BV1KgLU6REDF · 请不要叫我梁同学1 00:00:00,000 --> 00:00:02,299 欢迎来到今天的深度拆解 2 00:00:02,299 --> 00:00:04,320 今天咱们要一起扒一扒 3 00:00:04,320 --> 00:00:07,669 摩根斯丹利刚刚发布的一份重磅报告 4 00:00:07,669 --> 00:00:08,710 这份报告啊 5 00:00:08,710 --> 00:00:11,730 可以说是聚焦了当下云计算领域里 6 00:00:11,730 --> 00:00:16,019 一个极其反常又特别引人入胜的市场谜团 7 00:00:16,019 --> 00:00:18,809 也就是snowflake面临的困局 8 00:00:18,809 --> 00:00:21,289 熟悉科技板块的朋友肯定知道 9 00:00:21,289 --> 00:00:24,940 snowflake曾经绝对是全场最亮的星 10 00:00:24,940 --> 00:00:28,379 但眼下的情况却有点让人摸不着头脑 11 00:00:28,379 --> 00:00:31,179 这个是一个充满了反差的商业案例 12 00:00:31,179 --> 00:00:34,060 绝对值得咱们一起花点时间好好挖一挖 13 00:00:34,060 --> 00:00:35,079 背后的真相 14 00:00:35,079 --> 00:00:36,939 咱们直奔主题 15 00:00:36,939 --> 00:00:39,119 眼下我们都能明显感觉到 16 00:00:39,119 --> 00:00:43,268 整个公有云市场正借着AI的东风加速狂飙 17 00:00:43,268 --> 00:00:46,859 大厂们都在拼了命的砸钱搞基础设施 18 00:00:46,859 --> 00:00:48,820 但在这么好的大环境下 19 00:00:48,820 --> 00:00:50,640 作为行业里的顶尖玩家 20 00:00:50,640 --> 00:00:54,500 snowflake的业绩表现怎么就严重掉队了呢 21 00:00:54,500 --> 00:00:56,979 在一个大家都在起飞的风口上 22 00:00:56,979 --> 00:01:00,219 这家曾经的资本宠儿到底经历了什么 23 00:01:00,219 --> 00:01:01,320 俗话说 24 00:01:01,320 --> 00:01:03,920 没有对比就没有伤害 25 00:01:03,920 --> 00:01:05,980 你看看他身边的同行们 26 00:01:05,980 --> 00:01:07,500 过去一个月的拔线 27 00:01:07,500 --> 00:01:09,599 像MONGODB和NOTANEX 28 00:01:09,599 --> 00:01:13,060 大家都在云服务和数据管理这条广阔的赛道上 29 00:01:13,060 --> 00:01:15,040 人家今年到目前的涨幅 30 00:01:15,040 --> 00:01:17,140 已经分别达到了非常强劲的 31 00:01:17,140 --> 00:01:19,469 28percent和21percent的 32 00:01:19,469 --> 00:01:20,549 可以转头看 33 00:01:20,549 --> 00:01:24,150 snowflake股价今年居然暴跌了28percent 34 00:01:24,150 --> 00:01:26,629 这种极度冰火两重天的表现 35 00:01:26,629 --> 00:01:29,260 就是咱们今天必须要解开的结 36 00:01:29,260 --> 00:01:31,799 到底真的是公司本身出了大问题 37 00:01:31,799 --> 00:01:34,239 还是说市场情绪错杀了他 38 00:01:34,239 --> 00:01:36,239 为了搞清楚这个问题 39 00:01:36,239 --> 00:01:39,480 咱们第一步得先来体检一下 40 00:01:39,480 --> 00:01:41,168 看看它的基本面 41 00:01:41,168 --> 00:01:45,680 也就是底层业务到底还健不健康 42 00:01:45,680 --> 00:01:46,540 说实话 43 00:01:46,540 --> 00:01:50,060 摩根士丹利的这份调研结果挺让人意外的 44 00:01:50,060 --> 00:01:51,489 极其积极 45 00:01:51,489 --> 00:01:53,629 他们去底下摸牌了一圈 46 00:01:53,629 --> 00:01:56,879 发现市场需求其实非常健康 47 00:01:56,879 --> 00:01:58,280 河伴纷纷表示 48 00:01:58,280 --> 00:01:59,280 实际表现 49 00:01:59,280 --> 00:02:02,299 甚至比原先设定的计划还要好那么一点儿 50 00:02:02,299 --> 00:02:05,459 而且核心的数据仓库和云分析需求 51 00:02:05,459 --> 00:02:07,370 可以说是坚如磐石 52 00:02:07,370 --> 00:02:08,949 最让人松一口气的是 53 00:02:08,949 --> 00:02:12,389 之前大家总担心搞AI会挤占原有预算 54 00:02:12,389 --> 00:02:14,180 但事实证明并没有 55 00:02:14,180 --> 00:02:17,340 像cortex这种全新AI工具的采用率 56 00:02:17,340 --> 00:02:18,699 确实在稳步上升 57 00:02:18,699 --> 00:02:20,539 但完全没有蚕食掉客户 58 00:02:20,539 --> 00:02:22,959 原本在snowflake上的常规开销 59 00:02:22,959 --> 00:02:25,319 这绝对是个让人振奋的信号 60 00:02:25,319 --> 00:02:26,159 不信的话 61 00:02:26,159 --> 00:02:28,639 咱们可以看一个极其敏锐 62 00:02:28,639 --> 00:02:30,939 也做不了假的内部指标 63 00:02:30,939 --> 00:02:33,829 那就是他的岗位招聘趋势 64 00:02:33,829 --> 00:02:36,649 你看这显然是一家正在厉兵秣马 65 00:02:36,649 --> 00:02:38,780 积极准备大规模扩张的公司 66 00:02:38,780 --> 00:02:39,659 大家想啊 67 00:02:39,659 --> 00:02:42,120 如果底层基本面真的在恶化 68 00:02:42,120 --> 00:02:43,680 或者客户跑光了 69 00:02:43,680 --> 00:02:47,419 管理层怎么可能还会允许内部疯狂招人 70 00:02:47,419 --> 00:02:48,620 扩张工程的团队呢 71 00:02:48,620 --> 00:02:49,319 对吧 72 00:02:49,319 --> 00:02:51,550 既然基本面稳得很 73 00:02:51,550 --> 00:02:54,680 那骨架为什么还这么难看 74 00:02:54,680 --> 00:02:58,099 这就引出了咱们今天的第二部分 75 00:02:58,099 --> 00:03:01,280 一个极其复杂的模型设置 76 00:03:01,280 --> 00:03:05,020 其实啊这很大程度上是吃了基数的亏 77 00:03:05,020 --> 00:03:07,319 华尔街管这个叫TOFFERCOMS 78 00:03:07,319 --> 00:03:09,479 也就是艰难的比较基数 79 00:03:09,479 --> 00:03:10,680 简单解释一下 80 00:03:10,680 --> 00:03:12,599 当你接下来要公布的成绩单 81 00:03:12,599 --> 00:03:16,030 是跟去年同期极其辉煌的战绩做对比时 82 00:03:16,030 --> 00:03:17,150 你的近期增长 83 00:03:17,150 --> 00:03:20,189 在账面上看起来就会被人为的放缓了 84 00:03:20,189 --> 00:03:21,069 也就是说 85 00:03:21,069 --> 00:03:24,229 即将到来的第二季度纸面数据可能不太漂亮 86 00:03:24,229 --> 00:03:26,430 但这真不是因为公司不增长了 87 00:03:26,430 --> 00:03:28,330 仅仅是因为去年考的太好 88 00:03:28,330 --> 00:03:29,990 把基数拉的太高 89 00:03:29,990 --> 00:03:33,180 从而在心理层面压制了市场的短期预期 90 00:03:33,180 --> 00:03:33,719 好了 91 00:03:33,719 --> 00:03:35,240 抛开这些心理战 92 00:03:35,240 --> 00:03:37,740 咱们第三部分直接上干货 93 00:03:37,740 --> 00:03:39,159 用数据说话 94 00:03:39,159 --> 00:03:42,469 看看真实的财报预期到底是个什么水平 95 00:03:42,469 --> 00:03:46,509 咱们先拨开市场上那些乱七八糟的噪音 96 00:03:46,509 --> 00:03:48,830 摩根士丹利的分析师算了一笔账 97 00:03:48,830 --> 00:03:51,560 预计snowflake第一季度的产品收入 98 00:03:51,560 --> 00:03:53,759 会比公司自己之前给出的指引 99 00:03:53,759 --> 00:03:57,300 中位数硬生生高出大约3200万美元 100 00:03:57,300 --> 00:03:59,340 在现在的宏观大环境下 101 00:03:59,340 --> 00:04:00,919 这绝对不是一笔小钱 102 00:04:00,919 --> 00:04:02,539 他非常直接的证明了 103 00:04:02,539 --> 00:04:04,919 公司近期的执行力依然极其强悍 104 00:04:04,919 --> 00:04:07,310 业务引擎运转得非常高效 105 00:04:07,310 --> 00:04:10,150 这多出来的3000多万美元 106 00:04:10,150 --> 00:04:13,219 背后释放了一个更深层次的信号 107 00:04:13,219 --> 00:04:13,939 它意味着 108 00:04:13,939 --> 00:04:17,240 smoke fla有能力将产品收入的同比增速 109 00:04:17,240 --> 00:04:20,668 稳稳地维持在30percent这条生命线上 110 00:04:20,668 --> 00:04:22,668 了解SARS行业的朋友都知道 111 00:04:22,668 --> 00:04:24,189 在如今这么内卷 112 00:04:24,189 --> 00:04:27,220 而且自身体量已经如此庞大的情况下 113 00:04:27,220 --> 00:04:29,759 还能死死咬住30percent的增速 114 00:04:29,759 --> 00:04:31,740 这实力绝对是现象级的 115 00:04:31,740 --> 00:04:34,740 充分说明了客户根本离不开他的产品 116 00:04:34,740 --> 00:04:36,939 那既然一季度表现这么猛 117 00:04:36,939 --> 00:04:38,680 问题究竟出在哪儿 118 00:04:38,680 --> 00:04:40,839 大家看这组数据就明白了 119 00:04:40,839 --> 00:04:43,290 预期发生了严重的错位 120 00:04:43,290 --> 00:04:45,550 虽然一季度大概率会超预期 121 00:04:45,550 --> 00:04:47,589 但管理层出了名的谨慎 122 00:04:47,589 --> 00:04:50,490 预计二季度只会给一个跟华尔街共识 123 00:04:50,490 --> 00:04:51,730 差不多的指引 124 00:04:51,730 --> 00:04:53,329 这就会导致一个结果 125 00:04:53,329 --> 00:04:56,250 全年的总收入预期基本没变 126 00:04:56,250 --> 00:04:58,170 华尔街的逻辑非常现实 127 00:04:58,170 --> 00:04:59,629 你一季度好归好 128 00:04:59,629 --> 00:05:01,910 但既然你不上调全年的指引 129 00:05:01,910 --> 00:05:04,240 那短期内我就不给你重新估值 130 00:05:04,240 --> 00:05:06,959 这才是压在股家头上的那座大山 131 00:05:06,959 --> 00:05:07,879 除此之外 132 00:05:07,879 --> 00:05:11,779 咱们还得看一眼他的钱到底都是从哪儿赚来的 133 00:05:11,779 --> 00:05:14,040 看这个分布图非常极端 134 00:05:14,040 --> 00:05:17,370 高达85的收入纯靠美美市场 135 00:05:17,370 --> 00:05:18,370 这说明什么 136 00:05:18,370 --> 00:05:20,910 说明他虽然在欧洲和亚太 137 00:05:20,910 --> 00:05:23,639 还有广阔的星辰大海没去征服 138 00:05:23,639 --> 00:05:25,899 但在眼下他的业绩表现 139 00:05:25,899 --> 00:05:30,379 跟美美当地的宏观经济以及企业it支出周期 140 00:05:30,379 --> 00:05:32,309 是死死绑定在一起的 141 00:05:32,309 --> 00:05:33,968 完全是一荣俱荣 142 00:05:33,968 --> 00:05:35,168 一损俱损 143 00:05:35,168 --> 00:05:36,249 聊完业绩 144 00:05:36,249 --> 00:05:38,089 咱们再来看看估值 145 00:05:38,089 --> 00:05:39,850 摩根史丹利的分析师 146 00:05:39,850 --> 00:05:42,470 挖出了一个相当诱人的数据 147 00:05:42,470 --> 00:05:43,529 按照预测 148 00:05:43,529 --> 00:05:45,610 snowflake目前的交易价格 149 00:05:45,610 --> 00:05:47,949 仅仅是他2027年预期 150 00:05:47,949 --> 00:05:51,740 企业价值与自由现金流之比的1.35倍 151 00:05:51,740 --> 00:05:52,980 咱们直白点说 152 00:05:52,980 --> 00:05:56,639 考虑到它远超同行的增长潜力和盈利空间 153 00:05:56,639 --> 00:05:59,040 相比其他大型软件巨头 154 00:05:59,040 --> 00:06:02,879 这个估值倍数真的可以用非常不苛刻来形容了 155 00:06:02,879 --> 00:06:06,220 对于那些不看短期眼色的长线选手来说 156 00:06:06,220 --> 00:06:09,720 这没准儿就是个被错杀后砸出来的黄金坑 157 00:06:09,720 --> 00:06:12,019 综合了基本面和估值 158 00:06:12,019 --> 00:06:15,430 咱们来到最后一部分风险和回报 159 00:06:15,430 --> 00:06:17,910 看看投行是如何推演它 160 00:06:17,910 --> 00:06:21,240 一直到2030年的发展路线图的 161 00:06:21,240 --> 00:06:24,019 凡事咱们先做个最坏的打算 162 00:06:24,019 --> 00:06:26,860 在极其悲观的压力测试模型下 163 00:06:26,860 --> 00:06:29,418 目标价被定在了112美元 164 00:06:29,418 --> 00:06:31,019 这个剧本是怎样的呢 165 00:06:31,019 --> 00:06:35,079 就是三大公有云巨头开始疯狂下场肉搏 166 00:06:35,079 --> 00:06:38,519 残酷的竞争直接拖累了snowflake的增长 167 00:06:38,519 --> 00:06:42,310 连带着把它的定价权和利润率也给打压了下去 168 00:06:42,310 --> 00:06:45,850 如果你觉得他向其他数据领域扩张会彻底失败 169 00:06:45,850 --> 00:06:49,220 那这就是必须要防范的底线风险了 170 00:06:49,220 --> 00:06:50,060 反过来 171 00:06:50,060 --> 00:06:52,439 如果咱们把格局彻底打开 172 00:06:52,439 --> 00:06:54,060 乐观情形下的剧本 173 00:06:54,060 --> 00:06:56,100 绝对能让人肾上腺素飙升 174 00:06:56,100 --> 00:06:58,699 目标价值指415美元 175 00:06:58,699 --> 00:07:00,180 要实现这个飞跃 176 00:07:00,180 --> 00:07:01,000 Snowflake 177 00:07:01,000 --> 00:07:04,579 不仅得在老本行数据分析里继续大杀四方 178 00:07:04,579 --> 00:07:05,819 更关键的是 179 00:07:05,819 --> 00:07:09,279 他得把那个宏大的数据云愿景真正落地 180 00:07:09,279 --> 00:07:09,939 成功 181 00:07:09,939 --> 00:07:12,220 吃向那些相邻的全新市场 182 00:07:12,220 --> 00:07:16,259 依靠庞大的网络效应实现真正的爆发式跨越 183 00:07:16,259 --> 00:07:17,060 当然了 184 00:07:17,060 --> 00:07:18,279 回归现实 185 00:07:18,279 --> 00:07:19,759 摩根士丹利觉得 186 00:07:19,759 --> 00:07:22,860 概率最大的还是他们的基准情形 187 00:07:22,860 --> 00:07:24,660 维持超配评级 188 00:07:24,660 --> 00:07:27,029 目标价245美元 189 00:07:27,029 --> 00:07:29,389 这是一份非常务实的预测 190 00:07:29,389 --> 00:07:32,750 他们坚信凭借绝对硬核的产品力 191 00:07:32,750 --> 00:07:33,629 Snowflake 192 00:07:33,629 --> 00:07:37,490 完全可以在核心数据分析领域稳坐钓鱼台 193 00:07:37,490 --> 00:07:40,589 长期保持20盘以上的强劲增长 194 00:07:40,589 --> 00:07:44,139 并且利润率也能一步一个脚印地往上走 195 00:07:44,139 --> 00:07:44,779 好了 196 00:07:44,779 --> 00:07:47,579 盘完了这么多复杂的数据和推演 197 00:07:47,579 --> 00:07:51,459 其实今天就留下了这么一个值得深思的问题 198 00:07:51,459 --> 00:07:52,399 教给大家 199 00:07:52,399 --> 00:07:55,180 市场上现在满天飞的短期噪音 200 00:07:55,180 --> 00:07:55,800 是不是 201 00:07:55,800 --> 00:07:57,519 反而掩盖了snowflake 202 00:07:57,519 --> 00:08:00,750 长期基本面非常健康的真实信号 203 00:08:00,750 --> 00:08:02,670 当大家真正消化完 204 00:08:02,670 --> 00:08:06,189 这种因为基数太高而导致的纸面落差 205 00:08:06,189 --> 00:08:09,569 重新审视他在AI时代的战略布局时 206 00:08:09,569 --> 00:08:10,910 现在的这个低谷 207 00:08:10,910 --> 00:08:12,769 会不会正是长期主义者们 208 00:08:12,769 --> 00:08:14,870 等了很久的破局时刻呢 209 00:08:14,870 --> 00:08:18,370 这个问题值得我们每个人好好思考一下 210 00:08:18,370 --> 00:08:19,529 感谢大家的陪伴 211 00:08:19,529 --> 00:08:20,899 咱们下期再见
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