Evaluating a Proposal to Make the Facebook Stories Tray Twice as Tall

You are the product manager for Facebook Stories. The engineering team has proposed making the Stories widget twice its current height. Treat the widget as the horizontally scrolling row of Story cards that sits above the Feed in the Facebook app. Before the team builds it, lay out the likely advantages and disadvantages of the change. For each one, say who it affects and how you would find out whether it really happens, then give your recommendation. ```hint Count what the space displaces A taller widget does not create new screen space; it takes space from whatever sits below it. List every group of people whose experience changes, on both sides of that trade, before you sort the effects into pros and cons. ``` ### Clarifying Questions - What problem is engineering trying to solve: too few Stories views, too few people posting Stories, a new preview format, or something technical? - Will the taller cards show more of each Story, such as a larger or moving preview, or simply scale up today's thumbnail? - Does the change apply on every surface and screen size, including small phones and the desktop site? - Am I accountable for Stories metrics alone, or for overall Facebook engagement and revenue? ### What a Strong Answer Covers - Effects organized by the groups the change touches: people viewing Stories, people posting Stories, people whose Feed posts move down the screen, advertisers, and Facebook as a whole - The cost of moving Feed content and Feed ads lower, and whether Stories gains are new engagement or time moved away from the Feed - Practical costs: small screens, loading speed, data use, and users who never open Stories - A recommendation tied to an explicit goal, with the metrics, guardrails and test design that would confirm or refute it - Alternatives that keep most of the upside at a lower cost ### Follow-up Questions - The test shows Stories views up and Feed time slightly down, with total ad revenue flat. Do you ship? - A test that randomizes viewers cannot show whether people start posting more Stories. How would you measure that effect? - How would your recommendation change for users who have not opened a single Story in the past month?