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Cameron Michael Malloy 发布:Studio AI 试点预测零售购买行为

想分享最近试点的一些令人兴奋的结果: MìLà 进行了一项传统的消费者研究,以预测零售产品的购买行为。@tryStudioai构建了一个市场模型来盲目预测相同的行为。然后,我们将 Studio 的预测与传统市场研究在预测产品推出后真实消费者购买行为的准确性方面进行了比较。 Studio 在模拟购买行为方面的准确率超过 97.5%,高于综合小组、模拟实验室或传统市场研究发布的任何预测。该模型在 52 周总美元比较中的误差也降低了 22%,并且在各种销售指标和时间窗口的所有 18 项绩效评分削减中更接近。 到目前为止,我们不得不依赖人们的说法。 Studio 准确地预测了他们的行为。 http://trystudio.ai :)

查看英文原文

Wanted to share some exciting results from a recent pilot: MìLà fielded a traditional consumer study to forecast purchase behavior for a retail launch. @tryStudioai constructed a model of their market to forecast the same behavior blind. We then compared Studio's predictions and the traditional market research in their accuracy at predicting real consumer purchase behavior after the products were launched. Studio was 97.5%+ accurate at simulating purchase behavior, higher than any published forecast from a synthetic panel, simulation lab, or traditional market research. The model also had 22% lower error on the 52-week total-dollar comparison, and was closer in all 18 performance scoring cuts across a variety of sales measures and time windows. Till now, we've had to rely on what people say. Studio accurately predicts what they do. http://trystudio.ai :)

Wanted to share some exciting results from a recent pilot: MìLà fielded a traditional consumer study to forecast purchase behavior for a retail launch. @tryStudioai constructed a model of their market to forecast the same behavior blind. We then compared Studio's predictions and the traditional market research in their accuracy at predicting real consumer purchase behavior after the products were launched. Studio was 97.5%+ accurate at simulating purchase behavior, higher than any published forecast from a synthetic panel, simulation lab, or traditional market research. The model also had 22% lower error on the 52-week total-dollar comparison, and was closer in all 18 performance scoring cuts across a variety of sales measures and time windows. Till now, we've had to rely on what people say. Studio accurately predicts what they do. http://trystudio.ai :)

企业 Agent 的护城河开始从单一模型转向自有 Harness、成本收据与可替换能力

为什么值得看

模型快速更替后,企业真正可积累的是评测、数据、执行栈和逐调用成本账本;这些能力决定模型能否替换,以及 Agent 是否能进入业务结果。

最强反方

系统所有权仍是作者判断,Conifer 是早期发布,Studio AI 的效果数字来自发布方单次试点,当前没有跨企业 ROI 或长期稳定性读回。

原始出现与传播对照

1 条出现 · 本次 AIHOT 未精确命中

发现与解读

想分享最近试点的一些令人兴奋的结果: MìLà 进行了一项传统的消费者研究,以预测零售产品的购买行为。

想分享最近试点的一些令人兴奋的结果: MìLà 进行了一项传统的消费者研究,以预测零售产品的购买行为。@tryStudioai构建了一个市场模型来盲目预测相同的行为。然后,我们将 Studio 的预测与传统市场研究在预测产品推出后真实消费者购买行为的准确性方面进行了比较。 Studio 在模拟购买行为方面的准确率超过 97.5%,高于综合小组、模拟实验室或传统市场研究发布的任何预测。该模型在 52 周总美元比较中的误差也降低了 22%,并且在各种销售指标和时间窗口的所有 18 项绩效评分削减中更接近。 到目前为止,我们不得不依赖人们的说法。 Studio 准确地预测了他们的行为。 http://trystudio.ai :)

查看英文原文

Wanted to share some exciting results from a recent pilot: MìLà fielded a traditional consumer study to forecast purchase behavior for a retail launch. @tryStudioai constructed a model of their market to forecast the same behavior blind. We then compared Studio's predictions and the traditional market research in their accuracy at predicting real consumer purchase behavior after the products were launched. Studio was 97.5%+ accurate at simulating purchase behavior, higher than any published forecast from a synthetic panel, simulation lab, or traditional market research. The model also had 22% lower error on the 52-week total-dollar comparison, and was closer in all 18 performance scoring cuts across a variety of sales measures and time windows. Till now, we've had to rely on what people say. Studio accurately predicts what they do. http://trystudio.ai :)

Wanted to share some exciting results from a recent pilot: MìLà fielded a traditional consumer study to forecast purchase behavior for a retail launch. @tryStudioai constructed a model of their market to forecast the same behavior blind. We then compared Studio's predictions and the traditional market research in their accuracy at predicting real consumer purchase behavior after the products were launched. Studio was 97.5%+ accurate at simulating purchase behavior, higher than any published forecast from a synthetic panel, simulation lab, or traditional market research. The model also had 22% lower error on the 52-week total-dollar comparison, and was closer in all 18 performance scoring cuts across a variety of sales measures and time windows. Till now, we've had to rely on what people say. Studio accurately predicts what they do. http://trystudio.ai :)

直接发布标题Cameron Michael Malloy@CameronMalloy_打开该层出处 ↗

Wanted to share some exciting results from a recent pilot: MìLà fielded a traditional consumer study to forecast purchase behavior for a retail launch. @tryStudioai constructed a model of their market to forecast the same behavior blind. We then compared Studio's predictions and the traditional market research in their accuracy at predicting real consumer purchase behavior after the products were launched. Studio was 97.5%+ accurate at simulating purchase behavior, higher than any published forecast from a synthetic panel, simulation lab, or traditional market research. The model also had 22% lower error on the 52-week total-dollar comparison, and was closer in all 18 performance scoring cuts across a variety of sales measures and time windows. Till now, we've had to rely on what people say. Studio accurately predicts what they do. http://trystudio.ai :)

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