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Pinterest Pin Sharing Drop Investigation

Root Cause Analysis · beginner

Pinterest recently launched a new update to its mobile app that was supposed to improve the user interface. Instead, it seems to have caused a 15% decrease in pin sharing among users. You must diagnose the root cause of this decline. Focus on identifying the specific aspects of the update that could have led to this decrease. Do not propose any solutions yet.

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Community approaches

Dhruv’s approach

FRAMING Two users. The saver, who browses for ideas and keeps what they like. And the sender, who passes a pin to a friend. Pinterest runs on a loop: people save, boards get richer, recommendations improve, more people save. Shares also bring new users in, so this metric is engagement and acquisition at once. The tension in any redesign: a cleaner screen means fewer visible actions. Every control you hide to cut clutter costs some of the behaviour behind it. One clarification first. "Pin sharing" can mean saving a pin to your own board, or sending it to someone. Different flows, different causes. I would confirm which, and will assume sending. No solutions yet, as instructed. My output is a tested diagnosis.

  1. WHAT THE UPDATE COULD HAVE TOUCHED
  • The share control moved, shrank, lost its label, or went into an overflow menu.
  • The action bar went from always visible to appearing only on tap.
  • A gesture disappeared, such as long-press to share.
  • The share sheet was rearranged, shows fewer destinations, or gained a step.
  • Actions moved below the fold on the pin page.
  • Contrast dropped, so the icon blends into the image behind it.
  • A login or permission prompt now sits in the path.
  • The build is heavier, so the sheet is slow or fails on weak devices.
  • The share event was renamed or stopped firing in the new build.
  1. VALIDATE THE NUMBER
  • Count or rate? If sessions fell, share count falls with no change in behaviour. I want shares per pin viewed.
  • Is the event still firing? Releases change tracking as often as they change UI. Compare client events against server-side receipts.
  • Compare updated users against users still on the old build. A natural control group, and the fastest way to show whether the update caused this.
  • Does the drop track the rollout curve, or was it already sloping before release?
  • Did the definition change? Saves excluded, or multi-destination sends deduplicated.
  • Check YoY, since sharing is seasonal around holidays and weddings.
  • Split iOS and Android. They rarely update together, so a simultaneous drop is suspicious.
  1. WHERE IN THE FLOW IT BREAKS Shares = active users x pins viewed x share rate per pin x completion of the share flow. The flow: pin seen, pin opened, action bar seen, share tapped, destination chosen, sent. Three forks, each a different problem:
  • Fewer pins viewed, share rate flat. An engagement problem, not a sharing problem.
  • Views flat, share taps down. A discoverability problem. The control is harder to find.
  • Taps flat, completions down. The sheet itself broke. Find the screen people abandon. Then segment: new against tenured users, app version, device tier, network speed, destination.
  1. HYPOTHESES, ranked by likelihood x impact / cost to check H1 The event stopped firing. Confirm: server-side sends flat while client events fall, drop tracks version adoption exactly. Kill: server side confirms the fall. H2 The control is buried. Confirm: action bar views flat, share taps down, overflow menu opens up. Kill: taps per action bar view unchanged. H3 An extra step was added. Confirm: taps flat, completion down, a clear abandon point on the new screen. Kill: completion flat. H4 Lower visual salience. Confirm: drop sits with new and casual users who relied on the label, tenured users flat. Kill: drop is uniform across tenure. H5 A gesture was removed. Confirm: the opposite pattern, concentrated in heavy users who used the shortcut. Kill: drop sits with new users. H6 Performance. Confirm: sheet load time and error rate up, worse on low-end devices and slow networks. Kill: latency flat. H7 Mix shift. Confirm: count flat, rate down, because the update pulled in more light users. Kill: count down too.

WHAT I WOULD HAND OVER An attribution, not a single cause: how much of the 15% is measurement, how much discoverability, how much flow friction. H1 and the old-build comparison run first, because both are cheap and either can close the investigation in a day.

LearnProduct’s approach

  1. First analyse the user flow of the new UI update and check for the placement of share pin button.
  2. Validating the share rate between both the UI
  3. Checking the point of drop off rate in the UI
  4. Checking the post view rate
  5. Hypothesing the UI change in the pin share button causing the drop in the pin share rate
  6. Discoverability: the share button is less visible or moved behind an overflow menu, so fewer users find it (drop concentrated at the entry-point step).
  7. Added friction: the new share flow requires more taps or a new confirmation, so users start but don't complete (drop at the share-sheet step).
  8. Competing prominence: save/react/comment got more visually dominant, cannibalizing share taps.
  9. Recognition: icon or label changed and users no longer identify it as share.
  10. Instrumentation: the share event is under-logged post-update, so the "decline" is partly measurement.
  11. Upstream shift: the redesign changed the feed so users see fewer highly shareable pins.

Yuvraj’s approach

Identify potential causes linked to the UI update.: -The UI update in the app has caused resistance/friction for the existing users that were used to the old UI before the update was rolled out. This can be related to new pin sharing icon, button location change or navigation change. After the UI update, the pin sharing button is hidden deep and takes a few extra steps to reach. This can cause a decline in the sharing feature. -The pin sharing flow is broken or has some errors after the UI update was rolled out and skipped essential end to end testing. -The pin sharing is now available after the user logs in whereas earlier it was available for both logged in and logged out users. -External factors like competitor rolling out similar kind of feature and oulling engagement from our users.

Validate the metric or data showing the decrease.: -Avg pin sharing and per week before the UI update VS Avg pin sharing per week after the update -Daily pin sharing before and after

  • No of pin shares per user after the update -No of unique users pressing the pin sharing button daily

Break down the user flow to pinpoint where the drop occurs.: User logs in, views images of interest, finds pin sharing button. This is where the friction happens. The user is not accustomed to new UI and struggles to find the button because of wither- the icon or colour has changed or the location/position of the button has chnaged. This breaks the flow and interest of the user causing decline in the sharing feature.

Hypothesize specific UI changes that may have influenced behavior.:

  • navigation changes -location/position change of the button -icon chnage of the button -sharing icon colour change -extra step or screen before the pin gets shared