深入探讨:弗里德曼定律

On Generative AI and where retail goes next. On most days, I sit in a home office and read, write, think and hope to assimilate all of what I see, experience, and feel into unique human perspectives on complex topics. Unfortunately for me, generative artificial intelligence does much of that to the nth degree. Will we still value human-made creativity? The answer to that question is complicated. In April 2021, computer scientist, podcaster, and artificial intelligence researcher Lex Fridman tweeted the following:

Humans have been gradually merging with AI for 20+ years. At some point in this century, as a collective intelligence system, we will become more AI than human and we won’t notice.

Let’s call this “Fridman’s Law” (not to be confused with Friedman’s Law). We are nearing the point of 50%+ AI as our collective intelligence system. There are few better experts than him. Fridman – an emerging celebrity for his sheer thoughtfulness and openness to debate – is as prescient as ever. Generative AI, or artificial intelligence that can create new content by following prompts, is already making waves in various industries. From writing Drake hits to creating mind-blowing art, AI has already exceed genius levels of creativity. But, what about our shopping habits? How will generative AI shake things up in the world of retail? According to a recent Axios report:

Retail and packaged consumer goods companies would be in line for $660 billion a year in productivity gains, if “use cases were fully implemented” — which would mean a 44% boost to profits.

Picture this: You’re walking down a bustling street, and suddenly, you spot a store that seems to have been designed just for you. The colors, the layout, even the products on display – it’s like someone reached into your brain and pulled out your ideal brand fit. Imagine if this wasn’t a one-time thing, but rather the norm. Generative AI will revolutionize the way brands develop their retail spaces, making them more personalized and tailored to individual consumers by using data. It will analyze droves of information about consumers, from their shopping habits to their social media activity, and use this data to create customized store layouts and product offerings. This means that each store will be unique, catering to the specific needs and desires of its customers.

The rise of generative AI promises to revolutionize the retail and CPG landscape.

In the ongoing narrative of AI’s impact on various industries, retail and consumer packaged goods (CPG) hold a position of considerable interest. The sector stands on the brink of unprecedented transformation as generative AI – systems capable of creating new content – makes its mark. As we stand in 2023, we witness the blossoming of myriad start-ups leveraging this technology, and predict a near-future where more than 50% of consumerism and brand development will be influenced by generative AI.

Let’s dig in to the impact that analysts are anticipating.

Generative AI’s Impact on Brand Development

The traditional model of brand development has been largely human-driven, with marketers and product developers relying on customer surveys, focus groups, and trend analysis to create products and campaigns that resonate with the target audience. The ensuing process involves brainstorming, designing, testing, and iterating – a cycle that can be time-consuming and susceptible to error.

Generative AI promises to revamp this process, accelerating and enriching each step with data-driven insights and automation. For instance, AI’s ability to quickly aggregate and analyze market data allows for rapid testing of concepts, ideas, and models. Businesses are already leveraging these capabilities, using AI to generate style suggestions based on customer preferences, thereby improving their overall customer experience.

Generative AI will also help brands stay ahead of the curve when it comes to trends. The technology will be able to predict what the next big thing is before it even hits the market, allowing brands to develop and stock their stores with the hottest products.

Further, AI’s generative powers extend to creative tasks such as copywriting and visual design, areas previously considered solely human domains. By digitally generating numerous variations of copy and design, AI enables faster, more diverse ideation, allowing brands to quickly adapt to changing market trends and consumer preferences.

With smarter algorithms and predictive analytics, brands will be able to anticipate consumer demand and adjust their inventory accordingly. This means fewer out-of-stock items, less overstock, and an overall smoother shopping experience for everyone involved.

Generative AI and Consumerism

Generative AI also offers a dramatic shift in the consumerism landscape. In an era where personalization is paramount, AI’s ability to tailor experiences to individual preferences revolutionizes how consumers interact with brands. This extends from choosing products to ordering ingredients for a meal or interacting with chatbots for product recommendations.

You’ll walk into a store and find exactly what you’re looking for – or perhaps something even better that you didn’t know existed. With the personalized shopping experiences I mentioned earlier, it’s likely that we’ll see a shift towards quality over quantity. Instead of buying a ton of cheap, disposable items, consumers will be more inclined to invest in products that are tailored to their specific needs and preferences. This could lead to a decrease in fast fashion.

This advancement heralds a new era of “hyper-targeting”, where retailers use generative AI to sift through massive amounts of data, identifying precise segments of consumers that are a perfect fit for their products. The information derived from such analyses allows for highly targeted advertising, ensuring that consumers are exposed to products and services they are likely to be interested in.

The Transition and Challenges

The transition to a world where AI significantly influences brand development and consumerism is not without challenges. The deployment of AI systems raises important questions around the accuracy and veracity of generated content. Brands need to ensure the quality and reliability of AI-produced material, and instigate safeguards against potential adversarial attacks.

Moreover, AI’s ability to analyze and utilize personal data opens a Pandora’s box of privacy concerns. As retailers move towards a new form of hyper-targeting that we believed we’d left behind with the eschewing of third-party data usage, they need to balance personalization with respect for consumer privacy, a task that requires stringent data governance and ethical AI practices.

摘要

By 2030, the retail and CPG landscape is set to undergo a paradigm shift, driven by the capabilities of generative AI. It will change the very fabric of brand development, accelerating ideation, and enriching creativity. It will also redefine consumerism, paving the way for hyper-personalized, data-driven consumer experiences.

Yet, as we navigate this shift, the need for a human touch remains paramount but expect that shift to happen faster than any of us will appreciate. AI should augment human creativity, not replace it. Ethical considerations, especially regarding data privacy, must be central to AI deployment.

The journey towards this AI-dominated future will be fraught with challenges and opportunities. But, if navigated thoughtfully, the impact of generative AI on brand development and consumerism could usher in a new era of retail – one marked by enhanced creativity, efficiency, personalization, and above all, value for both businesses and consumers.

As we approach 2030, the retail industry stands poised to become a testament to the potential of generative AI. Yet, as we journey forward, we must remember that this technology should serve as a tool to amplify human potential, not replace it. Retailers and CPG companies that can strike this balance will thrive in the new era, crafting brands that resonate on a personal level and fostering a customer-centric model of business. The veracity and quality of AI-generated content must be held to high standards. As AI begins to create everything from product designs to ad campaigns, businesses must ensure that this content is not just compelling but also truthful and reliable.

Additionally, while generative AI offers many opportunities for streamlining operations and improving customer interactions, it also brings potential risks. As these AI models become more integral to business operations, they also become attractive targets for adversarial attacks. Thus, robust security measures will be paramount to protect both businesses and consumers.

The rise of generative AI promises to revolutionize the retail and CPG landscape. By 2030, it is likely that over half of all brand development and consumerism will be influenced by this technology. Yet, as we navigate this transition, we must ensure that the human element remains central to all developments. Only by balancing the potential of AI with a respect for human creativity and ethical considerations can we truly unlock the transformative power of AI in the retail sector. And if we don’t see it this way, there may not be a place left for us at all. The technology is already that good, years earlier than anticipated. Sooner than expected, organic, human-made content like this will be in the minority of collective intelligence – Fridman’s Law.

作者:Web Smith | 编辑:Hilary Milnes,美术:Christina Williams 和 Alex Remy

成员简介: b8ta 已测试

b8ta 的停业是零售业的一大损失,它结束了为改变这个发展速度比以往任何时候都快的零售业所做的勇敢努力。在某种程度上,b8ta 试图在一家店里重现 Soho 或奥斯汀南国会区的感觉。在 2018 年的《商品街坊》(Neighborhood of Goods)中,我解释道:

但是,当你离开苏荷区街道的砖砌小路时,你就不太可能再找到一个与之完全相同的地方了。无论是梅西百货最近在 Facebook 上推出的合作项目,还是 b8ta 商店、Four Post,甚至是 Neighborhood Goods,都不例外。每家店都有值得注意的不足之处:在 b8ta 和 Neighborhood Goods 发现的大多数商品,消费者都无法带着购买的商品离开商店。

b8ta 是零售业应对大流行病后果的最新牺牲品。首席执行官维布-诺比(Vibhu Norby)说,关闭公司的决定最终是由于与房东的谈判失败。不过,迫使 b8ta 于 2 月 18 日关闭美国门店的不仅仅是大流行病,该公司今天也在其网站上宣布了这一消息。对于数字原生品牌来说,实体零售业的发展已经超越了零售商的核心竞争力。 

该零售店旨在成为消费者体验新时代和数字原生品牌的目的地,这些品牌希望在不开放自有购物体验的情况下获得曝光。

b8ta 于 2015 年成立,当时是一家主要用于测试扬声器和健身自行车等消费类科技产品的商店。但该公司的愿景是重新思考批发与品牌之间的关系,它不仅是一家商店,还是一家 "零售即服务 "提供商。从这个意义上说,它对在其商店销售的品牌做出了更大的承诺。品牌商向 b8ta 支付一定的费用,以便在其货架上出现,并获得其软件的使用权,该软件可提供人流量和演示时间等顾客行为分析的洞察力。在体验式零售的高峰期,恰逢直接面向消费者的品牌向实体店转移,b8ta 被证明是一个很有前途的合作伙伴。b8ta 的模式对没有大型实体店的新品牌很友好,它们希望亲自测试顾客的接受程度。它还迎合了喜欢先试后买的顾客的需求,他们希望在一个地方就能买到精心挑选的新产品。

自 2015 年以来,购物中心所有者集团做出了许多类似的努力:Unibail-Rodamco-Westfield 在几家 Westfield 购物中心推出了 pop-ups;Macerich 也设计了类似的运营模式;Brookfield 也有自己的运营模式。但许多品牌开始完全跳过这个试验场。b8ta 也是商场和百货公司寻找新客流途径的一种资产。梅西百货主导了对b8ta的投资,并在其Market @ Macy's概念中使用了b8ta的技术。随着许多品牌开始投资于全渠道体验,体验式零售被外包。他们希望在商场里有自己的足迹,他们希望手头有存货,他们希望有一个处理退货的地方。

然而,该公司的软件正是许多商场建立数据驱动战略所需要的。b8ta 出售的软件类型与 Placer.ai 所说的商场为适应新一代需求所需的软件类型不谋而合。Placer.ai 在其 2021 年 "商场深度调查"报告中这样概括商场适应数字时代的需求:

大型商场容纳的租户不是几十家,而是上百家,因此连接所有不同零售商的库存数据库需要先进的技术资源。衡量这样一个平台的成功与否则更具挑战性,需要能够同步在线和离线数据的工具。因此,尽管已经有一些例外情况,但目前大多数商场仍然缺乏这种综合性在线应用程序或电子商务渠道。

b8ta 的衰落部分是由于缺乏电子商务销售。大流行导致人流量减少,甚至在商店停业重新开张后也能感受到这种影响,一些商店在重新开张后人流量下降了 98%。这份零售接触点报告描绘了一幅严峻的图景:

据媒体报道,即使在重新开业后,这些商店的经营状况也不尽相同;据《纽约时报》报道,b8ta 在休斯顿的分店在大流行前的一个典型周末平均有 1,000 名顾客,但在 2020 年 5 月的第一个周末,顾客人数下降到 40 人。 协议.奥斯汀店的客流量同样下降了 98%。

对于大多数零售商来说,实体店可以间接推动电子商务销售。而在 b8ta,门店直接负责在线零售销售。在大流行病初期的几个月里,由于门店关闭,b8ta 没有电子商务先行的机会可以依靠。然后,该零售商很可能要忍受无数影响其产品选择和供应的供应链问题。总之,市场力量、消费者行为变化和供应链偏好都导致了公司运营的终结。

但是,为了躲避最近的公告,b8ta 不得不尝试一种转机:把商店变成视频工作室,进行现场直播。这其中还有另一个教训。大流行时代的主流技术可能是一种资产,但不是救生艇。诺比告诉《现代零售业》,现场直播销售未能弥补 b8ta 面临的差距,最终导致一位房东决定不就其租约进行谈判:

"诺比说:"我们在整个科威德都很有创意。但他最后说他总结道:"可能钉在棺材上的钉子是房东的整体待遇,以及他们是否觉得你的公司很重要。我们用尽了所有办法,这是必须要做的事情"。

b8ta 的倒闭并不是简单的概念失败,而是市场力量吞噬零售业未来的结果。未来的迭代者最好注意:不要把所有精力都放在一个渠道上,即使是你正在重塑的渠道。该公司花了七年时间进行测试,而在此期间,整个行业经历了翻天覆地的变化。

作者:Web Smith | 编辑:Hilary Milnes,美术:Alex Remy 和 Christina Williams