LinkedIn’s engagement is falling by 10% day over day. What would you do?

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LinkedIn’s engagement is falling by 10% day over day. What would you do?

Asked at Linkedin in the past year

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Abhijeet Das · Answer 1 · 2025-07-02T05:52:22+0000

LinkedIn's engagement is falling 10% daily

Since when is this happening? Last one month

Any specific geography? India

Any specific users - Free/ Paid? Overall

Any specific user segments - Job seekers, Recruiters, Creators? All

Any specific platform- Mobile/ Web? Overall

Analysis -

Funnel analysis -

% users login
Login -> Home page
Time spent on home page
% posts read
% posts reacted to
% posts commented
% post shared
% post written

Module analysis -

Feeds
Jobs
Notifications
Messaging
Posts

We need to analyze the above metrics to pin point the exact issue where we could see this gradual decline in engagement

Hypothesis -

Internal factors -

Did we make any new feature release?
Did we make any UX changes?
Did we fix any bugs?
Did we make any changes to the algorithms related to priority order of posts being shown to users?

External factors -

Was there any price policy change recently?
Was there any seasonality invovled, e.g, holiday time during which the users are less active on LinkedIn?
Was there any new competitor offering rolled out recently?
Have we received any customer complaints lately? Split of issues?

Validations -

Internal factors - Any releases, bug fixes might have an immediate issue not gradual decline, so we rule these out.

However, algorithm change can ahve a gradual impact, where over time users realize that they are not able to see/ search their relevant content and as a result they are coming less often to LinkedIn.

External factors - Holiday season effect won't last over a month, it should have bounced back, so we can rule this one out.

Also, if price change has an impact, it will impact the paid users engagement majorly. But, as confirmed about both sets of users have seen a similar decline. so we can rule this one out as well.

Similarly, competitor offering will also have a immediate effect most likely where suers would churn away from LinkedIn and join the new platform, so we can rule this one out as well.

Apart from this, we need to analyze the customer complaints data, to understand what is the exact root cause of this gradual decline.

Solutioning -

In the short term, we need to revert the changes done to the system asap and clearly communicate to our users, and observe if the issue comes to normalcy again.

In the long term, we need to do a deep dive on customer complaints, revist our roadmap, prioritise the issues based on impact and effort and start fixing them and closely monitor the metrics.

In addition to that, we need to redo our analysis of optimising the content visibility for the users based on their past history of reactions and engagement with the content they found relevant and accordingly keep on continuously improve the recomemndation algorithm.

Success metrics -

Time spent in app

User activity (posts, impressions)

NPS

ManicPixieDream · Answer 2 · 2024-09-18T19:58:55+0000

Clarify the Problem:

Define "Engagement": Specify the engagement metrics experiencing the decline (e.g., likes, views, reposts, time spent, messages sent).
Establish the Timeframe: Determine the specific period over which the 10% day-over-day drop is occurring (e.g., past week, past month). This helps eliminate seasonality or temporary trends.

Focus the Investigation (Assumptions):

Prioritize Key Metrics: For this analysis, we'll focus on "likes" and "time spent" as primary engagement indicators. This assumes these are key indicators of early user engagement within the platform.
Set Analysis Period: We'll analyze data from the past month to minimize the impact of cyclical variations and capture a broader trend.

Rule Out External Factors:

Investigate External Events: Consider whether external factors like holidays, geopolitical events, or industry-specific trends could be contributing to the decline.

Root Cause Analysis (Assuming External Factors Are Ruled Out):

User Segmentation:

Divide users into segments based on demographics, industry, geography, or platform usage patterns.
Analyze engagement trends within each segment to identify if the decline is concentrated in a specific user group.

Product Feature Analysis:

Examine recent product updates or changes that might have impacted user experience.
Analyze user drop-off points within the platform to identify specific features or areas where users disengage.
Hypothesis 1: Changes in Scrolling Behavior: Investigate if modifications to the scrolling mechanism (e.g., infinite scroll, content loading speed) have negatively impacted user engagement.
Hypothesis 2: Content Relevance Algorithm: Analyze if adjustments to the content relevance algorithm are surfacing less engaging or irrelevant content to users, leading to decreased interaction.
Hypothesis 3: Perception of Likes: Explore whether changes in the display or visibility of "likes" within the feed (e.g., hidden like counts, changes in notification behavior) have affected users' perception of social validation and engagement.

Content Engagement Analysis:

Identify the types of content and actions in the feed that historically drive the most engagement (likes, comments, shares).
Investigate if there have been any changes in content strategy, algorithm, or user behavior that might be negatively impacting engagement with these high-performing content types.