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Proof A Live confirmed

Qwen App

GenAI shopping agent that searches, compares and places orders in a marketplace catalog from a chat interface

IndustryRetail & e-commerceLeverActivation / conversionFamilyConversationImplementationCustom AIStagediscovery -> consideration -> purchase -> post-purchase
Pattern proven in 9 industries still untouched in Banking, insurance & fintech, CPG & D2C, Tech & SaaS +3 See the pattern map
250M
Users who have made a first AI-driven purchase through Qwen since its launch (as of the quarter ended June 30, 2026)
"250 million users have had their first AI-driven shopping experience" S1

According to its results filed with the SEC, Alibaba counts 250 million users who made their first AI-driven purchase through the agentic features of the Qwen app (up from about 140 million at the end of February 2026), without publishing any effect on conversion or GMV.

Key points

  • Alibaba connects its Qwen AI app to Taobao, Tmall and fast delivery so users can shop in conversation.
  • Qwen agents with order, logistics and customer service skills, across more than 4 billion products.
  • 250 million users have made a first AI-driven purchase through Qwen.
  • Evidence A on scale only: no effect on conversion or GMV published, launch heavily subsidized.

Objective

Make Alibaba's consumer AI assistant a new entry point to its marketplaces, by moving the start of the purchase from the search bar to the conversation, and thereby extend the customer reach of the group's e-commerce.

The deployment

Qwen, Alibaba's consumer AI app, was connected on January 15, 2026 to the group's services (Taobao and Tmall, Taobao Instant Commerce, Amap, Fliggy, Alipay) to carry out real tasks: ordering a meal or groceries, booking a ticket, buying a product. The launch was driven by a Chinese New Year campaign starting February 6, with three billion yuan in incentives announced by the group. According to the quarterly results published in March 2026, about 140 million users had made their first AI-driven purchase through Qwen's agentic features by the end of February, and Qwen had passed 300 million monthly active users. On May 11, 2026, Alibaba opened the entire Taobao and Tmall catalog (more than 4 billion products) to the Qwen app, whereas the commerce features had until then covered only a few test categories, and launched a Qwen Shopping Assistant in the Taobao app, reachable from the messages tab: comparisons, virtual try-on for clothing, coupon stacking during shopping festivals, and 30-day price tracking that places the order automatically once the target price is reached. In its results for the quarter ended June 30, 2026, Alibaba reports 250 million users who have made their first AI-driven purchase through Qwen since its launch. The group, however, publishes no conversion, basket or GMV figure attributed to these agents; on the contrary, it cites a rise in inference costs tied to the Qwen app among the losses of its AI segment. The evidence therefore covers adoption at scale, not an isolated commercial effect, and that adoption was obtained with heavy subsidies.

Results Proof A

250M
Users who have made a first AI-driven purchase through Qwen since its launch (as of the quarter ended June 30, 2026)
"250 million users have had their first AI-driven shopping experience" S1
140M
Same indicator at the end of February 2026, after the Chinese New Year campaign
"approximately 140 million users have had their first AI-driven shopping experience" S2
300M+
Monthly active users of consumer Qwen, across all platforms (February 2026)
"consumer-facing Qwen has surpassed 300 million monthly active users across all platforms" S2
4 Mds+
Taobao and Tmall catalog products accessible to the agent since May 2026
"catalog of over 4 billion products" S3

The adoption figures appear in two earnings releases filed with the SEC (6-K); they prove scale, but no effect on conversion or GMV is published, and initial adoption was bought through a three billion yuan campaign.

How it works

Documented architecture
retours d'usage reels pour ameliorer les modeles Requete en langagenaturel (app Qwen ouonglet messages Taobao) Historique de commandeset avis clients Taobao Agents Qwen avecbibliotheque decompetences Qwen Catalogue Taobao etTmall, Taobao InstantCommerce Taobao / Tmall Commande dans le chat,logistique, apres-vente

The stack in detail

How it runs, concretely

For ops teams
CadenceReal time, at each user request in the chat; peak periods driven by campaigns (Chinese New Year, 618) with financial incentives.
Operated byThe consumer Qwen group (now AI Labs and Applications) for the app, Taobao and Tmall e-commerce teams for the integrated assistant and the catalog.
  1. 1
    Capture the intent AI

    The user describes a need in the chat; the agent asks follow-up questions about budget or style.

  2. 2
    Search and compare AI

    The agent queries the Taobao and Tmall catalog, suggests options or a product bundle and side-by-side comparisons, drawing on the order history.

  3. 3
    Order in the chat AI / user

    The transaction is completed in the conversation window, with platform coupons stacked; price tracking can trigger the purchase automatically at the threshold set by the user.

  4. 4
    Track and provide after-sales service AI / e-commerce platform

    The agent's skills cover order management, logistics and after-sales service.

The signal that drives it

The intent expressed in natural language and the user's order history. Without access to the full catalog and to the order and logistics skills, the agent can only advise and sends the user back to classic search.

How your customers perceive this type of use

Sourced studies

Les consommateurs n'acceptent pas les chatbots par defaut : 64% prefereraient que les entreprises n'utilisent pas d'IA dans leur service client (Gartner, 2024) et pres d'un utilisateur sur cinq du service client par IA n'en retire aucun benefice (Qualtrics, 2025). L'acceptation se construit sur trois conditions mesurees par Salesforce : savoir qu'on parle a une IA, pouvoir escalader vers un humain, comprendre la logique de l'agent.

64%
Consommateurs qui prefereraient que les entreprises n'utilisent pas d'IA dans leur service client (2024)
53%
Consommateurs qui envisageraient de passer a un concurrent s'ils apprenaient que l'entreprise prevoit d'utiliser l'IA pour le service client (2024)
pres de 75%
Consommateurs qui veulent savoir s'ils communiquent avec un agent IA (2024)

Acceptance conditions

  • Etre informe qu'on parle a une IA et non a un humain (pres de 75% le demandent, Salesforce 2024)
  • Un chemin d'escalade clair vers un agent humain (45% plus enclins a utiliser l'agent IA, Salesforce 2024)
  • Une logique de l'agent clairement expliquee (44% plus enclins, Salesforce 2024)

Red lines

  • Rendre l'humain injoignable : c'est la premiere inquietude des consommateurs sur l'IA dans le service client (Gartner 2024) et 50% craignent que l'IA les coupe du contact humain (Qualtrics 2025)
  • Remplacer le service client par l'IA sans alternative : 53% envisageraient de partir chez un concurrent (Gartner 2024)

Sources: Salesforce 2024 · Gartner 2024 · Qualtrics 2025

See full acceptance: by country, by use, by generation

How to replicate

Inference, not sourced

Data prerequisites

  • A structured product catalog that can be exposed to an agent (attributes, stock, prices, lead times)
  • Order history and customer reviews usable for personalization
  • Order, logistics tracking and after-sales APIs the agent can call

Org prerequisites

  • A clear decision on how the classic search journey and the conversational journey coexist
  • Guardrails on purchases triggered by the agent (confirmation, caps, cancellation)
  • Measurement of the incremental effect planned from the start, separate from adoption

Possible stack

  • General-purpose LLM with tool calling (function calling) connected to the commerce APIs
  • Agentic purchase protocols offered by platforms and payment providers
  • Existing product search engine exposed as a tool for the agent
Team to operateConversational commerce product manager, LLM and API integration engineers, data analyst for incremental measurement, lawyer for automatic purchases and data protection.

The plan, step by step

  1. Step 1
    Expose the catalog, the cart and order tracking as tools an agent can call.Deliverable: A documented and secured commerce API layer for the agent
  2. Step 2
    Launch a shopping assistant on a few test categories, with follow-up questions and comparisons.Deliverable: Assistant in production on a limited scope
  3. Step 3
    Run a controlled test against the classic search journey and read conversion, basket and returns.Deliverable: Measurement of the incremental effect, separated from volumes driven by incentives
  4. Step 4
    Extend to the full catalog and add after-sales skills and price tracking.Deliverable: Agent covering the whole journey, from inspiration to after-sales

First step: Pick a category where comparison is tedious (equipment, home appliances), connect an agent there that queries the catalog and prepares the cart, and compare its conversion with classic search on a randomly drawn sample.

Sources

  1. S1 Alibaba Group Announces June Quarter 2026 Results (Form 6-K, Exhibit 99.1) Primary sec.gov · 2026-08-20 · accessed 2026-10-05 archive pending
  2. S2 Alibaba Group Announces December Quarter 2025 Results (Form 6-K, Exhibit 99.1) Primary sec.gov · 2026-03-19 · accessed 2026-10-05 archive pending
  3. S3 Alibaba Opens All of Taobao to Qwen AI, Ushering in a New Agentic Shopping Experience - Alibaba Group Primary alibabagroup.com · 2026-05-11 · accessed 2026-10-05 archive pending
  4. S4 Alibaba in 3b yuan Lunar New Year red envelopes push - RTHK Established press news.rthk.hk · 2026-02-02 · accessed 2026-10-05 archive pending