The document discusses analyzing Instagram user data to derive insights. It describes extracting statistics on the oldest users, inactive users, users with the most likes, popular hashtags, best days to launch ads, average user engagement, and detecting bot/fake accounts. The analysis found that 26% of users were inactive, the most used hashtags were between 24-59 times, and Thursday, Sunday and Friday had the most user activity overall.

1. Instagram User
Analytics
Submitted by: Aniket Somani

2. Contents
Project Description
Approach
Tech-Stack Used
Insights
Result

3. Project
Description
This project revolves around the User Analytics for Instagram and derive trends like the number
of oldest users, number of inactive users, user with most likes, hashtag researching, launching ad
campaign, user engagement and details about bots & fake accounts, etc.
These stats are important for a company to analyze for better user engagement, thus it becomes
a crucial task for a Data Analyst.

4. Tech-Stack
Used
In this project, the dataset was relatively
smaller and the objects of the study were
suitable to achieve using MySQL and
Microsoft Excel only. Hence, the only tool I
used during the
study were MySQL Workbench 8.0 CE and
Mircosoft Excel 2022.

5. Approach
Step 1 Step 2 Step 3 Step 4
I cleaned the dataset as
the first step of my
analysis.
The process included the
identification and removal
of blanks, duplicates, etc.
I also renamed a few
columns for better
understanding.
I explored the cleaned
dataset and tried to
understand the pattern
and distribution of the
data across various
columns.
Here I derived the answers
to the leading questions
keeping the objective of
the study in mind.
I prepared pivot tables
and other calculated fields
to solve the case study
questions
Then I created tables and
graphs to analyze the dataset
Finally, I devised insights and
measured results to
communicate the findings
with the team

6. Oldest Users
Task: Find the 5 oldest users of the
Instagram from the database provided
55%
Out of the total 100 users we have took out the data of
the oldest 5 five users. All of them can be seen created
within a time frame of 10 days.
I haeve presented the data with their id number, username
and the date and time they have been created.
Female
40%
*other category accounts for 5%
ID USERNAME CREATED AT
80 Darby_Herzog 06-05-2016 00:14
67 Emilio_Bernier52 06-05-2016 13:04
63 Elenor88 08-05-2016 01:30
95 Nicole71 09-05-2016 17:30
38 Jordyn.Jacobson2 14-05-2016 07:56

7. Inactive Users 40,534
Human Resource
Marketing
53,625
53,297
Statistics 46,398
48,260
49,311
Operations
Task: Find the users who have never posted a single
photo on Instagram
46,867
Production
Sales
50,605
Female
Male
Out of the 100, there are 26 users who haven’t
posted since their account has been created
48,574
49,628
51,219
Finance
35,313
51,868
50,369
Service
51,019
53,558
Purchase
56,780
General Management
93,835
Username
Aniya_Hackett
Bartholome.Bernhard
Bethany20
Darby_Herzog
David.Osinski47
Duane60
Esmeralda.Mraz57
Esther.Zulauf61
Franco_Keebler64
Hulda.Macejkovic
Jaclyn81
Janelle.Nikolaus81
Jessyca_West
Julien_Schmidt
Kasandra_Homenick
Leslie67
Linnea59
Maxwell.Halvorson
Mckenna17
Mike.Auer39
Morgan.Kassulke
Nia_Haag
Ollie_Ledner37
Pearl7
Rocio33
Tierra.Trantow
Active
Users
74%
Inactive
Users
26%

8. Most Liked Photos
Task: Finding the contest winner of most
liked Instagram post from the database
provided
55%
Out of the total 100 users we have took out the data of
the oldest 5 five users. All of them can be seen created
within a time frame of 10 days.
I hae=ve presented the data with the username, id, url and
the total likes they got.
Female
40%
*other category accounts for 5%
ID USERNAME URL TOTAL LIKES
145 Zack_Kemmer93
https://jarret.na
me 48

9. Hashtag Research
Task: Find the hashtags to use in the post to
reach the most people on the platform from
the database provided
55%
Out of the total 100 users we have took out the data of
the most used tags which can be seen in the table
provided.
I have presented the data with their tag name and the total
number of times they have been used
.
Female
40%
*other category accounts for 5%
TAG NAME TOTAL
Smile
59
Beach 42
Party 39
Fun 38
Concert 24

10. Launching Ad Campaign
Task: Find the best day to launch the
Instagram ad campaign from the database
provided
55%
Out of the total database we have narrowed to 3 days in
the week which had most activities from users from the
database provided.
I have presented the data with the day and the total number
of activities on the particular day.
Female
40%
*other category accounts for 5%
DAY TOTAL
Thursday 16
Sunday 16
Friday 15

11. User Engagement Statistics
Task: Provide how many times does average user
posts on Instagram with the total number of
photos on Instagram with total number of users
Out of the total database we have
narrowed to the average number of
photos posted by users from the
database provided.
AVERAGE
2.57

12. Fake Account Statistics
Task: Provide data on bot users who have liked
every single photo on the site
Out of the total database we have
narrowed to 13 ids which had most likes
from users from the database provided.
I have presented the data with the id
and the likes of all the accounts which
have liked all the photos.
ID LIKES
Aniya_Hackett 257
Jaclyn81 257
Rocio33 257
Maxwell.Halvors
on
257
Ollie_Ledner37 257
Mckenna17 257
Duane60 257
Julien_Schmidt 257
Mike.Auer39 257
Nia_Haag 257
Leslie67 257
Janelle.Nikolaus
81
257
Bethany20 257

13. Insights
Oldest User Statistics Inactive User Statistics hashtag Statistics Fake Account Statistics
All the five hashtags
used remain between
the range from 24 to
59 , lowest to highest
respectfully
All the five oldest
accounts have been
created within 10
days of the starting
of data
We can see that twenty
six percentage of users
are inactive or they
haven’t posted a single
picture yet.
We can see that there
are about thirteen ids
which are infiltrated by
bots and have liked all
the posts

14. Results
01 02 03 04
I found some very
crucial insights
about the social
media function of
the company
Towards the end of
the case study, I
learned how a data
analyst can add
value to such a
manual task as
monitoring statistics
of the company
The highest
usage of the
application was
during Thursday,
sunday and
Friday
Most importantly,
the inactive user
statistics could
help the company
to specifically
target users to
post more pictures
and enable
engagement

15. Thank you!