Launching the first commerce chatbot in the 7-Eleven Thailand app for 16M+ users
7-Eleven Thailand has 15,000+ stores and an app with 16M+ monthly active users. The company wanted to open a new digital sales channel as part of its digital transformation.
I was the Program Manager at Sertis, embedded with the 7-Eleven team. I managed a $450K project across business, UX, data, engineering, marketing, and customer support. This was before ChatGPT, so every intent, conversation flow, and fallback was designed by hand.
- Role
- Program Manager · 2019 to 2021
- Industry
- Online Retail
- Skills
- Program Management · Delivery · Requirements Gathering · KPI Tracking · Conversational Design · Funnel Analysis · Stakeholder Management · UAT and Go-Live
- Tools
- Google Dialogflow · SQL · Python · RegEx
Requirements gathering
The brief was to bring commerce into chat, with no detailed requirements. I analyzed app usage data to find what users did most, like browsing products, tracking orders, and finding stores. I then ran requirements workshops with the business team and defined four core flows for v1, each with clear acceptance criteria.
Scope and timeline
The business team wanted more features than engineering could deliver by the launch date. I scoped v1 to the four flows based on usage data and moved the rest to a v2 backlog. I also built buffer into the timeline for UAT fixes.
- Chat commerce: Browse a product carousel and check out without leaving the chat
- Order tracking: Check delivery order status
- Store finder: Find nearby stores, hours, and promotions
- Customer support: [Confirm the fourth flow]
Delivery
I kept six teams aligned with a shared deliverable list, clear owners, and deadlines. I worked with UX and engineering on the conversational flows, including intents, fallbacks, and scripted vs open chat. When marketing and the app team had different launch dates, I ran a joint session to agree on one. I led UAT as the single point where every team’s work came together, then managed go-live.
KPI tracking and iteration
I set up post-launch monitoring so each team could track its flow’s performance. A few weeks in, funnel analysis showed about 70% of users dropped off in the product discovery flow, which asked two to three questions before recommending a product.
I segmented session data by user intent and ran follow-up surveys. Users who already knew what they wanted were leaving. We removed the questions and let users state what they want. I aligned the 7-Eleven business owner and marketing team on the change before release.
Result: All four flows launched on time. The chatbot handled 800K+ inquiries a month with replies in under 30 seconds. After the change, drop-off fell by ~22%, and the 7-Eleven marketing executive gave us very positive feedback.
What I learned
Validate with users early: Post-launch tracking caught a problem that planning missed, and fast iteration turned it around.