All Content from Business Insider 09月23日
AI初创公司增长模式:警惕“感觉良好”效应
index_new5.html
../../../zaker_core/zaker_tpl_static/wap/tpl_guoji1.html

 

前Facebook设计副总裁Julie Zhuo指出,许多快速增长的AI初创公司在初期依靠“直觉和感觉良好”来扩张,但当增长放缓时,它们将需要真实的数据来支撑生存。Zhuo强调,在AI时代,衡量成功的方式需要革新,特别是对于聊天机器人等产品,不能再依赖传统的点击量或页面浏览量,而需要利用LLM或ML模型来分析用户意图。她警告说,公司需要建立健全的数据基础设施和可观测性,以便在增长曲线趋于平缓时,能够准确理解用户行为和业务驱动因素,避免在关键时刻“手忙脚乱”。

🚀 AI初创公司初期增长模式的挑战:Julie Zhuo认为,许多AI初创公司在初期凭借“直觉和感觉良好”实现快速增长,但这种模式的持续性存疑。当增长放缓时,仅凭直觉已不足以应对复杂挑战,公司需要建立扎实的数据基础来支持可持续发展。

📊 数据驱动是AI公司长期生存的关键:Zhuo强调,数据分析对于理解用户行为、业务驱动因素以及识别用户流失原因至关重要。她指出,公司需要构建完善的数据基础设施和“可观测性”,以便在增长减速时,能够有效回答关键业务问题。

💡 重新定义AI时代的成功衡量标准:传统的衡量指标如点击量或页面浏览量已不足以评估AI产品(尤其是聊天机器人)的成功。Zhuo建议采用LLM或机器学习模型来分析用户意图,从而更准确地衡量用户价值和产品表现。

📈 AI市场过热的担忧与理性投资:文章提及,AI市场正经历前所未有的投资热潮,但也有投资者担忧市场过热,可能重蹈互联网泡沫覆辙。OpenAI CEO Sam Altman也对部分AI初创公司的高估值表示担忧,认为存在非理性繁荣的现象。

Former VP of design at Facebook Julie Zhuo says fast-growing AI startups are getting by on "good vibes" — but they'll need data to survive when growth slows.

Some of the hottest AI companies are scaling by "good instincts and good vibes" without much of a data foundation, a former Facebook vice president said.

Julie Zhuo, the former VP of design at Facebook who cofounded the AI analytics startup Sundial, said many startups riding the AI boom have grown at such a breakneck pace that they haven't had time to build proper data infrastructure.

"We see companies that are growing insane, and they're still about 10 people or two people," she said.

"They've got hundreds of millions in ARR and hundreds of millions of users, and you know what, they don't actually have all of that infrastructure, that logging, to be able to truly do data analysis," she added, speaking of annual recurring revenue.

Traditionally, companies didn't hit 100 million users overnight. Slower growth gave teams years to build out logging systems, hire a data team, and develop "observability" — the ability to understand what's actually driving user behavior and revenue, Zhuo said.

But Zhuo warned that the growth won't last forever. When the curve flattens, these startups will be "scrambling" to answer basic questions like why users churn, which features people value, and what levers really drive the business, she said.

"At that point, that's usually when people start investing a ton in data," she added. "Data helps you figure out what's actually happening."

Zhuo also said it's important to rethink how success is measured in the AI era, especially given the speed at which some companies are growing.

Products built around chatbots or conversational interfaces need new analytical methods. Instead of counting clicks or page views, "we have to probably use an LLM or a machine learning model to bucket user intent," she said.

Zhuo did not respond to a request for comment from Business Insider.

The boom of AI companies

The breakneck pace Zhuo described reflects a broader trend across the industry.

AI startups have been raising record amounts of money and soaring in valuations, with more than $35 billion raised in 2024, Business Insider reported last year.

A number of investors are concerned that the AI market might be overheating and that we're at risk of reliving the dot-com bubble burst in 2000. Some are wondering whether large language models are actually powerful enough to develop the long-desired superintelligence; some fear tech companies' massive expenditures won't pay off; and some are worried that less experienced investors are getting caught up in the hype.

OpenAI CEO Sam Altman said last month that it's "insane" and "not rational" that some tiny AI startups are getting funding at high valuations.

"Are we in a phase where investors as a whole are overexcited about AI? My opinion is yes," he told reporters, per The Verge. "Is AI the most important thing to happen in a very long time? My opinion is also yes."

Read the original article on Business Insider

Fish AI Reader

Fish AI Reader

AI辅助创作,多种专业模板,深度分析,高质量内容生成。从观点提取到深度思考,FishAI为您提供全方位的创作支持。新版本引入自定义参数,让您的创作更加个性化和精准。

FishAI

FishAI

鱼阅,AI 时代的下一个智能信息助手,助你摆脱信息焦虑

联系邮箱 441953276@qq.com

相关标签

AI初创公司 增长模式 数据分析 用户行为 AI时代 AI Startups Growth Models Data Analytics User Behavior AI Era
相关文章