Investigate why conversion fell after a Acrobat launch

Problem Statement Description

Product context: Adobe is a creative, document, and marketing software company; its products include Creative Cloud, Photoshop, Illustrator, Acrobat, Adobe Express, Firefly, and Experience Cloud.

Adobe Acrobat has recently launched an update or new experience aimed at video editors, and shortly after launch the team observes a meaningful drop in conversion. Conversion may refer to users moving from visit to trial, trial to paid subscription, upgrade, or checkout completion, so part of the investigation is to clarify the exact funnel and impacted user journey.

The affected users are video editors who rely on document workflows around production briefs, contracts, scripts, storyboards, review notes, transcripts, client approvals, and collaboration with creative or marketing teams. The drop may be tied to the new launch itself, changes in positioning, pricing, onboarding, AI-enabled features, account flows, performance, eligibility, or external market factors.

You are expected to frame a structured root-cause analysis, not jump directly to a fix. Focus on how you would verify the anomaly, segment the impact, inspect instrumentation, generate hypotheses, gather evidence, and decide what actions or mitigations are appropriate.

The experience should consider:

- The exact conversion metric definition, funnel step, denominator, time window, and baseline used before and after launch.

- Whether the decline is isolated to video editors or also visible across other Acrobat user segments, geographies, plans, devices, channels, or customer types.

- Instrumentation checks, including event tracking changes, attribution issues, experiment exposure, checkout logging, and data pipeline delays.

- Funnel segmentation across landing page, onboarding, feature discovery, sign-in, trial start, paywall, checkout, payment success, and post-trial upgrade.

- Launch-specific hypotheses such as messaging mismatch, broken flows, pricing or packaging confusion, performance regressions, eligibility issues, or feature expectations not being met.

- External hypotheses, including competitive activity, seasonality in creative work, acquisition channel mix changes, or shifts in demand from adjacent creative tools.

- Evidence needed to prioritize causes, such as cohort analysis, session replay, support tickets, qualitative feedback, sales/customer success input, and experiment results.

- Mitigation and prevention considerations, including rollback criteria, targeted communication, monitoring dashboards, and post-launch quality gates.

Your goal is to demonstrate how you would lead a clear, evidence-driven investigation that identifies whether the conversion decline is real, where it is happening, who is affected, why it is happening, and what near-term and long-term actions the Acrobat team should evaluate.