A social media analysis example is what many people are looking for - and what very few actually show. There is usually theory, frameworks or tool screenshots. But hardly anyone explains in concrete terms what an analysis looks like, which figures are considered and what can be derived from them. That's exactly what this article is for. No glossy gloss. No tool marketing. A sober, comprehensible example of what a social media analysis looks like in practice.
A social media analysis example shows
which KPIs are evaluated
how the data is interpreted
what conclusions are drawn from it
It's not about presenting perfect figures, but about showing: 👉 How to get from data to decisions.
To keep the example realistic, we set clear boundaries.
Initial situation (fictitious, but realistic):
Platform: Instagram
Account: Company profile (B2B service)
Time period: 30 days
Goal: Visibility + interaction
No growth hack, no viral case. Everyday life.
Before looking at figures, it must be clear: What should be evaluated?
In this marketing social media analysis example, the goal is
stable reach
increasing engagement
No analysis without a goal - just data collection.
For this goal, we deliberately choose few key figures:
Reach
impressions
Interactions
Engagement rate
Follower growth
More KPIs would dilute the example.
KPI | Value (30 days) |
Reach | 42.000 |
Impressions | 68.000 |
Interactions | 1.260 |
Engagement rate | 3,0 % |
Follower growth | +2,1 % |
This is not a dream figure - but it is realistic.
Reach increases slightly
Impressions are significantly higher than reach
👉 Interpretation:
Content is seen multiple times
Algorithm plays content repeatedly
Visibility is present
Reach alone says nothing about quality
1,260 interactions with 42,000 reach
Engagement rate: 3.0 %
In context:
Solid for B2B accounts
No viral signal, but stable reactions
👉 Important: Engagement is evenly distributed, not post-dependent.
Observations:
Specialist posts → high reach, few comments
Opinion posts → lower reach, more interactions
Reels → high impressions, fluctuating engagement
👉 Interpretation:
Reach ≠Effect
Different content types fulfill different goals
This is a typical finding from a real analysis.
+2.1 % growth in 30 days sounds unspectacular - and it is.
But:
Growth is stable
No slump despite constant posting frequency
👉 Conclusion: The content is not a deterrent - an important, often overlooked signal.
Classification:
Engagement rate slightly above industry average
Reach per post constant
👉 Result: Not an outlier, but a clean basis on which to optimize.
Benchmarks help with classification - not with evaluation.
What works:
consistent reach
Stable engagement rate
no negative signals
What doesn't:
no strong growth lever
Content formats not yet clearly separated
A good social media analysis example does not end with numbers.
Consequences:
Separate content more strongly according to target
Use opinion content in a more targeted way
Distinguish clearly between reach formats and engagement formats
Analysis without action is worthless.
In a nutshell:
unspectacular
data-based
interpretive
Not every month provides great insights, but every month provides signals.
Only list KPIs
No target definition
Compare platforms
Overvaluing individual posts
Using benchmarks without context
This example avoids exactly that.
As detailed as necessary - not as detailed as possible.
No. Platform analytics are sufficient for the basics.
Yes, which is precisely why it is deliberately unspectacular.
Regularly, but not daily. Trends take time.
Yes, especially for small and medium-sized teams.
A good social media analysis example shows
how people think
not how impressive numbers look
Analysis means: 👉 observe 👉 classify 👉 decide
Not: collect, compare, present.