 --> 00:10:36,137 have to start by defining 373 00:10:36,152 --> 00:10:36,857 who you're trying to 374 00:10:36,857 --> 00:10:38,357 target with this product. 375 00:10:39,257 --> 00:10:40,877 in my example of Cloud 376 00:10:40,877 --> 00:10:42,977 connectors, our target were 377 00:10:43,007 --> 00:10:44,327 confluent Cloud customers and. 378 00:10:46,032 --> 00:10:48,396 My PM and i, we sampled 379 00:10:48,456 --> 00:10:50,466 accounts across different 380 00:10:50,466 --> 00:10:52,536 geography and sizes for 381 00:10:52,536 --> 00:10:53,736 this interview so that we 382 00:10:53,736 --> 00:10:55,854 can get good coverage, of 383 00:10:55,854 --> 00:10:57,264 our potential customers. 384 00:10:58,284 --> 00:11:00,114 to generalize all of this, 385 00:11:00,114 --> 00:11:01,314 I would recommend that 386 00:11:01,314 --> 00:11:02,244 you work closely with 387 00:11:02,244 --> 00:11:03,984 your PM to help define 388 00:11:04,014 --> 00:11:05,514 that target account list. 389 00:11:05,863 --> 00:11:06,283 Elle: Mm-hmm. 390 00:11:06,324 --> 00:11:06,834 Sheryl: Then data 391 00:11:06,834 --> 00:11:07,674 science usually can 392 00:11:07,674 --> 00:11:08,604 help pull that list. 393 00:11:08,604 --> 00:11:09,384 If not your pm. 394 00:11:10,049 --> 00:11:10,469 Elle: Yes. 395 00:11:10,469 --> 00:11:11,519 So it's good to have an 396 00:11:11,519 --> 00:11:12,419 understanding of your 397 00:11:12,419 --> 00:11:14,129 ideal customer profile 398 00:11:14,129 --> 00:11:16,889 and make a short list of 399 00:11:16,889 --> 00:11:18,089 those target accounts. 400 00:11:18,449 --> 00:11:18,809 Okay. 401 00:11:18,869 --> 00:11:19,769 And then follow up 402 00:11:19,769 --> 00:11:21,779 question, what kind of 403 00:11:21,779 --> 00:11:24,509 questions did you ask to. 404 00:11:24,649 --> 00:11:25,789 These perspective, I 405 00:11:25,789 --> 00:11:26,959 guess like interviewees 406 00:11:26,959 --> 00:11:27,559 you could say. 407 00:11:28,168 --> 00:11:29,698 Sheryl: Yeah, so as we were 408 00:11:29,698 --> 00:11:31,498 scheduling the, the interviews 409 00:11:31,498 --> 00:11:33,418 with customers, we did draft, 410 00:11:33,696 --> 00:11:34,926 a short list of questions 411 00:11:34,926 --> 00:11:36,808 that we wanted to, make 412 00:11:36,808 --> 00:11:38,278 sure that we asked in every 413 00:11:38,278 --> 00:11:39,388 one of these interviews. 414 00:11:40,138 --> 00:11:41,458 a large part in our 415 00:11:41,458 --> 00:11:42,988 situation, they were. 416 00:11:43,274 --> 00:11:44,984 Discovery questions relating 417 00:11:44,984 --> 00:11:46,394 to our connectors product. 418 00:11:46,694 --> 00:11:48,074 So things like what 419 00:11:48,074 --> 00:11:49,424 type of data systems 420 00:11:49,424 --> 00:11:50,504 are in your tech stack. 421 00:11:50,834 --> 00:11:52,334 That way we would be able 422 00:11:52,334 --> 00:11:53,564 to know like what type of 423 00:11:53,564 --> 00:11:54,944 connectors uh, they would 424 00:11:55,123 --> 00:11:55,603 Elle: Uh, 425 00:11:55,966 --> 00:11:57,136 Sheryl: so understanding 426 00:11:57,136 --> 00:11:57,946 what they're currently 427 00:11:57,946 --> 00:11:59,266 using and why. 428 00:11:59,571 --> 00:12:00,411 There are also different 429 00:12:00,411 --> 00:12:02,001 alternatives for this product. 430 00:12:02,001 --> 00:12:02,871 So like I mentioned, 431 00:12:02,871 --> 00:12:04,011 there's an open source 432 00:12:04,281 --> 00:12:05,661 alternative they could 433 00:12:05,661 --> 00:12:06,921 build and, and create their 434 00:12:06,921 --> 00:12:08,241 own connector as well. 435 00:12:08,481 --> 00:12:09,621 So we wanted to really 436 00:12:09,621 --> 00:12:11,991 dig into, Uh, why they've 437 00:12:11,991 --> 00:12:13,371 made their choice and how 438 00:12:13,371 --> 00:12:16,071 open they are to adopting 439 00:12:16,071 --> 00:12:17,331 cloud connectors based on 440 00:12:17,331 --> 00:12:18,561 their current pain points. 441 00:12:19,107 --> 00:12:20,787 and then the last part is 442 00:12:20,787 --> 00:12:22,047 a bit more technical, and 443 00:12:22,047 --> 00:12:22,917 part of the reason why I 444 00:12:22,917 --> 00:12:24,327 wanted PM to sit into this 445 00:12:24,327 --> 00:12:26,697 conversation is in case there 446 00:12:26,697 --> 00:12:28,017 were product or technical 447 00:12:28,017 --> 00:12:29,757 blockers, we wanted to have 448 00:12:29,757 --> 00:12:30,957 the PM on the call to just 449 00:12:30,957 --> 00:12:32,247 dig in a little bit deeper. 450 00:12:32,307 --> 00:12:32,667 So we're 451 00:12:32,847 --> 00:12:33,987 Elle: Uh, for why. 452 00:12:34,677 --> 00:12:35,187 Yeah. 453 00:12:35,217 --> 00:12:35,697 Yeah. 454 00:12:35,727 --> 00:12:36,987 What's really interesting 455 00:12:36,987 --> 00:12:38,187 about how you structured 456 00:12:38,187 --> 00:12:39,837 your interview questions is 457 00:12:39,837 --> 00:12:42,327 that they almost mirror a 458 00:12:42,327 --> 00:12:44,307 positioning statement, right. 459 00:12:44,307 --> 00:12:46,532 You've uncovered the exact, 460 00:12:46,767 --> 00:12:47,787 that that first part of the 461 00:12:47,787 --> 00:12:48,657 positioning statement of 462 00:12:48,657 --> 00:12:49,857 who this is for with your 463 00:12:49,857 --> 00:12:51,027 ideal customer profile. 464 00:12:51,027 --> 00:12:51,627 Those are the people 465 00:12:51,627 --> 00:12:52,467 that you're interviewing. 466 00:12:53,012 --> 00:12:55,363 And then you try to 467 00:12:55,363 --> 00:12:56,533 uncover the pain points. 468 00:12:56,533 --> 00:12:57,853 That's what they're, um, 469 00:12:57,853 --> 00:12:59,083 the pains or tr challenges 470 00:12:59,083 --> 00:13:00,343 they're experiencing. 471 00:13:00,682 --> 00:13:01,642 and then the alternatives 472 00:13:01,642 --> 00:13:03,357 I. Who you know, right? 473 00:13:03,357 --> 00:13:05,217 That like, unlike X, Y, 474 00:13:05,217 --> 00:13:07,151 Z, you know, vendors. 475 00:13:07,151 --> 00:13:07,991 So the ineffective 476 00:13:07,991 --> 00:13:08,621 alternatives. 477 00:13:08,621 --> 00:13:09,581 I really like that you 478 00:13:09,581 --> 00:13:10,691 dug into that because 479 00:13:11,201 --> 00:13:13,301 sometimes that's missed 480 00:13:13,601 --> 00:13:15,791 in PMM investigation 481 00:13:15,791 --> 00:13:16,871 and research work when 482 00:13:16,871 --> 00:13:17,681 talking to customers. 483 00:13:17,681 --> 00:13:18,551 So I think that's really 484 00:13:18,551 --> 00:13:19,784 critical, that you 485 00:13:19,814 --> 00:13:20,804 included that into the 486 00:13:20,804 --> 00:13:22,394 interview questions. 487 00:13:22,634 --> 00:13:24,044 Okay, so quick recap. 488 00:13:24,104 --> 00:13:25,784 You step one. 489 00:13:26,079 --> 00:13:28,419 Looked at the product 490 00:13:28,479 --> 00:13:30,339 adoption metrics. 491 00:13:30,788 --> 00:13:33,548 step two, you did, um, some 492 00:13:33,548 --> 00:13:35,018 kind of benchmark analysis 493 00:13:35,018 --> 00:13:36,668 to see where your metrics 494 00:13:36,668 --> 00:13:38,348 stood against where you 495 00:13:38,348 --> 00:13:39,818 think they should be created, 496 00:13:39,818 --> 00:13:41,198 that North Star vision. 497 00:13:41,761 --> 00:13:42,721 I guess part of step two 498 00:13:42,721 --> 00:13:44,075 slash step three, did 499 00:13:44,075 --> 00:13:45,785 the investigation and the 500 00:13:45,785 --> 00:13:47,435 interviews with customers 501 00:13:47,945 --> 00:13:49,085 with PM in the room. 502 00:13:49,115 --> 00:13:49,655 I think that it's a 503 00:13:49,655 --> 00:13:50,945 very important tip. 504 00:13:51,425 --> 00:13:52,805 Uh, so what's next? 505 00:13:52,805 --> 00:13:53,855 After you did all 506 00:13:53,855 --> 00:13:54,995 of this research and 507 00:13:54,995 --> 00:13:55,895 then interviewing? 508 00:13:55,895 --> 00:13:55,925 I, 509 00:13:56,622 --> 00:13:57,492 Sheryl: Yeah, maybe I'll 510 00:13:57,492 --> 00:13:59,142 start by sharing some 511 00:13:59,142 --> 00:14:00,552 of our findings from the 512 00:14:00,602 --> 00:14:01,617 Elle: uh, yes. 513 00:14:01,747 --> 00:14:02,707 Sheryl: so from these 514 00:14:02,707 --> 00:14:04,357 calls, three key 515 00:14:04,627 --> 00:14:06,187 themes really surfaced, 516 00:14:06,275 --> 00:14:07,445 from, from customers. 517 00:14:07,445 --> 00:14:09,875 So the first one was around 518 00:14:10,295 --> 00:14:12,035 the fact that they needed 519 00:14:12,622 --> 00:14:14,542 variety of connectors to, 520 00:14:14,572 --> 00:14:15,982 to be able to connect to the 521 00:14:15,982 --> 00:14:17,212 different data systems they 522 00:14:17,212 --> 00:14:18,802 have in their tech stack. 523 00:14:19,102 --> 00:14:20,572 So about the breadth of 524 00:14:20,572 --> 00:14:21,772 our connector portfolio. 525 00:14:22,222 --> 00:14:23,632 Now, this was a problem 526 00:14:23,632 --> 00:14:25,372 that we were aware of. 527 00:14:25,702 --> 00:14:26,782 Uh, since this was a new 528 00:14:26,782 --> 00:14:28,762 product, um, we were rapidly 529 00:14:28,762 --> 00:14:30,832 adding more connectors rapidly 530 00:14:31,012 --> 00:14:32,572 to our roadmap, and it's 531 00:14:32,572 --> 00:14:33,622 already there and it should 532 00:14:33,622 --> 00:14:35,151 be resolved, fairly shortly. 533 00:14:35,796 --> 00:14:36,816 The second thing that we 534 00:14:36,816 --> 00:14:38,856 learned was that during the 535 00:14:38,856 --> 00:14:40,806 configuration and and setup 536 00:14:40,896 --> 00:14:42,246 of launching these cloud 537 00:14:42,246 --> 00:14:43,866 connectors, there were some 538 00:14:44,076 --> 00:14:45,666 unexpected friction points, 539 00:14:46,082 --> 00:14:47,312 that the customers brought up. 540 00:14:47,312 --> 00:14:49,442 And so with that, we've 541 00:14:49,442 --> 00:14:51,542 built in additional usability 542 00:14:51,542 --> 00:14:53,372 features into the product 543 00:14:53,372 --> 00:14:54,932 roadmap to help make all 544 00:14:54,932 --> 00:14:56,192 of that a bit easier. 545 00:14:57,062 --> 00:14:58,832 Now, the third thing that we 546 00:14:58,832 --> 00:15:01,316 realized, this was what really 547 00:15:01,466 --> 00:15:02,846 brought us back and, and. 548 00:15:03,266 --> 00:15:04,736 To the roadmap and, and really 549 00:15:04,736 --> 00:15:06,206 take a look at it end to end. 550 00:15:06,626 --> 00:15:08,396 It was that we've realized 551 00:15:08,396 --> 00:15:11,366 that with customers, are 552 00:15:11,366 --> 00:15:13,556 aware of the benefits of using 553 00:15:13,646 --> 00:15:15,536 cloud connectors, but they 554 00:15:15,536 --> 00:15:17,366 actually, they want to use it, 555 00:15:17,606 --> 00:15:19,256 but they are not able to do so 556 00:15:19,286 --> 00:15:20,816 because they're storing their 557 00:15:20,816 --> 00:15:22,526 most sensitive customer data 558 00:15:22,796 --> 00:15:24,191 in their Oracle databases. 559 00:15:24,390 --> 00:15:25,170 Elle: Of course. 560 00:15:25,230 --> 00:15:25,590 Yeah. 561 00:15:25,886 --> 00:15:27,206 Sheryl: With a cloud product 562 00:15:27,206 --> 00:15:28,406 and sending all that. 563 00:15:28,721 --> 00:15:29,621 Sensitive data 564 00:15:29,621 --> 00:15:30,611 over the internet. 565 00:15:30,971 --> 00:15:32,351 That's not something that 566 00:15:32,351 --> 00:15:34,001 their company's InfoSec policy 567 00:15:34,001 --> 00:15:35,201 will allow them to do, and 568 00:15:35,201 --> 00:15:36,761 that's just, uh, not something 569 00:15:36,761 --> 00:15:38,051 they're comfortable pursuing. 570 00:15:38,771 --> 00:15:40,961 that really informed us of 571 00:15:40,961 --> 00:15:43,061 a pressing need, this hard 572 00:15:43,061 --> 00:15:45,101 technical blocker of having 573 00:15:45,101 --> 00:15:46,601 connector private networking, 574 00:15:47,381 --> 00:15:48,881 was not something that we knew 575 00:15:48,881 --> 00:15:51,431 was so important and forefront 576 00:15:51,491 --> 00:15:52,901 in our customer's evaluation. 577 00:15:53,644 --> 00:15:54,184 Elle: Wow. 578 00:15:54,214 --> 00:15:54,394 Okay. 579 00:15:54,394 --> 00:15:55,174 So interesting. 580 00:15:55,174 --> 00:15:56,284 So there were some things 581 00:15:56,284 --> 00:15:56,944 where you were able to 582 00:15:56,944 --> 00:15:58,054 immediately influence the 583 00:15:58,054 --> 00:15:59,764 product roadmap and get 584 00:15:59,764 --> 00:16:00,814 those features created, 585 00:16:01,024 --> 00:16:01,984 but some which are a bit 586 00:16:01,984 --> 00:16:04,984 more technical and complex. 587 00:16:05,075 --> 00:16:05,973 it's a really interesting 588 00:16:05,973 --> 00:16:07,173 point because. 589 00:16:07,552 --> 00:16:08,752 Potentially surprising as 590 00:16:08,752 --> 00:16:10,972 well and a good, another 591 00:16:10,972 --> 00:16:13,162 good reason why to have PM 592 00:16:13,343 --> 00:16:15,293 in the room with you when 593 00:16:15,293 --> 00:16:16,523 you're doing these interviews. 594 00:16:16,583 --> 00:16:18,053 So what do you do in that 595 00:16:18,053 --> 00:16:20,221 scenario where you get a 596 00:16:20,221 --> 00:16:21,661 pretty surprising piece 597 00:16:21,661 --> 00:16:23,431 of feedback that's pretty 598 00:16:23,431 --> 00:16:25,591 serious and a technical 599 00:16:25,591 --> 00:16:27,871 blocker for your product? 600 00:16:27,871 --> 00:16:28,411 What do, what do you 601 00:16:28,411 --> 00:16:29,776 do in that scenario? 602 00:16:30,276 --> 00:16:31,326 Sheryl: Well, first of all, 603 00:16:31,326 --> 00:16:32,526 in the interview, since 604 00:16:32,526 --> 00:16:34,146 PM was in the room, they 605 00:16:34,146 --> 00:16:35,826 were actually able to dig 606 00:16:35,886 --> 00:16:37,806 deeper into the specific 607 00:16:37,806 --> 00:16:39,876 requirements that would. 608 00:16:40,341 --> 00:16:42,161 Enable, our customers to 609 00:16:42,161 --> 00:16:43,781 use our cloud connectors. 610 00:16:43,781 --> 00:16:45,581 And so with that and the 611 00:16:45,581 --> 00:16:46,751 themes that we've surfaced 612 00:16:46,751 --> 00:16:48,761 from these calls, we were able 613 00:16:48,761 --> 00:16:51,022 to gather, these meaningful 614 00:16:51,022 --> 00:16:52,732 qualitative insights. 615 00:16:52,738 --> 00:16:54,442 And we wanted to do a readout 616 00:16:54,602 --> 00:16:56,138 to share our our findings. 617 00:16:56,633 --> 00:16:58,912 And so with this presentation, 618 00:16:59,166 --> 00:17:00,794 we also included customer 619 00:17:00,794 --> 00:17:02,684 quotes and little soundbites 620 00:17:02,684 --> 00:17:03,854 from the call just 621 00:17:03,924 --> 00:17:04,514 to bring that 622 00:17:04,574 --> 00:17:05,594 All to life since our 623 00:17:05,704 --> 00:17:06,174 audience 624 00:17:06,174 --> 00:17:07,924 weren't in the calls with us. 625 00:17:07,924 --> 00:17:08,377 And then the, 626 00:17:08,412 --> 00:17:09,667 The other key Part of this 627 00:17:09,667 --> 00:17:12,127 readout was to make the 628 00:17:12,127 --> 00:17:13,297 recommendation to move 629 00:17:13,297 --> 00:17:15,157 up the timelines for this 630 00:17:15,157 --> 00:17:16,717 private networking features, 631 00:17:16,732 --> 00:17:18,127 as that's really the key 632 00:17:18,127 --> 00:17:19,807 feature that would unlock 633 00:17:19,807 --> 00:17:21,307 our customers, uh, to be 634 00:17:21,307 --> 00:17:22,957 able to use this product. 635 00:17:22,957 --> 00:17:23,977 However, whenever you're 636 00:17:23,977 --> 00:17:25,117 doing that, you're really 637 00:17:25,117 --> 00:17:27,067 making trade offs, so we 638 00:17:27,067 --> 00:17:28,477 wanted to be able to size 639 00:17:28,477 --> 00:17:30,187 this opportunity with a 640 00:17:30,187 --> 00:17:31,747 business case to be able 641 00:17:31,747 --> 00:17:33,157 to anticipate the questions 642 00:17:33,157 --> 00:17:34,395 that we might receive. 643 00:17:34,395 --> 00:17:35,475 Elle: Oh, very smart. 644 00:17:35,505 --> 00:17:38,687 Okay, so you, created this 645 00:17:38,687 --> 00:17:40,907 business case, essentially 646 00:17:40,907 --> 00:17:42,767 the readout for some 647 00:17:42,767 --> 00:17:44,267 internal stakeholders 648 00:17:44,597 --> 00:17:46,281 to, make the proposal and 649 00:17:46,281 --> 00:17:48,801 recommendation to move up. 650 00:17:48,891 --> 00:17:51,081 These really, I don't wanna 651 00:17:51,081 --> 00:17:52,221 say monstrous, because I'm, 652 00:17:52,221 --> 00:17:53,469 maybe I'm not, I don't know 653 00:17:53,469 --> 00:17:54,579 if I'm technical enough to 654 00:17:54,579 --> 00:17:55,744 call it quite that, but. 655 00:17:56,349 --> 00:17:57,819 We'll say pretty lofty 656 00:17:58,059 --> 00:17:59,199 road blockers for your 657 00:17:59,199 --> 00:18:00,339 customers that maybe 658 00:18:00,339 --> 00:18:01,449 weren't on the roadmap, 659 00:18:01,449 --> 00:18:02,709 but just not for a while. 660 00:18:02,889 --> 00:18:04,427 So, this business case 661 00:18:04,427 --> 00:18:07,037 can help justify why you 662 00:18:07,037 --> 00:18:08,087 would need to move that up. 663 00:18:08,087 --> 00:18:09,047 And as part of the business 664 00:18:09,047 --> 00:18:10,367 case, you sized the 665 00:18:10,367 --> 00:18:11,927 opportunity and I guess the 666 00:18:11,927 --> 00:18:13,927 business value and benefit to 667 00:18:13,927 --> 00:18:15,382 doing, uh, taking that action. 668 00:18:16,598 --> 00:18:16,898 Sheryl: Yeah. 669 00:18:16,898 --> 00:18:18,068 no, that's exactly right. 670 00:18:18,068 --> 00:18:19,058 So with a business case, 671 00:18:19,058 --> 00:18:19,988 you're basically making a 672 00:18:19,988 --> 00:18:22,418 financial model based on a 673 00:18:22,418 --> 00:18:23,978 set of reasonable assumptions. 674 00:18:24,218 --> 00:18:24,908 And then looking at 675 00:18:24,908 --> 00:18:26,018 what that upside is. 676 00:18:26,018 --> 00:18:27,728 If you did, uh, release 677 00:18:27,728 --> 00:18:29,018 this feature and all these 678 00:18:29,018 --> 00:18:30,248 customers were able to 679 00:18:30,248 --> 00:18:31,586 use, cloud connectors. 680 00:18:32,493 --> 00:18:33,273 Elle: And who was the 681 00:18:33,273 --> 00:18:34,458 audience for the readout 682 00:18:34,458 --> 00:18:35,643 for this business case? 683 00:18:35,643 --> 00:18:35,673 I. 684 00:18:36,318 --> 00:18:37,518 Sheryl: in our case, we 685 00:18:37,518 --> 00:18:39,498 did the presentation to our 686 00:18:39,498 --> 00:18:41,358 C-Suite executives, and the 687 00:18:41,358 --> 00:18:43,218 reason why we needed, needed, 688 00:18:43,889 --> 00:18:44,939 at the highest leadership 689 00:18:44,939 --> 00:18:46,649 level was because we needed. 690 00:18:47,894 --> 00:18:49,574 across the organization. 691 00:18:50,024 --> 00:18:51,674 And that's because private 692 00:18:51,674 --> 00:18:53,294 networking features were 693 00:18:53,294 --> 00:18:55,274 owned by, not by the Connect 694 00:18:55,274 --> 00:18:56,504 product team, but by a 695 00:18:56,504 --> 00:18:58,274 separate, uh, networking team. 696 00:18:58,724 --> 00:19:00,644 And so meeting this customer 697 00:19:00,644 --> 00:19:02,264 need required shifting 698 00:19:02,264 --> 00:19:04,037 resources, for the next 699 00:19:04,037 --> 00:19:05,237 two years essentially. 700 00:19:06,017 --> 00:19:07,667 so we were in a fortunate 701 00:19:07,667 --> 00:19:09,557 position at Confluent as PMM 702 00:19:09,677 --> 00:19:11,597 is a strategic function here. 703 00:19:11,987 --> 00:19:13,457 And so we already had. 704 00:19:14,492 --> 00:19:16,052 syncs and direct access 705 00:19:16,052 --> 00:19:17,312 to that leadership level. 706 00:19:17,732 --> 00:19:19,262 However, if you are not 707 00:19:19,262 --> 00:19:21,122 in that position, I would 708 00:19:21,122 --> 00:19:22,622 recommend going through an 709 00:19:22,622 --> 00:19:24,392 exec sponsor If you don't 710 00:19:24,392 --> 00:19:25,772 already have a CF table, I. 711 00:19:26,362 --> 00:19:27,392 Elle: Yeah, great tip. 712 00:19:27,392 --> 00:19:29,912 Who would be a good executive 713 00:19:29,912 --> 00:19:31,562 sponsor in your opinion? 714 00:19:32,362 --> 00:19:32,752 Sheryl: Yes. 715 00:19:32,752 --> 00:19:34,012 So since this is about 716 00:19:34,012 --> 00:19:35,332 the product roadmap, I. 717 00:19:35,332 --> 00:19:36,232 think you should find 718 00:19:36,292 --> 00:19:38,032 a PM leader who really 719 00:19:38,356 --> 00:19:38,476 Elle: I. 720 00:19:39,037 --> 00:19:40,267 Sheryl: about the outcome of 721 00:19:40,507 --> 00:19:42,187 product adoption and revenue. 722 00:19:42,802 --> 00:19:43,342 Elle: Yeah, 723 00:19:43,927 --> 00:19:44,797 Sheryl: them looped into 724 00:19:45,487 --> 00:19:46,777 the whole investigation 725 00:19:46,987 --> 00:19:48,997 also makes that easy, since 726 00:19:48,997 --> 00:19:50,377 they also want to do what's 727 00:19:50,377 --> 00:19:51,577 best for their product. 728 00:19:52,042 --> 00:19:52,402 Elle: yeah. 729 00:19:52,462 --> 00:19:54,292 Yet another reason to be 730 00:19:54,292 --> 00:19:55,762 hand in hand with your 731 00:19:55,762 --> 00:19:57,112 product counterparts. 732 00:19:57,864 --> 00:19:58,084 tip. 733 00:19:58,199 --> 00:19:59,819 Okay, so once you got the 734 00:19:59,819 --> 00:20:01,679 green light, how did you 735 00:20:01,679 --> 00:20:02,939 kind of tie up loose ends? 736 00:20:03,544 --> 00:20:04,144 Sheryl: Hmm. 737 00:20:06,094 --> 00:20:07,294 in real life, if you 738 00:20:07,294 --> 00:20:08,614 know anything about 739 00:20:08,944 --> 00:20:10,084 cloud networking, which 740 00:20:10,084 --> 00:20:11,194 I think you do al, 741 00:20:11,313 --> 00:20:13,053 Elle: I do working at Cisco. 742 00:20:13,053 --> 00:20:14,253 That is our bread and butter. 743 00:20:14,974 --> 00:20:16,354 Sheryl: It's a super hard 744 00:20:16,354 --> 00:20:17,464 problem to solve, and 745 00:20:17,464 --> 00:20:18,844 not one that you know 746 00:20:18,934 --> 00:20:20,314 has an easy solution. 747 00:20:20,734 --> 00:20:22,611 So these networking features 748 00:20:22,611 --> 00:20:24,201 actually got released over 749 00:20:24,201 --> 00:20:26,091 many quarters, and as they 750 00:20:26,091 --> 00:20:27,591 were released by cloud, 751 00:20:27,591 --> 00:20:29,271 by region, we had to make 752 00:20:29,271 --> 00:20:31,041 sure that we then go back 753 00:20:31,041 --> 00:20:32,451 and activate the field 754 00:20:32,451 --> 00:20:33,921 and notify the customers 755 00:20:34,161 --> 00:20:35,361 who gave that feedback. 756 00:20:35,856 --> 00:20:38,085 We also made comms, out 757 00:20:38,085 --> 00:20:39,525 to all of new confluent 758 00:20:39,525 --> 00:20:40,515 cloud customers that 759 00:20:40,515 --> 00:20:42,255 we've acquired over this, 760 00:20:42,338 --> 00:20:43,415 long period of time. 761 00:20:44,075 --> 00:20:44,975 And it's important to 762 00:20:44,975 --> 00:20:46,235 go and circle back. 763 00:20:46,325 --> 00:20:47,495 Otherwise, that business 764 00:20:47,495 --> 00:20:48,665 case would just stay as 765 00:20:48,665 --> 00:20:49,895 a model in Excel, right? 766 00:20:49,895 --> 00:20:51,125 You're making assumptions 767 00:20:51,125 --> 00:20:53,135 that you are unlocking 768 00:20:53,135 --> 00:20:54,515 and unblocking customers 769 00:20:55,385 --> 00:20:57,096 the quarters, in order 770 00:20:57,096 --> 00:20:58,146 to see that upside. 771 00:20:58,880 --> 00:20:59,600 Elle: Yeah, it's, 772 00:20:59,998 --> 00:21:00,973 Sheryl: you know, due to 773 00:21:01,033 --> 00:21:02,383 product and our go-to-market 774 00:21:02,383 --> 00:21:04,278 efforts, we have, grown 775 00:21:04,278 --> 00:21:05,208 our product adoption 776 00:21:05,208 --> 00:21:06,528 metrics for connectors 777 00:21:06,828 --> 00:21:08,148 significantly since then. 778 00:21:08,446 --> 00:21:08,954 Elle: brilliant. 779 00:21:08,954 --> 00:21:09,884 And I just wanna note 780 00:21:09,884 --> 00:21:11,475 that it was thoughtful. 781 00:21:11,619 --> 00:21:12,939 To circle back with 782 00:21:12,939 --> 00:21:13,989 the customers that you 783 00:21:13,989 --> 00:21:15,699 interviewed, to give them 784 00:21:15,879 --> 00:21:17,229 just some communication 785 00:21:17,439 --> 00:21:19,029 around how they're taking 786 00:21:19,029 --> 00:21:20,561 a part in influencing and 787 00:21:20,561 --> 00:21:21,761 shaping the roadmap too. 788 00:21:22,122 --> 00:21:23,209 I could imagine as a customer 789 00:21:23,209 --> 00:21:24,529 how that could go a long way 790 00:21:24,829 --> 00:21:26,389 in terms of feeling valued. 791 00:21:26,669 --> 00:21:28,035 in my experience, sometimes 792 00:21:28,035 --> 00:21:28,905 customers will even 793 00:21:28,905 --> 00:21:30,375 choose a vendor because 794 00:21:30,375 --> 00:21:32,175 they get to take part. 795 00:21:32,259 --> 00:21:33,369 In shaping the roadmap 796 00:21:33,369 --> 00:21:34,149 for the products that 797 00:21:34,149 --> 00:21:35,279 they use every day. 798 00:21:35,672 --> 00:21:36,962 so very helpful. 799 00:21:36,962 --> 00:21:38,642 So last question for you, 800 00:21:38,642 --> 00:21:40,292 Sheryl, on this topic. 801 00:21:40,802 --> 00:21:42,242 What piece of advice do 802 00:21:42,242 --> 00:21:43,442 you have for a product 803 00:21:43,442 --> 00:21:45,010 marketer who is trying to 804 00:21:45,010 --> 00:21:46,532 shape the product roadmap? 805 00:21:46,797 --> 00:21:48,297 Sheryl: Yeah, I would really 806 00:21:48,297 --> 00:21:49,887 advise that you build a 807 00:21:49,887 --> 00:21:51,537 strong relationship with 808 00:21:51,537 --> 00:21:53,427 product management and 809 00:21:53,517 --> 00:21:54,687 realistically, it takes 810 00:21:54,687 --> 00:21:56,127 time to build that trust. 811 00:21:56,547 --> 00:21:58,167 And what I encourage my 812 00:21:58,167 --> 00:21:59,277 team to do is to have 813 00:21:59,277 --> 00:22:00,507 regular things with them, 814 00:22:00,807 --> 00:22:01,947 to learn about their product 815 00:22:01,947 --> 00:22:03,817 vision, their roadmap, get 816 00:22:03,837 --> 00:22:05,457 to know them personally. 817 00:22:05,457 --> 00:22:06,027 And when you're 818 00:22:06,027 --> 00:22:07,407 working with pm. 819 00:22:08,007 --> 00:22:09,297 Especially for such a 820 00:22:09,297 --> 00:22:10,347 technical product that we 821 00:22:10,347 --> 00:22:12,207 have at Confluent, don't 822 00:22:12,207 --> 00:22:14,172 be afraid to ask questions. 823 00:22:14,172 --> 00:22:14,757 And I, I. 824 00:22:14,757 --> 00:22:16,017 think that really shows 825 00:22:16,017 --> 00:22:17,607 your genuine curiosity 826 00:22:17,607 --> 00:22:19,527 into the technology and 827 00:22:19,527 --> 00:22:20,547 willingness to learn. 828 00:22:20,734 --> 00:22:21,897 I've always found that 829 00:22:21,897 --> 00:22:24,208 PMs are really patient in 830 00:22:24,208 --> 00:22:26,278 educating you, and they 831 00:22:26,308 --> 00:22:28,348 find that as a signal of 832 00:22:28,348 --> 00:22:29,698 trust as well for you. 833 00:22:30,598 --> 00:22:31,888 And then finally, when you're 834 00:22:31,888 --> 00:22:32,938 working through your first 835 00:22:32,938 --> 00:22:34,378 launch together with your pm, 836 00:22:34,737 --> 00:22:35,907 they will be able to see the 837 00:22:35,907 --> 00:22:38,637 value that PMM brings into 838 00:22:38,637 --> 00:22:40,347 making all the hard work, 839 00:22:40,351 --> 00:22:42,518 for them and their ENG teams 840 00:22:42,518 --> 00:22:44,287 and bringing that to market. 841 00:22:44,340 --> 00:22:45,210 Elle: so with that. 842 00:22:45,372 --> 00:22:46,992 I would like to move on 843 00:22:46,992 --> 00:22:48,792 to the next segment of our 844 00:22:48,792 --> 00:22:51,282 show, the messaging critique. 845 00:22:51,659 --> 00:22:53,758 alright, so in this segment 846 00:22:53,788 --> 00:22:55,348 of the show, this is where 847 00:22:55,348 --> 00:22:57,058 Sheryl, you and I, as product 848 00:22:57,058 --> 00:22:58,318 marketing experts get to 849 00:22:58,318 --> 00:23:00,718 analyze real world messaging. 850 00:23:01,347 --> 00:23:03,087 it's so fun because you, 851 00:23:03,087 --> 00:23:04,257 Sheryl, my guest, get 852 00:23:04,257 --> 00:23:05,337 to pick the company. 853 00:23:05,907 --> 00:23:07,257 But before we get started, I 854 00:23:07,257 --> 00:23:08,907 want to lay out some ground 855 00:23:08,907 --> 00:23:10,647 rules for our listeners who 856 00:23:10,647 --> 00:23:11,967 may not be familiar with 857 00:23:11,967 --> 00:23:12,987 this segment of the show. 858 00:23:13,257 --> 00:23:15,313 So first, I want to 859 00:23:15,313 --> 00:23:15,913 hear something that 860 00:23:15,913 --> 00:23:17,023 you're loving about the 861 00:23:17,023 --> 00:23:18,673 messaging, what's working. 862 00:23:19,023 --> 00:23:19,953 What's not working? 863 00:23:20,043 --> 00:23:22,053 And then, uh, second, maybe 864 00:23:22,053 --> 00:23:23,013 share something that you wish 865 00:23:23,013 --> 00:23:24,723 the PMM would've considered 866 00:23:24,723 --> 00:23:25,803 or done differently. 867 00:23:26,043 --> 00:23:27,693 And thirdly, how could 868 00:23:27,693 --> 00:23:29,673 this PMM iterate on the 869 00:23:29,673 --> 00:23:31,983 messaging or storytelling? 870 00:23:31,983 --> 00:23:32,433 Like, what's a 871 00:23:32,433 --> 00:23:33,603 creative campaign or 872 00:23:33,603 --> 00:23:34,413 asset they could do? 873 00:23:34,413 --> 00:23:36,183 It's just fun brainstorming. 874 00:23:36,444 --> 00:23:38,240 and maybe a plug for that PMM 875 00:23:38,240 --> 00:23:39,590 who could be listening to, 876 00:23:40,074 --> 00:23:41,216 take it to the next level. 877 00:23:41,769 --> 00:23:43,268 okay, so with that, 878 00:23:43,358 --> 00:23:45,578 Sheryl, tell me what is 879 00:23:45,578 --> 00:23:46,778 a product or company that 880 00:23:46,778 --> 00:23:48,128 has caught your attention? 881 00:23:48,248 --> 00:23:49,058 Good, bad, or 882 00:23:49,058 --> 00:23:49,958 somewhere in between. 883 00:23:50,586 --> 00:23:51,426 Sheryl: Oh, I'm so excited 884 00:23:51,426 --> 00:23:53,286 for this segment and I 885 00:23:53,431 --> 00:23:54,241 Elle: It's so fun. 886 00:23:54,816 --> 00:23:55,236 Sheryl: I have two 887 00:23:55,381 --> 00:23:56,101 Elle: I love it. 888 00:23:56,479 --> 00:23:57,619 Sheryl: so when you originally 889 00:23:57,619 --> 00:23:58,879 came to me with this, and 890 00:23:58,879 --> 00:24:00,199 you mentioned about loving 891 00:24:00,199 --> 00:24:01,489 the messaging, I couldn't 892 00:24:01,489 --> 00:24:02,839 help but think of Apple 893 00:24:02,909 --> 00:24:03,029 Elle: I, 894 00:24:03,439 --> 00:24:04,399 Sheryl: and specifically 895 00:24:04,664 --> 00:24:05,069 Elle: of course. 896 00:24:05,963 --> 00:24:07,223 Sheryl: with their launch of 897 00:24:07,223 --> 00:24:08,873 the Dynamic Island feature. 898 00:24:09,613 --> 00:24:10,003 Elle: Okay. 899 00:24:10,003 --> 00:24:11,953 I have to admit, I had 900 00:24:11,953 --> 00:24:13,573 never heard of this before, 901 00:24:13,693 --> 00:24:14,555 and I don't know if maybe 902 00:24:14,555 --> 00:24:15,725 that's because I'm not 903 00:24:15,935 --> 00:24:17,811 a big enough Apple fan, 904 00:24:17,841 --> 00:24:19,300 which I, thought I was, 905 00:24:19,300 --> 00:24:21,130 but tell me more about it. 906 00:24:21,596 --> 00:24:22,436 Sheryl: Yeah, well 907 00:24:22,436 --> 00:24:23,486 you may not know it. 908 00:24:23,486 --> 00:24:25,166 by that name, but Dynamic 909 00:24:25,196 --> 00:24:26,636 Island is essentially that 910 00:24:26,636 --> 00:24:27,746 pill shaped cutout you 911 00:24:27,746 --> 00:24:29,006 have on top of your iPhone. 912 00:24:29,486 --> 00:24:32,276 And that replaced the notch on 913 00:24:32,276 --> 00:24:34,709 iPhone 14 versions or later. 914 00:24:35,519 --> 00:24:36,749 what I really love about this 915 00:24:36,749 --> 00:24:38,369 release is the creativity 916 00:24:38,639 --> 00:24:40,709 behind what the marketing 917 00:24:40,709 --> 00:24:42,419 and the software teams had 918 00:24:42,419 --> 00:24:43,559 done for what's essentially 919 00:24:43,619 --> 00:24:45,089 a hardware limitation. 920 00:24:45,509 --> 00:24:46,349 So functionally. 921 00:24:46,840 --> 00:24:48,190 the cutout houses, the 922 00:24:48,190 --> 00:24:49,390 front facing camera for your 923 00:24:49,390 --> 00:24:51,160 phone and face ID sensors. 924 00:24:51,550 --> 00:24:52,630 But instead of letting 925 00:24:52,630 --> 00:24:54,160 that become static dead 926 00:24:54,160 --> 00:24:56,020 space with software, it 927 00:24:56,020 --> 00:24:57,610 has transformed into a 928 00:24:57,610 --> 00:24:59,410 dynamic and an interactive 929 00:24:59,410 --> 00:25:00,100 part of the screen. 930 00:25:00,862 --> 00:25:01,312 Elle: Got it. 931 00:25:01,342 --> 00:25:01,642 Okay. 932 00:25:01,642 --> 00:25:03,142 And I have to say, how 933 00:25:03,142 --> 00:25:04,792 did you stumble upon this? 934 00:25:04,792 --> 00:25:06,618 Like, is it obvious or have I 935 00:25:06,618 --> 00:25:07,878 been living under a rock that, 936 00:25:07,878 --> 00:25:09,198 it's called Dynamic Island? 937 00:25:11,145 --> 00:25:12,285 Sheryl: So sometimes I 938 00:25:12,285 --> 00:25:14,237 would watch, the keynote 939 00:25:14,237 --> 00:25:15,377 for developer conferences 940 00:25:15,377 --> 00:25:16,337 at other companies. 941 00:25:16,637 --> 00:25:18,917 And so that's how I came 942 00:25:18,917 --> 00:25:20,807 across the awesome launch 943 00:25:20,807 --> 00:25:22,187 video in which they 944 00:25:22,187 --> 00:25:24,167 released Dynamic Island? 945 00:25:24,167 --> 00:25:24,797 at the time. 946 00:25:24,797 --> 00:25:24,887 I. 947 00:25:24,887 --> 00:25:25,577 think it's a few years 948 00:25:25,577 --> 00:25:26,717 ago by now, but you can 949 00:25:26,717 --> 00:25:27,737 still find on YouTube. 950 00:25:28,457 --> 00:25:29,777 it's only 40 seconds long. 951 00:25:29,942 --> 00:25:30,842 Super sleek. 952 00:25:30,932 --> 00:25:32,252 There's no narration. 953 00:25:32,312 --> 00:25:34,052 Only the most vibe, the 954 00:25:34,052 --> 00:25:36,092 music, and it shows you 955 00:25:36,152 --> 00:25:38,282 exactly how dynamic Island 956 00:25:38,282 --> 00:25:40,112 smoothly transitions from 957 00:25:40,112 --> 00:25:41,342 providing incoming call 958 00:25:41,342 --> 00:25:42,902 notifications to tracking your 959 00:25:42,932 --> 00:25:45,152 Lyft ride and playing music. 960 00:25:46,262 --> 00:25:47,942 I just find it such a 961 00:25:47,942 --> 00:25:49,262 refreshing change from 962 00:25:49,262 --> 00:25:51,302 some of our B2B marketing 963 00:25:51,302 --> 00:25:52,472 roles in which we have 964 00:25:52,472 --> 00:25:54,062 to use big, clunky words 965 00:25:54,122 --> 00:25:55,412 to describe something. 966 00:25:55,907 --> 00:25:56,447 Elle: Yeah, 967 00:25:56,492 --> 00:25:57,572 Sheryl: this 42nd video 968 00:25:57,572 --> 00:25:58,712 was just like the perfect 969 00:25:58,712 --> 00:26:00,482 example of show don't tell. 970 00:26:01,172 --> 00:26:01,852 Elle: I am really 971 00:26:01,852 --> 00:26:03,107 impressed that there's no. 972 00:26:04,182 --> 00:26:06,492 Like narration, voice or 973 00:26:06,492 --> 00:26:08,472 words, the show don't tell 974 00:26:08,472 --> 00:26:10,932 is very strong storytelling. 975 00:26:11,322 --> 00:26:12,882 Just for our listeners, I will 976 00:26:12,882 --> 00:26:16,062 track down that 42nd video and 977 00:26:16,062 --> 00:26:17,292 I'll put it in the show notes. 978 00:26:17,366 --> 00:26:18,049 I'm intrigued. 979 00:26:18,049 --> 00:26:18,529 I definitely 980 00:26:18,529 --> 00:26:19,309 wanted take a look. 981 00:26:19,770 --> 00:26:20,091 okay. 982 00:26:20,091 --> 00:26:21,081 And there was another company 983 00:26:21,081 --> 00:26:22,161 you wanted to chat about. 984 00:26:22,506 --> 00:26:23,016 Sheryl: Yes. 985 00:26:23,016 --> 00:26:24,486 So the other company that's 986 00:26:24,486 --> 00:26:26,226 caught my eye is called Dust. 987 00:26:26,916 --> 00:26:28,356 They are a Sequoia 988 00:26:28,356 --> 00:26:29,766 backed startup in the 989 00:26:29,766 --> 00:26:31,356 AG agentic AI space. 990 00:26:31,746 --> 00:26:32,676 And what their product 991 00:26:32,676 --> 00:26:34,045 does is, in their own 992 00:26:34,045 --> 00:26:36,255 words, a. AI operating 993 00:26:36,255 --> 00:26:38,025 system for enterprises. 994 00:26:38,025 --> 00:26:39,705 So a horizontal solution 995 00:26:39,915 --> 00:26:41,055 that will be able to serve 996 00:26:41,085 --> 00:26:42,345 all business units of a 997 00:26:42,345 --> 00:26:44,925 company to help use AI agents 998 00:26:44,925 --> 00:26:46,335 and boost productivity. 999 00:26:46,695 --> 00:26:47,655 And of course, this is all 1000 00:26:47,655 --> 00:26:50,205 powered by LLMs and grounded 1001 00:26:50,205 --> 00:26:51,615 by internal data sources. 1002 00:26:51,970 --> 00:26:52,450 Elle: Yeah. 1003 00:26:52,480 --> 00:26:52,630 Okay. 1004 00:26:52,630 --> 00:26:53,260 So I just pulled 1005 00:26:53,260 --> 00:26:54,130 up their website. 1006 00:26:54,310 --> 00:26:55,420 So for the listeners, 1007 00:26:55,420 --> 00:26:59,260 that's Dust, it's D UT tt. 1008 00:26:59,971 --> 00:27:01,621 I'm scrolling and they, 1009 00:27:01,621 --> 00:27:02,461 they've listed out a 1010 00:27:02,461 --> 00:27:04,501 couple example use cases. 1011 00:27:04,741 --> 00:27:06,151 One of them is for pmms, which 1012 00:27:06,151 --> 00:27:08,491 I really like, and they have 1013 00:27:08,491 --> 00:27:10,831 examples like write on brand 1014 00:27:10,831 --> 00:27:12,601 content in minutes, create 1015 00:27:12,601 --> 00:27:14,371 consistent launch messaging. 1016 00:27:14,671 --> 00:27:15,361 So I'm really 1017 00:27:15,361 --> 00:27:16,021 intrigued by that. 1018 00:27:16,021 --> 00:27:17,701 But tell me, what do 1019 00:27:17,701 --> 00:27:18,631 you love about the 1020 00:27:18,631 --> 00:27:20,071 messaging of this product? 1021 00:27:20,569 --> 00:27:21,769 Sheryl: Yeah, so I, I think 1022 00:27:21,769 --> 00:27:23,059 the product is super cool, 1023 00:27:23,059 --> 00:27:24,349 first of all, and like you 1024 00:27:24,349 --> 00:27:26,599 said, as A-P-M-M-I would 1025 00:27:26,599 --> 00:27:27,769 be able to build an AI 1026 00:27:27,769 --> 00:27:29,599 agent to quickly synthesize 1027 00:27:29,599 --> 00:27:31,039 customer insights from 1028 00:27:31,039 --> 00:27:33,169 gong calls or run a query. 1029 00:27:33,169 --> 00:27:34,599 I. data warehouse 1030 00:27:34,599 --> 00:27:35,379 to self-serve. 1031 00:27:35,379 --> 00:27:36,399 Some of That analysis 1032 00:27:36,399 --> 00:27:37,479 I talked about earlier 1033 00:27:37,900 --> 00:27:39,473 Using natural language. 1034 00:27:39,473 --> 00:27:40,553 So I could just describe 1035 00:27:40,553 --> 00:27:41,723 my criteria instead of 1036 00:27:41,723 --> 00:27:42,923 having to learn sql. 1037 00:27:43,663 --> 00:27:44,053 And 1038 00:27:44,143 --> 00:27:44,323 Elle: it. 1039 00:27:44,503 --> 00:27:45,463 Sheryl: Overall for 1040 00:27:45,463 --> 00:27:47,023 dust, their messaging 1041 00:27:47,023 --> 00:27:48,343 is, is really well done. 1042 00:27:48,703 --> 00:27:50,473 Uh, the website copy is tight 1043 00:27:50,473 --> 00:27:51,703 and I can quickly get a sense 1044 00:27:51,703 --> 00:27:53,293 of what I'm able to do with 1045 00:27:53,293 --> 00:27:55,003 dust and its value props. 1046 00:27:55,453 --> 00:27:57,013 And for a horizontal solution 1047 00:27:57,013 --> 00:27:58,903 like this, I really like 1048 00:27:58,903 --> 00:27:59,803 that they've included a 1049 00:27:59,803 --> 00:28:01,663 solution pages where I can 1050 00:28:01,663 --> 00:28:03,193 get more tailored messaging 1051 00:28:03,193 --> 00:28:04,363 based off the business 1052 00:28:04,363 --> 00:28:06,043 function I'm coming from and 1053 00:28:06,043 --> 00:28:07,453 also use case suggestions. 1054 00:28:08,133 --> 00:28:08,583 Elle: Awesome. 1055 00:28:08,613 --> 00:28:08,913 Okay. 1056 00:28:08,913 --> 00:28:09,213 Yes. 1057 00:28:09,213 --> 00:28:10,683 It's always such a win 1058 00:28:10,683 --> 00:28:11,913 when you can like very 1059 00:28:11,913 --> 00:28:13,473 quickly understand 1060 00:28:13,593 --> 00:28:14,853 what a company does. 1061 00:28:14,853 --> 00:28:16,353 And I gotta say, in the 1062 00:28:16,353 --> 00:28:17,823 world of AI we're in, 1063 00:28:17,943 --> 00:28:20,013 everyone is just jamming 1064 00:28:20,013 --> 00:28:22,194 AI into as a buzzword into. 1065 00:28:22,744 --> 00:28:24,034 Like every single header and 1066 00:28:24,034 --> 00:28:26,663 subheader I can think of, it's 1067 00:28:26,663 --> 00:28:27,923 pretty impressive that you can 1068 00:28:27,923 --> 00:28:30,233 be clear and concise and still 1069 00:28:30,233 --> 00:28:31,643 show your differentiation. 1070 00:28:31,643 --> 00:28:33,533 So hats off to the dust team. 1071 00:28:33,743 --> 00:28:34,583 That's very cool. 1072 00:28:34,613 --> 00:28:35,333 I'm impressed. 1073 00:28:35,693 --> 00:28:36,758 okay, so what's something 1074 00:28:36,758 --> 00:28:37,748 though that maybe you wish 1075 00:28:37,748 --> 00:28:39,188 the PMM would've considered? 1076 00:28:39,911 --> 00:28:40,991 Sheryl: Yeah, so I've actually 1077 00:28:40,991 --> 00:28:42,761 met the dust team before 1078 00:28:42,761 --> 00:28:44,081 and they run super lean, 1079 00:28:44,171 --> 00:28:45,491 maybe because they use dust, 1080 00:28:45,964 --> 00:28:47,065 but they don't actually 1081 00:28:47,065 --> 00:28:48,835 have dedicated pmms yet 1082 00:28:49,374 --> 00:28:50,334 Elle: Oh wow. 1083 00:28:50,597 --> 00:28:51,977 I'm even more impressed then. 1084 00:28:53,118 --> 00:28:53,988 Sheryl: Exactly. 1085 00:28:54,738 --> 00:28:56,748 something we've discussed is 1086 00:28:56,748 --> 00:28:58,728 the challenge of identifying 1087 00:28:58,788 --> 00:29:00,468 the right and consistent 1088 00:29:00,528 --> 00:29:02,748 buyer persona, uh, for a 1089 00:29:02,748 --> 00:29:04,338 horizontal solution like this. 1090 00:29:05,178 --> 00:29:06,888 within the organization has 1091 00:29:06,888 --> 00:29:08,418 the pain around this lack 1092 00:29:08,418 --> 00:29:10,428 of productivity, but also 1093 00:29:10,488 --> 00:29:11,718 the budget influence to 1094 00:29:11,718 --> 00:29:12,918 be able to champion this? 1095 00:29:12,933 --> 00:29:16,413 And once a company implements 1096 00:29:16,413 --> 00:29:18,799 dust, how will it be used? 1097 00:29:18,799 --> 00:29:20,809 Like, is everyone expected 1098 00:29:20,809 --> 00:29:22,339 to build their own agents 1099 00:29:22,339 --> 00:29:23,689 or will it really be, 1100 00:29:24,186 --> 00:29:25,926 concentrated in a handful 1101 00:29:25,926 --> 00:29:27,786 of super users who build 1102 00:29:28,146 --> 00:29:30,096 reusable agents that everyone 1103 00:29:30,096 --> 00:29:32,076 else then, uh, just use? 1104 00:29:32,556 --> 00:29:34,056 And the other thing that's. 1105 00:29:34,341 --> 00:29:35,931 Comes to mind is how 1106 00:29:35,931 --> 00:29:37,011 is dust different 1107 00:29:37,161 --> 00:29:38,691 from all the other AI 1108 00:29:38,790 --> 00:29:39,450 Elle: Mm-hmm. 1109 00:29:39,681 --> 00:29:40,671 Sheryl: Enterprise 1110 00:29:40,671 --> 00:29:42,591 search agent products? 1111 00:29:43,011 --> 00:29:44,481 Uh, for example, like Glean. 1112 00:29:45,201 --> 00:29:46,491 so getting a better 1113 00:29:46,491 --> 00:29:48,921 understanding on their primary 1114 00:29:48,921 --> 00:29:51,471 buyer persona will help inform 1115 00:29:51,501 --> 00:29:53,001 the messaging on the homepage. 1116 00:29:53,557 --> 00:29:53,947 Elle: Right. 1117 00:29:53,947 --> 00:29:54,217 Yeah. 1118 00:29:54,217 --> 00:29:55,027 So this sounds 1119 00:29:55,027 --> 00:29:56,227 like a really great 1120 00:29:56,227 --> 00:29:58,417 segmentation opportunity. 1121 00:29:58,417 --> 00:29:59,317 And then from there. 1122 00:29:59,982 --> 00:30:01,872 They could hone in on 1123 00:30:01,872 --> 00:30:02,892 particular pain points 1124 00:30:02,892 --> 00:30:03,942 they're trying to solve for 1125 00:30:03,942 --> 00:30:05,652 their priority target market. 1126 00:30:05,892 --> 00:30:06,882 They could understand how 1127 00:30:06,882 --> 00:30:08,202 they're trying to solve 1128 00:30:08,202 --> 00:30:09,492 those pains and how that's 1129 00:30:09,492 --> 00:30:11,142 different from all those other 1130 00:30:11,142 --> 00:30:12,822 AI powered agents like lean. 1131 00:30:13,158 --> 00:30:14,148 I could totally see that 1132 00:30:14,148 --> 00:30:16,038 being a good next step. 1133 00:30:16,206 --> 00:30:17,046 okay, cool. 1134 00:30:17,076 --> 00:30:19,566 So lastly, if you were the 1135 00:30:19,566 --> 00:30:22,176 PMM here, what would you do 1136 00:30:22,176 --> 00:30:23,616 to take it to the next level? 1137 00:30:23,616 --> 00:30:24,126 Like do you have any 1138 00:30:24,126 --> 00:30:25,536 super creative ideas for 1139 00:30:25,536 --> 00:30:26,826 our friends over at Dust? 1140 00:30:27,588 --> 00:30:28,908 Sheryl: just brainstorming 1141 00:30:28,908 --> 00:30:30,408 out loud here, maybe some 1142 00:30:30,408 --> 00:30:31,998 sort of creative campaign 1143 00:30:31,998 --> 00:30:33,828 that will target a few 1144 00:30:33,828 --> 00:30:35,088 key business functions. 1145 00:30:35,088 --> 00:30:35,748 To start, 1146 00:30:36,138 --> 00:30:36,348 I'm 1147 00:30:36,372 --> 00:30:36,592 Elle: Ooh. 1148 00:30:36,918 --> 00:30:37,848 Sheryl: Marketing, 1149 00:30:37,938 --> 00:30:39,138 uh, engineering. 1150 00:30:39,528 --> 00:30:40,968 And based on the performance 1151 00:30:40,968 --> 00:30:42,498 of that campaign, the team 1152 00:30:42,498 --> 00:30:43,523 will be able to get a clear. 1153 00:30:44,410 --> 00:30:45,882 understanding of which 1154 00:30:45,882 --> 00:30:48,672 functions has that most pain 1155 00:30:48,672 --> 00:30:51,132 and ROI balance, uh, for a 1156 00:30:51,132 --> 00:30:53,262 tool like this and be able 1157 00:30:53,262 --> 00:30:54,942 to start there as an entry 1158 00:30:54,942 --> 00:30:56,892 into the organization and 1159 00:30:56,892 --> 00:30:58,332 build out like a repeatable 1160 00:30:58,332 --> 00:30:59,352 go-to-market motion. 1161 00:30:59,352 --> 00:30:59,382 I. 1162 00:31:00,105 --> 00:31:00,585 Elle: Yes. 1163 00:31:00,615 --> 00:31:00,975 Okay. 1164 00:31:00,975 --> 00:31:01,755 I love that. 1165 00:31:01,760 --> 00:31:04,125 It's like a BM style, 1166 00:31:04,125 --> 00:31:05,475 land, and expand 1167 00:31:05,835 --> 00:31:06,855 kind of opportunity. 1168 00:31:07,671 --> 00:31:08,721 that could be a really 1169 00:31:08,721 --> 00:31:09,531 strategic way to 1170 00:31:09,531 --> 00:31:10,971 partner with sales too. 1171 00:31:11,262 --> 00:31:12,342 you know, I might also 1172 00:31:12,342 --> 00:31:14,202 suggest as part of the 1173 00:31:14,202 --> 00:31:16,632 segmentation exercise, doing 1174 00:31:16,632 --> 00:31:18,492 that like ideal customer 1175 00:31:18,732 --> 00:31:20,262 profile exercise too. 1176 00:31:20,562 --> 00:31:21,762 So when they create that 1177 00:31:21,792 --> 00:31:22,782 ideal customer profile 1178 00:31:22,782 --> 00:31:23,502 they wanna target, they 1179 00:31:23,502 --> 00:31:24,762 can establish super strong 1180 00:31:24,762 --> 00:31:26,622 personas across the buy team. 1181 00:31:26,862 --> 00:31:27,642 And I think that could 1182 00:31:27,642 --> 00:31:29,754 really, pair nicely with your. 1183 00:31:30,338 --> 00:31:31,628 sort of land and expand, 1184 00:31:31,628 --> 00:31:32,378 sort of, I'm putting 1185 00:31:32,378 --> 00:31:33,158 words in your mouth now. 1186 00:31:35,144 --> 00:31:36,044 Sheryl: No, that's exactly it. 1187 00:31:36,482 --> 00:31:37,442 Elle: very cool. 1188 00:31:37,442 --> 00:31:39,002 Solid messaging critique. 1189 00:31:39,002 --> 00:31:40,682 Sheryl, also, I now want 1190 00:31:40,682 --> 00:31:42,302 to use their tool because 1191 00:31:42,302 --> 00:31:44,552 it's just looks really cool. 1192 00:31:45,842 --> 00:31:48,062 Shout out to Apple as always. 1193 00:31:48,062 --> 00:31:49,292 Yeah, the goat and 1194 00:31:49,532 --> 00:31:50,972 marketing and messaging 1195 00:31:51,122 --> 00:31:52,382 and then of course to the. 1196 00:31:52,807 --> 00:31:53,887 Yeah, of course. 1197 00:31:53,887 --> 00:31:55,867 To the dust pmms out there. 1198 00:31:56,467 --> 00:31:57,607 You've got some fans. 1199 00:31:57,637 --> 00:31:59,047 Great job with the messaging. 1200 00:31:59,677 --> 00:32:00,997 Uh, okay, Sheryl, before 1201 00:32:00,997 --> 00:32:02,197 we go, I just wanna have 1202 00:32:02,197 --> 00:32:03,637 a gratitude moment and say 1203 00:32:03,667 --> 00:32:04,807 thank you so much for your 1204 00:32:04,807 --> 00:32:07,057 willingness to share your 1205 00:32:07,057 --> 00:32:08,797 knowledge and expertise 1206 00:32:08,797 --> 00:32:09,997 with the product marketing 1207 00:32:09,997 --> 00:32:11,887 community today and me. 1208 00:32:11,887 --> 00:32:13,207 How lucky am I that I just 1209 00:32:13,207 --> 00:32:14,497 got like a mini coaching 1210 00:32:14,497 --> 00:32:15,757 session on shaping the 1211 00:32:15,757 --> 00:32:17,347 product roadmap, so cool. 1212 00:32:18,528 --> 00:32:18,748 Sheryl: No. 1213 00:32:18,863 --> 00:32:19,733 Uh, thank you so 1214 00:32:19,733 --> 00:32:21,353 much for having me. 1215 00:32:21,803 --> 00:32:22,433 Um, it. 1216 00:32:22,553 --> 00:32:24,683 Been really fun to be able to 1217 00:32:24,713 --> 00:32:26,663 come on and, and share, uh, 1218 00:32:26,693 --> 00:32:27,713 some of the projects we've 1219 00:32:27,713 --> 00:32:29,213 been working on at Confluent. 1220 00:32:29,693 --> 00:32:30,983 But one thing that 1221 00:32:30,983 --> 00:32:31,673 I don't know if you 1222 00:32:31,673 --> 00:32:32,873 still remember, but. 1223 00:32:33,188 --> 00:32:33,938 At the beginning you 1224 00:32:33,938 --> 00:32:35,348 were mentioning how I 1225 00:32:35,348 --> 00:32:36,878 didn't have like, uh, a 1226 00:32:36,878 --> 00:32:38,768 traditional background 1227 00:32:38,985 --> 00:32:39,435 Elle: Right, 1228 00:32:39,691 --> 00:32:40,261 Sheryl: marketing, 1229 00:32:40,635 --> 00:32:41,175 Elle: right. 1230 00:32:41,251 --> 00:32:41,821 Sheryl: Were one of 1231 00:32:41,821 --> 00:32:43,561 the first pmms that I 1232 00:32:43,561 --> 00:32:45,511 reached out to at Twilio 1233 00:32:45,675 --> 00:32:46,575 Elle: I remember, 1234 00:32:47,071 --> 00:32:48,391 Sheryl: to make that switch. 1235 00:32:48,721 --> 00:32:50,956 And you to kind of. 1236 00:32:51,011 --> 00:32:52,391 Take me under your 1237 00:32:52,391 --> 00:32:53,561 weighing and give me 1238 00:32:53,771 --> 00:32:55,181 little assignments, and you 1239 00:32:55,181 --> 00:32:56,531 really taught me kind of 1240 00:32:56,531 --> 00:32:57,551 the importance of having 1241 00:32:57,551 --> 00:32:59,351 customer proof points to 1242 00:32:59,351 --> 00:33:00,641 strengthen your messaging. 1243 00:33:01,080 --> 00:33:02,060 Elle: oh, thanks for that. 1244 00:33:02,065 --> 00:33:02,745 Shout out. 1245 00:33:02,801 --> 00:33:03,911 Sheryl: yeah, you honestly 1246 00:33:03,911 --> 00:33:05,411 have shaped, uh, my 1247 00:33:05,411 --> 00:33:06,791 career as PMM as well. 1248 00:33:06,855 --> 00:33:07,755 Elle: Aw, I'm so 1249 00:33:07,755 --> 00:33:08,843 touched to hear that. 1250 00:33:08,979 --> 00:33:10,188 yeah, whenever I get a chance 1251 00:33:10,188 --> 00:33:11,568 to meet amazing pmms like 1252 00:33:11,568 --> 00:33:12,953 yourself, I do get curious. 1253 00:33:12,953 --> 00:33:13,523 I'm like, how did they 1254 00:33:13,523 --> 00:33:14,903 get to be so amazing? 1255 00:33:15,031 --> 00:33:16,051 not trying to toot 1256 00:33:16,051 --> 00:33:16,982 my own horn, but I, 1257 00:33:19,081 --> 00:33:20,341 I got to help this one. 1258 00:33:21,302 --> 00:33:22,352 Sheryl: A hundred percent. 1259 00:33:22,502 --> 00:33:23,552 And I think it would be 1260 00:33:23,552 --> 00:33:24,662 really cool if we did 1261 00:33:24,662 --> 00:33:26,552 a podcast episode that 1262 00:33:26,552 --> 00:33:29,066 switches, the interviewer 1263 00:33:29,066 --> 00:33:30,326 and the interviewee, and you 1264 00:33:30,326 --> 00:33:32,336 could be the guest to your 1265 00:33:32,575 --> 00:33:34,705 Elle: Oh, so fun. 1266 00:33:35,246 --> 00:33:36,416 Sheryl: Your expertise in this 1267 00:33:36,595 --> 00:33:37,645 Elle: Oh, that's so 1268 00:33:37,645 --> 00:33:39,325 sweet and so fun. 1269 00:33:39,385 --> 00:33:40,885 Yeah, I should definitely 1270 00:33:40,885 --> 00:33:42,145 consider that sometime. 1271 00:33:42,518 --> 00:33:43,688 any other shout outs to 1272 00:33:43,688 --> 00:33:46,274 pmms who have shaped how you 1273 00:33:46,274 --> 00:33:47,564 got to where you are today? 1274 00:33:47,999 --> 00:33:48,599 Sheryl: Yeah. 1275 00:33:48,599 --> 00:33:49,409 definitely. 1276 00:33:49,409 --> 00:33:50,759 So the first one 1277 00:33:50,759 --> 00:33:51,929 is Nick Bryan. 1278 00:33:51,929 --> 00:33:53,459 He was my manager for 1279 00:33:53,459 --> 00:33:55,799 many years Confluence, 1280 00:33:55,799 --> 00:33:56,909 and honestly, he's taught 1281 00:33:56,909 --> 00:33:57,809 me everything I know. 1282 00:33:58,504 --> 00:34:00,538 And, he is a great product 1283 00:34:00,538 --> 00:34:02,608 marketer, perfect blend of 1284 00:34:03,028 --> 00:34:04,828 creativity and messaging, 1285 00:34:05,128 --> 00:34:07,195 technical, aptitude and 1286 00:34:07,195 --> 00:34:09,565 also analytical powerhouse. 1287 00:34:09,745 --> 00:34:11,726 And, under his leadership, 1288 00:34:11,726 --> 00:34:13,346 I was able to grow a lot. 1289 00:34:13,676 --> 00:34:14,966 And now that I have my own 1290 00:34:14,966 --> 00:34:17,216 team, I still hear his voice 1291 00:34:17,216 --> 00:34:20,816 in my head about how to 1292 00:34:22,046 --> 00:34:23,936 get crisp, clear messaging. 1293 00:34:24,206 --> 00:34:25,391 Um, so he's been. 1294 00:34:25,871 --> 00:34:26,891 A huge influence 1295 00:34:26,891 --> 00:34:28,211 to my PMM career. 1296 00:34:29,381 --> 00:34:30,641 another colleague, 1297 00:34:30,671 --> 00:34:31,841 uh, Greg Murphy. 1298 00:34:32,171 --> 00:34:34,528 Uh, we did, a launch together, 1299 00:34:34,528 --> 00:34:35,608 and that was my first, 1300 00:34:36,070 --> 00:34:37,987 official launch as a PMM. 1301 00:34:38,437 --> 00:34:40,578 And, he just has such a 1302 00:34:40,578 --> 00:34:41,988 high bar for excellence. 1303 00:34:41,988 --> 00:34:43,488 He, and it's just so 1304 00:34:43,488 --> 00:34:44,838 great at communicating 1305 00:34:44,838 --> 00:34:46,338 through written words. 1306 00:34:46,758 --> 00:34:48,168 And so he always strived 1307 00:34:48,168 --> 00:34:49,989 me to, be better, 1308 00:34:50,359 --> 00:34:50,959 Elle: Yeah. 1309 00:34:51,159 --> 00:34:52,569 Sheryl: then get better again. 1310 00:34:53,119 --> 00:34:54,499 Elle: I love those PMM 1311 00:34:54,499 --> 00:34:57,019 friends who help us really 1312 00:34:57,019 --> 00:34:58,189 understand like, this is 1313 00:34:58,189 --> 00:34:59,779 what excellence look like. 1314 00:34:59,899 --> 00:35:02,510 And honestly, that is why 1315 00:35:02,510 --> 00:35:03,650 I wanted to create this 1316 00:35:03,650 --> 00:35:05,630 podcast and why I thought of 1317 00:35:05,630 --> 00:35:08,240 you to be such a great guest 1318 00:35:08,240 --> 00:35:09,650 for the show because you 1319 00:35:10,010 --> 00:35:11,690 strive for that excellence 1320 00:35:11,690 --> 00:35:12,890 and obviously have had 1321 00:35:12,890 --> 00:35:14,600 such great mentorship. 1322 00:35:14,600 --> 00:35:14,720 So. 1323 00:35:15,660 --> 00:35:16,680 Those mentors are such, 1324 00:35:16,680 --> 00:35:18,090 they're the secret sauce to 1325 00:35:18,150 --> 00:35:19,920 how we get to where we are. 1326 00:35:19,920 --> 00:35:20,917 And, now you're gonna 1327 00:35:20,917 --> 00:35:21,637 be able to shape that 1328 00:35:21,637 --> 00:35:23,017 for our PMM community. 1329 00:35:23,047 --> 00:35:24,817 So thank you so much. 1330 00:35:24,817 --> 00:35:25,987 And for people who are 1331 00:35:25,987 --> 00:35:27,007 listening and thinking, 1332 00:35:27,007 --> 00:35:27,637 I need to have more 1333 00:35:27,637 --> 00:35:28,927 Sheryl in my life, like, 1334 00:35:28,987 --> 00:35:30,667 how can they find you 1335 00:35:31,225 --> 00:35:31,795 Sheryl: Uh, I think 1336 00:35:31,795 --> 00:35:32,695 on LinkedIn is 1337 00:35:32,695 --> 00:35:34,105 probably the best bet. 1338 00:35:34,225 --> 00:35:34,975 Yeah, I would love 1339 00:35:35,299 --> 00:35:35,659 Elle: great. 1340 00:35:35,965 --> 00:35:36,715 Sheryl: Connect and, 1341 00:35:36,715 --> 00:35:37,885 and share ideas. 1342 00:35:38,200 --> 00:35:38,920 Elle: I love it. 1343 00:35:38,920 --> 00:35:40,220 Thank you so much, Sheryl, 1344 00:35:40,240 --> 00:35:41,680 and thank you to our 1345 00:35:41,680 --> 00:35:42,910 listeners for coming on this 1346 00:35:42,910 --> 00:35:44,200 adventure with us today. 1347 00:35:44,590 --> 00:35:46,420 I hope this episode leaves you 1348 00:35:46,420 --> 00:35:48,650 with inspiration in taking the 1349 00:35:48,700 --> 00:35:50,200 next step in your own journey.