We looked at a proprietary dataset to see what would be the best template for Instagram posts. Key Take Aways: - Keep a distinct colour palette of warm colours - Use hashtags but be smart about it - Keep it simple in the description

1. WWW.YOURDOMAIN.COMCOMPANY NAME
1
Team 3 -- Challenge 1B:
Which contents perform
better on Instagram ?

2. 2
Ka Man CHEUNG
Meet the team
Yousseff
JACTTHAR
Ediz KOCABAS Ziae MUSTAFA
Chieri NAITO Shivanand RAI Daniel RAMOS Qinjiong ZENG

3. 3
Using Launchmetrics data we have created a comprehensive
guide with Machine Learning on HOW to create high-impact
posts on Instagram. We are looking at all aspects of a post
Colour Palette Analysis
Colour analysis of the most high impact posts
Nomenclature Definition
Explanation of regression, new measures and results
Topic Definition
Scraped all of the content to categorize topics with ML
Textual Analysis
Value of hashtags (content & number)
Cluster Analysis
Deep Dive into Beauty Topics and the cluster profiles.
Methodology
Our Approach by focusing on beauty
#T
Tools Used

4. A good post is determined by its properties and not by the poster’s
audience size.. Since audience plays such a big part in MIV, we wanted to
quantify the post nomenclature has independent of it
MIV/ 1000 Users
The measure we are using to determine our analysis
Engagement
The quality of content and response from users
Actions
Users liking and replying to a post
MIV
Kepler Weighted MIV
Audience Size
The largest determinant of MIV ~50% of results
Our Main Metrics
Dependent variable :
[MIV/Audience]*1000
MIV
4, 847
MIV/1000 users
1, 460
MIV
622, 208
MIV/1000 users
1020

5. 5Data Cleaning and Preparation
New Features derived from the
data
DERIVED
DATA
A count of the number of emojis within
the content text to measure if emojis
make a difference.
Number of Emojis
Modulating the initial timestamp to
correct it by country to represent the
local time of posting
Time by locality
Looking at recurrence of Hashtags in
topics to understand the most
“valuable” ones
Hashtag Value
Most important dependent variable
for a variety of analysis
MIV/1000 Users
The number of words in a post to
determine what is the ideal length?
Length of Post
Understanding the impact of the
hashtags on Adjusted MIV
Number of Hashtags
#T

6. 6NOMENCLATURE SELECTION
Ordinary Least Squares Regression R2= 75%
Post Time & Data Voice TypeContent Type
Number of emojis
Post length Topic
factor engagement rate
#T
Hashtag Value
Replies
Brand Manager
Region
brand name

7. 7TOPIC MODELING
That's definitely my new favourite photo of mine. #makeup#editorialmakeup
#eyelook#eyemakeup #eyemakeupideas#makeuplook #highlighter
#makijazoka#makijaz #mua #london
[that, definite, new, favourite, photo, mine, makeup, editorial, makeup, eye, look, eye
makeup, eye, makeup, ideas, makeup, look, highlight, mua, london]
Post 1 Post 2 Post 3 Post 4 Post 5
How does it Work?

8. 8TOPIC MODELING
6. Advertisement - Traditional
1. Fashion - Professional
2. Fashion - Casual
3. Advertisement
- Holiday
4. Beauty - Care
5. Beauty - Makeup
The Big Topics

9. 9CLUSTERING
Topic Selection
Significant Variables
Beauty - Makeup
Beauty - Care
Fashion - Professional
Fashion - Casual
Advertisement- Traditional
Advertisement -Holiday
Voice Type
Nomenclature
Content Type
Number of Hashtags
Post Length
Day of Publication
Hour of
Publication
WHO? HOW? WHEN?
Influencers
Media
Influencers
Brands and
Celebrities
Influencers
and media
Brands and
Celebrities
All other
voices
Total MIV = 122K
Total MIV = 256KPotential
+1B MIV

10. 10
Beauty Influencers
Voice Type Influencers Others (Brand, media, celebrities)
Post Length (average words) 70 - 110 words 30 words
Use of Hashtags (average) 23 3
Type of content Video + Gallery Photos
Day of Publication Tuesday, Wednesday, Sunday Friday, Saturday
Hour (time-slot) night morning, afternoon
MIV / 1000
audience
MIV / 1000
audience
A Success story

11. 11
Post No. Hashtags
Adjusted
MIV
1
#beauty #eyebrows
#wakeupandmakeup
#clarins #skincare
78
2
#makeup #beauty
#skincare
22
3
#motd #beauty
#1minutemakeup
#makeup
47
Post
No.
Hashtag Number Hashtag
A-
MIV
1 1 beauty 78
1 2 eyebrows 78
1 3
wakeupandmake
up
78
1 4 clarins 78
1 5 skincare 78
2 6 makeup 22
2 7 beauty 22
2 8 skincare 22
3 9 motd 47
3 10 beauty 47
3 11 1minutemakeup 47
3 12 makeup 47
Hashtag
Count
Frequency
Average Adjusted
MIV
beauty 3 =(78+22+47)/3=49
eyebrows 1 78
wakeupandmakeup 1 78
clarins 1 78
skincare 2 =(78+22)/2=50
makeup 2 =(22+47)/2=34.5
motd 1 47
1minutemakeup 1 47
Extract Hashtags from every posts
Get Hashtag-MIV information
from every Post Count Hashtags and calculate the
average MIV for every Hashtag
Hashtag-MIV analysis for the 2 clusters
Filtered out Hashtag Frequency < 200
NLP - Hashtag Analysis
The MIV/1000 Users for every #Hashtag

12. 12
Other Beauty Voices (Brand, media, celebrities) :
Average Adjusted MIV per hashtag -- 11 (per 1k audience)
● Majority of the hashtags are Brands.
● Generic terms.
Beauty Influencers:
Average Adjusted MIV per hashtag -- 52 (per 1k audience)
● Less Brands/official Hashtags.
● Personal and interesting topic hashtags.
Brands Name Hashtags
Topic Name Hashtags
Size-- Total Impact
Value
NLP - Hashtag Analysis

13. 13
Topic related Hashtags for The Beauty Influencer cluster
Average Adjusted MIV per
hashtag (Per 1K Audience)
Insights:
1. Content Topic should be more
related to lifestyle and
educating.
2. Trending/seasonal Hashtags
are more likely to have higher
influence and higher MIV.
Size-- Total influence of
that topic
NLP - Hashtag Analysis

14. 14
Saturation
Brightness
Colorfulness
1.Color Property
Image Analysis on Beauty Brands
2. Color Ratio
Scrape from IG
Vectorize
Analyze

15. 15
Feature Importance
Top 50 Bottom 50
Color Ratio
Elastic Net Regression Result
Brightness, Saturation, Color ratio of Magenta, Pink, and Red have the positive impact on MIV.
Normalized RMSE 0.13

16. 16
Good & Bad Examples
42%
26%10%
Bad Example
MIV /1000 users : 1,150
Brightness : 0.4
Saturation : 0.2
Magenta : 0%
Pink : 1%
Good Example
MIV/1000 users : 48,731
Brightness : 0.6
Saturation : 0.5
Magenta : 9%
Pink : 34%

17. 17
Influencers
Media
Influencers
Brands and
Celebrities
Influencers
and media
Brands and
Celebrities
All other
voices
Total MIV = 122K
Total MIV = 256K
Intense color palette and
uniform colors
(cleaner images)
Seasonal hashtags
carry the most
value
Happy Hash-loween
Focus to Perform
Too much
variables, too little
time
Eye Candy
Color is Important,
but so is
brightness
Find your Balance
A hashtag’s worth
a thousand views
#HashCash
People want to
feel a real
connection with
the product
Generic = boring
Key Takeaways
What we should learn from
Influencers (KIngs of Instagram)
Can we transfer this recipe to leverage the
audiences of Brands and Celebrities?

18. 18
#THANKYOU
See You Next Time