· PM Editorial · Product Sense · 6 min read
Improve Instagram Stories: Complete Product Sense Answer
A structured product sense framework for the classic 'How would you improve Instagram Stories' interview question, covering engagement, creator tools, monetization, and discoverability.
Updated July 2026
“How would you improve Instagram Stories?” is one of the most common product sense prompts in PM interviews, precisely because most candidates know the product well enough to have opinions, but few structure those opinions into a defensible, prioritized answer. This guide walks through a complete answer using a repeatable framework, then applies it across four dimensions: engagement metrics, creator tools, monetization, and discoverability.
Overview
Before jumping to solutions, ground the answer in what Stories actually does for Instagram’s business and for users. Stories is a low-friction, ephemeral content format that increases posting frequency (because the 24-hour expiry lowers the bar for what’s “postable”) and increases session frequency (because users check back multiple times a day to avoid missing content before it disappears).
Any improvement needs to be evaluated against these core mechanics: does it increase posting frequency, does it increase return visits, does it deepen creator investment, or does it open new monetization surface, without breaking the low-friction, low-stakes feel that makes Stories work in the first place.
| Framework Step | What to Cover |
|---|---|
| 1. Clarify | Who is the user, what does “improve” mean (engagement, revenue, retention?) |
| 2. User segments | Casual posters, power creators, lurkers/viewers, businesses |
| 3. Pain points | Map friction per segment |
| 4. Solutions | Generate ideas per segment, per pain point |
| 5. Prioritize | Impact vs effort, tie to a north star metric |
| 6. Metrics | Define how you’d measure success and guard against regressions |
Engagement Metrics
Start by clarifying what “engagement” means for Stories specifically, since it’s a different metric from feed engagement. The core engagement metrics for Stories are: stories posted per DAU, story completion rate (percentage of a story sequence watched through), reply rate (DMs or reactions triggered by a story), and repeat-viewing sessions per day.
A common pain point: casual users post Stories rarely because they feel pressure to make each one “good,” which undercuts the low-friction premise of the format. A concrete improvement here is lowering the creative bar further, for example AI-assisted caption suggestions, one-tap templated layouts pulled from camera roll photos, or “draft and auto-post later” flows that reduce the in-the-moment social pressure of posting live.
On the viewing side, completion rate often drops mid-sequence when users hit a low-interest story from an infrequently-viewed friend. A ranking-based reorder of story order (already partially in place) rewards high completion-rate posters with earlier placement, but the interview answer should acknowledge the tradeoff: over-optimizing order for completion rate can suppress reach for less “produced” posts from close friends, which is exactly what makes Stories feel authentic. The recommendation should be to rank primarily by relationship closeness signals first, and use completion-rate signals only as a secondary tiebreaker.
Creator Tools
Power creators are a distinct segment with different needs: they want richer editing (multi-clip stitching, better text/sticker tools, template reuse across days) and better performance visibility (who’s viewing, where drop-off happens within a multi-slide story, which slides drive replies).
A concrete gap: today’s Stories analytics are shallow compared to what serious creators get on TikTok or YouTube Shorts. Adding slide-level drop-off analytics (similar to a funnel view) would let creators iterate on pacing and hook strength within a single story sequence, directly increasing completion rate at scale by helping the highest-volume posters improve their own content.
Template reuse is another underserved need: creators who post daily “get ready with me” or routine-style Stories currently rebuild the same layout from scratch each time. A “story templates” feature, letting a creator save a layout (sticker positions, text style, music cue) and reapply it to new photos/video, reduces production time and increases posting frequency among the highest-value creator segment.
Monetization
Stories currently monetizes primarily through full-screen ads inserted between organic stories. The core monetization tension is that ad load directly competes with completion rate and session length, since ads interrupt the exact behavior (rapid, low-friction browsing) that makes the format valuable.
A better lever is monetizing the creator economy side rather than pure ad load: expanding “swipe up to shop” style commerce stickers to more creators, adding native tipping/gifting during live-adjacent story content, and building affiliate link stickers with in-app checkout attribution. These increase Meta’s take-rate on commerce that’s already happening informally (creators posting product photos and driving traffic to external stores) while giving creators a direct incentive to post more frequently and with commercial intent, without adding interruptive ad load.
Discoverability
Stories discovery today is almost entirely relationship-driven: you see stories from people you follow, ranked by a mix of recency and relationship signals. This means new creators and businesses have almost no organic discovery path within Stories specifically, unlike Reels which has a dedicated discovery surface.
A concrete improvement is a lightweight “Stories you might like” tray, surfacing a small number of public-account stories from outside your follow graph, similar to how Explore surfaces Reels, but scoped conservatively (2-3 slots max) to avoid diluting the close-friends feel that defines the format. This would need careful metric guardrails, since over-indexing on discovery content risks eroding the core “keeping up with friends” value proposition that drives daily return visits.
Prioritization and Wrap-Up
If asked to prioritize across all four areas in an interview, a strong answer ties prioritization back to the stated goal. If the goal is engagement/retention, prioritize the low-friction posting tools and ranking refinement first, since they compound across the entire user base. If the goal is revenue, prioritize commerce stickers and affiliate checkout, since ad load has diminishing returns and creator commerce is a largely untapped adjacent surface. If the goal is competitive response (e.g., against TikTok), prioritize creator analytics and templates, since creator retention is the binding constraint in a multi-platform creator economy.
FAQ
Should I pick one focus area or cover all four in an interview? Structure your answer to briefly acknowledge all four, then explicitly choose one or two to go deep on based on the stated goal, rather than giving equal shallow treatment to everything.
How do I handle the interviewer asking “how would you measure success” for a specific idea? Tie the metric directly to the mechanic the idea targets: posting-frequency ideas should be measured by stories-posted-per-DAU, discovery ideas by session frequency and time-to-first-story-of-the-day, monetization ideas by revenue-per-story-impression alongside a completion-rate guardrail metric.
Is it okay to critique existing features? Yes, and it strengthens your answer, provided the critique includes the tradeoff the current design is likely optimizing for, not just “this feature is bad.”
What’s the biggest mistake candidates make on this question? Jumping straight to a list of feature ideas without first clarifying the goal and segmenting users, which makes the prioritization step later in the interview feel arbitrary.
How long should this answer take in a real interview? Roughly 20-25 minutes for the full loop: 3-5 minutes clarifying, 5 minutes on segments/pain points, 10-12 minutes on solutions and tradeoffs, 3-5 minutes on prioritization and metrics.
For a complete set of structured answers to product sense questions like this one, see The 100x Product Manager Interview Playbook on Amazon.