Glance and True Fit Partner: AI Eliminates Size Guesswork in Online Shopping
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- Glance menggandeng True Fit untuk menggabungkan penemuan produk berbasis percakapan dan data kecocokan ukuran, mengurangi ketidakpastian belanja fesyen daring.
- Data True Fit menunjukkan lebih dari 70 persen pembeli menanyakan soal ukuran kepada agen AI, menandakan pergeseran perilaku konsumen.
- Integrasi ini akan tersedia pada musim liburan 2026, dengan perluasan ke merchant True Fit pada 2027, berpotensi mengubah lanskap ritel fesyen global termasuk Indonesia.

AI-powered personalized shopping platform Glance has officially partnered with True Fit, a company specializing in apparel size and fit intelligence. This collaboration aims to answer the classic question that often haunts online shoppers: will this clothing fit?
This move combines two complementary capabilities. Glance brings conversational product discovery technology and generative virtual try-ons, while True Fit provides an intelligence layer built from nearly two decades of transaction and return data. As a result, consumers can not only find their desired style but also receive more precise size recommendations.
According to Mansi Jain, Chief Operating Officer of Glance, artificial intelligence is now shifting more purchasing decisions into conversations. "AI agents must be able to answer questions that determine whether someone makes a purchase. In fashion, size is one of them," she stated. True Fit's internal data reveals that over 70 percent of shoppers ask AI agents about sizing, indicating that fit issues are a major barrier in online fashion transactions.
This partnership is more than just a technical integration. For Glance, access to True Fit's return and purchase data strengthens the accuracy of size recommendations, which has long been a weak point in online shopping. Conversely, True Fit gains a broad distribution channel across various consumer devices, expanding the reach of their solutions. "Glance can help shoppers discover products and see them on themselves, while True Fit adds evidence of which size is most likely to fit based on real purchase and return behavior," Jain explained. "When those signals come together, shoppers can act with more confidence, and retailers have a greater chance of converting intent into lasting sales."
In the context of the global retail industry, this move reflects a trend towards agentic commerce, where AI agents not only assist with searching but also make purchasing decisions. True Fit's nearly 20 years of experience provide a strong data foundation, while Glance offers a conversational interface increasingly favored by consumers. Jessica Murphy, co-founder and CEO of True Fit, believes the value of the agentic commerce experience heavily depends on the quality of the decisions produced. "Glance demonstrates how our Intelligence Layer can accompany the shopping experience across various consumer surfaces, bringing specific size guidance to the moment shoppers need it," Murphy stated.
For Indonesia, this development has the potential to transform the fashion e-commerce landscape, which has long been characterized by high return rates due to sizing issues. With a large digital population and rapid AI adoption, platforms like Tokopedia, Shopee, or Zalora could adopt similar technologies to reduce reverse logistics costs and enhance customer satisfaction. However, the main challenge lies in the availability of representative local sizing data, as body shapes and size preferences in Indonesia may differ from True Fit's global data. This partnership also opens opportunities for local brands to reach international markets through more accurate recommendations.
Looking ahead, the big question is how quickly this integration can be widely adopted and whether similar models will soon emerge in Southeast Asia. With a launch schedule set for the 2026 holiday season, competition in AI-powered fashion shopping is predicted to intensify, and consumers will become increasingly accustomed to shopping experiences guided by intelligent agents.



