Diagnose a 20 percent drop in activation for Stays

Problem Statement Description

Product context: Airbnb is a travel marketplace connecting guests and hosts; its products include stays, experiences, host tools, guest booking, trust and safety, payments, and reviews.

Airbnb has observed a 20% drop in activation for Stays, specifically affecting first-time guests. In this context, activation should be treated as the point at which a new guest reaches a meaningful early success milestone in the Stays journey, such as completing a first booking or another clearly defined conversion event agreed upon during the interview.

You are asked to diagnose the issue as a product RCA. Focus on how a first-time guest moves through Airbnb’s Stays experience: landing on Airbnb, searching for a destination, viewing listings, evaluating trust and price, checking availability, creating an account or logging in, booking, paying, and receiving confirmation. Consider that Airbnb operates as a global marketplace where guest demand, host supply, pricing, trust, availability, and policy changes can all affect activation.

Your task is not to jump to a fix, but to structure the investigation. Clarify the metric, validate whether the drop is real, isolate where in the funnel it occurs, identify affected segments, generate hypotheses, and describe what evidence you would use to confirm or rule them out.

The experience should consider:

- How activation is defined, including numerator, denominator, time window, and whether it applies to all new users or only eligible first-time guests

- Whether the 20% drop is a true product/business issue or caused by tracking, attribution, experimentation, data pipeline, or definition changes

- Funnel steps for first-time Stays guests, from acquisition and search through checkout, payment, and booking confirmation

- Segmentation by geography, platform, traffic source, trip type, device, app version, guest cohort, listing category, price band, and host supply availability

- Marketplace factors such as inventory quality, host response behavior, cancellations, fees, pricing, trust signals, reviews, and safety concerns

- External factors such as seasonality, holidays, travel restrictions, macroeconomic pressure, competitor promotions, airfare changes, or regional events

- Evidence needed from dashboards, experiment logs, release notes, customer support contacts, search logs, checkout errors, payment failures, and host-side supply metrics

- Immediate mitigation, monitoring, communication, and prevention steps once the likely cause is identified

The goal is to demonstrate a clear, structured RCA approach that can help Airbnb determine why first-time guest activation for Stays declined, how severe and localized the problem is, and what evidence would guide the next product or operational response.